Advances in Agronomy, Volume 84

VOLUME 84 Advisory Board John S. Boyer University of Delaware Paul M. Bertsch University of Georgia Ronald L. Phil...

Author: Donald L. Sparks

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VOLUME

84

Advisory Board John S. Boyer University of Delaware

Paul M. Bertsch University of Georgia

Ronald L. Phillips University of Minnesota

Kate M. Scow University of California, Davis

Larry P. Wilding Texas A&M University

Emeritus Advisory Board Members Kenneth J. Frey Iowa State University

Eugene J. Kamprath North Carolina State University

Martin Alexander Cornell University

Prepared in cooperation with the American Society of Agronomy Monographs Committee Diane E. Stott, Chair Lisa K. Al-Almoodi David D. Baltensperger Warren A. Dick Jerry L. Hatfield John L. Kovar

David M. Kral Jennifer W. MacAdam Matthew J. Morra Gary A. Pederson John E. Rechcigl

Diane H. Rickerl Wayne F. Robarge Richard Shibles Jeffrey Volenec Richard E. Zartman

Edited by

Donald L. Sparks Department of Plant and Soil Sciences University of Delaware Newark, Delaware

2004

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Contents CONTRIBUTORS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . PREFACE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

xi xiii

STATE OF THE ART ON SOIL -RELATED GEO -MEDICAL ISSUES IN THE WORLD J. Deckers and E. Steinnes I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Current Trends in Soil-Related Studies Relevant to Human Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. The Soil-to-Man Chain in the Supply of Mineral Nutrients . . . . . . . . . . . . A. Direct Supply of Mineral Matter by Soil Ingestion—Geophagia . . . . . . B. Bioavailability of Soil Mineral Elements. . . . . . . . . . . . . . . . . . . . . . . C. Indirect Supply of Elements Through the Food Chain . . . . . . . . . . . . . IV. Geographical Dimension of Human Health Issues . . . . . . . . . . . . . . . . . . . V. Problems of Deficiency and Excess of Mineral Elements in Animal Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Elements in Soil that may have Beneficial or Negative Effects on Human and Animal Health . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Aluminium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Arsenic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Boron . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Cadmium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Calcium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Cerium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . G. Chlorine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . H. Chromium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . I. Copper . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Fluorine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . K. Iron. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Iodine . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. Lead . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . N. Manganese . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . O. Mercury . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Molybdenum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Q. Phosphorus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . R. Potassium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S. Magnesium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . T. Nitrogen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . U. Sodium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Selenium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . W. Zinc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

2 3 6 6 7 8 9 10 11 11 11 13 13 14 15 15 16 16 17 17 18 18 19 21 21 21 22 22 23 24 24 25

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VII. Geo-Medical Issues Related to Under-Nutrition and Malnutrition . . . . . . . VIII. Geo-Medical Issues and Contaminated Land Policies . . . . . . . . . . . . . . . . IX. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

26 27 28 29

GASEOUS EMISSIONS OF NITROGEN FROM GRAZED PASTURES: PROCESSES, MEASUREMENTS AND MODELING, ENVIRONMENTAL IMPLICATIONS, AND MITIGATION N. S. Bolan, S. Saggar, J. Luo, R. Bhandral and J. Singh I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Nitrogen Input in Grazed Pasture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Biological Fixation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Fertilizer Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Deposition of Animal Excreta . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Manure Application and Effluent Irrigation . . . . . . . . . . . . . . . . . . . . . III. Nitrogen Dynamics in Pasture Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Biotic Transformations. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Abiotic Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Gaseous Emission of Nitrogen from Grazed Pasture . . . . . . . . . . . . . . . . . A. Ammonia Volatilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Denitrification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Factors Affecting Gaseous Emission. . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Ammonia Volatilization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Denitrification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Measuring and Modelling Gaseous Emissions. . . . . . . . . . . . . . . . . . . . . . A. Measurement Techniques . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Modelling Approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Environmental Implications of Gaseous Emissions . . . . . . . . . . . . . . . . . . A. Acid Rain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Ozone Depletion and Global Warming . . . . . . . . . . . . . . . . . . . . . . . . VIII. Management Practices to Control Gaseous Emission . . . . . . . . . . . . . . . . . IX. Conclusions and Future Research Needs . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

38 40 40 41 43 45 48 48 52 53 53 63 67 67 69 76 76 83 94 95 96 98 102 104 104

MODELING CADMIUM UPTAKE AND ACCUMULATION IN PLANTS L. Tudoreanu and C. J. C. Phillips I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

122

CONTENTS II. Empirical Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Root Uptake of Cadmium. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Empirical Relationships in Foliar Uptake of Cadmium . . . . . . . . . . . . III. Mechanistic Models. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Root Uptake Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Dynamic Foliar Uptake Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Cadmium Uptake and Accumulation-A Modeling Perspective on the Main Processes and Phenomena Related to Uptake and Accumulation of Cadmium in Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Cadmium Influx to the Root . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Foliar Uptake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Accumulation Mechanisms in Plant Tissues . . . . . . . . . . . . . . . . . . . D. Root Parameters Affecting Cadmium Accumulation by Plants . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Ion Competition. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. The Influence of Symbiotic Fungi on Cadmium Uptake . . . . . . . . . . . G. Short Distance Cadmium Transport . . . . . . . . . . . . . . . . . . . . . . . . . H. Long Distance Cadmium Transport. . . . . . . . . . . . . . . . . . . . . . . . . . V. Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Summary. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Conclusions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

vii 124 124 128 129 129 132

133 133 134 136 139 140 141 142 143 144 144 146 147

VARIABLE CHARGE SOILS: THEIR MINERALOGY, CHEMISTRY AND MANAGEMENT N. P. Qafoku, E. Van Ranst, A. Noble and G. Baert I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Mineralogy of Variable Charge Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Mineralogy in General . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Highly Weathered Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Volcanic Ash Soils . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. The Chemistry of Variable Charge Soils. . . . . . . . . . . . . . . . . . . . . . . . . A. Chemical Characteristics in General . . . . . . . . . . . . . . . . . . . . . . . . . B. Soil Particles and Their Surface Charge . . . . . . . . . . . . . . . . . . . . . . C. Sorption . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Chemical Reactions at Solid: Aqueous Interfaces in VCS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. The Management of Variable Charge Soils . . . . . . . . . . . . . . . . . . . . . . . A. Chemical Degradation of Variable Charge Soils . . . . . . . . . . . . . . . . B. Management of Variable Charged Soils . . . . . . . . . . . . . . . . . . . . . . Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

160 161 161 163 164 167 167 168 172 176 193 194 195 202 203

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UNDERSTANDING AND REDUCING LODGING IN CEREALS P. M. Berry, M. Sterling, J. H. Spink, C. J. Baker, R. Sylvester-Bradley, S. J. Mooney, A. R. Tams and A. R. Ennos I. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . II. Observations of Lodging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Types of Plant Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Temporal Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Spatial Patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III. Effects of Lodging on Cereal Yield and Quality . . . . . . . . . . . . . . . . . . . A. Yield. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . IV. Mechanics of Lodging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Bending Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Stem Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Anchorage Failure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Models of Lodging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V. Avoidance Through Crop Management. . . . . . . . . . . . . . . . . . . . . . . . . . A. Cultivations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Sowing Date, Rate and Depth. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Growth Regulators. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . E. Summary of Management Factors. . . . . . . . . . . . . . . . . . . . . . . . . . . VI. Avoidance Through Plant Breeding . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Effects of Dwarfing Genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Potential for Further Progress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . VII. Lodging-Proof Ideotype . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Quantifying a Lodging-Proof Ideotype . . . . . . . . . . . . . . . . . . . . . . . B. Can Cereals Be Made Lodging-Proof? . . . . . . . . . . . . . . . . . . . . . . . VIII. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Progress in Understanding Lodging During the Last 30 Years . . . . . . B. Further Understanding Required . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

218 220 220 222 223 225 225 226 228 228 232 233 235 236 236 239 242 245 253 254 254 255 257 257 260 261 261 262 263

ALTERING FATTY ACID COMPOSITION IN OIL SEED CROPS J. W. Burton, J. F. Miller, B. A. Vick, R. Scarth and C. C. Holbrook I. Soybean . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Unsaturated Fatty Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

274 274 274

CONTENTS

ix

C. Saturated Fatty Acids . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Genetic Engineering Soybean Oil with Novel Fatty Acids . . . . . . . . . II. Sunflower . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . B. Nusun Sunflower Oil . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Reducing Saturated Fatty Acids in Sunflower Oil . . . . . . . . . . . . . . . D. Tocopherol Role in Nusun Sunflower Oil . . . . . . . . . . . . . . . . . . . . . III. Brassica . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Intraspecific and Interspecific Crosses . . . . . . . . . . . . . . . . . . . . . . . . B. Mutagenesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C. Transformation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Production of Modified Oil Cultivars . . . . . . . . . . . . . . . . . . . . . . . . IV. Peanut. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Introduction, Breeding Objectives, and Rationale . . . . . . . . . . . . . . . B. Increasing Oleic Acid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

279 281 283 283 284 289 291 292 292 294 296 297 297 297 298 301

INDEX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

307

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Contributors Numbers in parentheses indicate the pages on which the authors’ contributions begin.

G. BAERT (157), Hogeschool Gent, Gent, Belgium C. J. BAKER (215), School of Engineering, The University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom P. M. BERRY (215), ADAS High Mowthorpe, Duggleby, Malton, N Yorks YO178BP, United Kingdom R. BHANDRAL (37), Institute of Natural Resources, Massey University, Palmerston North, New Zealand N. S. BOLAN (37), Institute of Natural Resources, Soil & Earth Sciences, Massey University, Private Bag 11 222, Palmerston North, New Zealand J. W. BURTON (271), USDA-ARS, Fixation Unit, 3127 Ligon Street, P. O. Box 7631, Raleigh, NC 27695-7631 J. DECKERS (1), Department of Land Management, K. U. Leuven, Vital Decosterstraat 102, B-3000 Leuven, Belgium A. R. ENNOS (215), School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, United Kingdom C. C. HOLBROOK (271), USDA-ARS, PO Box 748, Tifton, GA 31793 J. LUO (37), AgResearch, Hamilton, New Zealand J. F. MILLER (271), USDA-ARS, Northern Crop Science Laboratory, Fargo, North Dakota S. J. MOONEY (215), School of Life and Environmental Science, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom A. NOBLE (157), International Water Management Institute (IWMI), Bangkok, Thailand C. J. C. PHILLIPS (121), School of Veterinary Sciences, University of Queensland, Gatton 4343, QLD, Australia N. P. QAFOKU (157), Pacific Northwest National Laboratory, P. O. Box 999, MSIN:K3-61, Richland, WA 99352 S. SAGGAR (37), Landcare Research, Palmerston North, New Zealand R. SCARTH (271), Department of Plant Science, University of Manitoba, Winnipeg, MB R3T2N2, Canada J. SINGH (37), Institute of Natural Resources, Massey University, Palmerston North, New Zealand J. H. SPINK (215), ADAS Rosemaund, Preston Wynne, Hereford HRI 3PG, United Kingdom E. STEINNES (1), University of Trondheim, Department of Chemistry, Trondheim, Norway N-7034 M. STERLING (215), School of Engineering, The University of Birmingham, Edgbaston, Birmingham B152TT, United Kingdom xi

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CONTRIBUTORS

R. SYLVESTER-BRADLEY (215), ADAS Boxworth, Boxworth, Cambridge CB3 8NN, United Kingdom A. R. TAMS (215), School of Life and Environmental Science, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom L. TUDOREANU (121), Department of Mathematics, Physics and Informatics, University of Agronomy and Veterinary Medicine, Bucharest, Romania E. VAN RANST (157), Ghent University, Gent, Belgium B. A. VICK (271), USDA-ARS, Northern Crop Science Laboratory, Fargo, North Dakota

Preface Volume 84 contains six outstanding reviews on various aspects of agronomy. Chapter 1 is a timely treatise on soils and health. Chapter 2 deals with gaseous emissions of nitrogen from grazed pastures and includes discussions on processes, measurements and modeling, environmental implications, and mitigations. Chapter 3 covers aspects of modeling cadmium uptake and accumulation in plants. Chapter 4 is a contemporary and useful review on variable charge soils including their mineralogy, chemistry, and management. Chapter 5 provides extensive information on understanding and reducing lodging in cereals including effects of lodging on cereal yield and quality, observations of lodging, mechanics of lodging and avoidance through crop management and plant breeding. Chapter 6 is a contemporary review on altering fatty acid composition in oil seed crops. Many thanks to all the authors for their excellent reviews. DONALD L. SPARKS University of Delaware

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STATE OF THE ART ON SOIL-RELATED GEO-MEDICAL ISSUES IN THE WORLD J. Deckers1 and E. Steinnes2 1

Laboratory for Soil and Water Management, KULeuven, Vital Decosterstraat 102, 3000 Leuven, Belgium 2 Department of Chemistry, Norwegian University of Science and Technology, NO-7491 Trondheim, Norway

I. Introduction II. Current Trends in Soil-Related Studies Relevant to Human Health III. The Soil-to-Man Chain in the Supply of Mineral Nutrients A. Direct Supply of Mineral Matter by Soil Ingestion— Geophagia B. Bioavailability of Soil Mineral Elements C. Indirect Supply of Elements Through the Food Chain IV. Geographical Dimension of Human Health Issues V. Problems of Deficiency and Excess of Mineral Elements in Animal Nutrition VI. Elements in Soil that may have Beneficial or Negative Effects on Human and Animal Health A. Aluminium B. Arsenic C. Boron D. Cadmium E. Calcium F. Cerium G. Chlorine H. Chromium I. Copper J. Fluorine K. Iron L. Iodine M. Lead N. Manganese O. Mercury P. Molybdenum Q. Phosphorus R. Potassium S. Magnesium 1 Advances in Agronomy, Volume 84 Copyright q 2004 by Elsevier Inc. All rights of reproduction in any form reserved. DOI 10.1016/S0065-2113(04)84001-X

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J. DECKERS AND E. STEINNES T. Nitrogen U. Sodium V. Selenium W. Zinc VII. Geo-medical Issues Related to Under-nutrition and Malnutrition VIII. Geo-medical Issues and Contaminated Land Policies IX. Conclusions References This paper reviews the present knowledge base on soil and human health. After a brief historical introduction the most important issues are introduced. Attention is paid to the soil-to-man chain in the supply of mineral nutrients. The most important elements having positive or negative effects on human health are discussed per element in terms of their role in the human body, sources in the diet, and positive or negative effects. The geographical dimension of geo-medicine is treated with special focus on (1) aspects of malnutrition in developing countries and (2) contaminated lands in Western societies. The paper calls for interdisciplinary cross-links and concludes by listing issues for future geo-medical research. q 2004 by Elsevier Inc.

I. INTRODUCTION It is surprising to note how little attention has been paid by soil scientists as well as medical professionals to the relationship between soil and human health. To some extent this important issue was touched upon by geo-chemists and only in exceptional cases by medical scientists. In fact, the veterinarian profession has been much more aware of this kind of relationship, and an extensive literature exists on the problems on deficiency and excess of mineral elements in animal nutrition (Lewis and Anderson, 1983; Mills, 1983; Frøslie, 1990). Geo-medicine, however, is not new. Hippocrates and Plinius the Elder wrote the first records on the relationship between geo-chemistry and geo-medicine. The Chinese had already paid attention to it as early as the 4th century AD (Mills, 1996). Later in history, Marco Polo described health problems in humans and animals in China, the symptoms of which were later identified as selenium deficiency (La˚g, 1986). In addition, iodine deficiency in man was already recognised at that time as a disease caused and associated to a geo-chemical deficiency (Crounse et al., 1983). In Europe, such information was almost anecdotal until the 19th century (Mills, 1996). The first clear geo-medical evidence was established by the French chemist Chatin in 1851 (Beeson and Matrone, 1976), who linked prevalence of goitre in the Alps to deficiency of

STATE OF THE ART ON SOIL-RELATED GEO-MEDICAL ISSUES

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iodine in the soil environment. Apart from iodine and iron, studies of the effects of elements on human health were not started until 1928 (McDowell, 1992). Human health status is to a large extent conditioned by the intake of mineral elements in the daily diet, through drinking water, and by inhalation of dust. These elements include, on the one hand, macro- and micronutrients which are essential in human nutrition and lead to health problems if they are deficient in the body, and on the other hand, elements which are toxic to the human organism. Actually most essential nutrient elements are toxic if they are absorbed in excessive quantities. Since about 98% of the human food is produced on the land, soil is a primary source of these elements, which get into the human food chain via plants that absorb them from the soil and are consumed directly as vegetative material or indirectly as animal products (meat, milk, etc.) via animals using the vegetation as fodder. Intake of micronutrients from drinking water represents only a small fraction (some 10%) of the total intake (Jacks, 1983; Deckers et al., 2000). Macro nutrients available in the soil comprise calcium, potassium, phosphorus, magnesium, sodium, chlorine, sulphur and nitrogen. Essential microelements for human health include chromium, fluorine, iron, iodine, copper, manganese, molybdenum, selenium and zinc (Masironi, 1983; Friberg et al., 1986). Microelements that are toxic above certain concentrations are aluminium, arsenic, cadmium, lead, mercury and tin. The role of nutrient elements, especially microelements, in human nutrition is very complex, as discussed in various papers cited by Gawthorne et al. (1982) and Oliver (1997). A specific element may fulfil a large number of roles in metabolism. Although he does not give a figure for humans alone, O’Dell (1982) states that approximately 100 zinc-dependent enzymes have been described in all animal species. Elements, furthermore, interact with each other, often in an antagonistic way. The best known is probably the copper – molybdenum antagonism, which is often a problem in domestic animals. A further complication is that various factors affect the bioavailability of mineral nutrients in food to humans. A classical example is found in the Mseleni area in South Africa where the maize and groundnut diet of the population is severely deficient in calcium. The wild spinach, which is another important dietary item in the area, has a high calcium content, but it is also high in fibre, oxalate and phytate (Fincham et al., 1986), all of which interfere with calcium absorption and lower its bioavailability.

II. CURRENT TRENDS IN SOIL-RELATED STUDIES RELEVANT TO HUMAN HEALTH Most studies in Western countries focus on the relationship between soil pollution and human health status. At the recent Fifth International Conference

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J. DECKERS AND E. STEINNES

on the Biogeochemistry of Trace Elements, there was, e.g., practically no paper dealing with mineral deficiencies; almost all papers dealing with soils concentrated on toxicity (Wenzel et al., 1999a,b). The spectacular industrialisation in the West and the Far East, unfortunately, went along with uncontrolled growth of industrial waste, which in many cases was dumped as such on or into the soil, for lack of waterproof recycling systems. Industrial and mining spoil, sewage sludge, dredging materials, household wastes and other wastes often contain high concentrations of inorganic (heavy metals, cyanide, etc.) as well as organic (halogenated hydrocarbons, polychlorinated biphenyls, polyaromatic hydrocarbons) pollutants. If these components are not sufficiently contained in the soil, they can get into the human nutrition cycle via dust, aerosols, irrigation water, groundwater, and drinking water or indirectly via plant uptake. The soil profile therefore can be considered as a labile reservoir of chemicals, which may play an important role in human health. The degree to which the soil withholds or buffers pollutant flows determines its capacity to store waste. Once this carrying capacity for pollutants is exceeded, a breakthrough will occur and dangerous pollutants may flow into the groundwater cycle and endanger human health. This may, for instance, happen when contaminated agricultural land is turned into forest in Western Europe, e.g., in the absence of annual fertilisers the pH drop may cause cadmium to become mobile, thus contaminating the groundwater. Although the industrial, mining and urban pollutants are very potent, they often affect only a small portion of the total land area. Kabata-Pendias and Stuczinsky (1999), e.g., show that soils subjected to industrial, mining and urban pollution in Poland do not account for more than 0.3% of the arable land. Actual impacts may be large, however, since such areas are close to densely populated urban, industrial and mining areas and also because the pollutants may end up in domestic drinking water sources, or kick up with dust in case of wind erosion. The agricultural sector in developed countries also holds responsibility with regard to essential mineral element supply to the world population on the one hand and prevention of mineral toxicities in food on the other hand. Use of agrochemicals has become a condition to maintain the present high production levels and to meet world food demand. Decay of a number of agro-chemicals in the soil is slow; some of them are mobile and can move uncontrolled to ground- and surface waters. High concentrations of inorganic (nitrate, phosphate, copper, etc.) and organic (pesticides, fungicides, herbicides) chemicals in the environment may constitute a risk for human health, which is difficult to quantify (Abts et al., 1991; Deckers et al., 1995). Intensive agricultural practices often lead to deficiencies of elements, which are critical in the human diet. Classical examples are zinc deficiencies induced by excessive phosphate levels (e.g., Laker, 1964); boron, copper and zinc deficiencies caused by excessive applications of phosphate and potassium (Newnham, 1982); and manganese deficiency caused by injudicious liming (Xilinas, 1983). Intensive farming, taking high yields off


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the land, has in many cases led to exhaustion of the reserves of a number of elements in the soil. It must be kept in mind that only a limited number of elements are applied to agricultural fields as fertilizers. Some of the elements that are essential for human health are not essential for plants. Crop yields are, therefore, not affected by them and consequently farmers cannot afford to spend money on applying them. “There is normally no thought of increasing the trace element content of crops so that the ultimate consumer may be healthier” (Newnham, 1982). Ironically, therefore, microelement deficiencies are relatively common in the diets of people in developed countries (Abdulla et al., 1982). In discussing the role of boron deficiency in arthritis, Newnham (1982) states: “It becomes evident that arthritis and rheumatism is a disease of modern living brought on by a universal exploitation of the soil. In order to have a healthy population we must have a foundation in a healthy soil.” In the developing countries of the world, deficiencies of most mineral elements essential to human health are widespread. Various factors are responsible for this situation. First, these countries are in areas with a much poorer soil resource base than the fertile soils of Europe and North America. Many are in the humid tropics with extremely infertile, highly weathered and/or highly leached soils, which are intensely deprived of nutrients. The rest are mainly in the semi-arid to arid areas adjacent to the latter, where alkaline and calcareous soil conditions severely limit the plant-availability of microelements. Secondly, plant-available nutrient element levels in soils have been drastically reduced in these countries due to exhaustive cropping and severe human-induced soil erosion. Exhaustive cropping is exacerbated by poverty and lack of infrastructure, which hamper application of fertilizers—especially trace element supplementation. Soil erosion is aggravated by extreme pressures on the land because of population numbers, which exceed the human carrying capacity of the land. These widespread nutrient element deficiencies are a cause for concern especially since it has been clearly indicated that many nutrient elements, notably some trace elements, have important roles in the development and maintenance of the immune system in humans (Nauss and Newberne, 1982). Furthermore, they are a baseline for a generally balanced human development. Subsistence communities in remote rural areas of developing countries offer the best opportunities for studies of relationships between soil factors and human nutrition, because in such communities each family feeds on crops from their own cultivated plot. Unfortunately a whole range of elements is often deficient in a high incidence area for a specific disease, making it difficult to identify which deficiency is actually responsible for the elevated incidence of the disease. Last but not the least, parent materials and/or soils may emit radon, which is radioactive and carcinogenic. Concentrations of radon are usually greater in soils on granitic rocks than in soils derived from other rock types. Factors that favour transmission of radon through soil are permeability (Sharman, 1992), carbon dioxide that acts as a carrier (Ball et al., 1985) and moisture, which

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reduces diffusion of radon. In open air, these hot spots of radon emissions are not so problematic as such. The problem starts when radon moves into the house through a poorly isolated basement. If ventilation in the house is insufficient, cumulative exposure to low levels of inhaled radon may trigger lung cancer. As people spend a lot of time indoors, the cumulative effect of the small quantities of radon present may lead to surprising consequences. According to UNSCEAR (1982), radon accounts for about 50% of the radiation dose received by people living in areas of normal background (Steinnes, 1990). A similar figure was reported by Oliver (1997) for people living in Britain.

III. THE SOIL-TO-MAN CHAIN IN THE SUPPLY OF MINERAL NUTRIENTS A. DIRECT SUPPLY OF MINERAL MATTER BY SOIL INGESTION— GEOPHAGIA The simplest form of mineral element intake from the environment is “geophagia” or direct eating of soil by human beings. Geophagia is widely reported in literature and can vary from undeliberate taking in of soil, e.g., by playing children to deliberate eating of soil either pure or mixed in other food substances. One of the first reports on geophagia is from Von Humbolt, who writes in his travel reports from South America between 1799 and 1804 that clay was eaten to some extent at all times by the Otomac tribe along the Orinocco River, and in Peru he saw mothers give their children lumps of clay to keep them quiet (Halsted, 1968). Geophagia is common among traditional societies, e.g., in sub-Saharan Africa. Soil may be directly eaten from the ground, but in many situations there is a cultural preference for soil from “special sources” such as the walls of termite nests or in traditional herbal –soil mixtures. These are taken as a “special remedy” during pregnancy and by children when micronutrient requirements are increased (Smith et al., 2000). In many studies, quoted in Smith et al. (2000), geophagia is considered as “good for health,” especially for strengthening the blood and promoting growth and physical strength. It is not 100% clear what the precise reasons are for a beneficial effect of geophagia—are mineral elements exchanged from the CEC-complex under the acidic conditions in the stomach? Exchange reactions may also explain absorption on the clay surface of possible dietary toxins such as alkaloids, tannins and bacterial toxins. For instance, Johns and Duquette (1991), in Oliver (1997), describe clay being eaten a.o. by Pomo Indians to detoxify bitter potatoes (Solanum spp.). Intake of soil is usually associated with risk of human diseases. Examples are pathogens such as tetanus (Clostridium tetani), worm infections such as


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hookworm (Ancyclostoma duodenale, Necator americanua) or even non-filarial elephantiasis, which may enter through skin abrasions. In traditional societies where geophagia is common practise, parasite-causing soil-born patogens are important to understand the aetiology of certain human diseases. The nonfilarial elephantiasis or podoconidiosis is an interesting case: small worms in soil cause swelling of the legs by blocking lymph nodes! The disease is common in tropical highland areas on basaltic volcanic geology on “fine reddish brown soils”—most likely Nitisols (Nachtergaele et al., 2000). Price (1988) reports on the ecological niche of this disease. It seems to occur in wellpopulated regions between 1250 and 2500 m altitude, with moderate mean annual temperature around 208C, and with more than 1000 mm of rain in the hot season. This covers areas such as the volcanic Highlands in Ethiopia, Kenya, Tanzania, Burundi and Cape Verde (Price and Plant, 1990). Very small particles of kaolin, amorphous silica and some quartz and iron were found in phagosomes of macrophages. The specific role of these soil minerals is still not yet clear and should be further investigated. In Addis Ababa, an outbreak of encephalitis in 1987 was linked to dust storms which affected the area in the dry season.

B. BIOAVAILABILITY OF SOIL MINERAL ELEMENTS Presence or absence of mineral elements is one aspect of geo-medical correlations, however, only few scientists have investigated their bioavailability, which may be defined as the total fraction of an element available for absorption during transit through the small intestine (Smith et al., 2000). These authors argue that this lack of data on bioavailability in literature is in part due to the lack of a suitable sophisticated model for the human digestive system. Simple extractions of mineral elements, which are taken as proxy for human uptake, ignore the effect of changes in the Eh/pH regime and kinetics during passage through the human gut. In order to come to grips with this, Smith et al. (2000) developed the concept of a “physiologically based extraction test (PBET),” on the basis of which it can be predicted how much percentage of a mineral element effectively gets into the blood when going through the gut. Data for Mg and Ce indicate typical bioavailability in the range of 7 –33% and 0.26 –15%, respectively. With these figures in mind, the relative importance of geophagia versus drinking water as a source of mineral elements takes different proportions. For the case of Uganda, Smith et al. (1998) conclude that from a nutritional standpoint, only in the case of Fe does the ingestion of soil account for a major proportion of the recommended daily intake (RDI). Despite its higher bioavailability, the lower Mg content in the soils provides only a small percentage of the RDI of this element through geophagia.

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There seems to be a correlation between particle-size distribution of the soil and bioavailability, e.g., Ce is most accessible in the 63 –20 mm size range. This is most likely related to the specific surface area of the particles, which dictates mineral dissolution kinetics. Smith et al. (1998) show that soils from different sources have considerably different trace elements and bioavailability, and confirm that geophagia represents a significant source of trace elements in the human diet. However, as soil ingestion may compromise the health of children and pregnant women, as major source of intestinal parasites, boiling of dietary earth could be suggested by health workers to overcome this problem.

C. INDIRECT SUPPLY OF ELEMENTS THROUGH THE FOOD CHAIN Except where nutrient elements are taken in as tablets, humans must obtain these elements from the soil via the food chain. This simply means that the minerals must be absorbed from the soil by plants, which are then eaten by the humans (keeping in mind that about 95% of the human diet is vegetative) or by animals, which give rise to products included in the human diet. A key factor thus is the plant-availability of an element in the soil. All soil factors affecting plant-availability are therefore important, e.g., soil properties such as pH, redox potential, drainage, organic matter status, texture and soil management are of critical importance. Pedogenetic factors such as parent material and climate also play an important role. Intake of mineral elements from the soil environment varies according to species and function of forage behaviour. Wild animals, for instance, usually forage over extensive areas and therefore stand a reasonable chance to ingest the necessary critical load of essential elements. On the other hand, domesticated animals, particularly ruminants, are more vulnerable to low levels of essential elements because of confined grazing areas. Human food supply usually originates from a wide area, either because man travels over great distances or because food is transported. The same applies to drinking water, the second most important source of micronutrients in human diet (Piispanen, 1990). As most people in developed countries consume piped drinking water that is pumped over great distances, correlation between composition of local water sources and health status is poor. In view of the foregoing, geographical correlations between mineral elements and human health status are mainly limited to isolated locations where people live on local agricultural produce and drink from local water resources. Apart from a few exceptional reported cases, the relationships between soil type, soil quality and human health are still little understood at present. Intrinsic soil fertility determines the carrying capacity of the land, and hence the food supply situation of the local population (Deckers and Vanclooster, 1998).


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Infertile soils, as are common in a number of developing countries, may explain recurrent food shortages and hence cause qualitative and quantitative malnutrition, which will inevitably lead to shortages of macro- and/or micronutrients. Furthermore, as pointed out by Oliver (1997) intake of minerals in food depends on lifestyle, sex, age and general well-being of people; children, elderly, and pregnant women are particularly vulnerable to deficiency or toxicity of trace elements (Rogan, 1995 in Oliver, 1997): children because they often eat a limited range of foods and are growing rapidly, and neonates and elderly because they absorb trace elements poorly.

IV. GEOGRAPHICAL DIMENSION OF HUMAN HEALTH ISSUES The first geo-medical correlations generally recognized were the linking of goitre to iodine deficiency, which dates back to the 19th century, and observations of dental fluorosis in Iceland following volcanic eruptions (La˚g, 1990). Such examples are typically limited to isolated geographical areas. Most geo-medical studies lead to the identification of one or more specific element, which is either in short supply or excessively available. In a number of cases the link is not so evident at first glance, as is the case with low concentrations of lead, which may accumulate slowly in the body over a very long period of time and cause health problems. In a number of cases, statistical differences are found but researchers were unable to point a finger at a clear factor or mechanism, leading to the geo-medical correlation. A typical example of the latter is the study by Munro et al. (1997), drawing a linkage between infant mortality and soil type in south-central England. They studied infant mortality in a region with soils overlaying areas of varying lithologies and hydrologies, ranging from porous and permeable chalk and limestones to generally wet and impermeable clays. Between 1981 and 1990 they found proportionally more infant deaths on the “wet” soils, and a gradation towards lower infant mortality rates on the drier soils. This relation between infant mortality and soil moisture remained after the effect of social class was removed. Infant mortality in this study was used as a proxy for general health level of the human population. The effect was not large but it was highly significant—the overall infant mortality on the wet soils was 31.9% greater than on the “dry” soils, for reasons that remain unexplained. It was hypothesized that the wetter and perhaps colder air on wet soils might result in babies or mothers suffering from more colds or respiratory illnesses than would otherwise be the case. In damp conditions, these afflictions could deteriorate more rapidly and become more serious than in a drier environment. Interestingly, Munro et al. observed that the difference in death rate

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decreased during the 10 years from 1981 to 1991, which may be explained by improved health care. Improved and more “water-proof” building techniques may also be a factor here. Another way to explain the interesting differences in infant mortality between wet and dry soils in 1981– 1990 may be a change in climate, i.e., the latter years may have been systematically warmer and dryer than the former years (Bullock, 1997). In the discussion note on this paper, Bullock points to possible contributions of wet soil and climate to health, e.g., the fact that wet soils usually lie in low landscape positions with a higher prevalence of mist and fog. Pollutants are likely to be held over the ground in the mist whereas over dry soil they escape or are diluted by circulating air. Furthermore, there is still much to learn about the soil fauna and microflora. The type of organisms that flourish in wet soil is likely to differ from that in dry soil, but whether the “wet soil suite” of, e.g., microorganisms can affect human health in a more deleterious way than the “dry suite” is unknown (Bullock, 1997). Munro et al. (1997) further point out that it may be significant that the sudden infant death syndrome (SIDS)—when death cannot be attributed to any known disease—is very largely a winter phenomenon (Swindon Health Authority, 1992), and that one of the areas where it was most pronounced during the early years of the period studied is the low lying and relatively damp area of East Anglia (Dorling, 1995). Oliver et al. (1992) identified another rare disease that seems to be related to the environment—childhood cancer—in a study in the West Midlands of England; however, no clear soil factor was yet revealed (Oliver et al., 1992).

V. PROBLEMS OF DEFICIENCY AND EXCESS OF MINERAL ELEMENTS IN ANIMAL NUTRITION Like many diseases in man, several disease conditions in animals show a definite geographical distribution. That may be due to a number of different factors. Among those, disorders related to soil chemistry constitute a significant part. Most relevant in this connection are the trace elements, in particular the essential ones. Deficiencies of such elements are of main concern in a global context (Frøslie, 1990). Domestic animals in most cases have to manage with the feed they are offered or which they can come across when grazing. Local deficiencies in nutrients are therefore likely to be reflected in their nutritional status, unless they are given supplementary feed containing the nutrient in question. Therefore geo-medical problems are much more likely to occur in animals than modern man, whose diet is normally composed of foodstuffs from different parts of the world. Among the domestic animals, the ruminants are the most exposed to trace element

STATE OF THE ART ON SOIL-RELATED GEO-MEDICAL ISSUES 11

deficiencies. Wild animals are able to graze selectively and therefore more likely to avoid deficiency problems. Most trace element problems in domestic animals are concentrated on a few elements: copper, cobalt, molybdenum and selenium. Occasionally problems in livestock farming related to the environment have also been experienced with fluorine, iodine and zinc. Some of the most common problems in animals related to environmental trace elements are described in Section VI on individual elements. Deficiency conditions in ruminants may lead to considerable economic losses. In Scotland alone, measures to prevent and treat copper deficiency were calculated to cost about 1 million US dollars annually (Scottish Agricultural Research Institutes, 1982, cited in Frøslie, 1990).

VI. ELEMENTS IN SOIL THAT MAY HAVE BENEFICIAL OR NEGATIVE EFFECTS ON HUMAN AND ANIMAL HEALTH In the following sections, a selection of soil-related geo-medical issues is discussed element by element.

A. ALUMINIUM Although aluminium is ubiquitous in the environment, it is present as a trace element in most biota. Studies suggest that less than 1% of dietary aluminium is absorbed in humans; factors affecting absorption may include vitamin D, fluoride and presence of complexing agents (WHO, 1996a). Aluminium from drinking water usually contributes to only a very small proportion of daily human intake. The major part of a typical 20 mg/day daily intake comes from food (e.g., tea), food additives containing aluminium such as preservatives, fillers, colouring agents, etc. Aluminium may also be leached from cooking utensils if exposure is long enough. Some studies associate aluminium with the brain lesions characteristic of Alzheimer disease, however, the balance of epidemiological and physiological evidence does not at present support a causal role for aluminium in Alzheimer disease (WHO, 1996a,b). Further research on the biological role of Al is warranted.

B. ARSENIC Arsenic is relatively scarce (20th position in elemental abundance in the continental crust). However, it is widely distributed in nature and can be found

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in detectable amounts in nearly all soils. Arsenopyrite is the main commercial ore of arsenic worldwide, but arsenic compounds (mainly As2O3) are also recovered as by-products of lead, zinc, copper, gold and silver ore treatment. The arsenic content of soils is obviously in relation to the geological substratum that forms the soil and a rather wide range of arsenic levels have been found in soils around the world with an average of 5– 10 ppm in uncontaminated soils (Fergusson, 1990). Arsenic, however, may accumulate intensely in soils due to human activities such as waste discharges from metal processing plants, burning of fossil fuels, mining of arsenic containing ores and agricultural use of arsenical pesticides. Arsenic is a harmful element with different degrees of toxicity depending on the speciation of arsenic, route and dose of exposure, and individual and local tissue susceptibilities (Nriagu, 1994). Arsenic is a semimetallic element and its behaviour in soils resembles that of group V A elements more than that of heavy metals. The oxidation state of arsenic is important since it affects the movement and persistence of arsenic in soils and sediments. The (phyto)-toxicity of arsenic also depends on its oxidation state. In oxygen-rich environments and well-drained soils, arsenate 22 in alkaline soils). (þ V) species dominate (H2AsO2 4 in acidic and HAsO4 Under reducing conditions, such as regularly flooded soils, arsenite (þ III) is the stable oxidation state, but elemental arsenic and arsine (2 III) can also be present in strongly reducing environments. Arsenic may also exist in organometallic forms such as monomethylarsenic acid, dimethylarsenic acid and the more volatile methylarsines. Iron, aluminium and calcium arsenates are, like the corresponding phosphates, insoluble in water and exhibit a phosphate-like specific adsorption (inner sphere complexation) on oxide and clay surfaces. Arsenites, however, are (10 times) more soluble and mobile and more toxic than arsenates. Arsenic is commonly found in present-day or in paleo-acid sulphate soils [Thionic Fluvisols (Nachtergaele et al., 2000), Sulfaquepts (Soil Survey Staff, 1998)]. Henceforth, high arsenic contents are expected in floodplains along estuaries of major rivers and tidal flats in coastal areas. Arsenic came into focus of the media recently with the case of massive arsenic poisoning of large human populations in Bangladesh by water from recently drilled shallow wells. Feasibility studies of this shallow well project never paid attention to the possible presence of arsenic as a threat to human health. However, as the affected area is geographically located in a paleo-estuarine system from the Brahmaputra river, presence of pyrite and arsenite containing old alluvia (buried Thionic Fluvisols) in the lower strata could have been inferred. When the groundwater table dropped upon massive water extraction from the shallow wells, arsenic poisoning became evident from a number of typical syndromes such as hair drop, hyperkeratosis (increased thickness of the upper layer of skin) of the palms and the soles of the feet. Other effects of arsenic


reported in literature are: hyperpigmentation (increased melanin), vascular disorders (e.g., blackfoot disease, a form of gangrene), rashes (Tseng, 1977; Thornton, 1996) and cancer of the internal organs (Chen et al., 1992).

C. BORON The presence of boron in the environment originates from sea spray, volcanic activity and industrial pollution. In foodstuffs, boron occurs in plant tissues of which legumes contain the highest levels followed by fruits and vegetables (WHO, 1996a,b). Excessive boron intake caused symptoms of boron poisoning such as: gastrointestinal disturbances, erythematous skin eruptions, signs of central nervous system stimulation followed by depression (WHO, 1996a,b). Boron is an issue for concern in irrigated agriculture, as high boron levels in irrigation water may cause boron levels in the soil to raise to such an extent that crop levels become too high.

D. CADMIUM Cadmium is one of the most toxic trace elements in soils, normally occurring in concentrations of 0.08 – 0.5 mg Cd per kg soil. High cadmium levels in soils in many cases originate from pollution throughout the 20th century in and around Pb and Zn smelters through atmospheric deposition, burning of fossil fuels, waste disposal (Cd-containing batteries) and sewage sludge. The geographical distribution of these cadmium hotspots is mainly limited to the relative vicinity of the place of origin and possible effluent zones, e.g., flood plain alluvia from rivers contaminated by waste waters, but in some cases surface soil concentrations may also be significantly enhanced by long-range atmospheric transport (Steinnes et al., 1989; Page and Steinnes, 1990). A much more dispersed accumulation of cadmium has taken place in agricultural lands as a consequence of cadmium-containing phosphate fertilisers over the last 50 years. Though nobody will query the importance of phosphates as a key element for agricultural production, past cadmium accumulation in soil is mainly linked to the use of phosphate fertiliser. Rock phosphate contains on average 170 mg cadmium per kilogram phosphorus. Between 5 and 30% of Cd is taken away in the process of making high-grade phosphate fertilisers. Presentday phosphate fertilisers are almost cadmium-free. However, in view of a longstanding phosphate application history, old agricultural land may contain sizeable amounts of cadmium, built up over the years. Cadmium availability to plants is influenced by a number of factors such as soil pH, redox potential, organic matter content and potassium content (Kaarstad, 1991). Low pH increases the mobility and availability, hence plants accumulate

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most Cd under acid soil conditions. Hydrous oxides of Al and Fe adsorb Cd and decrease its availability to plants in the short term. However, very little is known about long-term attenuation of Cd upon dehydration of sequioxides in soil horizons (e.g., Spodic Horizons). In reducing conditions, Cd is held as CdS, which is insoluble and hence less available than in well-aerated soil (Oliver, 1997). The practical consequence of this is that in contaminated rice fields it is better not to drain the fields too long before harvest, as Cd levels in the grains increase (Page et al., 1981). Cadmium is labile and accumulates in food plants, especially cereals, often at sub-phytotoxic concentrations. Fairly large amounts can accumulate in plants without them showing stress. This increases the risk for potential intake in the diet without it being noticed (Oliver, 1997). Davis and Carlton-Smith (1980) show that lettuce, spinach, celery and cabbage tend to accumulate large concentrations of Cd, whereas potatoes, maize, French beans and peas accumulate only small amounts (Oliver, 1997). Food is the main pathway by which Cd enters the body—cereals account for 50% of Cd intake; the maximum tolerable intake recommended by WHO (1973) is 70 mg Cd/day. As Cd accumulates in the body, small concentrations in food can have significant long-term effects. Consequently the risk for health effects increases with age. In Japan, cadmium was identified as the cause of the itai – itai disease (osteomalacia with simultaneous renal dysfunction). The patients ate rice that originated from cadmium-contaminated paddy fields (Asami, 1991). The river water with which these rice fields were irrigated was contaminated with cadmium. Diseases of bone, osteomalacia and osteoporosis, have been observed only in Japan where the effects of Cd toxicity was exaberated by dietary deficiencies of Ca, vitamin D and protein, together with the effects of pregnancies and ageing. It seems that Cd affects Ca and vitamin D metabolism resulting in the decalcification of bones (WHO, 1992 in Oliver, 1997). A study in Scotland indicated a relationship between high cadmium levels and high cancer incidence in an area where cancer is prevalent (Scott et al., 1982). A study in the United States indicated a relationship between learning disability in children and high cadmium similar to the effect of high lead (Harland et al., 1982).

E. CALCIUM Calcium is an important element in the human body, 99% of which is located in the skeleton. The remaining 1% is dissolved in extracellular water or serves in intracellular structures and cell membranes. Green vegetables and meat are main sources of Ca intake. Calcium adsorption is increased by the presence of vitamin D. In literature, the linkage between the prevalence of cardiovascular


diseases and Ca-content of drinking water has been reported, however, the conclusion is that possible effects are confounded with factors such as smoking, dietary imbalances, physical activity, blood pressure, etc. (Masironi, 1983; Alexander, 1986). Hard Ca-rich water is saturated with high Ca salts, which originate from the geological layers though which the water has been seeping. Many households in Western Europe decalcify hard water to protect household equipment against deposits of CaCO3. In most cases, Ca is exchanged for Na, which effectively “softens” water. What people usually do not know is that the quality of their “soft” tap water certainly loses out in the process, as consumption of high quantities of Na ion may create metabolic imbalances.

F. CERIUM Illustrative for the complexity of geo-medicine is the study of Smith et al., 2000, on Mukono District, Uganda. They found a common cardiac disease, “endomyocardial fibrosis (EMF),” to be related to the presence of elevated levels of dietary Ce and deficient levels of dietary Mg. EMF is characterized by the growth of a thick meshwork of fibrous tissues (collagen and elastin) within the endocardium and heart valves (Davies, 1961). The presence of this thickened tissue significantly reduces the efficiency of the heart, resulting in both pulmonary and peripheral oedema. The disease is prevalent throughout the tropics—in Uganda, it constitutes the second or third most common form of heart disease amongst young children (Sezi, 1993; Freers et al., 1996 in Smith et al., 2000).

G. CHLORINE Chlorine in the form of the chloride anion occurs widely in foodstuffs, however, there is a wide variation in human intake in view of the kitchen salt added to the food at the table. In humans, 88% of chloride is extracellular and contributes to the osmotic activity of body fluids. Electrolyte balance is maintained by adjusting total dietary intake and by excretion via the kidneys and gastrointestinal tract. Toxicity of chlorides depends on the cations present; that of chloride itself is unknown. In the soil, chloride occurs in certain types of saline soils as NaCl, KCl, CaCl2 and MgCl2. All have a strong effect on osmotic pressure in the soil and hence influence crop yield. Toxicity of chlorides for crops depends on solubility—the more soluble ones as CaCl2 and MgCl2 being highly toxic. As WHO (1996b) proposes no health-based guideline for drinking water, it can be assumed that health hazard of chloride is no major cause of concern in the human diet.

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Most of the chlorine at the Earth’s surface is present in the oceans. Thus atmospheric supply of chlorine in the form of marine salt aerosols is a dominant source of chlorine in surface soil, at least in coastal regions (La˚g and Steinnes, 1976).

H. CHROMIUM The function of chromium in the human body seems closely associated with that of insulin, and most Cr-stimulated reactions depend on insulin (Anderson, 1981 in Oliver, 1997). It plays a role in carbohydrate and lipid metabolism, and for the utilisation of amino acids. Fresh food and Irish potatoes are a main source of chromium intake. At normal soil pH, chromium is present as Cr3þ, which is fairly insoluble and immobile. It is only under very acid soil conditions that Cr may be released in sizeable quantities from the exchange complex. Chromium is necessary in the human body as co-factor for insulin and henceforth plays a role in sugar metabolism. Chromium deficiencies may lead to arteriosclerosis. Excessive intake of chromium is associated with renal dysfunctions. It should be noted that toxicity of chromium depends on oxidation status—chromium (VI) is mutagenic whereas chromium (III) is not (WHO, 1996a). In epidemiological studies, an association is found between occupational exposure through inhalation to chromium (VI) and mortality due to lung cancer.

I. COPPER Copper deficiency is widespread all over the world. Copper deficiencies in plants are common with high soil pH, high organic carbon content and excessive drainage conditions. Copper plays an essential role in the human body as part of metalloproteins, e.g., haemoglobin. Zinc and iron are strong antagonists to Cu, and large intake of them can lead to Cu deficiency (Oliver, 1997). Copper deficiency may lead to typical disease symptoms such as anaemia, deformations of the skeleton, neural disorders, colour change of hair, degeneration of the heart muscle, reduced elasticity of arteries and loss of pigment in the skin. Copper deficiency in man is very rare but may occur in under-nourished children. Main sources are meat, mainly liver followed by fish, nuts and seeds. Geo-medical correlations with copper in human medicine remain inconclusive so far. In animals, both copper deficiency and copper poisoning problems related to natural pastures are quite common, in particular in sheep (Frøslie, 1990). In both cases, the condition may be influenced by the antagonistic effect on copper exerted by molybdenum. Thus the copper/molybdenum ratio in the feed is important, in particular with ruminants. Excess of molybdenum can cause copper deficiency at otherwise sufficient copper levels (molybdenosis), whereas


poisoning may occur at relatively moderate copper levels if the molybdenum intake is too low. Interestingly, copper deficiency and/or molybdenosis may have been the reason for a complex disease observed in moose in a region of Sweden affected by acidic precipitation (Frank, 1998). The clinical signs of this disease were multiple, including sudden heart failure and osteoporosis, and the reason was thought to be increased pH in soil and water in the moose environment and corresponding changes in plant availability of Cu and Mo.

J. FLUORINE Fluorine occurs in small but very variable quantities in almost all soils, groundwaters and animals (Havell et al., 1989) and forms an essential component of the bone and tooth glazing. Correlation between fluorine content in the human diet and the soil type was established for the first time in New Zealand (Ludwig et al., 1962). Adding fluoride to drinking water in fluorine-deficient areas has long been a point of strong debate. At present, it is generally accepted that these fluoride supplements to the drinking water are effective against tooth caries. A minimal level of 0.8 mg F/l seems to be required in drinking water to effectively offer protection against dental caries. When F concentrations in drinking water exceed 1 mg/l, mottling of the teeth will be the physical evidence of F toxicity (WHO, 1996b). This problem may be enhanced in hot climates where people drink more of high fluorine-containing water. Fluorine carency may also lead to osteoporosis. Most plants absorb little fluorine, except tea. The most important source of fluorine in human diet is sea fish and drinking water. Industrial fluorosis, associated with contamination of pastures with fluorides from industrial emissions, has been a problem in many countries, especially in the vicinity of aluminium smelters.

K. IRON Iron is an important element in all living organisms, as key component of haemoglobin, myoglobin and a number of enzymes. The most important iron sources in the human diet are meat, eggs, vegetables and cereals. Among traditional societies in Uganda, Smith et al. (2000) found evidence that direct ingestion of Fe via geophagia accounted for a major proportion of the RDI. Even though iron is one of the most common soil constituents, it is generally accepted that iron deficiency is the main form of food insufficiency in developed as well as developing countries (Borch-Iohnsen, 1994). Causes are many: (1) low iron content in the daily diet and/or low biological availability; (2) blood loss;

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(3) defect absorption mechanisms caused by bacterial infections; (4) parasites such as hook worms in developing countries. Iron deficiency causes anaemia. Mobility of iron in the soil depends on its redox potential, which in turn depends on soil pH, organic matter content, microbial activity, compaction and moisture content. The most important cause of plant-available iron deficiencies in soils is high pH, and especially the presence of free lime.

L. IODINE Iodine forms an essential part of the thyroid hormone thyroxine and triiodothyronine. Deficiency can lead to a broad spectrum of symptoms, the most spectacular of which is goitre, which is well known in humans as well as in domestic animals. There are other diseases related to iodine deficiency such as impaired mental function and cretinism. The latter is a serious affection with children, who appear to be normal at birth, but become physically and mentally retarded when they are 6 months old (Pharoah, 1985). Iodine intake via meat, fish and vegetables clearly mirror iodine concentrations of the soil environment. Iodine originates from the ocean, from where it is released from the sea surface as methyl iodide, subsequently transported to the land and deposited on vegetation and topsoil through wet and dry deposition. The iodine content of surface soils decreases rapidly with increasing distance from the sea (La˚g and Steinnes, 1976). High pH and large calcium content reduce the bioavailability of I and decrease its uptake by plants (Oliver, 1997). Iodine deficiencies in the soil may occur in areas where the iodine-containing topsoil has been removed by either glacial movement or soil erosion. From case studies we also know that long-standing leaching of the soil by percolation or by seasonal flooding may lead to iodine deficiencies, e.g., in the North American central plains, the lowlands of Central Africa and the Po plains in Italy (Meltzer and Glattre, 1992). Iodine deficiency is still quite common in sea-locked remote areas of sub-Saharan Africa such as the Ethiopian Highlands, mountainous zones of China, in the inter-Andine Depression in South America. In Europe, a strong contrast exists between the Scandinavian countries, where almost no goitre occurs (due to iodine additions to animal feed) versus south- and east-Europe, where the number of goitre cases seems to increase (Meltzer and Glattre, 1992). In the USA, iodine is currently added to kitchen salt in iodine-deficient zones. In South Africa, the use of iodized table salt has been a general practice for several decades now.

M. LEAD Lead is taken up through food, direct ingestion or inhaled as dust (Oliver, 1997). It is a widespread pollutant in soil in and around industrial metallurgy


plants; however, hot spots of lead in the environment may also occur where parent rock contains high levels of lead-bearing minerals. Lead in air is readily available for long-range atmospheric transport (Murozumi et al., 1969; Amundsen et al., 1992), which may lead to significant contamination of surface soils far away from the source region (Steinnes et al., 1997; Page and Steinnes, 1990). Reported effects of excessive intake of lead comprise: brain problems, hyperactivity and deficiency in fine motor functions.

N. MANGANESE Manganese appears to be a relatively neglected trace element in biogeochemistry and geo-medicine compared to the attention that is given to “popular” elements like zinc, iron, selenium and copper. Yet, manganese appears to be very important in human health. Most attention is given to its possible role as an anti-carcinogen. In a quantitative comparative study on possible relationships between trace element levels and cancer incidence, Marjanen and Sioni (1972) found a remarkably tight negative linear relationship between soil manganese content and cancer incidence (all types of cancer included) in a study comparing 179 parishes in Finland. A 3-fold decrease in cancer incidence was associated with increased soil manganese concentration. The “easily dissolved” manganese contents of old arable lands were much lower than those of new arable lands, clearly indicating the potential danger of exhaustive cropping. In the Transkei area of South Africa, cancer of the oesophagus became an “epidemic” outbreak shortly after World War II. This was not long after severe depletion and impoverishment of the soils in the 1930s when severe droughts were followed by torrential rains, leading to devastating erosion (Burrell et al., 1966). Very large differences in the incidence of the cancer occur between different districts and between different areas within a district. “Black spots” or “cancer gardens” were almost exclusively confined to areas underlain by Beaufort sediments (mainly mudstones and shales) (Marais and Drewes, 1962). Soils on the sediments are much less fertile and much more eroded than the soils on dolerite. A series of studies compared low and high-incidence districts in Transkei, low and high-incidence areas within a high-incidence district in Transkei and low and high-incidence areas in the Caspian littoral of Iran (Laker et al., 1981; Kibblewhite et al., 1984; Laker, 1999). The so-called “Asian oesophageal cancer belt” starts just east of the Caspian sea and runs from there all the way into the People’s Republic of China. In the detailed study within the high-incidence Butterworth district in Transkei, two strips with very high cancer incidence were separated by a strip where very few cancer cases occurred over 23 years. The low cancer incidence strip is of a different geology, most of it being dolerite dyke intrusions. In the high-incidence strip, 83% of the maize plants contained less than 40 mg/kg Mn (the discriminating value identified in

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the inter-district study), whereas in the low-incidence strip only 41% of the samples had such low values. The dolerite contained 881 mg/kg Mn, compared with only 332 mg/kg in the Beaufort sediments. In the Caspian littoral, the plantavailable Mn contents of the soils of the low-incidence area were much higher than those of the soils from the high-incidence area. The low-incidence area is characterized by very high rainfall (up to 1600 mm per annum) and highpotential soils with relatively low pH (Laker, 1978). In contrast, the highincidence area has extremely low rainfall and very poor quality soils with very high pH (. 7.5), rendering an element like manganese unavailable. From these studies, several geo-medical linkages become evident: (1) incidence of oesophagus cancer and geology; (2) these geological formations differ in Mn chemistry, which is reflected in the soil and also in maize plants growing on it; (3) soil degradation leads to nutrient deficiencies and may lead to increased incidence of oesophagus cancer; (4) factors leading to lower availability of Mn (drought, high pH) correlate with higher incidence of oesophagus cancer. In view of its redox capabilities, manganese could be seen as an anti-oxidant, which may explain its role in controlling certain types of cancer. This role may, however, be indirect, in view of the fact that vitamin C and vitamin B12 contents of plants depend upon the amount of manganese available to the plant (Marjanen, 1970). Vitamin C is the best-known anti-oxidant, which has also been proven to be a nitrite reductant, preventing nitrosamine production in the process. Nitrosamine is believed to be strongly carcinogenic. It is not impossible that the following chain reaction may be involved: low manganese availability in soil ! manganese deficiency in plants ! vitamin C deficiency ! nitrite accumulation ! nitrosamine production ! cancer (Laker et al., 1981). Furthermore Laker et al. (1981) point out that molybdenum, iron, copper, manganese and zinc are all involved in various steps of the reduction of nitrates to ammonia in plants and that deficiencies of any of these may also play a role in this chain. Fincham et al. (1981) speculated that the Mseleni Joint Disease (MJD), which they call a “strange affliction” of the hip of people of the Mseleni area on the northern KwaZulu-Natal coastal plain in South Africa, may be related to a manganese deficiency. They base this on the fact that the diet of the people consists mainly of maize grain produced by themselves on the highly leached, infertile albic sandy soils of the area and they believe such diet could never supply adequate manganese. An interesting response to this speculation came from Xilinas (1983): “Some years ago I reached a similar conclusion regarding congenital dislocation of the hip, the incidence of which is high in certain isolated areas of Southern Finistere (France), in Island Lake and Red Sucker Lake Farms in Manitoba (Canada) and in Many Farms Indians in Arizona (USA). Epidemiological studies led us to suggest that in Finistere the disease is caused by a manganese deficiency which results from the practice of alkalizing the soil, thereby impairing the absorption of manganese by plants and giving rise to severe manganese deficiency in all vegetation.”


These few examples regarding manganese illustrate the importance of understanding (1) pedogenesis and (2) effects that farming practices may have on supply of trace elements in human nutrition, e.g., land drainage or raising soil pH may lead to reduced Mn uptake by plant roots, hence lower Mn content in the harvested crops.

O. MERCURY For inorganic mercury in the environment, a distinction should be made between mercury (II) chloride which is readily soluble, the much less soluble mercury (I) chloride, and mercuric sulphide of very low solubility. Apart from the inorganic forms mercury may exist as methyl mercury or dimethyl mercury, which form under reducing conditions in water and other environments rich in organic matter. Methyl mercury is almost completely absorbed through the gastrointestinal tract and readily appears in the blood upon absorption. The greater intrinsic toxicity of methyl mercury as compared to inorganic mercury is due to its lipid solubility, which enables it to cross biological membranes more easily, especially to the brain and the spinal cord and peripheral nerves, and to cross the placenta (WHO, 1996b). Among consequences are concentric restriction of visual field, deafness, dysarthria and ataxia. An interesting case of organo-mercury poisoning occurred in Canada with the Cree Indians in the vicinity of James Bay (Dumont and Kosatsky, 1990). The area is renomated for its wet Podzols which produce mobile organic components which enter into the lake waters. In a bacterial process methyl mercury is formed and subsequently absorbed in the food chain via algae through fish, which is eventually eaten by the Indians.

P. MOLYBDENUM Molybdenum plays a biochemical role in enzymes of man and animals such as aldehyde oxidase and xanthine oxidase (Havell et al., 1989). Legumes, grains and organ meats are good sources of molybdenum; fruits, root, stem vegetables and muscle meat are poor ones (WHO, 1996a). As the minimum intake requirement of 180 mg/day is easily reached under a normal diet, molybdenum deficiencies are seldom the case. Molybdenum excess is also rare, however, it may lead to copper deficiency in animals due to the interaction between Cu and Mo as discussed above. Similarly Mo toxicity may occur in animals where soil Cu is low.

Q. PHOSPHORUS Phosphorus is essential in the skeleton, which contains 85% of the phosphate in the human body. Furthermore it plays an important role in energy metabolism

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as essential part of the adenosine triphosphate (ATP), and in a number of other essential functions. Phosphate is mainly taken up from protein-rich food such as milk, meat, fish and cereals. As almost all human foods contain relatively more phosphate, deficiencies are exceptional (Havell et al., 1989), but when they occur, that may lead to general weakness and pain in the bones. Excess uptake of phosphate may lead to renal and liver dysfunctions. Phosphate in soil is bound to organic matter or to clay and sequioxides. Transfer dynamics to plant roots are dependent on pH, effective CEC and redox potential. In strongly weathered soils (Ferralsols, Nitisols, Acrisols), phosphate may be completely fixed which may lead to severe phosphate deficiencies in crops. This results in extremely low yield levels of low-phosphate-containing cereals. The consequences of this phenomenon for human health have never been researched and warrant urgent attention. In Flanders, phosphate in groundwater has been a matter of concern in view of extremely high sewage sludge applications on sandy soils. Also here the phosphate mobility can be predicted from the free iron content of the soil.

R. POTASSIUM Potassium is the most important intracellular cation in the human body. Under normal circumstances, potassium intake via daily food consumption is ample to meet our requirements. Jasson (1991) discovered a striking geographical correlation between glacially truncated zones in the USA and colorectal cancers. These areas had in common a low K/Na ratio in the soil. Furthermore, it is interesting to note that anti-carcinogen agents such as vitamin A, carbon and fibres seem to result in an increase of the intracellular K/Na ratio, whereas products such as lipids, alcohol, cholesterol have the opposite effect (Jasson, 1991). Laker came to a similar conclusion in a geographically totally different area, namely in South Africa and the Iranian Caspian Sea catchment (Laker, 1978; Laker et al., 1981). He discovered in a large-scale study, an increase of oesophageal cancer in areas characterised by a low K status in the soil and a low K/Mg ratio (Laker et al., 1981; Kibblewhite et al., 1984). In Sweden, it was found that human intake of K was low, compared with the recommended dietary allowance, as was also the case with magnesium, zinc, copper and selenium (Abdulla et al., 1982).

S. MAGNESIUM As Mg – ATP complex, magnesium plays an essential role in all biosynthetic processes, glycolysis, formation of cyclic-AMP, energy-dependent membrane transport, and transmission of the genetic code. Magnesium deficiencies in


the human diet were so far reported only sporadically as the element is abundantly taken up by plants from the soil and gets into the human diet via leafy vegetables. Shortage of Mg may disturb electrolyte balance, whereas excessive intake is reported to cause overall weakness in the muscles (Havell et al., 1989).

T. NITROGEN Nitrogen in the human body is a core substance of most proteins. The major intake source is from vegetables and drinking water if nitrate concentrations of the latter are high. It is important to note that some of the nitrate in our body originates from bacterial endogenous nitrate synthesis. High concentrations of nitrate in food or drinking water may lead to microbial reduction of nitrate 2 (NO2 3 ) to nitrite (NO2 ) in the oesophagus and in the stomach when pH is higher than 4. In the stomach of healthy people, normal concentrations of nitrite are 2– 3 mol/l, whereas for people with hypo- or achlorhydria this number may rise to 30 –120 mol/l (Alexander, 1986; WHO, 1996a). Babies younger than 12 months may show achlorhydria because the stomach wall does not excrete acid in sufficient quantities. Whereas nitrate is relatively less toxic, the reduced form (nitrite) is involved in the oxidation of normal haemoglobin to methemoglobin, which is unable to transport oxygen to the tissues. This results in anoxia and cyanosis when about 10% of all haemoglobin is transformed. Most cases of methemoglobinemia are associated with nitrate contents in drinking water exceeding 25 mg N/l. It should be stressed, however, that this only applies to just-born babies. In adults, methemoglobinemia is a great exception and may be triggered by other affections of stomach and/or oesophagus. One may question if the huge cost on society to impose the general standard for drinking water at 10 mg nitrate-nitrogen is really warranted in view of the scanty scientific evidence for the ill-health effects of nitrogen in human metabolism. As babies are the major risk group, use of bottled water for babies would be the obvious solution to the problem. Furthermore, nitrite was shown to react in the human stomach to form N-nitroso compounds, most of which have been found to be carcinogenic in all animal species tested, so that they are probably also carcinogenic to humans (WHO, 1996b). Suggestive evidence relating dietary nitrate exposure to cancer, especially gastritic cancer, has been provided by geographical correlation or ecological epidemiological studies, but the results have not been confirmed by more definite analytical studies. Nitrate is very mobile in the soil—it can move almost freely via groundwater into deep-seated aquifers from where drinking water is pumped. Organic carbon is the key binding agent of nitrogen in the soil, from where it is slowly released through mineralization processes. Speed of nitrogen mineralization depends on soil type and climatic conditions. As nitrate is readily taken up by plants, nitrate levels of crops mirror nitrate status in the soil.

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U. SODIUM Although sodium is ubiquitous in drinking water, the major part of the daily sodium intake in humans comes from food. It is difficult to assess intake quantities in view of the fact that many people add salt to their food at the table. A high sodium diet has been associated with hypertension and certain diseases such as coronary heart diseases. The scientific base is controversial to say the least. The most striking evidence may be that in “non-westernized” populations diets are low in sodium, the prevalence of hypertension is low, and blood pressure does not increase with age. Although it is tempting to conclude that a causal relationship exists, a number of differences between “westernized” and nonwesternized populations might account for the difference (WHO, 1996b).

V. SELENIUM Deficiency of selenium in the human body leads to a decrease in activity of glutathione peroxidase, a selenium-containing enzyme that occurs in human tissue and provides protection against oxidation of lipid membranes (Morales et al., 1991). The most important role of this enzyme is protection against damage caused by oxygen radicals in cellular structures. In this way it is complementary to the activity of vitamin E, which also fulfils a role of anti-oxidant in the cell membrane (Frøslie, 1991). Selenium deficiency has been reported to lead to cardiovascular problems such as cardiomyopathy (Ringstad, 1986). In areas where soil selenium is low and people live mainly from locally grown food, such as in parts of China, severe problems associated with Se deficiency may occur. The first disease associated with Se deficiency was Kashin-Beck disease, discovered in 1849 in China (Oliver, 1997). It occurs in the mountains and hills of central China extending across the country from north-east to southwest (Xu and Jiang, 1986). It also occurs in eastern Siberia and North Korea. It is an endemic osteoarthropathy, which results in chronic arthritis and deformity of the joints in children and teenagers. In China, Zhu (1982), Vandenbergh (1982) and later Tan (1984) established the link between selenium deficiency and the Keshan disease. This is an endemic cardiomyopathy, whereby heart muscles are damaged. It is interesting to note that the disease seems more prevalent in the eroded hills where Regosols and Leptosols are dominating the soil scape. The lower lying Cambisols and Fluvisols were much better in selenium supply. Furthermore, it is of interest to note that different crops react differently in this selenium-poor environment. The selenium content of most cereals was rather deficient with the exception of rice, which seemed to concentrate selenium from the environment. People on a high rice diet clearly showed less selenium deficiency symptoms compared to people with other eating habits. Zhu (1982)


refers to the supplementation of Se via salt and tablets as early as 1974 in China. Since 1984, selenium is added systematically to the human diet in China via kitchen salt or by distribution of selenium tablets to the people. These additions resulted in a spectacular drop of the Keshan disease symptoms. Atmospheric deposition is one of the most important sources of selenium in the soil (La˚g and Steinnes, 1974; Steinnes, 1991). Selenium seems to originate from the sea from where it comes into the atmosphere as (CH3)2Se produced by bacteria. A second source of Se in the soil is atmospheric pollution. Selenium speciation in the soil depends on pH. In neutral or acid soils, selenite (SeO22 3 ) is dominant, which easily binds to iron to form the less-soluble iron selenite. In well-aerated alkaline soils, selenate (SeO22 4 ) becomes important, which is readily taken up by plant roots (Sogn et al., 1991). Almost all Se in humans is taken in by food, the content of which is set by the soil conditions in the place of origin. In view of its widespread deficiency, selenium is added to mineral fertilisers in Finland and New Zealand at a rate of 6 g Se per ton fertiliser (Sippola and Jansson, 1991). As a consequence, it is estimated that Se uptake by man has increased 5-fold in the target area. So far, no clear scientific evidence has been reported on the effect of this increased Se uptake on human health status. Last but not the least it should be noted that excessive levels of selenium intake may cause toxicity in man and animals.

W. ZINC Zinc is one of the most important essential trace elements in human nutrition. It is essential for the functioning of so many enzymes. A small selection of these include: (1) its utmost importance during pregnancy, pregnant women requiring much more zinc in their diet than otherwise (Jameson, 1982), (2) its importance for brain growth in infants (Prohaska, 1982), (3) its extreme importance in immunocompetence (Nauss and Newberne, 1982) and (4) its possible role as anti-carcinogen. Next to whole grains, pulses and unpolished rice, red meat is an important source of daily Zn intake (Oliver, 1997). Zinc deficiency was first observed and reported among rural inhabitants of the Middle East in the early 1960s (Nauss and Newberne, 1982). Zinc deficiencies are not uncommon in the diet of the population in USA, with children inter alia exhibiting zinc deficiency “although there has been little evidence for nutritional deprivation” (Nauss and Newberne (1982). Dietary zinc deficiencies are also found in Sweden and other industrialised countries (Abdulla et al., 1982). After phosphate, zinc is the nutrient element, the deficiencies of which are probably the most widespread in the world under natural conditions (Laker, 1964). In the late 1950s, only phosphate was applied more widely on croplands of the USA than zinc. During the mid-1960s, zinc deficiencies became such a big problem in the maize-growing areas of South Africa that zinc was included in commercial NPK

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fertilizers and super phosphate, a practice that is still being followed. In view of the widespread natural occurrence of low Zn contents in virgin soils, widespread zinc deficiencies can be expected in the diets of people in developing countries. The availability of Zn depends on pH: it is mobile at slightly acidic conditions and is immobilized in alkaline soils. Reported antagonisms with zinc in the soil have been reported, e.g., for P, Ca, Fe, Cu and Ni. Zinc concentrations in crops reflect what is available in the soil. Zinc deficiencies occur mainly on sandy soils and on soils with a pH (water) of more than 6.0, hence continuous fertilization may induce severe zinc deficiencies. Maize is a very poor accumulator of zinc, especially the higher yielding hybrids (Laker, 1964). This is a very important negative factor in a region such as southern Africa, where maize is the main staple food for the majority of the population.

VII. GEO-MEDICAL ISSUES RELATED TO UNDER-NUTRITION AND MALNUTRITION From the foregoing, it has become clear that human health problems due to mineral deficiencies mainly occur in poor communities where daily calorie intake is insufficient. A major problem in developing countries is that poor people do not have access to a sufficient quantity of high-quality foods, for lack of purchasing power for food from elsewhere. Whereas in high-income countries the focus of geo-medicine goes to excess situations, in low-income countries the opposite holds true. Health status of people strongly correlates to land carrying capacity, which is defined as the number of people that can be fed in a balanced way, without compromising future generations to be fed (De Cuypere et al., 1995). The carrying capacity of the land is influenced by (1) the genetic diversity of species; (2) productivity of the soil; (3) the climate; (4) the quantity and the quality of water resources. From FAO estimates, it can be established that some 22% of the world land area is potentially suitable for agriculture. About half of this (1475 million ha) is presently under cultivation, out of which some 230 million ha are irrigated (Dudal, 1992). It can be concluded that the natural resources should be ample to safeguard a balanced feeding regime to all people who presently live on the globe. Many (e.g., Borlaug and Dowswell, 1994) are of the opinion that the problem of under-nutrition is not so much a matter of production capacity, but rather relates to an inequitable distribution of wealth. This poverty in South countries is a threat to the sustainability of the agricultural enterprise itself. As the poor lack the means to appropriately intensify agriculture, they often have no choice but to over-use or misuse the natural resource base to meet their basic needs.


The problem of malnutrition in sub-Saharan Africa has not improved over the last 20 years. Soil fertility research should receive the highest priority in this region. Related to geo-medical issues in relation to under-nutrition, the key issue is severe deficiency of macronutrients such as N, P and K in developing countries/areas. Unlike the present situation in developed countries/areas, deficiencies of macronutrients are crippling crop production, and export figures of NPK in terms of exported cash crops are sky rocketing. In the Western World, people are a.o. concerned about excessive phosphate levels in the soil. The opposite holds true for Africa, where P applications will have to quadruple in order to achieve sustainability. It is estimated that 80% of this nutrient will have to come in the form of inorganic fertilisers, because the other sources are too small to cope with what is actually required. People tend to forget that initially high crop yields in developed countries were possible only because of high P applications to overcome the inherent P deficiencies in virgin soils. They, of course, did not take account of the fact that P builds up in the soil and did not cut back to subsistence application levels. It is a pity to note that Western ignorance, short-sightedness and biases created by the problem of overfertilisation seems to lead to deprivation of South countries of the absolutely essential agricultural inputs, which are indispensable for sustainable development (Laker, 1993). In terms of geo-medicine, the vast under-nutrition that presently prevails in South countries, is not only in total dietary intake and quality of the diet, but especially in terms of intake of essential nutrients. Under- and malnutrition of pregnant women, infants and young children lead to permanent damage to such children from which they can never recover. Zinc is, e.g., essential for brain growth (Prohaska, 1982). Zinc deficiencies (and some other element deficiencies) during pregnancy or infancy can cause permanent under-development of the brain, putting the person at a permanent disadvantage not because of hereditary reasons but because of the nutrient element deficiency at a critical developmental stage. Certain mineral element deficiencies during infancy and young childhood lead to dwarfism (e.g., Fincham et al., 1981).

VIII. GEO-MEDICAL ISSUES AND CONTAMINATED LAND POLICIES In Western Europe, people only recently started to take the threat of soil pollution seriously. Most of the pollution cases concern point events, which require in the best cases treatment of the soil over a limited surface (e.g., industrial terrain surrounding non-ferro industries, fertiliser factories, tanneries, etc.). Other types of more regional soil contamination concern contaminations either caused by emissions from non-ferrous industries, cadmium-containing

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phosphate fertilisers, pollutants redistributed by rivers, etc. A difference should be made here on basis of land use. In soils under forest cover, pollution with heavy metals is more acute in view of the low pH that prevails in these soils. The contaminants are therefore mobile and can either be taken up by plants or move towards the groundwater table. In line with findings by Steinnes (1991) in Norway, the threat of cadmium is far less in agricultural land due to the high pH and the dilution effect of cadmium over the entire plough layer. However, when agricultural land is taken out of cultivation, as recommended by the EU set-aside policy, the sudden drop in soil pH may trigger a number of heavy metals to dissolve and move towards the groundwater table.

IX. CONCLUSIONS From this literature review it is clear that important correlations exist between human health and chemical substances in the soil environment. This relationship applies to macronutrients such as potassium and nitrate as well as to micronutrients such as fluorine, iron, iodine, manganese, zinc and selenium. In a number of cases, the levels of these elements in the soil environment could be linked to soil genetic processes and factors of soil formation. Bear (1958, pp. 274 – 283) already outlined these relationships for a number of trace elements, as did Kubota in the USA in a number of papers summarized by Kubota (1981). Understanding of soil genesis in the landscape may therefore be a key for early discovery of geo-medical issues. More research is needed, however, to come to a better understanding of cause – effect relationships. Great geographical differences exist in geo-medical issues in the world. Whereas most South countries struggle with mineral deficiencies, caused among others by malnutrition and large-scale nutrient mining, the Western world is only now discovering the problems related to excesses of soil pollution. Although the surface areas of polluted land are limited, they are important due to their location in the vicinity of urban areas or by the threat they pose for groundwater contamination. Geographical data of geo-medicine are abundant, but unfortunately dispersed between the geo-chemists on the one hand and the medical scientists on the other. Real progress in the field of geo-medicine will depend on effective multidisciplinary interaction and cooperative research between experts in fields such as human and animal health, nutrition and the earth sciences, including soil science. Relations between human health and the environment are very complex and so far poorly understood—there is need for a more holistic approach.


Precise geo-referencing of both geo-medical data as well as accurate geochemical mapping of element concentrations and pathways are the way forward. A GIS approach is called for. Scope for future geo-medical studies: † ethnographic and nutritional studies of geophagia in traditional societies (Smith et al., 2000); † determination of bioavailability of essential and potentially toxic trace elements in areas of the world in which geophagia remains a common practice; † survey of baseline composition of trace elements in original parent materials, soils and geophagic materials; † distinction between naturally occurring geo-chemical hazards versus humancaused pollution situations; † assessment of naturally occurring attenuation mechanisms leading to lower transfer of elements to plants and hence lower concentrations in the food chain (Cappuyns et al., 2002a,b); † feasibility of cropping different species and cultivars to deliberately modify the supply of mineral elements in the diet in developing countries (Oliver, 1997); † optimal daily dose of elements from the environment, safe limits for trace element concentrations—how they affect health; † concentrations of elements in the soil atmosphere and resulting bioavailability þ toxicity/deficiency in the diet.

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Scott, R., Aughey, E., Reilly, M., Cunningham, C., McLelland, A., and Fell, G. S. (1982). The cadmium content in human kidneys. In “Trace Element Metabolism in Man and Animals” (J. M. Gawthorne, J. M. Howell, and C. L. White, Eds.), pp. 445–449. Springer, Berlin. Scottish Agricultural Research Institutes (1982). Trace element deficiency in ruminants. Report of a study group, Scottish Agricultural Colleges, Edinburgh. Sezi, C. L. (1993). Current status of endomyocardial fibrosis in Uganda. In “Endomyocardial Fibrosis” (M. S. Vallathan, K. Somers, and C. C. Kartha, Eds.), pp. 10–16. Oxford University Press, Oxford. Sharman, G. (1992). Seasonal and spatial variation in Rn-222 and Rn-220 in soil gas, and implications for indoor radon levels. Environ. Geochem. Health 14, 113 –120. Sippola, J., and Jansson, H. (1991). Experience with selenium intermixture in commercial fertilisers in Finland. In “Human and Animal Health in Relation to Circulation Processes of Selenium and Cadmium” (J. La˚g, Ed.), pp. 191–198. The Norwegian Academy of Science and Letters, Oslo. Smith, B., Chenery, S. R. N., Cook, J. M., Styles, M. T., Tiberindwa, J. V., Hampton, C., Freers, J., Rutkinggirwa, M., Sserunjogi, L., Tomkins, A. M., and Brown, C. J. (1998). Geochemical and environmental factors controlling exposure to cerium and magnesium in Uganda. J. Geochem. Explor. 65, 1–15. Smith, B., Rawlins, B. G., Cordeiro, M. J., Hutchins, M. G., Tiberindwa, J. V., Sserunjogi, L., and Tomkins, A. M. (2000). The bioassessibility of essential and potentially toxic trace elements in tropical soils from Mukono District, Uganda. J. Geol. Soc., London 157, 885–891. Sogn, L., Skorge, P., Froslie, A., Aasen, I., Stabbetorp, H., and Ruud, L. (1991). Effects of selenium enriched complex fertilisers on selenium concentrations of small grains. In “Human and Animal Health in Relation to Circulation Processes of Selenium and Cadmium” (J. La˚g, Ed.), pp. 199 –211. The Norwegian Academy of Science and Letters, Oslo. Soil Survey Staff, (1998). “Keys to Soil Taxonomy”, 8th edn. Steinnes, E. (1990). Effects of natural ionizing radiation. In “Geomedicine” (J. La˚g, Ed.), pp. 163 –169. CRC Press, Boca Raton, FL. Steinnes, E. (1991). Influence of atmospheric deposition on the supply and mobility of selenium and cadmium in the natural environment. In “Human and Animal Health in Relation to Circulation Processes of Selenium and Cadmium” (J. La˚g, Ed.), pp. 137–152. The Norwegian Academy of Science and Letters, Oslo. Steinnes, E., Solberg, W., Petersen, H. M., and Wren, C. D. (1989). Heavy metal pollution by long range atmospheric transport in natural soils of Southern Norway. Water Air Soil Pollut. 45, 207–218. Steinnes, E., Allen, R. O., Petersen, H. M., Rambæk, J. P., and Varskog, P. (1997). Evidence of large scale heavy-metal contamination of natural surface soils in Norway from long-range atmospheric transport. Sci. Total Environ. 205, 255–266. Swindon Health Authority (Department of Public Health), (1992). “Infant Mortality in Swindon”. Swindon Health Authority, Swindon. Tan, J. (1984). Selenium ecological chemo-geography and endemic Keshan disease and the KaschinBeck disease in China. In “Selenium in Biology and Medicine”. Third International Symposium, Beijing, PRC (G. F. Combs, and S. B. Combs, Eds.), pp. 859–876. Van Nostrand Reinhold Company, New York. Thornton, I. (1996). Sources and pathways of arsenic in the geochemical environment: health implications. In “Environmental Geochemistry and Health”. Special Publication No. 113 (J. D. Appleton, R. Fuge, and G. J. H. McCall, Eds.), pp. 153– 161. Geological Society, London. Tseng, W. P. (1977). Effects of dose-response relationships on skin cancer and Blackfoot disease with arsenic. Environ. Health Perspect. 19, 109– 119. UNSCEAR, (1982). “Ionozing Radiation: Sources and Biological Effects”. United Nations Scientific Committee on the Effects of Atomic Radiation, 1982 Report to the General Assembly. United Nations, New York.

STATE OF THE ART ON SOIL-RELATED GEO-MEDICAL ISSUES 35 Vandenbergh, D. A. (1982). “Selenium Impact: Multidisciplinair Onderzoeksproject”. Universitaire Instelling Antwerpen, Antwerpen, 175 pp. (in Flemish). WHO, (1973). “Trace Elements in Human Nutrition”. Technical Report Series No. 532. World Health Organisation, Geneva. WHO, (1992). “Health Criteria 134. Cadmium”. World Health Organisation, Geneva. WHO, (1996a). “Elements in Human Nutrition and Health”. World Health Organisation, Geneva. WHO, (1996b). “Guidelines for Drinking-Water Quality”. World Health Organisation, Geneva. W. W. Wenzel, D. C. Adriano, B. Alloway, H. E. Doner, C. Keller, N. W. Lepp, M. Mench, R. Naidu, G. M. Pierzynski (Eds.) (1999). Proceedings of Extended Abstracts: Fifth International Conference on the Biogeochemistry of Trace Elements, Vienna , Vol. I, pp. 1–598. International Society For Trace Element Research, Vienna. W. W. Wenzel, D. C. Adriano, B. Alloway, H. E. Doner, C. Keller, N. W. Lepp, M. Mench, R. Naidu, G. M. Pierzynski (Eds.) (1999). Proceedings of Extended Abstracts: Fifth International Conference on the Biogeochemistry of Trace Elements, Vienna, Vol. II, pp. 599–1190. International Society For Trace Element Research, Vienna. Xilinas, M. E. (1983). Manganese intake and congenital dislocation of the hip. S. Afr. Med. J. 63, 393. Xu, G. L., and Jiang, Y. F. (1986). Selenium and the prevalence of Keshan disease and Kashin-Beck disease in China. In “Proceedings of the First International Symposium on Geochemistry and Health” (I. Thornton, Ed.), pp. 192–204. Science Reviews Ltd, Northwood, UK. Zhu, L. (1982). Keshan disease. In “Trace Element Metabolism in Man and Animals” (J. M. Gawthorne, J. M. Howell, and C. L. White, Eds.), pp. 514–517. Springer, Berlin.


GASEOUS EMISSIONS OF NITROGEN FROM GRAZED PASTURES: PROCESSES, MEASUREMENTS AND MODELLING, ENVIRONMENTAL IMPLICATIONS, AND MITIGATION Nanthi S. Bolan,1 Surinder Saggar,2 Jiafa Luo,3 Rita Bhandral1 and Jagrati Singh1 1

Institute of Natural Resources, Massey University, Palmerston North, New Zealand 2 Landcare Research, Palmerston North, New Zealand 3 AgResearch, Hamilton, New Zealand

I. Introduction II. Nitrogen Input in Grazed Pasture A. Biological Fixation B. Fertilizer Application C. Deposition of Animal Excreta D. Manure Application and Effluent Irrigation III. Nitrogen Dynamics in Pasture Soils A. Biotic Transformations B. Abiotic Transformation IV. Gaseous Emission of Nitrogen from Grazed Pasture A. Ammonia Volatilization B. Denitrification V. Factors Affecting Gaseous Emission A. Ammonia Volatilization B. Denitrification VI. Measuring and Modelling Gaseous Emissions A. Measurement Techniques B. Modelling Approaches VII. Environmental Implications of Gaseous Emissions A. Acid Rain B. Ozone Depletion and Global Warming VIII. Management Practices to Control Gaseous Emission IX. Conclusions and Future Research Needs Acknowledgements References

37 Advances in Agronomy, Volume 84 Copyright q 2004 by Elsevier Inc. All rights of reproduction in any form reserved. DOI 10.1016/S0065-2113(04)84002-1

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“One feature that has become increasingly clear is that large gaseous and leaching losses are liable to occur from the livestock excreta returned to the soil by grazing animals. Urine patches in particular contain extremely high but localized concentrations of plant-available N. These concentrations greatly exceed the uptake capacity of the grass, and urine patches are therefore especially susceptible to ammonia volatilization, denitrification and leaching” (Whitehead, 1995)

Grazing-managed pasture is a major system of livestock production in many countries. Grazed pastures receive large inputs of nitrogen (N), derived from biological fixation of atmospheric N, through the addition of manures and fertilizers, and the deposition of animal excreta. However, only a small proportion of the N (,15%) consumed by grazing animals is converted to milk or live weight gain, the reminder is excreted. Loss of N occurs mainly through ammonia (NH3) volatilization, release of gaseous N such as nitric oxide (NO) and nitrous oxide (N2O) through biological denitrification, and nitrate (NO2 3 ) leaching, which has both economical and environmental implications. Nitrogen is an important plant nutrient and its loss affects both the quality and quantity of feed, thereby leading to poor animal production. Recently there have been increasing concerns about the environmental impacts of N loss through leaching (i.e., methaemoglobinaemia) and gaseous emission (i.e., greenhouse gas). In this chapter, the various sources of N input to grazed pasture are discussed in relation to the dynamics of N, the measurement and modelling gaseous emissions of N, and the implications of gaseous emission in relation to economic loss and environmental degradation. The dynamics of N transformations in soil–plant system with particular emphasis on the biochemistry of gaseous emission, and the measurement techniques and the use of process-based models to predict gaseous emissions are discussed. The practical implications of gaseous emission are discussed in relation to acid rain and climate change (i.e., the Kyoto Protocol). Grazing and farm management practices to mitigate gaseous emissions are highlighted. q 2004 by Elsevier Inc.

I. INTRODUCTION With the estimated increase in world human population from 5.4 billion in the 1990s to 8.5 billion by 2025, an increase in food production of 60 –70% will become necessary to meet world food demands and to minimise malnutrition. With the continuous decline in the availability of land area for crop production, the increase in food demand is likely to be met mainly through intensive animal production.

GASEOUS EMISSIONS OF NITROGEN

39

Managed pastures cover about 20% of the earth’s land surface and rangelands cover another 30% (Snaydon, 1981). Of this total area, only a small proportion was originally under natural grassland and most of this has now been affected by humans. Unlike natural rangeland pastures, the managed pastures are highly productive as increased pasture production leading to higher per-hectare animal productivity is the major goal for the pastoral farmers. A significant portion of world milk (27%) and beef (23%) production is derived from managed pastures (Sere et al., 1995). The continued existence and the productivity of managed pasture depends on management practices, such as grazing intensity and frequency, burning and cultivation, resowing and renovation, recycling of animal wastes, fertilizer application, and pesticide use. The fertility of pasture soils can be substantially altered by grazing animals, mainly through the deposition of dung and urine and their subsequent transformation and transport in soils (Haynes and Williams, 1993). Grazing-managed pastures is a major system of livestock (i.e., sheep, beef and dairy cattle, and deer) production in many countries. In grazed pastures, nitrogen (N) is derived from biological fixation of atmospheric N, through the addition of manures and fertilizers, and the uneven deposition of animal excreta. In nonlegume-based pastures, such as grass pastures in Europe, most N is derived from fertilizer and manure application. Although in legume-based pastures most of the N is derived from biological N fixation, a small amount of N is traditionally added during the early spring season, mainly to overcome the deficiency caused by the slow rates of biological fixation and mineralization of soil organic matter (SOM). There has recently been a steady increase in N inputs to grazed pastures and this increase is expected to continue in the foreseeable future. Increased fertilizer N inputs along with continued high intake of animal protein in developed countries and changes in diet of people in developing countries are likely to exacerbate the N losses from global food production (McCarl and Schneider, 2000; Mosier et al., 2001). The increasing N input to grazed pastures has rekindled the debate on its impact on atmospheric, terrestrial and aquatic environments. Loss of N, occuring mainly through ammonia (NH3) volatilization, biological denitrification and nitrate (NO2 3 ) leaching, has both economical and environmental implications. Conventionally, most research on N loss has been examined in relation to economic implications. Nitrogen is an important plant nutrient and its loss affects both the quality and quantity of feed, thereby leading to poor animal production. Recently, however, there have been increasing concerns about the environmental impacts of N loss through leaching and gaseous emission. For example, an increase in NO2 3 concentration in groundwater resulting from leaching has been linked to increasing incidences of NO2 3 toxicity in human and livestock (i.e., methaemoglobinaemia). Similarly, grazed pastures are identified as an important source of NH3 and nitrous oxide (N2O), which are implicated in acid rain, ozone depletion and global warming (i.e., greenhouse gas). Although a number of reviews have examined the economic and health

40

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impacts of NO2 3 leaching (Di and Cameron, 2002), there has been no comprehensive review of the environmental impacts of gaseous emission of N from grazed pasture. The present review brings together fundamental aspects of the dynamics of N in grazed pastures, recent developments in the measurement and modelling of spatially and temporarily variable gaseous emissions, and the implications of gaseous emission of N for economic loss and environmental degradation. The article first outlines the various sources of N input to grazed pasture. It then discusses the dynamics of N transformations in soil – plant system with particular emphasis on the biochemistry and factors affecting the processes of gaseous emission of N. Farm-scale and site-specific measurement techniques and the use of process-based models to predict gaseous emissions for developing national inventories are described. The practical implications of gaseous emission are discussed in relation to acid rain and climate change (i.e., the Kyoto Protocol). Future research should aim to focus on grazing and farm management practices to minimise gaseous emission of N in pasture soils and to explore further the role of soil amendments in influencing gaseous emissions of N.

II. NITROGEN INPUT IN GRAZED PASTURE A. BIOLOGICAL FIXATION In many countries including Australia, New Zealand and parts of North America and Europe, the use of legume-based pasture is the most common grazing management practice. In such pastures, N is derived mainly from the biological fixation of atmospheric N by a group of bacteria (known as rhizobium) living in the root nodules of the legume plants. The amount of biological N fixation depends on a number of factors including legume species, soil and climatic conditions, nutrient supply and grazing management (Table I). For example, biological N fixation rates in the range of 100 – 300 kg N ha21 yr21 are common for grass/clover pastures in New Zealand (e.g., Ledgard et al., 1990). High levels of available P in soils are required to maintain both the presence and N2-fixing activity of legumes in the legume-based pastures and the N input in these pastures. Similarly, adequate levels of other nutrients such as sulphur and molybdenum, in particular, are required. In soils where the concentration of inorganic N is high, legumes tend to utilize soil N, which results in less biological N fixation. Nitrogen fertilizer addition to pasture soils has often been shown to decrease biological N fixation. For example, in New Zealand, with increasing N addition N fixation by clover continued to decrease and the percentage decrease varied between 30 and 70%, depending on the time of application and the grazing management (Ledgard et al., 1996).


41

Table I Selected References on Biological Nitrogen Fixation in Grazed Pastures Dominant legume species

Proportion of legume (%)

Amount of N fixed (kg N ha21 yr21)

White clover White clover White clover

– 28 73–75

190 184 227 –268

New Zealand New Zealand Switzerland

Red clover

61–92

165 –373

Switzerland

White clover

50

155 –171

United Kingdom

White clover White clover White clover

– 13–27 8–20

57 –135 104 –175 20

White clover

56.8

294

Australia New Zealand South-west Victoria (Australia) South Africa

Causcasian clover White clover White clover White clover

52.8

232

New Zealand

Pakrou and Dillon (2000) Widdup et al. (2001)

16.8 9–20 23

112 79 –212 33

New Zealand New Zealand Australia

Widdup et al. (2001) Ledgard et al. (2001) McKenzie et al. (2003)

Country

Reference Crush (1979) Hoglund et al. (1979) Boller and Nosberger (1987) Boller and Nosberger (1987) McNeill and Wood (1990) Smith et al. (1993) Spronsen et al. (1997) Riffkin et al., 1999

Various reasons have been given for the decrease in N fixation due to N fertilizer application (Fig. 1). These include: (1) inhibition of infection of legume roots by nodule bacteria and decrease in effective nodule formation; (2) inhibition of nitrogenase enzyme activity in the nodule due to modification of the nitrogenase iron protein, decrease in bacterial membrane potential and the inhibition of the leghaemoglobin; (3) decrease in the supply of photosynthate to the rhizobium due to the assimilation of mineral N in the shoot; and (4) decrease in legume growth with fertilizer N application mainly due to an increased competition by the grass (O’Connor, 1982).

B. FERTILIZER APPLICATION Fertilizer applications have greatly increased pasture production on many grassland soils that are inherently deficient in nutrients. The high-yielding improved pasture species used for managed ecosystems are generally adapted to high-fertility conditions and do not perform well in less-fertile soils.

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Figure 1 Effect of inorganic nitrogen on biological nitrogen fixation.

Nitrogen fertilizers are used widely in the grass-based intensive pasture production of Europe and the North America. Pure grass pasture often responds linearly up to 200 –400 kg N ha21 yr21 and application rates in this range are common (Whitehead, 1995). Where pastures are cut for conservation, large quantities of nutrients are removed and the optimum N rate can be greater than that under grazed swards, where N is returned to pasture in the form of animal excreta (see below). In legume-based pastures, a small amount of N fertilizer is traditionally added mainly during the winter/spring period for a number of reasons. First, any marginal increase in pasture production during this period is likely to have a high return in terms of milk production because of low pasture growth rates and high feed requirements by the lactating cows. Second, during the winter/spring period the rate of biological N fixation by legumes is not adequate enough to meet the demands of the pasture. Third, the rate of mineralisation of organic matter is very slow, especially during the winter period, 2 which results in low levels of mineral N [ammonium (NHþ 4 ) and NO3 ] for plant uptake; hence pasture plants respond to N fertilizer application. The recent sudden increase in the sale of N fertilizers is attributed to increased use in horticultural and agricultural industries including grazed pasture. Various reasons have been given for this increase: (1) extra feed can be produced throughout the year that can be used to increase the stocking rate, achieve early


43

calving, extend lactation later into autumn and make more high-quality silage to feed later in the lactation; (2) feed obtained from the N fertilizer application can be used to replace more expensive feed supplements; (3) the productivity and the profitability of the farm can be increased by fertilizer N application; and (4) the cost of N as a percentage of milk fat price has decreased from 24 to 15% during the past 10 years, inducing farmers to use more N fertilizers. The most common N fertilizers used in grazed pastures include urea (46% N), ammonium sulphate (21% N), diammonium phosphate (DAP; 18% N), and organic manures such as “blood and bone” (8% N). The form of N fertilizer used on dairy pastures depends not only on the cost per unit N but also on the overall efficiency of the fertilizer N. Such efficiency varies among fertilizer forms, which is attributed to the difference in the effects of fertilizers on the rate of uptake and assimilation of N, the losses of N through NH3 volatilization, denitrification and leaching, the N-induced cation/anion balance in the plants, and the acidifying effects of N. The effects of fertilizers on the above processes should be considered before any decision is made on the choice of N fertilizer for grazed pastures.

C. DEPOSITION

OF

ANIMAL EXCRETA

In grazed pastures, a substantial amount of N is recycled through the direct deposition of animal excreta. Cattle retain up to 20% of the total N intake via fodder and feeds in animal products (i.e., milk and meat). The remaining intake is excreted in urine and faeces. The proportion of total N intake excreted and its partition between urine and faeces is dependent on the type of animal, the intake of dry matter, and the N concentration of the diet (Whitehead, 1970, 1986). For sheep and cattle, faecal excretion of N is usually about 0.8 g N 100 g21 of dry matter consumed, regardless of the N content of the feed (Barrow and Lambourne, 1962; Whitehead, 1995). Similarly, Lantinga et al. (1987) found that, irrespective of the N level of feed intake, dairy cattle excreted an average of 132 g N cow21 day21 in the form of faeces. The majority of the N is excreted in the urine and the proportion of N in the urine increases with increasing N content of the diet. Barrow and Lambourne (1962) found that for sheep ingesting herbage containing . 4% N, 80% of the N was excreted as urine, whereas with herbage containing 0.8% N, the proportion of the excreted N in the urine was only 43%. In most intensive high-producing pasture systems, where animal intake of N is high, more than half the N is excreted as urine. Oenema et al. (1997) observed that sheep and dairy cattle excreted 70– 75% and 60– 65% of N in urine, respectively, when grazing N-rich grass/legume pastures. The concentration of N in urine may vary from 1 to 20 g N l21 because of factors such as N content in the diet and the volume of water consumption, but is normally in the range of 8 – 15 g N l21 (Whitehead, 1970). The proportion of urine N present as urea increases with an increase in N intake

44

N. S. BOLAN ET AL.

(Topps and Elliott, 1967). Typically, over 70% of the N in urine is present as urea; the rest consists of amino acids and peptides (Haynes and Williams, 1993). The bulk of the N in faeces is in organic form. About 20 – 25% of faecal N is water-soluble, 15 –25% is undigested dietary N, and the remaining 50 – 65% is present in bacterial cells (Oenema et al., 1997). Grazing animals deposit excreta unevenly across the pasture. The distribution of nutrients in grazed pasture returned in the form of dung and urine is greatly influenced by stock behaviour (e.g., camping of stock in small areas of the field) and stock management (e.g., having separate fields for day time and night time grazing). Cattle excreta cover a larger area than sheep excreta. The surface area of cattle dung patches is about 0.05 –0.09 m2; that of sheep dung patches is about 0.007 – 0.025 m2. Cattle and sheep urine patches (wetted area) cover about 0.19 –0.49 m2 and 0.03 m2, respectively. Due to diffusion, some of the nutrients in urine, such as N and K, cover a greater surface area than that covered by the urine water: N deposition ranges from 20 – 80 g m22 in dung patches to as high as 50– 200 g m22 in urine patches (Oenema et al., 1997). Animals generally deposit more excreta on areas where they congregate (stock camps)—beneath trees and hedges, around gateways and water troughs, on areas away from roadsides, and on ridges and hillcrests on hill country farms (Gillingham and During, 1973). A proportion of excreta is deposited when the animals are not on the pasture but are on non-productive areas of the farm, such as feeding platforms, stock-handling sheds, milking sheds, yards, and raceways (MacDiarmid and Watkin, 1972b). On hill country pastures, stock tend to camp on flat areas of land, and significant quantities of nutrients are transported to these areas from the steeper slopes where the sheep and beef cattle graze (Gillingham and During, 1973; Rowarth and Gillingham, 1990; Saggar et al., 1990a,b). Measurements on hill country lands have shown that 60% of dung and 55% of urine are deposited in campsite areas that occupy only 15 –31% of the total land area (Saggar et al., 1990a). As a result of this uneven pattern, there is a build-up of nutrients in the campsite areas and depletion in nutrient status on the remainder of the pasture. As stocking rate increases there is less tendency for animals to camp and consequently a more even distribution of excreta over the paddock. This leads to reduced transfer losses of nutrients and more efficient cycling of nutrients within the system. Thus, increasing the stocking rate through subdivision of paddocks and the use of rotational grazing rather than set stocking can reduce the camping effects on nutrient transfer. For farms that are not equipped to redistribute the effluent back onto the pasture, the nutrients in the excreta are lost from the pastoral area. For example, on dairy farms where cows are taken off the pasture twice a day for milking, the amounts of nutrients lost this way have been estimated as 2– 11 kg N, 4 –14 kg K, 0.5 – 3 kg P, and 1– 2 kg S cow21 yr21 (Goold, 1980; Williams et al., 1990).


D. MANURE APPLICATION

AND

45

EFFLUENT IRRIGATION

Due to ever-increasing production of livestock and poultry products for human consumption, more and more manure by-products from these industries have to be dealt with to abide by environmental regulations, including safe disposal onto land. Confined animal production (i.e., beef and dairy cattle, poultry and swine) is the major source of manure by-products in most countries. For example, of about 900 million Mg (tonne) of organic and inorganic agricultural recyclable by-products generated in the US, approximately 45.4 million Mg are dairy and beef cattle manure, and 27 million Mg are poultry and swine manure. These manure by-products generate annually about 7.5 million Mg of N and 2.3 million Mg of P, compared with 9 million Mg of N and 1.6 million Mg of P that are applied to agricultural land in the form of commercial fertilizers (Bolan and Adriano, 2004). In countries such as Australia and New Zealand, where open grazing is practised, large amounts of manure are directly deposited onto pastureland. The manure by-products have the potential to be recycled on agricultural land (Eck and Stewart, 1995). Beneficial use through land application is based on their ability to favourably alter soil properties, such as plant nutrient availability, soil reaction, organic matter content, cation exchange capacity (CEC), water holding capacity, and soil tilth. Application of manures to pasture and crop lands has been shown to increase the dry matter yields and enhance the nutrient status of soils. Optimum use of these by-products requires knowledge of their composition not only in relation to beneficial uses but also to environmental implications. Environmental concerns associated with the land application of manure byproducts from the confined animal industry encompass all aspects of non-point source pollution, including contamination of surface water with soluble and particulate P, leaching losses of N in subsurface drainage and to groundwater, reduced air quality by emission of volatile organic compounds and greenhouse gases, and increased metals’ input. Maintaining the quality of the environment is therefore a major consideration when developing management practices to use manure by-products effectively as a nutrient resource and soil conditioner in agricultural production systems (Sharpley et al., 1998). Most of the environmental problems associated with land application of manure by-products have centered on the contamination of ground and/or surface water with two major nutrients, N and P. These by-products also contain appreciable quantities of potentially toxic metals, such as As, Cu and Zn. For example, about 25 –40% of the total annual Cu, Ni and Zn inputs to agricultural lands in England and Wales from various sources were derived from animal manure. Similarly, poultry manure addition is considered to be one of the major sources of As input to soils. In the Delaware– Maryland– Virginia peninsula along the Eastern shore of the US, 20 –50 Mg of As is introduced annually to the environment through the use of As compounds (e.g., Roxarsone, ROX) in poultry

46

N. S. BOLAN ET AL. Table II Annual Nutrient Value of Piggery and Dairy Effluents (Bolan et al., 2003) New Zealand

Global

Nutrient

Piggery

Dairy

Piggery

Dairy

Nitrogen (Mg) Phosphorus (Mg) Potassium (Mg) Value ($ million)

2600 1300 6800 7.6

5500 1200 8600 13.5

213,000 110,000 748,000 964

1,125,000 310,000 2,314,000 3296

feed. Edwards and Someshwar (2000) have pointed out that “to reduce the risk of offsite contamination, land application guidelines should be developed that consider the total composition of the animal manure by-products rather than only one component, i.e., N and/or P concentration.” Similarly, farm effluents contain a large reserve of plant nutrients. For example, in New Zealand, dairy and piggery effluents can supply annually N, P and K equivalents of 17,500 tonnes of urea, 12,500 tonnes of single super phosphate, and 28,300 tonnes of potassium chloride, respectively, with a net fertilizer value worth 21.1 million dollars (Table II). The nutrients in farm effluents can meet the N and P requirements of approximately 50,000 ha of pasture. At a global level, dairy and piggery effluents can annually supply N and P for approximately 6.7million ha of pasture. Application of these effluents to pasture lands has been shown to increase the dry matter yields and enhance the nutrient status of soils (Cameron et al., 1997). In most countries, including New Zealand and Australia, dairy and piggery farm effluents are often treated biologically using two-pond systems (Photo 1). In a two-pond system, the first pond is anaerobic and its waste loading is such that the oxygen in the pond is entirely consumed. The second pond, which is often termed aerobic, is usually a facultative pond, with an aerobic top layer over an anaerobic base. The aerobic pond treatment is followed by discharge of the effluent to land or stream. Biological treatment of farm effluents using the two-pond system should achieve a high degree of removal of the carbon and the suspended solids of the waste (Mason, 1997). Nutrients such as N, P and K are not removed in the two-pond systems (Hickey et al., 1989; Bolan et al., 2004) (Table III), therefore these nutrients in farm effluents, become pollutants when discharged to streams. However, with the introduction of the Resource Management Act (1991) in New Zealand, discharge of effluents to surface waters is now a controlled or a discretionary activity, which requires resource consent. Commonly the resource consent will require the effluent nutrient concentration to be minimised before entering the surface waters. This can be achieved by nutrient stripping of the effluent by tertiary treatment or land disposal


47

Photo 1 Biological treatment of farm effluents using pond system.

of the effluent. The common method of using dairy and piggery shed wastes has been to return them directly to land (Photo 2). Local authorities in many countries including New Zealand and Australia currently encourage this practice as being less harmful to water quality.

Table III Chemical Characteristics of Dairy Shed and Piggery Effluents (Bolan et al., 2003) Dairy shed

Characteristics Suspended solids (g m23) Chemical oxygen demand (g m23) Biochemical oxygen demand (g m23) Total nitrogen (g m23) Ammoniacal nitrogen (g m23) Nitrate nitrogen (g m23) Total phosphorus (g m23) Dissolved reactive phosphorus (g m23) Total sulphur (g m23) Total potassium (g m23) Total calcium (g m23) Total magnesium (g m23) Total sodium (g m23)

Piggery

Anaerobic pond

Oxidation pond

Percent removal

Oxidation pond

320 950 210 125 115 5 28 21

185 615 91 110 95 15 24 18

42 35 56 12 17 – 14 14

154 520 105 85 72 13 18 15

3 175 22 11 10

2 168 23 14 8

33 4 – – 20

3 143 17 15 11

48

N. S. BOLAN ET AL.

Photo 2 Effluent irrigation to pasture.

III. NITROGEN DYNAMICS IN PASTURE SOILS The transformation of N in a legume-based pasture is presented in Fig. 2. The N transformation reactions in soils include: mineralisation, immobilisation, 2 nitrification, denitrification, NH3 volatilization, NHþ 4 fixation and NO3 leaching. While the first four reactions involve soil microorganisms (biotic), the last three involve only the chemical/physical processes (abiotic). It is important to understand these transformation processes in order to understand the environmental and economic implications of N cycling in soils.

A. BIOTIC TRANSFORMATIONS 1. Mineralisation Because the bulk of the N in urine and faeces is in organic forms it must first undergo microbial mineralisation before it is released as mineral forms. The amount of N mineralised is closely related to the total N content, but N mineralisation is slower from faeces than from urine and the plant materials they were derived from. For example, although the C:N ratio of sheep dung (22:1 to 27:1) was found to be similar to that of the ingested herbage, a large proportion of the C content of faeces consists of undigested fibrous material (cellulose, hemicellulose, and lignin), which degrades only slowly. The slow degradation of faecal material results in a slow release of other nutrients present in organic form (Barrow, 1961; Whitehead, 1995).


49

Figure 2 Dynamics of nitrogen transformations in legume-based pastures (Dr M. J. Hedley, Personal communication).

The mineralisation process involves the conversion of plant-unavailable organic forms into plant-available inorganic forms by soil microorganisms. The process includes aminization and ammonification reactions. The plant-unavailable organic forms include protein and amino acid and the plant-available 2 inorganic or mineral forms include NHþ 4 and NO3 . Aminization. The organic forms of N are first subjected to a microbial process known as aminization. It is a microbial process in which the heterotrophic microorganisms hydrolyse the macromolecules of organic N compounds, such as proteins, into simple N compounds, such as amines and amino acids. For example, when blood and bone fertilizer, which contains protein as the major N compound, is added to pasture soils, it first undergoes aminization reactions [Eq. (1)]. In grazed pastures, unused herbage and silage residues undergo similar aminization reactions: Proteins ! aminesðR – NH2 Þ þ CO2

ð1Þ

Ammonification. The amines formed from the SOM and the organic form of fertilizers (by the aminization process) and also added through urine and urea fertilizer undergo ammonification reactions. Ammonification is a biological process in which a group of microorganisms converts amines and amino acids into NHþ 4 ions. For example, urea [CO(NH2)2] in animal urine and fertilizers undergoes the ammonification reaction [Eq. (2)]. This process is also known as “urea hydrolysis” and is carried out in the presence of the urease enzyme in

50

N. S. BOLAN ET AL.

the soil. In this process, NHþ 4 ions are produced. This process also releases hydroxyl (OH2) ions and hence the pH around the urea granules or urine spots in soil increases to a maximum of 8: 2 COðNH2 Þ2 ) 2NHþ 4 þ 2OH þ CO2

ð2Þ

The NHþ 4 ions formed through ammonification of urine or added through ammonium fertilizers (ammonium sulphate and DAP) are subjected to several fates in the soil which include: † † † † †

uptake by plants 2 conversion to NO2 2 and NO3 (nitrification) utilization by microorganisms (immobilization) retention onto soil particles (ammonium fixation) loss through NH3 volatilization. 2.

Nitrification

2 The biological conversion of NHþ 4 to NO3 is known as nitrification [Eq. (3)]. þ NH4 ions are released either indirectly from the ammonification reaction of organic matter, urea and organic forms of N fertilizers or directly from the solubilization of ammonium fertilizers. The nitrification reaction is a two-step process in which the 2 2 NHþ 4 ions are first converted (oxidised) into nitrite (NO2 ) and then to NO3 . Since the 2 2 þ rate of conversion of NO2 to NO3 is faster than the conversion of NH4 to NO2 2 , it is unlikely that NO2 , which is toxic to plants, accumulates under most soil and climatic 2 conditions. The nitrification process produces Hþ ions, thereby decreasing the pH. Since, per unit N, more Hþ ions are produced during nitrification than OH2 ions during ammonification, urine and urea fertilizer ultimately acidify the soils [Eq. (4)]. Ammonium fertilizers (ammonium sulphate and DAP) undergo only the nitrification process releasing Hþ ions. This is one of the reasons why these fertilizers are more acidifying than urea fertilizer:

2 þ 2NHþ 4 þ 4O2 ! 2NO3 þ 4H þ 2H2 O

Net effect

COðNH2 Þ2 ! 2NO3 þ 2Hþ

ð3Þ ð4Þ

Nitrate formed through nitrification of NHþ 4 or added through nitrate fertilizers (e.g., calcium ammonium nitrate) is subjected to various processes, which include: † † † †

plant uptake leaching losses immobilisation denitrification.


3.

51

Immobilization

Immobilization is a microbial process in which the plant-available NHþ 4 and NO2 3 ions are converted to plant-unavailable organic N. In arable soils, the addition of carbon-rich substances such as maize stubble and cereal straw promotes the immobilization and reduces N availability to plants. Similarly, in grazed pastures, the addition of silage promotes immobilization. Plant residues returned to soils need to be broken down to release the nutrients stored in the organic matter. Soil microorganisms play a vital role in the break down (or decomposition) of plant residues; the rate of decomposition and the subsequent release of nutrients depend on the quality of the residues. Of major concern from a practical point of view is the amount of carbon (C) relative to N (i.e., C:N ratio) in the decomposing organic matter. Problems arise when the N content of the decomposing organic matter is small, because microbes may become deprived of N and compete with the higher plants for the available N in the soils. Thus the C:N ratio of organic materials is an indication of the likelihood of N shortage and competition between microbes and higher plants for the available N in the soil. Microbes tend to maintain a low C:N ratio in their body tissue (about 8), and during the decomposition of organic matter they need one unit of N for every eight units of C assimilation. Therefore, when plant residues with a high C:N ratio are added to soils, the lack of N will inhibit the decomposition or the microbes will compete for available N from the soil, resulting in a deficiency of N for the subsequent crop. When a crop is grown without N fertilizer application, symptoms of leaf chlorosis are often noticed soon after the incorporation of maize or sorghum stubbles, which have high C:N ratios. This results from the deficiency of N due to immobilization of soil N by the microorganisms, and is commonly referred to as “sorghum sickness” or “stubble sickness” (Russell, 1973). Thus the addition of plant residues with a high C:N ratio induces immobilization of soil N by the microorganisms, thereby decreasing the amount of plant-available soil N. Conversely, plant residues with a low C:N ratio induce the mineralization of N from the plant residues, thereby increasing the amount of plant-available soil N. It has often been observed that immobilization exceeds mineralization when the C:N ratios are above 30. In the C:N ratio range of 20 – 30, immobilization and mineralization are about equal. Mineralization exceeds immobilization when the C:N ratio of the decomposing materials is less than 20. The N factor is a convenient term used to express the extent to which a material is deficient in N for decomposition. The nitrogen factor is defined as the number of units of inorganic N that must be applied for every 100 units of organic material to prevent a net immobilization of N from the soil environment. The N factor depends on C:N ratio, and since the C content of plant residues is relatively constant, the N factor increases with an increase in the C:N ratio. The nitrogen factor for a plant residue can be calculated from its C content and the C:N ratio.

52

N. S. BOLAN ET AL.

4. Denitrification In water-logged soils, some microorganisms obtain their oxygen from NO2 3, 2 resulting in the reduction of NO2 3 . The reduction of NO3 proceeds in a series of steps, producing NO2 2 , nitric oxide (NO), nitrous oxide (N2O) and N2 gas [Eq. (5)]. Denitrification results not only in the loss of a valuable plant nutrient but also in the release of N2O (green house gas), which is implicated in the destruction of atmospheric ozone. The biochemistry of denitrification, and the soil and climatic conditions under which it occurs, are discussed in detail in Sections IV and V: 2 NO2 3 ) NO2 ) NO ) N2 O ) N2

ð5Þ

B. ABIOTIC TRANSFORMATION 1.

Ammonium Fixation

Ammonium ions are retained on inorganic and organic soil particles by cation exchange reactions and also fixed in the interlayers of 2:1 phyllosilicate clay minerals, such as mica, vermiculite and illite (Nommik and Vathras, 1982). When other cations are added through fertilizer application, the NHþ 4 ions on the cation exchange sites are released into the soil solution through cation exchange process. Potassium ions, which are almost similar in size to that of NHþ 4 ions (ionic radius of Kþ ¼ 0:133 nm and NHþ 4 ¼ 0:143 nm), have often been shown þ to replace the fixed NHþ 4 ions, thereby releasing NH4 into the soil solution (McBride, 1994). The ammonium fixation process affects the N leaching and NH3 volatilization (see below).

2.

Nitrate Leaching

Being a cation, ammonium is strongly retained onto cation exchange sites, whereas NO2 3 , being an anion, is very weakly adsorbed onto the soil particles. Nitrate moves with water, and subsequent NO2 3 leaching not only results in the loss of a valuable nutrient but also causes groundwater pollution. A high NO2 3 concentration in drinking water is toxic, especially to infants, and has been shown to cause “blue baby syndrome” (methaemoglobinaemia). Nitrate is first reduced to NO2 2 in the stomach by microoganisms and then absorbed into the blood stream. 2 The NO2 2 in the blood converts back to NO3 , thereby decreasing the oxygen carrying capacity causing cellular anoxia. It is a serious concern in infants because 2 the microorganisms in their stomach are capable of reducing NO2 3 to NO2 (Bruningfann and Kaneene, 1993). The World Heath Organisation has stipulated a safe upper limit of 11.3 mg NO3-N l21 (or 50 mg NO3 l21) in drinking water.


53

Ammonium ions need to be converted to NO2 3 ions (nitrification process) before any leaching loss can occur. In many areas, NO2 3 leaching occurs during late autumn, winter and early spring as a result of high rainfall and low evapotranspiration. However, even during summer, rainfall with high intensity could cause NO2 3 leaching due to rapid water infiltration through cracks, root channels and earthworm holes. Although leaching losses occur from both fertilizer N and urine N, a number of studies have shown that in grazed pastures, the latter forms the major source of NO2 3 leaching (Di and Cameron, 2002). The release of mineral N from faeces results in elevated concentrations of mineral N in the soil below the dung patch. The high concentrations of NO3 in dung patches (e.g., 90 – 130 mg N kg21) (Ryden, 1986) can also be a significant source of both NO2 3 leaching and gaseous losses of N2O and N2 (through denitrification/nitrification) from grazed pastures.

3.

Ammonia Volatilization

Ammonium ions in an alkaline medium dissociate into gaseous NH3, which is subjected to volatilization losses [Eq. (6)]. Ammonia volatilization occurs when the soil pH is high (. 7.5). In the case of urea application and urine deposition, the initial increase in soil pH through the ammonification process is likely to result in NH3 volatilization. The chemistry of NH3 volatilization and the soil and climatic conditions under which it occurs are discussed in detail in Sections IV and V: 2 NHþ 4 þ OH ! NH3 " þH2 O ðpKa 7:6Þ

ð6Þ

IV. GASEOUS EMISSION OF NITROGEN FROM GRAZED PASTURE In grazed pastures, N is lost through NO2 3 leaching, NH3 volatilization and denitrification. The sources and forms of N inputs to grazed pastures and the processes of gaseous emission are listed in Table IV. The extent of NH3 volatilization and denitrification in grazed pastures is given in Tables V and VI. The factors affecting NH3 volatilization and denitrification in grazed pastures are given in Fig. 3.

A. AMMONIA VOLATILIZATION Ammonia volatilization is purely a chemical reaction that occurs only under alkaline conditions. pH, in particular, affects the equilibrium between NHþ 4 and NH3. In grazed pastures, although most NH3 volatilization occurs from urine

54

N. S. BOLAN ET AL. Table IV Nitrogen sources and gaseous emission of N from grazed pasture N formsa

N sources

Gaseous N

Biological N fixation

NH4

NO, N2O, N2 through denitrification following mineralisation

Excreta Dung Urine

Organic

Effluent and slurry

Organic

NO, N2O, N2 through denitrification following mineralisation NH3 volatilisation following ammonification NO, N2O, N2 through denitrification following mineralisation NO, N2O, N2 through denitrification following mineralisation Direct NH3 volatilisation NO, N2O, N2 through denitrification

NH2

NH4 NO3 Fertilizer

NH4 (AS) NO3 (CAN) NH2 (urea)

Manure

Organic

Direct NH3 volatilisation NO, N2O, N2 through denitrification following mineralisation NH3 volatilisation following ammonification NO, N2O, N2 through denitrification following mineralisation NO, N2O, N2 through denitrification following mineralisation

a

NH4, Ammonium; NO3, nitrate; NH2, amide; AS, Ammonium sulphate; CAN, Calcium ammonium nitrate.

patches, Black et al. (1985a) showed that approximately 12, 5 and 1% of N is lost through NH3 volatilization when N is added as urea, DAP and ammonium sulphate, respectively.

1.

Process of Ammonia Volatilization

As indicated earlier, urea N in urine and urea-based fertilizers undergoes hydrolysis, catalysed by the enzyme urease, to form ammonium carbonate

Table V Selected References on Ammonia Volatilization from Pasture Soils

Sandy loam

Sandy loam Fine Sandy loam to Silt loam – Brookston-Crosby

Country

Methods of NH3 flux measurement

Rate 3

21

England

Pig slurry

50 –100 m ha

Netherlands

Cattle slurry

15 m3 ha21

Canada

Dairy manure

– –

Manure Liquid swine

75 m3 ha21 18 –64 m3 ha21 101–1100 kg N ha21 574 kg N ha21

Manure Urea Urea DAP AS

167–341 kg N ha21 30, 100, 300 kg ha21 30, 60, 100, 200 30 30

Silt loam Udic Ustochrept

N sources

New Zealand New Zealand

Micrometeorological methods (mass balance)

Volatilization (kg N ha21) 12.7–31.3

Reference Pain et al. (1989)

16.6 Theoretical profile shape Direct manure sampling Chemical trapping with volatilization chamber Enclosure method Enclosure technique

23 –106 4.5 –20 17 –316 373 16.2–53.8 3, 17, 99 4, 12, 25, 60, 2 0.3 0.3

Gordon et al. (2000) Lauer et al. (1976) Hoff et al. (1981)

Black et al. (1987) Black et al. (1985a)


Soil type

(continued)

55

56

Table V Continued

Soil type

Country

N sources

Rate

Canada

CAN Urea

30 kg N ha21 100 kg N ha21

Denmark Australia

Cattle slurry Urea

30 m3 ha21 0.2053 g micropot21

United Kingdom

Mollic Gleysol

Switzerland

20 –120 m3 ha21 60 m3 ha21 20, 40 kg ha21

Loam

United Kingdom

Cattle Slurry Ammonium nitrate Sheep grazed

0, 420 kg N ha2

Sand, Silt loam, Clay loam

New Zealand

Urea

100 kg N ha21

a

Percent of total ammoniacal nitrogen (TAN) present in slurry.

Volatilization (kg N ha21)

Reference

Using surface chamber

20 –26

Rawluk et al. (2001)

Wind tunnel Mass balance micrometeorological Wind tunnel

33.3–82.9b 23

Sommer et al. (1991) Prasertsak et al. (2001)

16.5–73 33.2 1.15–1.51

Thompson et al. (1990)

4.04 and 9.64

Jarvis et al. (1991b)

8.5 –53.0

Selvarajah et al. (1989)

Micrometeorological technique Mass balance micrometeorological Enclosure technique

Herrmann et al. (2001)

N. S. BOLAN ET AL.

Clay loam and Fine Sandy loam Sandy Clay (Tropeptic Haplorthox) –

Methods of NH3 flux measurement

Table VI Selected References on Nitrous Oxide Emission from Organic and Inorganic Nitrogen Sources from Pasture Soils

Soil type

Sandy soil

Netherlands

Piggery effluent Dairy effluent Cattle slurry Surface Injected Artificial urine

Sandy soil

Netherlands

Cattle slurry

–

Japan

–

USA

Cattle slurry Piggery effluent Poultry litter Composed Fresh Cattle slurry Surface Injected Solid feedlot Manure

Poorly drained Sandy soil

New Zealand New Zealand England

N source

Netherlands

Typic Haploboroll

Canada

Gleyed Melanic Brunisol

Canada

Liquid dairy cattle manure

N input (kg ha21)

Denitrification loss (kg N ha21)

368 400

6.99 1.2

45 45 400

0.004 0.081 64

0 365 230 400

0.9 13.7 0.195 0.392

336 336

1.00 3.36

Reference Khan (1999) Khan (1999) Ellis et al. (1998)

De Klein and van Logtestijn (1994) De Klein et al. (1996) Watanabe et al. (1997) Thornton et al. (1998)

Velthof et al. (1996) 45 45 0 268 537 806 0 136 340

0.1 0.1 0.7 11 23 56 ,0.5 0.5 1.5

Chang et al. (1998)


Wakanui Silt Loam Sandy Loam Silty Clay Loam

Country

Paul et al. (1993)

57

(continued)

58

Table VI Continued Soil type

Country

N source

Solid beef cattle manure

Well-drained Medium textured

Canada

Dairy cattle slurry

Coarse textured

Dairy cattle slurry Manure

– Sandy loam

– Denmark

Dairy cattle slurry Cattle slurry

–

USA

Liquid dairy manure

Silty Clay Loam (poorly drained) Sandy loam Typic Xerorthents

England

Dung Urine NH4Cl KNO3 summer Winter

Silty loam Silt Loam Dystric gleysol

New Zealand California

New Zealand New Zealand England

Urea KNO3 KNO3

680 180 450 900 0 600 0 600 0 600 0 600 264 0 492 0 174 25 78 400 300 300 400 50 mg N kg21 soil 0 25

Denitrification loss (kg N ha21) 16 ,0.25 0.25–0.5 0.5–10.5 3.28 52.19 36 156 0.73 9.49 37 95 46 0.24 7.70 6.39 16.4–20.8 0.059 0.341 2.8 9.9 4.2 1.3 0.40 0 15

Reference

Paul and Zebarth (1997)

Thompson (1989) Christensen (1983) Comfort et al. (1990) Yamulki et al. (1998) Khan (1999) Rolston et al. (1978)

Ruz-Jerez et al. (1994) Luo et al. (1999a) Scholefield et al. (1997)

N. S. BOLAN ET AL.

Manure

N input (kg ha21)

England Germany Scotland

Sand

USA

NH4NO3 CAN AS Urea CN AN KNO3

Silt loam

Yolo silt loam

Silty clay loam

Dystric Eutrochrept

England

Sandy Clay loam

Pakistan

KNO3 (NH4)2HPO4 Urea

Loam to Clay loam soil

England

AN

22 56 54 35 0.07 1.9 0.2 0.8 0.5 0.4 16.06 45.26 31.75 6.57 5.84 13.14 0.365 0.73 0.73 0.365 2.55 0.365 22 0.15 5.8 8.0 11.8 1.6 11.1 29.1

Weier et al. (1993)

Abbasi and Adams (2000) Mahmood et al. (1997)

Ryden (1983a)

59

CAN, calcium ammonium nitrate; AS, ammonium sulphate; CN, calcium nitrate; AN, ammonium nitrate; KNO3, potassium nitrate.

Ellis et al. (1998) Mogge et al. (1999) Clayton et al. (1997)


Silty clay loam Sandy loam Clay loam

50 100 150 200 60 78 360 360 360 360 0 50 100 0 50 100 0 50 100 0 50 100 100 250 0 100 200 0 250 500

60 N. S. BOLAN ET AL.

Figure 3 Factors affecting denitrification and ammonia volatilization in grazed pastures.


61

[(NH4)2CO3] [Eq. (7)], which in turn, being unstable, dissociates into NHþ 4 and 22 2 carbonate (CO22 3 ) ions [Eq. (8)]. The CO3 ions release hydroxyl (OH ) ions [Eq. (9)], thereby resulting in a high pH close to the site of hydrolysis ðNH2 Þ2 CO þ 2H2 O ! ðNH4 Þ2 CO3

ð7Þ

22 ðNH4 Þ2 CO3 ! NHþ 4 þ CO3

ð8Þ

2 2 CO22 3 þ 2H2 O ! HCO3 þ OH

ð9Þ

A necessary prerequisite for NH3 volatilization is a supply of free NH3 near the soil surface. The conversion of NHþ 4 ions to NH3 [Eq. (6)] is thus the major process regulating the potential loss of NH3 from soils. Thus, NH3 volatilization is driven by the difference in partial pressure of NH3 between the air and soil atmospheres. The partial pressure of NH3 in the soil is controlled by the rate of removal of NH3 in solution. The equilibrium between NHþ 4 and NH3 is affected by many factors, but the supply of NH3 is generally favoured by high soil pH and high temperatures (Haynes and Sherlock, 1986). The high concentration of NHþ 4 and high pH in the urine patch both favour NH3 volatilization losses. Temperature is a particularly important factor. Lockyer and Whitehead (1990) obtained a positive correlation between soil temperature at a 3 cm depth during the 3 days following urine application and the extent of volatilization loss from urine patches. Urea hydrolysis is rapid, and Sherlock and Goh (1984) calculated half-lives of urine urea as 3.0 and 4.7 h, respectively, under summer and autumn conditions in New Zealand. The reduction in hydrolysis rate in autumn was attributed to lower soil temperatures. When urine urea is added to the soil, its hydrolysis is more rapid than that of pure urea under similar conditions (Sherlock and Goh, 1984). The major reason for this is that hippuric acid, a minor nitrogenous constituent of animal urine, has a stimulatory effect on urea hydrolysis (Whitehead et al., 1989). The high pH of urine (8.6) would also directly favour the hydrolysis of urea (Sherlock and Goh, 1984) because this is the optimum pH for urease activity (Vlek et al., 1980). Vallis et al. (1982) found that in a subtropical pasture more than 80% of urea in urine voided onto the pasture was hydrolysed in 2 h as a result of the urease enzyme in soil or plant residues. This resulted in high pH, and high NHþ 4 and NH3 concentrations within 24 h of urine application. In addition, urea in animal urine hydrolyses extremely rapidly after release from the animal, suggesting that urease activity is already present in the voided urine. During the first 24 h after a urination event, as urea hydrolysis proceeds, there is a rapid rise in soil pH in the urine patch. The rise is greatest near the soil surface and decreases with soil depth (Ball et al., 1979; Vallis et al., 1982). A rise in pH

62

N. S. BOLAN ET AL.

of 2.5 –3.5 pH units is not uncommon in the surface 0.5 cm of soil (Vallis et al., 1982; Sherlock and Goh, 1984). Following urea hydrolysis, large amounts of NHþ 4 accumulate in the soil. By 24 h after a urination event, concentrations of NHþ 4 in the surface 10 cm of soil in the urine patch commonly reach 100 – 250 mg N g21 (Ball et al., 1979; Carran et al., 1982; Sherlock and Goh, 1984). Concentrations of NHþ 4 from 500 to 1000 mg N g21 have been observed in the surface 2.5 cm (Vallis et al., 1982). Ammonium ions interact with the cation exchange complex in the soil, resulting þ in electrostatic binding of NHþ 4 ions to clay and organic colloids. Some NH4 can also become fixed in the lattices of 2:1 clay minerals (Carran and Theobald, 1995).

2. Ammonia Volatilization in Grazed Pastures In grazed pastures, biological degradation of animal excreta (dung and urine) and hydrolysis of fertilizers containing urea and NHþ 4 leads to the continuous formation of NH3 in the soil, which volatilizes to the atmosphere. The rate of volatilization of NH3 is controlled by the rate of removal and dispersion of NH3 into the atmosphere (Peoples et al., 1995). Ammonia is lost from decomposing dung, particularly during the first week after deposition (MacDiarmid and Watkin, 1972a). Over the first 13 days of decomposition of cattle dung, MacDiarmid and Watkin (1972a) measured a loss of 4.7% of the dung N, and Ryden et al. (1987a) measured losses of 1.2 and 12.0%, respectively, for cattle and sheep dung over a 2-week period following deposition. Losses of NH3 from urine patches generally represent 4 – 46% of urine N. Hot, dry, summer conditions favour losses, whereas cool, moist, winter conditions minimise losses. Thus Sherlock and Goh (1984) measured mean urine patch volatilization losses of 22% in summer, 25% in autumn, but only 12% in winter. Under conditions in which mean air temperatures were 168C, Ryden et al. (1987a) measured losses of urine N of 22%; when mean air temperatures were 88C, losses of only 10% were recorded. In the tropical dry season Vallis et al. (1985) observed losses as high as 46%. Under a rotational grazing system Ryden and McNeill (1984) showed NH3 losses were greatest from pastures during, and immediately after, grazing and the highest rates of loss were associated with high stock densities. The bulk of such NH3 would have originated from recently formed urine patches, although some could have come from dung patches. Between grazing, NH3 losses continued at a low rate. Jarvis et al. (1989) measured NH3 losses from grazed ryegrass swards, which received 210 and 420 kg N ha21 yr21, of 0.8 and 5.9 kg N ha21 yr21, respectively; losses from a grass/clover pasture estimated to be fixing 160 kg N ha21 yr21 were 0.7 kg N ha21 yr21. The much larger losses from the high-N ryegrass pasture were attributed to the larger number of stock carried and


63

also the greater proportion of ingested N being returned in the form of urine in this high-N treatment. Recently, Jarvis and Ledgard (2002) have made a critical comparative analysis of NH3 emission from two contrasting model dairy systems in the United Kingdom and New Zealand. The UK farm on moderately to poorly drained soil with 250 kg N fertilizer ha21 yr21 produced sufficient grass to maintain 102 milking cows and a total of 164 livestock units, and the New Zealand farm on freely draining soil with N inputs by N2 fixation supported 202 livestock units. The desk study has demonstrated distinct differences between the two farming systems in terms of total N input, N off-take, N surplus and per-hectare NH3 emission. These values were 1.7, 1.2, 1.8 and 2.4 times greater in UK than in New Zealand, respectively. The greater per-hectare loss of NH3 in the UK farm is attributed mainly to the higher fertilizer N input, and the housing of animals and the subsequent spreading of the manure to the farm. However, when NH3 loss is expressed in relation to the farm N surplus, there is little difference between the two farms with NH3 loss being ca. 20% of the surplus in each case.

B. DENITRIFICATION Denitrification is the conversion of NO2 3 to gaseous N products and occurs worldwide in terrestrial and aquatic ecosystems. Denitrification is an agriculturally important process, since it can lead to losses of valuable N from agricultural systems and thus decrease the efficiency of fertilizer use and reduce agricultural production. Apart from the agricultural interest in denitrification associated with the loss of N, there are increased concerns about the environment. Denitrification can be both detrimental and beneficial to the environment. For example, N2O, one of the gaseous products from denitrification, has possible deleterious effects on global warming (Wang et al., 1976), and also has a possible catalytic effect on the destruction of stratospheric ozone (Crutzen, 1981). In contrast, denitrification can be used as a means to remove N from wastewaters, thereby minimizing NO2 3 contamination of groundwater from land-based wastewater treatment systems (Knowles, 1982; Schipper and Vojvodic-Vukovic, 2000).

1. Process of Denitrification Denitrification is the last step in the N cycle, where the fixed N is returned to the atmospheric pool of N2. Biological denitrification is defined as the 2 dissimilatory reduction of NO2 3 or NO2 by essentially anaerobic bacteria producing molecular N2 or oxides of N when oxygen is limiting (Payne, 1981; Zumft, 1997). Denitrification is carried out by respiratory denitrifiers that gain

64

N. S. BOLAN ET AL.

energy by coupling N-oxide reduction to electron transport phosphorylation (Tiedje, 1988). Denitrifying bacteria can be present in nearly all soils and are generally facultative aerobes (Tiedje, 1988). It is accepted that the main genera capable of denitrification in soil include Pseudomonas, Bacillus, Alculigenes and Flavobacterium (Payne, 1981; Firestone, 1982; Tiedje, 1988). Many denitrifying bacteria are chemoheterotrophs, i.e., they can use NO2 3 as their primary electron acceptor to obtain energy from organic compounds (heterotrophic denitrification). In addition, some autotrophic organisms can obtain energy by using NO2 3 for oxidation of inorganic compounds, such as elemental sulphur (autotrophic denitrification). As facultative aerobes, denitrifiers can be considered bacteria that prefer to use O2 as their electron acceptor, and can use NO2 3 as a terminal acceptor of electrons only when O2 is not available. Under conditions of limited O2 availability, aerobic respiration can apparently provide the energy needed for synthesis of new enzymes required for NO2 3 reduction. The general pathway of the reduction of NO2 3 during the denitrification process may be represented by Eq. (5) (Payne, 1981; Firestone, 1982). The following stoichiometric equation for denitrification is often cited, with glucose as the C substrate [Eq. (10)]: þ 5ðCH2 OÞ þ 4NO2 3 þ 4H ! 2N2 þ 5CO2 þ 7H2 O

ð10Þ

The description of mechanisms involved in denitrification can be found in several reviews (e.g., Firestone, 1982; Knowles, 1982). The general requirements for biological denitrification are: (1) the presence of bacteria possessing the metabolic capacity; (2) suitable electron donors such as organic C compounds; (3) anaerobic conditions or restricted O2 availability; and (4) N oxides, NO2 3, NO2 2 , NO, or N2O as terminal electron acceptors. The process of denitrification is therefore generally promoted under anaerobic conditions, high levels of soil NO2 3 , and a readily available source of carbon; and it is positively related to soil pH and temperature. Although many soil bacteria seem able to denitrify, denitrifying bacteria exhibit a variety of reduction pathways. Some bacteria produce only N2, while others give a mixture of N2O and N2, and some only N2O (Stouthamer, 1988). There has been some doubt whether NO is a true intermediate or a by-product (Amundson and Davidson, 1990). N2O and N2 are normally produced in soils in varying ratios, depending on the substrate, the environmental conditions, the organisms involved, and the time that has elapsed since the onset of denitrifying activity (Sahrawat and Keeney, 1986; Arah and Smith, 1990). The relative proportion of N2O/N2 evolved during denitrification increases as the soil becomes more aerobic (Firestone, 1982).


65

The biological denitrification process is not solely responsible for the reduction of NO2 3 in soil. It is also subject to chemical reactions that lead to production of N2 by non-enzymatic pathways under fully aerobic conditions (Paul and Clark, 1989).

2.

Denitrification in Grazed Pastures

Several studies have shown higher rates of denitrification loss from grazed pasture than from comparable ungrazed pasture (Ryden, 1985, 1986; Luo et al., 1999a; De Klein et al., 2001). High denitrification rates in grazed pastures are often associated with N and C from the deposition of animal excreta to the soil by grazing animals (Ryden, 1986; Saggar et al., 2002). Factors that enhance denitrification associated with grazing could also include more anaerobic environments as a consequence of soil compaction caused by animal treading (Oenema et al., 1997). Anaerobic microsites caused by high O2 consumption by soil microorganisms in urine-affected soil and an increase in the solubility of SOM resulting from an increase in soil pH from urea hydrolysis are also likely to encourage denitrification (Monaghan and Barraclough, 1993; Bhandral et al., 2003). About 20 – 40% of urine N could be lost via denitrification in urineaffected soil in grazed pastures, as suggested by several studies (Ball et al., 1979; Carran et al., 1982; Vertregt and Rutgers, 1988; Fraser et al., 1994; Clough et al., 1996). N2O emission rates following urine application were substantial, and ranged from 40 to 600 mg N2O m22 d21 (De Klein and van Logtestijn, 1994; Allen et al., 1996; Lovell and Jarvis, 1996). However, the high N2O emission was generally short-lived (e.g., , 40 days, Lovell and Jarvis, 1996). Several researchers have found denitrification is the dominant process of N2O production in urine patches (Monaghan and Barraclough, 1993; De Klein and van Logtestijn, 1994; Williams et al., 1998). Application of N fertilizer generally increases denitrification rates in comparison with unfertilized pasture soils, and the rates tend to increase with increasing fertilizer rate (e.g., Estavillo et al., 1994; Ellis et al., 1998). The responses of denitrification rates to fertilizer N are often due to the limitation of native NO2 3 -N and the high organic C in pasture soils (Webster and Dowdell, 1982; Christensen, 1983; Ryden, 1983a). Studies showed N losses through denitrification from managed pasture ranged from 0 to 25% of the fertilizer input (Colbourn and Dowdell, 1984; Ryden, 1983a, 1986; Jarvis et al., 1991a; Barraclough et al., 1992; De Klein and van Logtestijn, 1994; Ledgard et al., 1996; Prasertsak et al., 2001). Mean daily rates were found to range from 0.01 to 0.9 kg N ha21 following fertilizer application (Egginton and Smith, 1986; De Klein and van Logtestijn, 1994; Schwartz et al., 1994; Ellis et al., 1998). Increased denitrification rates from animal slurry or manure applied to pasture are also reported (Ryden, 1986; Thompson et al., 1987). A few measurements

66

N. S. BOLAN ET AL.

have shown large denitrification fluxes in the order of 130– 800 g N ha21 d21 following slurry application (Thompson, 1989; Allen et al., 1996). The slurry or manure provides both N and C for denitrifying bacteria, and hence increases denitrification rates. It is also suggested that the increased water content and transient anaerobic conditions, initially as a result of the water applied with the slurry, may also be responsible for the increased denitrification rates (Comfort et al., 1988; Cameron et al., 1995). Thompson et al. (1987) found denitrification losses of 12 and 21% of total N applied to a pasture soil in winter following surface application and injection of slurry, respectively. A lysimeter study of the fate of N in pig slurry applied to a silt loam soil under pasture found that between 30 and 39% of applied slurry N was lost by denitrification (Cameron et al., 1995; Carey et al., 1997). It was also found that application of cattle slurry to pasture soil stimulated greater N2O production and increased losses over a longer time period compared with mineral fertilizer additions (Ellis et al., 1998). Several studies have shown that N2O emission from fertilizer N is greatly increased immediately after the application of cattle slurry mainly due to an increase in the supply of readily available C for the denitrifying bacteria (Clayton et al., 1997; McTaggart et al., 1997; Barton et al., 1999; Stevens and Laughlin, 2001). A number of studies have shown soil denitrification and N2O emission rates are highly variable throughout the season and high rates are associated with grazing and fertilizer application in grazed pastures (e.g., Ryden, 1981; Ruz-Jerez et al., 1994; Williams et al., 1998; Luo et al., 1999a; Saggar et al., 2002, 2003, 2004). Temporal variations can also be explained by corresponding variations in soil temperature and water content (Ryden, 1986; Aulakh et al., 1991). In addition to the heterogeneous distribution of biological hotspots, which are responsible for the spatial variability of denitrification rates in the field environment, grazing also introduces additional spatial variability to denitrification rates because of the random nature of excretal returns of N and animal treading to the soil (Saggar et al., 2002; Bhandral et al., 2003). On an annual basis, total N losses through denitrification in unfertilised dairygrazed grass/clover pasture in New Zealand were found to be about 5 kg N ha21 (Ledgard et al., 1999; Luo et al., 2000). However, following the application of up to 400 kg urea-N ha21 to dairy-grazed pasture, total denitrification rates increased to about 19 N ha21 (5% of the fertilizer N applied) (Ruz-Jerez et al., 1994) and about 25 kg N ha21 (6% of the fertilizer N applied) (Ledgard et al., 1999). Saggar et al. (2002, 2003, 2004) observed that the measured emissions changed with changes in soil moisture resulting from rainfall and were about 20% higher in poorly drained silt-loam soil than in well-drained sandy loam soil. Annual net emissions of 1.8 and 1.6 kg N2O-N ha21 (ungrazed pastures), and 9.7 and 11.7 kg N2O-N ha21 (grazed pastures) were measured for the well-drained and poorly drained soils, respectively. These emissions were 2.0 and 2.5% of the excretal and fertilizer N in these two soils and were mainly produced by denitrification. Nitrous oxide emissions from the fertilised dairy pasture soils in


67

Victoria, Australia, ranged from 6 to 11 kg N2O-N ha21, and extensive grazed pastures and rangelands contributed annually about 0.2 kg N2O-N ha21, whereas in arable cropping, N2O emissions ranged from , 0.01 to 9.9% of N fertilizer applications (Dalal et al., 2003). Ryden (1986) found greater rates of denitrification from grazed pastures than from cut swards, and estimated N losses of 40 and 20 kg N ha21 yr21, respectively, through denitrification from grazed and cut swards of ryegrass receiving 420 kg N ha21 yr21. The reasons for this difference may be the considerably higher contents of both soil NO2 3 -N and soil water in the urine- and dung-affected areas than in the remainder of the sward. Gaseous losses of N2O can also occur during the process of nitrification (Bremner and Blackmer, 1978). During nitrification, N2O evolution increases as oxygen concentrations decrease (Goodroad and Keeney, 1984). For example, Koops et al. (1997) and Klemedtsson et al. (1988) have suggested that nitrification may well be the major source of N2O production from urine patches and soils receiving urea or ammonium fertilizers, respectively. The large amounts of NHþ 4 typically nitrified in the urine patch make it likely that nitrification would contribute significantly to N2O losses from grazed pastures. However, Saggar et al. (2002) found dentrification the major contributor to N2O loss from dairygrazed pastures. Their results suggest that although both nitrification and denitrification may have contributed to the emissions in grazed dairy pastures, the very high fluxes associated with water-filled pore space values . 0.60 are more likely to have come from denitrification.

V. FACTORS AFFECTING GASEOUS EMISSION A. AMMONIA VOLATILIZATION The key factors that determine the extent of NH3 volatilization loss from soils are those that affect (1) the rate of conversion of NHþ 4 to NH3 gas (pH and partial pressure gradient of NH3), and (2) the transfer of NH3 gas between the soil solution and the atmosphere (area of solution – atmosphere interface, velocity of air across the soil surface). Soil and climatic factors that control these two aspects of NH3 volatilization include soil pH, soil moisture, soil texture, soil CEC, temperature, and wind velocity (Fig. 3).

1. Soil Factors pH and CEC are the most important soil properties controlling NH3 volatilization. pH, in particular, affects the equilibrium between NHþ 4 and

68

N. S. BOLAN ET AL.

NH3, and as the pH changes from 6 to 7, 8 and 9 the relative concentration of NH3 increases from 0.1 to 1, 10 and 50%, respectively (Freney et al., 1983). This is one of the reasons why NH3 volatilization is negligible in the case of acidforming fertilizers, such as ammonium sulphate. Although urea and DAP are also considered acid-forming fertilizers, their initial alkaline reactions in soils result in an increase in NH3 volatilization (Selvarajah et al., 1989; Harrison and Webb, 2001). The difference in NH3 volatilization amongst these fertilizers is attributed to the difference in their acidifying effects. It has often been shown that NH3 volatilization increases with soil pH. For example, Whitehead and Raistrick (1990) obtained a strong exponential relationship between NH3 volatilization from surface-applied N fertilizers and cattle urine and the pH of the soils. Although higher NH3 volatilization losses are expected from calcareous soils that are high in pH, the extent of NH3 volatilization depends on the carbonate concentration in the soil solution, which in turn is affected by the solubility of the calcium salts formed by the anion added through the NH3 source. The CEC of soils influences the NH3 concentration through the reaction of NHþ 4 ions with the negatively charged cation exchange sites. Hence soils with low CECs are more prone to high NH3 volatilization than are soils with high CECs. For example, Selvarajah et al. (1989) obtained an inverse relationship between the NH3 volatilization and CEC of a number of soils, which they attributed to increased retention of NHþ 4 onto the cation exchange sites. Whitehead and Raistrick (1993) also obtained an inverse relationship between NH3 loss and CEC, but the relationship was stronger for urine than for urea. They concluded CEC is likely to have a greater effect on NH3 volatilization from urine than from urea because of the greater contact between soil and urinederived NHþ 4 ions. Plants affect NH3 volatilization by decreasing the concentration of NHþ 4 ions in the soil solution through plant uptake and by altering the pH of the rhizosphere soil. Furthermore, plant cover influences wind speed, temperature, and moisture conditions at the soil surface. For example, soil temperature is generally lower under grass cover than under fallow conditions, leading to lower NH3 volatilization under grass cover.

2.

Climatic Factors

The release of NH3 gas from the soil to the atmosphere depends on the partial pressure of NH3 in the atmosphere. Hence temperature and wind speed affect NH3 volatilization through their effect on partial pressure close to the soil surface. As expected, NH3 volatilization increases with increasing temperature and wind velocity. Increasing temperature increases the relative proportion of NH3 to NHþ 4 present, decreases the solubility of NH3 in water, and increases the diffusion of


69

NH3 away from the air – soil interface (Bouwman et al., 2002). Furthermore, since urea hydrolysis is a function of microbial activity, the production of NHþ 4 ions and the subsequent loss of NH3 should essentially stop if the temperature is reduced to a point where microbial activity ceases (i.e., below 2 48C). For example, Gould et al. (1986) observed that the Arrhenius plot of urease activity increased linearly with an increase in temperature from 2 to 458C, with an optimum temperature of 378C for urease activity. Soil moisture content at the time of urination has little effect on NH3 volatilization, unless the soil is very dry so that urease activity is inhibited. However, when the soil is moist at the time of urination but the weather is dry subsequently, the dry condition is likely to increase volatilization. Conditions that favour the evaporation of soil moisture enhance NH3 volatilization because as the soil moisture content decreases the NH3-enriched water moves towards the surface, leading to volatilization loss.

B. DENITRIFICATION Environmental parameters that affect denitrification have been identified in laboratory studies (reviewed by Payne, 1981; Firestone, 1982; Knowles, 1982), and the relative importance of these parameters has been investigated in a number of field studies (e.g., Ryden, 1983a; Rolston et al., 1984; Davidson and Swank, 1986; Aulakh et al., 1991; Luo et al., 2000). The diverse environmental factors affecting denitrification have been broadly grouped into proximal and distal regulators (Fig. 3). Proximal regulators affect the immediate environment of the bacterial cell, and include factors such as NO2 3 concentrations, C levels, O2 contents, and temperature. Distal regulators control the proximate regulators on a larger scale and include factors such as plant growth, animal grazing, soil texture, rainfall and irrigation (Fig. 3). In general, denitrification appears to proceed in soils under a much broader range of conditions than would be predicted on the basis of the biochemistry of the process and the physiology of denitrifiers. Denitrification is promoted by high soil moisture conditions, neutral soil pH, high soil temperature, a low rate of O2 diffusion, and the presence of soluble organic matter and NO2 3.

1. Soil Factors Soil Water and Aeration. Soil water content together with the rate of oxygen consumption (respiration) determines the oxygen availability (Tiedje, 1988). Oxygen availability is one of the most important factors affecting denitrification in soil. Field studies have shown that an increase in denitrification rate is

70

N. S. BOLAN ET AL.

associated with restricted soil aeration at high soil water content in pasture systems (e.g., De Klein and van Logtestijn, 1994; Ledgard et al., 1999; Luo et al., 2000). Studies (e.g., De Klein and van Logtestijn, 1994) showed the existence of a soil water threshold (Table VII) above which denitrification rates increased sharply with increasing soil water content. Below this critical water threshold value, denitrification rates appeared to be unrelated to soil water content. The threshold value differs according to soil type and is expressed as water-filled porosity (WFP). De Klein and van Logtestijn (1996) suggested the critical WFP for many soils is equivalent to field capacity or above. In general, water thresholds decreased when soil texture became finer. It is also suggested that low soil oxygen content resulting from soil compaction through animal treading, particularly when soils have high water content, could increase denitrification rates in grazed pastures (Luo et al., 1999a). The soil water content can affect the N2O:N2 ratio in the gaseous products of denitrification, and the N2O:N2 ratio decreases with increasing soil water content (Colbourn and Dowdell, 1984; Rudaz et al., 1999). Nitrate Concentration. The availability of NO2 3 for denitrifying bacteria is the first step in biological denitrification, and the denitrification rate would therefore be expected to depend on NO2 3 concentration. The relationship between denitrification rates and NO2 3 concentration is well established and could generally be described by a Michaelis-Menten mathematical function (Weier et al., 1993; Parton et al., 1996). The availability of NO2 3 to denitrifying bacteria is dependent on the rate of nitrification, the rate of N consumption by non-denitrifiers including plants and bacteria, and NO2 3 leaching and diffusion rates through the soil (Tiedje, 1988). It has often been found that the denitrification rate increases after NO2 3 addition (e.g., through return of animal excreta during grazing, nitrogen fertilizer or manure application) in the field (Ryden, 1983a; Corre et al., 1990; Jarvis et al., 1991a,b; De Klein and van Logtestijn, 1994; Ledgard et al., 1999; Saggar et al., 2002, 2003, 2004), as discussed in Section IV, but there is usually no effect of NO2 3 addition if organic C is limited (McCarty and Bremner, 1992). It has also been observed that the rate of diffusion of NO2 3 to the denitrification microsites is the limiting factor for denitrification in grazed pasture, especially when the soil is dry (Luo et al., 1999b). Nitrate from nitrification also controls denitrification, as nitrification and denitrification can occur simultaneously (Abbasi and Adams, 1998, 2000). Nitrification inhibitors (NI) play a significant role in reducing denitrification loss (De Klein and van Logtestijn, 1994; De Klein et al., 1996; Puttanna et al., 1999) (refer to Section VIII). Nitrate concentrations have also been observed to influence the N2O:N2 ratio in the gaseous products of denitrification. NO2 3 usually inhibits N2O reduction to N2 (Bremner and Blackmer, 1978). Therefore, at low NO2 3 concentration, N2 is concentrations, N2O often the predominant product and at high NO 2 3 predominates (Arah and Smith, 1990).

Table VII Selected References Examining the Effect of Soil Moisture on Nitrous Oxide Emission from Pasture Soils Soil type

Country

WFPSa/SWCb

Reference Prade and Trolldenier (1988)

60 –99%

Threshhold levels were 82, 83, 71% for sandy, loamy and peat soil, respectively

De Klein and van Logtestijn (1996)

0.10–0.30 g water per g dry soilb 63% 71% 84% 63 –93%

Dentrification increased exponentially above 0.16–0.2 g water per g soil 0.46 kg N2O ha21 d21 0.92 kg N2O ha21 d21 3.38 kg N2O ha21 d21 Threshhold level 83%; denitrification rate increased when WFPS was above the threshold level Denitrification losses: 0.02– 0.18 mg N per kg soil 14–18.6 mg N per kg soil 50-fold increase in denitrification within 70– 90% WFPS Denitrification increased with increasing WFPS. At highest WFPS, 10-fold higher denitrification in clay loam compared with sandy loam soil

Klemedtsson et al. (1991)

Germany

75 –97%

Silt loam

Lincoln, US

60 –90%

Silty Clay loam Sand Sand

Netherlands

Loam Peat Loam

Sweden

Clay Loam

UK

Alluvial soil

New Zealand

Silty clay Silty loam Sandy loam Stagno-Dystric Gleysol Clay Loam

USA, India 60% 90% 70 –90% 50 –70%

Weier et al. (1993)

Abbasi and Adams (2000)

Ruz-Jerez et al. (1994) Aulakh et al. (1991)


Threshhold level 88 –90%; above which exponential increase in denitrification rates was observed Denitrification increased with increase in WFPS; the increase was gradual in sandy soil

Loess

UK USA

Observations (N2O emissions)

Scholefield et al. (1997) Sexstone et al. (1988)

Sandy Loam

71

72

N. S. BOLAN ET AL.

Carbon Availability. The supply of readily decomposable organic matter in soil is also critical in controlling the rate of denitrification (Burford and Bremner, 1975; Payne, 1981; Reddy et al., 1982; Robertson and Tiedje, 1984; Beauchamp et al., 1989) (Table VIII). Permanent pastures develop surface layers rich in organic material with potential for denitrification when fertilized or when urine and dung are deposited during grazing (Ryden, 1986). The presence of an ample C substrate can also result in rapid O2 consumption and possible O2 depletion, which may then also indirectly enhance the potential for denitrification (Firestone, 1982). It has been suggested that decomposition of plant litter, animal faeces, and root exudates from the perennial plant cover maintain moderate to high levels of available carbon in grazed pasture soils for denitrification (Carran et al., 1995). Limmer and Steele (1982) found soil carbon limited denitrification in leguminous pasture soils. High denitrification rates are found in soils where the plants have been cut or damaged, and the roots remain in the soil (Beck and Christensen, 1987; Robertson et al., 1987). It has been suggested that easily available organic C can leak out from the roots after the plants have been damaged. High N2O emissions from grass-covered soils after the grass was cut were also demonstrated in a field study by Conrad et al. (1983). However, Hutchinson and Brams (1992) reported that emission of N2O from pasture was not stimulated by clipping and removal of the grass. The study of Beck and Christensen (1987) also has indicated that mature roots may supply more organic C to the soil than young roots. Furthermore, the accessibility of C supply to bacteria also has a strong regulatory effect on denitrification, especially in field conditions. Myrold and Tiedje (1985) showed that the diffusion rate of organic compounds in some soils limited the denitrification rate. Organic C content decreases with depth in most mineral soils. Thus, although leaching of NO2 3 -N into lower horizons is a common phenomenon in most agricultural soils, the availability of organic C is usually one of the main factors limiting denitrification activity in subsoils (Weier and Doran, 1987; Parkin and Meisinger, 1989; Luo et al., 1996, 1998). The availability of C has also been reported to influence the proportion of N2O and N2 produced. Limited supply of carbon is likely to cause partial denitrification, resulting in the release of intermediate gases such as NO and N2O. Thus, it is generally concluded that increasing C availability decreases the ratio of N2O:N2 (Smith and Tiedje, 1979; Arah and Smith, 1990; Dendooven et al., 1998). Soil pH. Most denitrifying bacteria grow best near neutral pH conditions (pH 6 –8). But the pH range for denitrification is broad (Knowles, 1982). Denitrification slows down in acid conditions (Bremner and Shaw, 1958; Bryan, 1981; Nagele and Conrad, 1990), but denitrification can still occur at pH values as low as 3.5 and can account for significant N losses in naturally acid soils (Parkin et al., 1985; Weier and Gilliam, 1986). The mechanism of pH control of denitrification is not clear. It has been speculated that indirect effects of low pH,

Table VIII Selected References Examining the Effect of Carbon on Denitrification from Pasture Soils Soil type

Country

Carbon source

Devon, UK

Glucose

Tokomaro Silt

New Zealand

Glucose

Sand

California, USA

Glucose

Silt Loam

Typic Xerorthents

Sandy Loam (Frilsham Series) Gleyed Melanic Brunisol

Aeric Ochraqualf (Capac clay loam)

Heavy clay

Glucose

California, USA

England Canada

Chopped barley straw Grassland Arable land Glucose

0

94 kg N ha21

394 kg ha21 0 0.3 g C kg21 soil 0 kg C ha21 180 kg C ha21 360 kg C ha21 0 kg C ha21 180 kg C ha21 360 kg C ha21 0

105 kg N ha21 0.02 mg N2O kg21 d21 0.37 mg N2O kg21 d21 44 g N ha21 d21 25 g N ha21 d21 51 g N ha21 d21 18 g N ha21 d21 91 g N ha21 d21 188 g N ha21 d21 4.1 kg N ha21

10 Mg ha21 0.76% org C 2.55% org C 0

14.9 kg N ha21 166 g N ha21 d21 242 g N ha21 d21 10.4 mg N2O g21 soil d21 44.0 mg N2O g21 soil d21 40–63% increase in denitrification capacity over control

500 mg C g21 soil USA

UK

Dried milled alfalfa tops

Glucose

Denitrification rate

0 5.8 Mg ha21 0

67 mg N2O kg21 soil h21

Reference Scholefield et al. (1997) Luo et al. (1999a) Weier et al. (1993)

Rolston et al. (1984)

Bijay et al. (1989) Tenuta and Beauchamp (1996)


Stagno-Dystric Gleysol

Rate

Myrold and Tiedje (1985)

Dendooven et al. (1998)

73

(continued)

74

Table VIII Continued Soil type

Country

Carbon source

Denmark

Yolo Soil

USA

Solodized Solonets

Australia

Soil C at different soil horizons

–

Michigan

Grass shrub .20 yr Hard wood .80 yr Old growth .300 yr Sucrose

Typic Hapludalf

Canada

Fresh manure Digested manure Manure

Denitrification rate

Reference

0.1 g C kg21 soil 234 mmol DOC 74 mmol DOC 34 Mg ha21 Summer Winter Soil depth (cm) 0 –8 8 –30 30 –45 45 –75 75 –105 105–137 137–155 0.10% OC

76 mg N2O kg21 soil h21 14.9 nmol N cm22 h21 3.8 nmol N cm22 h21

Petersen et al. (1996)

Org C (%) 0.91 0.49 0.23 0.16 0.07 0.06 0.04

218 kg N ha21 32.8 kg N ha21 Denitrifying activity (mg N kg21 h21) 0.49 0.12 0.03 0.03 0 0 0.01 1.31 kg N2O ha21 yr21

1.75% OC

1.11 kg N2O ha21 yr21

1.62% OC

1.97 kg N2O ha21 yr21

0

3.95 kg N ha21 yr21

420 kg C ha21

115.58 kg N ha21 yr21

Rolston et al. (1978)

McGarity and Myers (1968)

Robertson and Tiedje (1984)

WagnerRiddle et al. (1996)

N. S. BOLAN ET AL.

Denchworth Series Typic Haplumbrept

Rate


75

such as C availability, may limit the size of the denitrifier population in acid soils (Koskinen and Keeney, 1982; Fillery, 1983). Higher rates of denitrification from urea fertilizers compared with ammonium-based fertilizers (e.g., DAP) have often been attributed to the direct supply of carbon by the urea fertilizer and the solubilization of soil carbon resulting from the increase in soil pH caused by the initial ammonification (Fenn and Hossner, 1985; Barton et al., 1999). The degree of soil acidity also influences the N2O:N2 ratio in the gases produced. It has been observed that the proportion of N2O increases as pH decreases, with N2O frequently appearing as the dominant product in acid soil (Christensen, 1985; Parkin et al., 1985). For example, Rochester (2003) derived a negative exponential function between N2O/N2 mole fraction and soil pH from a number of laboratory and field studies involving a range of soil types. A greater proportion of N2O relative to N2 is emitted from acid soils; approximately equivalent amounts of each gas are emitted from soil of pH 6.0 and for the alkaline grey clays (pH 8.3– 8.5) the N2O/N2 mole fraction was about 0.024. It has been suggested that the presence of increasing amounts of NO2 2 at lower pH levels may have been partly responsible for the increased mole fraction of N2O (Koskinen and Keeney, 1982).

2.

Climatic Factors

Soil temperature affects denitrification directly in that microbial activity generally increases with increasing temperature up to a maximum temperature of 308C. Denitrification can occur at a wide range of soil temperatures between less than 0 and 758C (Knowles, 1982). Temperature correlation factors (Q10) of 2 have been often reported for denitrification in soils (Reddy et al., 1982; Dorland and Beauchamp, 1991). As temperature affects denitrification indirectly through its effect on both O2 solubility and O2 diffusion in water (Craswell, 1978), and also affects a range of other biological process such as mineralization and nitrification, its overall effect on soil denitrification may be very complex. Temperature is thought to be one of the main factors causing temporal fluctuations in denitrification (Ryden, 1983a). Studies by Powlson et al. (1988) and Malhi et al. (1990) indicate denitrifying bacteria can adapt to soil temperature conditions, so the optimum temperature for denitrification could differ in different regions. Several researchers have found that denitrification losses during the winter period were limited by the soil temperature (Ryden, 1986; Jarvis et al., 1991a,b; De Klein and van Logtestijn, 1994), although rapid losses of N by denitrification were reported after the addition of mineral fertilizers and organic manure at low soil temperatures (Egginton and Smith, 1986; Thompson et al., 1987; Schwartz et al., 1994). Dorland and Beauchamp

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(1991) reported C amendment lowered the temperature threshold at which denitrification can occur in soil. A relatively high denitrification rate is often observed in winter in New Zealand (Ruz-Jerez et al., 1994; Luo et al., 2000), although the soil temperature is below 108C. Active denitrification in winter appears to be associated mainly with high soil moisture content due to frequent rainfall and low evaporation. Field studies have demonstrated the rate of denitrification often remains negligible during dry seasons, but then increases briefly when soil water content increases after rainfall (e.g., De Klein and van Logtestijn, 1996; Luo et al., 1999a). The N2O:N2 ratio in the gases produced by denitrification was found to decrease with soil temperature (e.g., Maag and Vinther, 1996). However, other studies did not observe any relationship between denitrification rates and soil temperature (e.g., Focht, 1974).

VI.

MEASURING AND MODELLING GASEOUS EMISSIONS A. MEASUREMENT TECHNIQUES 1. Ammonia Volatilization

Ammonia volatilization has been estimated indirectly using a mass balance approach and directly by measuring NH3 gas emission. In grazed pasture, the mass balance approach involves the measurement of various N inputs, such as fertilizer and manure application, effluent irrigation, biological N fixation, mineralization, and the deposition of animal excreta, and N outputs, such as leaching, denitrification, immobilization, the transfer of animal excreta and plant uptake. In grazed pastures, the measurement of these inputs, and outputs is complicated by continuous return of animal excreta and the dynamic nature of N transformation reactions in soils. Direct measurement of NH3 emission gives an accurate estimate of volatilization losses. A number of methods are used to measure NH3 emission in pasture soils. These include enclosure methods, micrometeorological methods and wind tunnel measurements (Jayaweera and Mikkelsen, 1991; Harrison and Webb, 2001). Enclosure Methods. Enclosure methods are most commonly used in NH3 volatilization measurements (Denmead, 1982). A variety of enclosure designs are used to measure NH3 losses (Harrison and Webb, 2001). These methods are simple and convenient, and can be used successfully to evaluate NH3 losses under a variety of experimental variables. The disturbance of natural conditions, however, makes the interpretations of these measurements somewhat questionable in terms of actual field conditions.


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Kissel et al. (1977) designed and tested an automated device that could be used to measure NH3 volatilization under field conditions without creating an artificial environment in the vicinity of the applied fertilizer or urine deposition. The basic system developed consists of a vacuum pump, a chemical trap to capture NH3, and a volatilization chamber. The chemical trap generally consists of boric acid or sulphuric acid or oxalic acid (Schjoerring et al., 1992). Sherlock and Goh (1984) used the enclosure technique to measure NH3 volatilization losses from pasture in New Zealand receiving either sheep urine or aqueous urea, at rates equivalent to 500 kg N ha21, in the field during the summer, autumn and winter periods. Mean volatilization losses for urine treated plots were 22.2% of the applied N in summer, 24.6% in autumn and 12.2% in winter. Black et al. (1985b) compared three methods of estimating NH3 volatilization from urea broadcast (100 kg N ha21) on to pasture: an enclosure system with continuous air flow (EM), an unconfined micrometeorological method (integrated horizontal flux method—IHFM), and by mass balance analysis (MBA). The cumulative loss after 96 h measured by the three methods was 24, 25 and 30%, respectively, of the N applied. The slightly higher estimated loss by the MBA was attributed mainly to microbial immobilization of applied N, which was not accounted for in the mass balance. Hoff et al. (1981) showed the intermittent enclosure technique could greatly underestimate NH3 loss when high winds prevailed between periods of lid closure. This technique should therefore be used only when ambient windspeeds are low (e.g., green house experiments) or where windspeed is known to have little effect or where other suitable precautions are taken. Lightner et al. (1990) carried out field measurements of NH3 volatilization from fertilized plots using ventilated chambers in spring and summer over 2 years. Ammonia volatilization ranged from 27 to 41% of applied N in spring and from 12 to 27% in summer. Micrometeorological Methods. Micrometeorological methods have been developed for making accurate measurements of NH3 volatilization in the field (Denmead, 1982; Sherlock et al., 1995; Wood et al., 2000). Micrometeorological techniques have an advantage in that they do not disturb the natural environmental conditions that influence NH3 volatilization, rather they provide an average integrated flux over a large area, which minimizes the sampling variability. These techniques, however, are difficult to use in practice, as they are costly in instrumentation, laborious, site-specific and weather-dependent in their application to the experimental area. There are three general types of micrometeorological methods: (1) eddy correlation; (2) gradient diffusion; and (3) mass balance (Harrison and Webb, 2001). A simplified micrometeorological approach to measure NH3 volatilization losses was proposed by Wilson et al. (1982), in which it is only necessary to measure the NH3 concentration and wind speed at one height (ZINST). At this ZINST height, the relationship between horizontal and vertical fluxes of a gas constituent is relatively constant for a wide range of atmospheric stability

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conditions. This method has the advantage that circular plots as small as 40 m in diameter can be used to measure losses rather than the much larger treatment areas needed for the full-profile micrometeorological methods. Results from this simplified micrometeorological method have been shown to be quite well correlated with results obtained by the full-profile, mass-balance micrometeorological methods (McInnes et al., 1985). An even greater simplification was proposed by Leuning et al. (1985), in which a sampler trap consisting of vanes causing it to point horizontally into the wind is used at the ZINST height. The samplers were designed so that air flows through them at a rate directly proportional to the wind speed. Any NH3 present in the air passing through the sampler is absorbed by oxalic acid on the interior surfaces in the sampler. It is not necessary constantly to measure wind speed and NH3 concentration with this sampler. Sherlock et al. (1989) showed that the losses measured with this sampler at the ZINST height were quite close to those measured with the fullprofile, mass-balance micrometeorological reference method (11.6% loss with the sampler versus 13.4% loss with the full-profile method). Fox et al. (1996) and Prasertsak et al. (2001) used this simplified micrometeorological method to successively estimate NH3 volatilization losses from a number of fertilizers applied to pasture soils. Zhu et al. (2000) investigated the feasibility of using denuder tubes with the relaxed eddy-accumulation (REA) technique to measure NH3 fluxes. The denuder tubes, coated with oxalic acid, were used at the inlet of the REA system to trap NH3 in air. Ammonia volatilization is estimated as the difference between the equilibrium concentration of NH3 in the air above the treatment and the ambient concentration above the soil multiplied by the mass transfer coefficient (ka) between the soil surface and the air. The ka is calculated by measuring the deposition on the oxalic acid filter directly exposed to the air at the soil surface and ambient NH3 concentration above the soil at the same level (Svensson and Ferm, 1993). The use of denuder technique even in highly ventilated chambers could sometimes be limited due to water condensation in the denuders (Larsson et al., 1998). Larsson et al. (1998) also occasionally observed very high NH3 concentrations exceeding the upper limit for this method and used a diffusive sampler that consisted of a tube open at one end and containing an impregnated oxalic acid filter at the other end. The gas was transported through the tube to the filter by molecular diffusion. With a diffusive sampler the sampling rate can be determined from the diffusion coefficient and the dimensions of the tube where the passive sampling rate is equivalent to an active sampling rate of 40 ml min21. The sampling rate for the denuder is generally kept at 1 –2 l min21. Wind Tunnel Measurements. Lockyer (1984) developed a system of small wind tunnels to study NH3 volatilization losses under field conditions from grassland without inducing marked changes in the microclimate of the sward. Weerden et al. (1996) obtained a recovery of 86 and 90% NH3 for two systems of


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small wind tunnels commonly used for studying NH3 volatilization losses from grassland. Sommer et al. (1991) measured NH3 losses from surface-applied cattle slurry under field conditions using a wind-tunnel system that allowed variables affecting NH3 loss to be examined under controlled conditions. The experiments were carried out on a sandy soil with seven different surface covers. The NH3 loss rate increased when wind speeds increased up to 2.5 m s21.Thompson et al. (1990) conducted three experiments to examine the influence of slurry application rate, wind speed and applying slurry in narrow bands on NH3 volatilization from cattle slurry surface-applied to grassland. The experiments were conducted in the field using a system of small wind tunnels to measure NH3 loss. There was an inverse relationship between slurry application rate and the proportion of NHþ 4 -N volatilized. Sommer and Jensen (1994) used the wind tunnel technique to measure NH3 volatilization from various N fertilizers applied to a sandy soil.

2.

Denitrification

Two basic approaches have been used to determine the extent of denitrification in soils: the first relies on the N balance; the second involves the determination of the amount of N gases produced in the soil. The N balance method involves the calculation of denitrification losses from the N balance budget, accounting for plant uptake, leaching, NH3 volatilization, and soil immobilisation. The major limitations of the N balance approach in estimating denitrification loss are that alternative pathways of gaseous loss exist and that errors in the estimation of the components of the balance can be cumulative. Denitrification has been widely measured by direct gas analysis in the last few decades. Several methods are available, including: † The use of acetylene (C2H2) to inhibit N2O reduction to N2 so that total denitrification N losses can be measured as N2O; the approach has been facilitated by the development of gas collection systems and detectors for use in gas chromatography. This technique is discussed further in the following sections. † The use of 15N-labelled fertilizer to increase the isotope enrichment of the 15 NO2 3 pool. The N-labelled gases are then measured by mass spectrometry to quantify N2 production due to denitrification against the large background of N2 in ambient air. Use of 15N in the measurement of denitrification has been reviewed by Nason and Myrold (1991). Direct measurement of 15N-gaseous emission can be used only where substrate NO2 3 for denitrification is added at a high level of 15N enrichment and requires accumulation of evolved gases into a confined atmosphere. It is also necessary to ensure the 15N-labelled

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2 NO2 3 is evenly distributed through the native NO3 -N pool in the soil. The cost of this method is relatively high, and the measured rate of denitrification may be artificially high because of the addition of 15N as NO2 3 , particularly in soils where denitrification is limited by the availability of NO2 3. † The use of the radioactive isotope, 13N, to measure nitrogenous gas production in short-term laboratory studies. Generally, the use of 13N has been considered inappropriate due to its short half-life (9.96 min) (Tiedje et al., 1979), although Smith et al. (1978) successfully used 13N to confirm that the C2H2 inhibition was an effective means of measuring denitrification rates in soils. † A flowing helium atmosphere system has been recently developed for directly measuring N2 and N2O produced by denitrification (Cardenas et al., 2003). Intact soil cores are incubated in a flowing atmosphere of helium and oxygen, after first purging the soil and incubation vessel free from dinitrogen. This technique allows the simultaneous determination of N2 and N2O, and can be used to measure the effects of soil and other environmental factors on denitrification. † A micrometeorological approach for measuring the trace gases. Micrometeorological methods are conceptually ideal for measuring trace gas emissions over large ecologically uniform areas, and the techniques can reduce the spatial variability problems inherent in some other techniques. However, the techniques have not been extensively used to measure N2O flux, because analytical methods that respond rapidly enough, or are sensitive enough to quantify N2O are not available.

Theory of Acetylene Inhibition Method. Denitrification assays are based on blocking the reduction of N2O to N2 by C2H2 (Yoshinari et al., 1977). The accumulation of N2O can be detected using a gas chromatograph equipped with an electron capture detector (ECD) (Kaspar and Tiedje, 1980). The development of the acetylene inhibition method was a major milestone in denitrification measurement, leading to an explosion of denitrification studies and an improved understanding of the process. Laboratory studies have shown that N2O is the sole gaseous product of denitrification in soils incubated in atmospheres containing 0.1 –10% vv21 C2H2, and the amount of N2O with C2H2 is equal to that of N2O plus N2 without C2H2 (Ryden et al., 1979a). By comparing the C2H2 inhibition method with the 15N method, Parkin et al. (1985) concluded that denitrification rates from the C2H2 core method were not significantly different from the estimate by the 15N technique. Even distribution of sufficient C2H2 through the soil is essential for accurate measurement of the denitrification rate, and 10% of C2H2 in the headspace volume is recommended (Tiedje, 1982). The acetylene inhibition technique was reviewed by Tiedje et al. (1989). With sufficient care in the application of C2H2, the method can be a useful


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approach to the direct measurement of denitrification in field studies. However, as C2H2 also inhibits nitrification, it might be expected that denitrification would be inhibited by a reduced supply of NO2 3 . To avoid this potential shortage of NO2 3 , the acetylene method should be applied for only short periods. Acetylene inhibition of nitrification in natural ecosystems can be solved using the gas-phase recirculation core method. Measurement locations should also be changed frequently to avoid problems associated with microbial utilisation of C2H2. Underestimates of denitrification in anaerobic microaggregates within aerobic soils could also be caused by C2H2-catalyzed NO oxidation reaction, as suggested by Bollmann and Conrad (1997). However, a study conducted by Murray and Knowles (2001) indicates that under strongly anaerobic conditions and in the presence of adequate C, the C2H2-catalyzed NO oxidation reaction should not substantially reduce the total amount of N2O produced by denitrification. Field Application of Acetylene Inhibition Method. There are two variants of the acetylene inhibition method that can be used in the field; one variant uses soil chambers, the other involves coring. In the chamber technique, the experimental equipment for measurement of denitrification in the field consists essentially of three components: a chamber to confine the surface N2O flux; a system to inject C2H2; and a system to take gas samples (Ryden et al., 1979b). The method involves placing chambers over the soil surface and either measuring the accumulation of N2O in the air space of the chamber or analysing N2O in the exit air stream (Jury et al., 1982). The main advantage of chamber methods is that they allow for in-field measurement of actual fluxes of N2O from the soil to the atmosphere, and these methods cause minimal physical disturbance to the soil. Site spatial variability is undoubtedly the greatest problem in using chamber techniques to estimate N2O flux from a field or ecosystem. However, this problem can be largely overcome by increasing the number and size of the flux chambers used. Acetylene is either injected into the headspace in the chambers or added directly to the soil using probes (Ryden et al., 1979b; Hallmark and Terry, 1985; Egginton and Smith, 1986; McConnaughey and Duxbury, 1986). The rate at which N2O accumulates in the chamber headspace is then calculated (Tiedje et al., 1989) The core technique involves incubation of minimally disturbed soil cores with C2H2 in a container (Ryden et al., 1987b). The rate of N2O evolution is then measured for a fixed period of time. Soil cores can either be incubated in the field (e.g., Luo et al., 2000) or in the laboratory (e.g., Robertson et al., 1987). The core technique appears to be the most commonly used method for measuring denitrification rates in the field. The technique enables numerous incubations to be carried out cheaply and quickly. A further advantage is that the relatively short-term exposure of soil to C2H2 overcomes the problem that the C2H2 may inhibit nitrification and therefore reduce the rate of denitrification. The use of cores can be problematic since the coring process may disturb the soil

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environment and create effects on denitrification rates that are difficult to interpret. The core method can cause underestimation of denitrification, as the removal of the core from the soil allows O2 to enter the core and thus reduce the denitrification rate (De Klein and van Logtestijn, 1994). Measurement of N2O. Gas chromatography is the most used method and permits convenient analysis of N2O. The major characteristic of the ECD is its great selectivity based on the electron absorption coefficients of the compounds, which pass through the detector. Nitrous Oxide has been shown to have a high electron absorption coefficient at temperatures around 3008C (Kaspar and Tiedje, 1980). The gas chromatography system can provide a linear response to a large N2O concentration range. In summary, analytical techniques investigating abatement strategies require simultaneous measurements of both NH3 and N2O gases. Nitrous oxide fluxes are determined from the headspace samples periodically collected from closed chambers, whereas NH3 flux measurements require an active flow rate. Passive sampling for NH3 results in poor and variable recoveries (20 –60%) (Jagrati Singh, personal communication). Landcare Research and Massey University have recently developed closed chamber techniques that provide measurements of NH3 and N2O from in situ soil-pasture cores (see Photo 3). This technique provides a means for studying the mechanisms and factors affecting NH3 and N2O emissions from intact soil cores.

Photo 3 Chamber technique for simultaneous measurement of ammonia volatilization and denitrification.


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B. MODELLING APPROACHES 1.

Ammonia Volatilization

Rachhpal-Singh and Nye (1986) presented a mechanistic model to predict NH3 volatilization loss following application of urea to soil. This model combines the process of NH3 volatilization with the simultaneous transformation and movement of urea and its products in soil. The process of NH3 volatilization is the transfer of NH3 gas in the soil air from the soil surface to the immediate atmosphere. The rate of NH3 loss is given by [Eq. (11)] FNg ¼ Ka DNg

ð11Þ

where FNg is the flux of NH3 gas and DNg the NH3 gas concentration difference across the soil surface – atmosphere air boundary layer and Ka the mass transfer coefficient, which depends on many factors, of which surface roughness, temperature and the wind velocity over the soil surface are most important. Since the concentration of NH3 gas in the atmosphere is usually negligible, Eq. (11) is simplified to Eq. (12): FNg ¼ Ka ½Ng 0

ð12Þ

where [Ng]0 is the concentration of NH3 gas at the soil surface. Thus the total amount of N volatilized can be calculated directly from the flux of NH3 gas at the soil surface [Eq. (13)]: Total N loss ¼

X Ka T½Ng 0 £ surface area

ð13Þ

where T is time step, and the summation is taken over all time steps. Rachhpal Singh and Nye (1986) observed that the amount of NH3 volatilized calculated using this method was exactly the same as that obtained from the reduction in mass balance of N in soil. The integrated horizontal flux method is often used to estimate NH3 volatilization (Denmead and Raupach, 1993). This method involves a mass balance approach that employs the measurement of the mean atmospheric NH3 gas density minus the background gas density and the mean horizontal wind speed at several heights downwind from the leading edge of a plane source. Neglecting the turbulent component, the product of these measurements gives the horizontal flux. To obtain a well-defined horizontal gas profile, Denmead (1982) suggested at least five sample heights should be used to measure both the wind speed and NH3 concentration. Since measurement of NH3 gas at multiple heights is laborious, Wilson et al. (1982) proposed a model based on measurement of gas density at one height.

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Genermont and Celilier (1997) proposed a detail mechanistic model to predict NH3 volatilization following manure slurry application in the field. The model consists of six submodels: 1. 2. 3. 4. 5. 6.

Physical and chemical equilibria of NH4-N in the soil Aqueous and gaseous NH4-N transfers through the soil Gaseous NH3 transfer from the soil to the atmosphere Water transfer in the soil Heat transfer in the soil Energy budget, water and heat exchange between the soil and the atmosphere.

The first three submodels deal with the transfer of NH4-N in soil/atmosphere. The remaining three submodels simulate heat and water transfer in the soil and are included to account for the temperature and soil water concentration dependent equilibria as NH3 is transported with water in the soil. The major components of the models are described below. The physical and chemical equilibria of NH4-N (submodel 1) include the partitioning of NHþ 4 ions between the soil solid fraction and the soil aqueous phase, and the solubility of NH3. The equilibrium partitioning of NHþ 4 ions þ ) and the soil aqueous phase (NH between the soil solid fraction (NHþ 4 4 ) is described by a Freundlich isotherm [Eq. (14)]: þ bs ½NHþ 4 ðsÞ ¼ as ½NH4 ðaqÞ

ð14Þ

where as and bs are adsorption coefficients for NHþ 4 ions in soil. The solubility of volatile weak electrolytes like NH3 results from two equilibria: ionization [Eq. (15)] and liquid-gas equilibria [Eq. (16)]: þ NHþ 4 ðaqÞ þ H2 O X NH3 ðaqÞ þ H3 O ðaqÞ

ð15Þ

NH3 ðaqÞ X NH3 ðgÞ

ð16Þ

The proportions of NHþ 4 (aq) and NH3 (aq) are determined by the pH of the solution and the equilibrium or dissociation constant, KA, expressed as an exponential function of the temperature of the solution [Eq. (17)]: KA ¼ ½H3 Oþ þ ðaqÞ

½NH3 ðaqÞ ½NHþ 4 ðaqÞ

ð17Þ

where [] denotes the molar concentration of the solute (mol l21). The gas – liquid equilibrium is accounted for by the Henry’s law constant KH, also expressed as an exponential function of the temperature of the solution [Eq. (18)]: PNH3 ¼ KH ½NH3 ðaqÞ where rNH3 is the density of atmospheric NH3.

ð18Þ


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Combining Eqs. (3) and (4) provides the solubility expression as a function of the total aqueous NH4-N concentration of the soils solution {[AN(aq)]} [Eq. (19)]: PNH3 ¼ KH

½ANðaqÞ ½H Oþ ðaqÞ 1þ 3 KA

ð19Þ

The transfer of aqueous and gaseous NH4-N transfers between the soil layers (submodel 2) is described by the classical convection –diffusion scheme using Fick’s law [Eq. (20)]:

›ð½ANðaqÞuw Þ ›ðJw ðuw Þ½ANðaqÞÞ › W ›½ANðaqÞuw ¼2 þ ðD þ Þ ›z NH4 ›t ›z ›z

ð20Þ

where Jw is vertical flow of water in the soil and uw the water content. Þ depends on the NH4-N The NH4-N diffusion coefficient in the soil ðDW NHþ 4 diffusion coefficient in water, and on the soil water content and porosity, integrated in tortuosity factor. The transfer of NH3 gas to the atmosphere (submodel 3) is given by the mean NH3 surface flux of the field [Eq. (21)]: 0:3X 2bi fNH3 ¼ ai ðkup ÞrNH3 ð21Þ z0 where fNH3 is NH3 gas flux, ai and bi the advection coefficients, k von Karman constant (0.40), u p the friction velocity, rNH3 atmospheric NH3 density, X the field lengh, and z0 the roughness length for the wind speed. The water transfer between the soil layers (submodel 4) is described by Darcy’s flux density equation for vertical flow of water in the soil [Eq. (22)]: Jw ðuw Þ ¼ 2Kw ðuw Þ

›hw ðuw Þ þ K w ð uw Þ ›z

ð22Þ

where hw is the pressure head, Kw the hydraulic conductivity and uw the water content of the soil. Similarly, the soil surface temperature and evaporation are calculated using the energy balance equation of the bare soil surface [Eq. (23)]: R n 2 G ¼ H þ lE

ð23Þ

where Rn is the net radiation, G the soil heat flux by conduction, H the sensible heat flux to the atmosphere, and lE the soil evaporation. This model provided a fair picture of the NH3 fluxes throughout volatilization, including total NH3 volatilized, the change in daily loss and their short-term variation due to the influence of meteorological conditions on soil surface temperature, and atmospheric diffusion following spreading slurry over a bare

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soil (Genermont and Celilier, 1997). The model was used successfully to simulate the influence of various meteorological condition and agricultural techniques on NH3 volatilization.

2.

Nitrous Oxide Emissions

In the last 3 decades, the measurement techniques and instrumentation for quantifying gaseous N fluxes have been improved considerably. However, the uncertainties in the regional budgets have not yet been reduced due to large spatial heterogeneity and temporal variability of the factors that control N fluxes in ecosystems. Mathematical models are important in understanding complex phenomena, achieved by testing different hypotheses by comparing model output with measured data. The models can then be used at different scales to extrapolate measured data to wider temporal and spatial scales. Those countries that ratify the Kyoto Protocol are required to produce an annual inventory of N2O emission from all anthropogenic sources (i.e., the result of human activities) to assess the magnitude and change in total emissions. Quantification of N gas emissions from soils requires field and laboratory studies that characterize the fluxes from a range of soil types, vegetation and climatic conditions. Estimates of anthropogenic N2O emissions have traditionally been based on measurements of gas fluxes. Emissions of N2O from the same site and under similar pastoral management are variable in time and space. Thus to assess and predict the long-term effects of anthropogenic N on N2O emissions, adequate models both for N cycling within and N transport between ecosystems are needed. Ideally, spatially extensive and continuous measurements from agroecosystems are required to assess N2O fluxes. Alternatively, we must rely on simulation models for these emission estimates. The Intergovernmental Panel on Climate Change (IPCC) default methodology has been used to estimate global agricultural N2O emissions (IPCC, 1997; Mosier et al., 1998a). Based on a review of field studies by Bouwman (1996), this methodology uses a fixed N2O emission rate of 1.25% for all N applied as fertilizer, manure, green manure or fixed by leguminous crops. The IPCC guidelines provide default factors for estimating emissions (see Mosier et al., 1998a), but also encourage country-specific factors. For example, New Zealand currently uses a modified animal IPCC methodology to produce an annual emission inventory for N2O (Fig. 4). This requires animal population statistics for each region, and the direct and indirect emissions from animal excreta (dung and urine) are estimated using N excreted by each animal type. The emission factor used is 0.01 kg N2O-N kg21 excreted N, which is based on two New Zealand studies of representative pastures (Carran et al., 1995; Muller et al., 1995). The IPCC guidelines divide the agricultural emissions into three categories: direct emissions from agricultural land; emissions from animal waste management


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Figure 4 Schematic presentation of IPCC methodology used in New Zealand to calculate agricultural nitrous oxide emissions.

systems; and indirect emissions associated with N that is volatilized, leached, removed in biomass, or otherwise exported from agricultural land. Each of these categories is estimated to contribute an equal one-third of the total estimated agricultural source (Table IX). This global atmospheric N2O budget is the least well-constrained of the global trace gas budgets. The uncertainty arises from the lack of measurements of N2O fluxes and from the difficulty in scaling-up measurement data. The problem in scaling measurements of biogenic fluxes from soils is also related to their extreme spatial and temporal variability and to large uncertainty; their validation is virtually impossible (Bouwman et al., 2000).

Table IX Global Nitrous Oxide Emissions Calculated with the Revised IPCC Guidelines (Adapted from Mosier et al., 1998a,b) Emission Direct soil emission Animal production Indirect emissions Atmospheric deposition Leaching and runoff Human sewage Total

Amount (Tg N yr21) 2.1 2.1 2.1 0.3 1.6 0.2 6.3

(0.4–3.8) (0.6–3.1) (0.23–11.9) (0.06–0.6) (0.13–7.7) (0.04–2.6) (1.2–17.9)

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The IPCC agricultural N2O emission estimate of 6.3 Tg N yr21 is about 40% higher than the observed atmospheric N2O increase of 3.9 Tg N yr21 (Prinn et al., 1990, 1994). This discrepancy may be due to the overestimation of anthropogenic sources by the IPCC methodology (Nevison, 2000). To calculate national emissions of N2O from agricultural soils the IPCC methodology distinguishes three sources: direct emissions from agricultural soils; emissions from animal production systems; and N2O emissions indirectly induced by agricultural activities. The IPCC guidelines appear to be too simplistic and generalised. They treat all agricultural systems as being the same under all climates, in all soils, in all crops and in all management systems (Mosier et al., 1998a,b), ignoring all site-specific controls. They use animal population statistics for each country to estimate that country’s N2O emission inventory from animal production. Direct and indirect emissions from animal excreta (dung and urine) are estimated using emission factors for N excreted by each animal type and N applied in fertilizers. This highly empirical IPCC default methodology is a first approximation, because of (1) uncertainty in emission factors, (2) uncertainty in indirect emissions, (3) limited data on the type and amount of N excreted by grazing animals, and (4) spatial and temporal variability of N2O emission. Second, the IPCC methodology is not sufficiently flexible to allow mitigation options to be assessed. International experience in deriving emission factors from field measurements at sites with different soil types, climate and crops (IPCC, 1997) shows that these emission factors have a large range, which leads to a large uncertainty in emission estimates (Brown et al., 2001). The major difficulty in quantifying annual N2O fluxes at the field scale is the high degree of spatial and temporal variability. Few field measurements are available for commercial farms, and most do not cover long enough periods to capture seasonal variations. Accordingly, a more robust, process-based approach is required that is internationally acceptable and quantifies N2O emissions at the field level more accurately than the IPCC methodology. Such an approach is needed to develop regional and national scale inventories with known levels of uncertainties. Improved assessment of N2O emission also requires techniques to reduce random variation within farm units, and knowledge of factors that result in systematic variation among different farms and across seasons. Therefore, all the process-based models of N gas emissions must consider the ecosystem N cycle and the interaction of the N cycle with the C cycle, and the environmental and other biophysical conditions that result in systematic variations. In the past 20 years, considerable progress has been made on the development of accurate emission estimates for N2O. Most estimates were initially computed by extrapolating average fluxes from chamber-based measurements by an areal extent of that system (Bowden, 1986; Davidson, 1991), and, like the IPCC methodology, did not account for spatial, seasonal and interannual variability in climate and edaphic controls on emission rates


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(Schimel and Potter, 1995; Potter et al., 1996). Several detailed biochemical process-based models of N gas emissions have been developed over the last several years. About 60 process-based models are available from internet sites, such as: http://yacorba.res.bbsrc.ac.uk/cgi-bin/somnet; http://eco.wiz.uni-kassel. de/ecobas.html While most of these models can be parameterised for individual sites, more generalised ecosystem models are required to calculate temporal and regional integrated fluxes (Potter et al., 1996). Among these 60 models, the three DNDC (Li et al., 1992), DAYCENT (Parton et al., 1996; Del Grosso et al., 2001) and CASA (Potter et al., 1996) are generally used to provide site-specific and regional estimate N2O emissions from soils in recent years, and are described here. DNDC. The Denitrification and Decomposition (DNDC) model (Li et al., 1992) has reasonable data requirements and has produced robust regional estimates for the US (Li et al., 1996), China (Li et al., 2001) and the UK (Brown et al., 2000, 2001, 2002). A modified “NZ-DNDC” model simulated effectively most of the WFPS and N2O emission pulses and trends from ungrazed and grazed dairy pastures and fairly reproduced the real variability in underlying processes regulating N2O emissions (Saggar et al., 2002, 2004). The DNDC model consists of four submodels: thermal-hydraulic, cropgrowth, decomposition, and denitrification. The model is based on the kinetic processes of N2O production where denitrification is activated by a rainfall event that saturates the soil. Soil temperature and moisture are the key factors controlling both decomposition and denitrification. The thermal-hydraulic submodel uses basic climate data to simulate soil moisture conditions and to capture anaerobic microsite formation and sequential substrate reduction. The crop growth submodel simulates growth of various crops from sowing to harvest. Biomass is accumulated based on daily N and water uptake, and thermal degreedays. Yield and N content of above- and below-ground plant components are modelled. The decomposition submodel has four soil carbon pools: litter, microbial, labile and passive. Each pool has a fixed C:N ratio and decomposition rate influenced by soil texture (clay content), and soil moisture and temperature. The decomposition submodel provides initial NO2 3 and soluble C pools for the initiation of denitrification, which is also activated by rainfall and increased WFPS. An increase in the WFPS by rain or irrigation events decreases soil oxygen availability. The WFPS, soluble C, soil temperature, soil pH, available N and denitrifier biomass control the rate of denitrification (Frolking et al., 1998). The DNDC model is designed in such a way that soil moisture has a large influence on N2O fluxes through its impact on the volume of soil in which denitrification occurs and the duration of denitrifying conditions. Water infiltration also causes NO2 3 leaching. Therefore, successful simulation of N2O emissions will depend on the successful simulation of soil moisture conditions. The original version of DNDC has default parameters for soil-water content at field capacity and wilting point as a function of soil texture. The model uses

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a multi-layered soil for simulating soil water conditions. Numerous international researchers from Canada, the UK, Germany, the Netherlands, Italy, Finland, Australia, New Zealand, China, Japan, Thailand and the Philippines have made significant contributions to development of the model and its applications (Table X; Li and Salas, 2003). Saggar et al. (2004) recently modified DNDC to better represent New Zealand’s grazed pasture systems and the modified model “NZ-DNDC” was then used to simulate N2O emissions from pastures grazed by dairy cattle. Overall, the NZ-DNDC was very well able to predict the annual measured emission from both the grazed and ungrazed farms (Fig. 5); annual emission estimates for both farms were within 10% of the measured values, and within the uncertainty range of the measured values. The modified model fairly reproduced some of the variability in underlying processes regulating N2O emissions. However, estimates based on the NZ-refined IPCC methodlogy (New Zealand Climate Change Project 2002) were about 25 –60% lower than for the measured values. The NZ-DNDC model was, therefore, better at predicting N2O emissions than the refined IPCC methodology. Saggar et al. (2002, 2004) suggested that to achieve more reliable field-scale estimates of N2O emissions for grazed pastoral systems further model refinement is needed to account for slow winter pasture growth and N uptake and the flush of spring pasture growth. NZ-DNDC appears to capture the key processes controlling N2O emissions, and offers a robust platform for future achievement of this goal (Saggar, 2002). Current research on N2O abatement in New Zealand (Saggar et al., 2003) focuses also on using NZ-DNDC to monitor the efficacy of mitigating fertilizer- and urine-induced N2O emissions from grazed pasture systems, using NI, and on developing best management practices for efficient effluent application to reduce N2O emissions. DAYCENT. A daily time-step version, DAYCENT was developed to simulate trace gas fluxes that often result from short-term rainfall, snowmelt or irrigation events (Del Grosso et al., 2001). The model’s structure is similar to that described above for the DNDC model, and is a modification of the CENTURY ecosystem model (Parton et al., 1987, 1994) to include trace gas fluxes of CO2, N2O and CH4 (Parton et al., 1996). DAYCENT consists of four submodels: SOM decomposition; land surface parameters; plant productivity; and N gas fluxes. The land surface submodel simulates water content and temperature for various soil layers and evapotranspiration. Plant growth is limited by temperature, water and nutrient availability. The plant productivity submodel simulates plant growth and partitions biomass accumulation based on vegetation type. Transfer of C and nutrients from dead plant material to SOM and available nutrient pools is controlled by lignin concentration, the C:N ratio of the material, the abiotic temperature, soil water decomposition factors and soil physical properties related to texture. Decomposition of the SOM is divided into three pools (active, slow and passive) based on turnover rates. This submodel also describes N

Table X Countries Where DNDC has been Tested at Site Scale and Applied for Regional Inventory Studies (Li and Salas, 2003) Validation

Australia

CO2 and N2O from cropland, grassland, and rainforests NO and N2O from forests N2O fluxes from cropland

Austria Canada China Costa Rica

CO2, CH4 and N2O from cropland and grassland N2O from cropland

Denmark Germany

NO and N2O from forests NO and N2O from forests

India Italy Japan New Zealand

N2O and CH4 from rice paddies N2O from cropland CO2 and N2O from cropland N2O fluxes from pasture

Thailand UK

CH4 from cropland N2O fluxes from cropland and pasture

USA

CO2 and N2O from cropland and grassland

USA

CO2 and CH4 from wetland

Application Trace gas flux assessment and regional inventory Trace gas flux assessment National N2O inventory for agricultural lands National C sequestration, CH4 and N2O inventory for cropland Regional N2O inventory for agricultural land NO and N2O inventory for cropland and forests N2O inventory for agricultural lands Developed NZ-DNDC for farm scale N2O inventory for grazed pastures Developed UK-DNDC for national N2O inventory for agricultural lands National C sequestration and N2O inventory for cropland

Reference Wang et al. (1997) Stange et al. (2000) Smith et al. (2002) Xiu et al. (1999) and Li et al. (2001) Plant et al., 1998 Stange et al. (2000) Butterbach-Bahl et al. (2001) Bidisha Banerjee (unpublished) Mulligan (2002) (unpublished) Cai et al. (2003) Saggar (2002) Saggar et al. (2004) Cai et al. (2003) Brown et al. (2002)


Country

Li et al. (1996) Zhang et al. (2002)

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Figure 5 Annual-measured, model-predicted and IPCC-calculated nitrous oxide emissions from the two ungrazed and dairy-grazed sites (adapted from Saggar et al., 2004).

mineralisation, N fixation and N fertilisation, all of which feed into the available nutrient pool. þ The N gas submodel uses NO2 3 and NH4 concentrations, predicted within the SOM decomposition submodel, to predict N2O and NOx emissions from nitrification and denitrification (Parton et al., 2001). Nitrification rates, and associated N2O emissions, are controlled by NHþ 4 concentration, water content, soil temperature, soil pH and texture. Nitrous oxide emissions are assumed to be linearly proportional to the nitrification rate: the equation calculating the N2O flux via nitrification can be found in Parton et al. (2001) (enclosed within report). Peak nitrification rates are assumed to occur when WFPS is , 50%, while nitrification activity decreases exponentially as soil pH falls below 7 due to acidity (Del Grosso et al., 2001). Denitrification rates are controlled by labile C availability, NO2 3 concentration, and O2 availability. Modelled soil respiration is used as an estimate for labile C availability and soil NO2 3 is simulated by DAYCENT. The O2 status is calculated as a function of WFPS, soil physical properties that control gas diffusivity, and O2 demand. When WFPS is less than , 55%, it is assumed that no denitrification occurs. Between , 55 and , 90%, denitrification rates increase exponentially and the rate of increase levels off as soils approach saturation (Parton et al., 2001). Once emissions of N2O and N2 via denitrification have been calculated, an N2 to N2O ratio function is used to infer the N2O and N2 emissions. This ratio is a function of soil gas diffusivity, and the ratio of NO2 3 to labile C (Del Grosso et al., 2001).


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CASA. This model is based on a conceptual “hole-in-pipe” model of Firestone and Davidson (1989) with an extended version of the Carnegie –Ames –Stanford (CASA) Biosphere model (Potter et al., 1993, 1996). The model is a process formulation of coupled ecosystem production and soil C and N fluxes, and simulates seasonal patterns in C assimilation, nutrient allocation, soil C inputs, N mineralisation, and N2O production. The model is driven by global data sets for climate, radiation, and a remotely sensed vegetation index (Normalised Difference Vegetation Index, NDVI). The net primary production (NPP) is calculated from the fraction of intercepted, photosynthetically active radiation (FPAR), surface solar irradiance, and light utilisation efficiency. Soil and climatic variables control the spatial and temporal distribution of C and N fluxes among SOM pools in a similar way to the CENTURY model. N gas emission estimates in the model are based on predicted rates of N mineralisation and an index of water-filled pore space. The net mineralisation fluxes to the mineral-N pool are calculated as a difference between the gross mineralisation and immobilisation fluxes controlled by the C:N ratio. The model produces and emits N2O at intermediate WFPS and higher soil moisture levels and, with increased lack of oxygen, N2O emission increases exponentially. CASA, CENTURY (DAYCENT) and DNDC are three major biogeochemical models developed in the US for predicting C sequestration and non-CO2 greenhouse gas emissions from agricultural sectors. These models differ in the original purposes for their development and thus have advantages and disadvantages across a potentially wide range of applications. The CASA model was supported by NASA in order to use remote sensing for estimating C and N dynamics over large regions (Potter et al., 1993). CASA can directly use remotely sensed information and convert it into biophysical and biogeochemical features. CASA has been successful in estimating above-ground biomass and SOC dynamics at a large scale, and requires relatively less input parameters, therefore it can be applied to large scales with a high efficiency. Many detailed management measures, such as fertilization timing and depth, irrigation water amount, manure types, etc., are not currently handled by CASA. CENTURY was originally developed for predicting C dynamics in grassland (Parton et al., 1993) and has done a fair job in estimating C storage and dynamics in semi-arid grassland in the US with N simulation lagging behind C simulation. The US Environmental Protection Agency (USEPA) initiated DNDC in 1989 to estimate N2O emissions from US agriculture (Li et al., 1992). The demand forced DNDC to incorporate detailed processes of N transport and transformation into the model framework. Carbon dynamics and crop growth were later developed in DNDC to support the N simulations. Detailed information about farming practices is required by DNDC to track their effects on C and N dynamics. The coupling of the detailed N processes and detailed management information provides a sound basis for DNDC to assess the impacts of management alternatives on N gas emissions and N leaching. During the last decade, all

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the three models basically reached their initial goals, and tended to expand their objectives. The expansions have made the models share common features, such as predicting plant growth, SOC turnover, and trace gas emissions. However, the three models still differ in many ways because they possess different structures at the biochemical/geochemical process level, which are inherently related to their original purposes and applications. The differences in these models influence the capacity, and hence utility, of the models for a broad range of potential applications to assess atmospheric and aquatic impacts of agroecosystems. Both the DNDC and DAYCENT can be used to simulate N2O production from soils after parametrisation with local data, and appropriate modifications and verifications against measured N2O emissions under different management regimes (Dalal et al., 2003).

VII. ENVIRONMENTAL IMPLICATIONS OF GASEOUS EMISSIONS In the context of global climate change and environmental pollution, N gases, such as NH3, N2O and NO, provoke attention/cause concern because of their radiative or chemical effects in the atmosphere. The human-induced input of reactive N in the global biosphere has increased to approximately 150,000 Mg N each year and is expected to continue to increase for the foreseeable future. This increase in the reactive N comes at, in some instances, significant cost to society through increased emissions of NOx (pronounced “knox”, sum of NO and NO2), NH3, N2O, and NO2 3 and deposition of NOy (sum of knox plus all other oxidised forms of N such as HNO3 and peroxyacetyl nitrate in the atmosphere) and NHx (Mosier et al., 2001). A portion of the N applied to agricultural soils in the form of chemical fertilizers, animal excreta, organic manures or fixed by legumes, is released to the atmosphere in gaseous forms such as NH3, NO, N2O and N2. Thus, agriculture is one of the major sources of gaseous N emissions that result from increased N fertilizer use, thereby polluting the environment. For example, NH3 affects visibility, aerosol chemistry, and health and climate as it causes acidification and eutrophication when deposited in soils and waters. It also acts as a neutralising agent for acidic aerosols besides affecting vegetation and forming NO2 3 . Ammonia has a short lifetime in the atmosphere but it can act as a secondary source of NO and N2O. The oxidised N species, NO and N2O, play an important role in tropospheric chemistry. They regulate the photochemical production of ozone and the abundance of the OH2 radical, which is the main oxidant in the atmosphere. They are directly or indirectly involved in global warming and the production and consumption of atmospheric oxidants (such as ozone), and in the photochemical formation of nitric acid (acid rain). Ozone


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protects the biosphere from the harmful effects of solar ultraviolet radiation. Emissions of NO contribute to acid deposition and to ozone formation in the troposphere. Nitric oxide reacts with OH2 radicals in the atmosphere that are involved in the removal of other greenhouse gases, such as methane (Williams et al., 1992).

A. ACID RAIN Carbon dioxide combines with water in the air to form a dilute solution of carbonic acid (H2CO3) at about pH 5.6. For this reason, acid precipitation is arbitrarily defined as precipitation with a pH below 5.6. The acidity of rain, snow and atmospheric particulates that fall upon much of the world appears to have increased significantly over the last 4 decades. In addition to natural sources of acid precipitation that result from geological weathering, volcanic eruption, anaerobic decomposition of organic matter, air-borne sea salt sprays, and lightning, most of the increased acid precipitation burden has been attributed to consumption of fossil fuels, especially coal. Major anthropogenic sources include combustion of fossil fuels, smelting of ores, exhausts from internal combustion engines, and N fertilization of agricultural and forest lands (Binns, 1988; Longhurst, 1991). Widespread occurrence of acid precipitation and dry deposition results in large part from industrial emissions of SOx and NOx (Longhurst, 1991). These gases are transformed in the atmosphere to sulfuric and nitric acids, transported over long distances, and deposited on vegetation, soils, surface water, and building materials. While the majority of the NOx emissions are local/natural in origin, SOx emissions are often transboundary in nature. The average annual ratio of sulfuric acid to nitric acid is about 2:1 in North America, but nitric acid is becoming progressively more important because of the installation of flue gas desulfurisation (FGD) systems in coal-fired power stations, and the increased use of N fertilizers in agriculture (Edwards and Someshwar, 2000). The reaction of NO2 with OH2 ions in the atmosphere is very fast and produces HNO3 that is removed from the atmosphere by a heterogeneous interaction with raindrops, which results in acid rain. In the atmosphere, increases in acid deposition (NOy and NHx) have led to the acidification of aquatic and soil systems and to reductions in forest and crop system productions (Mosier et al., 2001). Soil acidification can exert itself in several ways: (1) increase in soil acidity or decrease in pH; (2) decrease in base saturation; (3) unbalanced availability of elements in the root environment; or (4) decrease in the acid neutralizing capacity (ANC) of the soil (Van Breemen, 1991). Soil acidification caused by these processes can have adverse impacts where soils are unable to buffer against pH decrease. For example, in parts of North America and Europe, soil acidification

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caused by acid precipitation has resulted in forest decline (Binns, 1988; Longhurst, 1991). Similarly, Pitcairn et al. (1998) found that NH3 emissions from livestock operations adversely affected flora in woodlands within a 300 m radius of the NH3 source in England: the number of natural species in the woodland decreased and weedy species increased. Based on the results from this study, a critical deposition load of . 20 kg N ha21 was identified above which undesirable changes in species diversity occurred.

B. OZONE DEPLETION

AND

GLOBAL WARMING

Nitrous oxide is an important atmospheric constituent and a major source of stratospheric NO (Cicerone, 1989). The atmospheric concentration of N2O is about 310 ppbv and its lifetime is 166 ^ 16 years (Prinn et al., 1990). In the troposphere, N2O absorbs terrestrial thermal radiation and thus contributes to greenhouse warming of the atmosphere. The global warming potential (GWP) of each molecule of N2O is about 300 times more than that of CO2 (Rodhe, 1990). Nitrous oxide currently accounts for 2 – 4% of total GWP (Watson et al., 1992) and an increase of 0.2 – 0.3% in N2O concentrations in the atmosphere would contribute about 5% to greenhouse warming (Cicerone, 1989). In the troposphere, N2O absorbs terrestrial thermal radiation and contributes to greenhouse warming of the atmosphere, while in the stratosphere N2O is involved in the depletion of the ozone layer that protects the biosphere from the harmful effects of solar ultraviolet radiation (Crutzen, 1981). Nitrous oxide is photolytically oxidised to NO, which reacts with the ozone and absorbs harmful solar ultraviolet radiation. Therefore, the major sink for N2O is photolysis in the stratosphere, leading to the NO products that influence levles of stratospheric ozone (O3). Nitrous oxide present in the atmosphere is dissociated by an excited atom of oxygen (O(1D)) produced from the photochemical reaction of O3 with ultraviolet light (hn) [Eq. (24)] followed by the destruction of O3 [Eq. (25)] NO2 þ Oð1 DÞ ! 2NO

ð24Þ

O3 ! O2 þ O

ð25Þ

Therefore, the net reaction is [Eq. (26)]: NO2 þ O3 $ 2NO þ O2

ð26Þ

so that high concentrations of NO tend to drive the reaction backward and the concentration of O3 is determined by [Eq. (27)] (Seinfeld, 1989): O3 ðppmÞ ¼ 0:021½NO2 =½NO

ð27Þ


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Ozone is subjected to further photochemical reaction involving ultraviolet light (hn), with wavelengths , 310 nm, producing an excited atom of oxygen [O (1D)] [Eq. (28)], which further reacts with water, resulting in the production of OH2 radicals [Eq. (29)]. The OH2 radical persists only for a few seconds and further reacts to produce HO2 [Eq. (30)] and H2O2 [Eq. (31)]: O3 þ hn $ O2 þ Oð1 DÞ

ð28Þ

Oð1 DÞ þ H2 O $ 2OH2

ð29Þ

2OH þ 2O3 $ 2HO2 þ 2O2

ð30Þ

2HO2 $ H2 O2 þ O2

ð31Þ

The OH2 radicals are the major source of oxidizing power in the troposphere (Schlesinger, 1996). In areas, where the concentration of NOx is high, effective control of atmospheric O3 levels may also depend on the regulation of volatile hydrocarbons (Seinfeld, 1989). About 80% of the N2O reaching the stratosphere is destroyed in a reaction producing N2 and the remaining 20% in a reaction with an excited atom of oxygen [O (1D)] that produces NO (Warneck, 1988). It is the NO produced from N2O that destroys O3. In the last few decades, the concentration of N2O in the atmosphere has progressively increased at an annual rate of 0.2– 0.3% as a result of human activities (Rasmusen and Khalil, 1986; Prinn et al., 1990), and about 70% of the anthropogenic N2O increase is attributed to agriculture (Watson et al., 1992). Since 1900, the global anthropogenic fixation of reactive forms of N has increased from less than 5000 to approximately 20 000 Mg N in 1950 to almost 150,000 Mg N in 1996, and is expected to approach 190,000 Mg N by 2020. This newly fixed N is derived from production of synthetic fertilizers, from the increased production of crops that fix N biologically, and from fossil fuel consumption (Mosier and Kroeze, 2000). It is generally recognised that the use of chemical N fertilizer is the most important contributor to N2O emissions from agricultural soils. It is estimated that about 1500 Mg of N is injected annually into the atmosphere as N2O as a result of fertilizer application, which represents about 44% of the anthropogenic input and about 13% of the total annual input of N2O to the atmosphere (Watson et al., 1992). Alkali-hydrolysing N fertilizers, such as urea, affect organic matter degradation by promoting microbial activity, including nitrification and denitrification processes. The N2O emissions from the ammonium-based fertilizers could be substantial and proportional to NO2 3 formation (Goodroad and Keeney, 1984). Crop residues with a low C:N ratio that are easily decomposable can promote high N2O emissions (Khalil et al., 2001). Biological N fixation and animal manures are the other major contributors to N2O atmospheric input. Atmospheric N2 fixed by legumes can be nitrified and

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denitrified in the same way as fertilizer N, thus resulting in N2O emission. Legumes can thus increase N2O emission by a factor of 2 –3 compared with nonlegume pastures (Duxbury et al., 1982). Addition of animal waste/manure to soil supplies additional quantities of C and N, promotes microbial activity, and may release substantial amounts of N2O (Beauchamp, 1997). A 5- to 10-fold increase in N2O was observed in grazed pasture compared with ungrazed pasture (Saggar et al., 2002, 2004). These results confirmed that in grazed pastures it is animal excreta deposited in the form of dung and urine that provide high concentrations of available N and C, and are the principal source of N2O production. The amount of N applied to agricultural land from animal excreta (urine and dung) and organic manures (animal and plant waste products) is nearly equal to that from chemical fertilizers.

VIII. MANAGEMENT PRACTICES TO CONTROL GASEOUS EMISSION Loss of N caused by human activities leads to environmental problems locally, nationally and globally, and agriculture is the single largest contributor to the N loss. Anthropogenic N losses enter the environment through the use of N ferilizers and the presence of N in food and fodder. Another important source of gaseous N emissions is the combustion of fossil fuels. A reduction in N losses from agriculture will significantly reduce the total gaseous N loss to the atmosphere. For overall protection of the entire environment the emission of N gases and their mitigation should be considered. At the same time the needs of the consumers and producers of biomass (food, feed, raw materials and energy) must be fulfilled. Several options for the mitigation of gaseous emission of N have been suggested in a number of reviews (Ryden, 1983b; Cole et al., 1996; Mosier et al., 1996, 1998a,b, 2002; Freney, 1997; Smith et al., 1997; Oenema et al., 1998). These options are aimed at increasing the efficiency of N fertilizer use and on reducing the amount of N cycling through an agricultural system. The primary consideration for mitigating gaseous N emissions from pastoral land is to match the supply of mineral N (from ferilizer application, legume-fixed N) to its spatial and temporal needs. Although it is possible to achieve uniform application of N fertilizers, it is difficult to control the uneven excretal distribution in the annually grazed pastures. In general, management practices help to optimise the pasture’s natural ability to compete with processes such as leaching, denitrification and NH3 volatilization, all of which lead to the loss of plant-available N from the soil –plant system. These management practices include optimum N supply to pasture crops, proper animal residue management, controlled-release fertilizer (CRF) use, NI, and proper water management. Strategies and best management


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practices for gaseous N emission abatement from grazed pastures as identified by Whitehead (1995) and Oenema et al. (1998) are outlined below: † †

†

†

Reduce accumulation of mineral N in soil by restricted grazing and properly timed slurry and fertilizer application Increase efficiency of N utilization by W Increasing productivity per animal and reducing the stockingrate W Lowering feed N content to lower urine N content W Storing and utilizing animal excreta effectively W Adjusting fertilizer N application, i.e., B No nitrate-containing fertilizers on wet soils B No autumn or winter fertilization B Use urease and NI, where appropriate B Modest amounts adjusted to crop demand Proper drainage, runoff control and irrigation management W Prevent large groundwater fluctuations W Prevent flooding W Prevent surface runoff Proper sward and soil management W Establish and maintain productive swards W Prevent soil compaction W Maintain soil pH between 5.5 and 6.0 W Whenever applicable, grow cover crops during autumn and winter.

As discussed above, in grazed grassland systems, N returned in the animal excreta, particularly in the urine, is a major source of N2O and NH3 emissions. Additionally, the indirect greenhouse gas NH3 emitted from animal excreta, acts as a precursor for N2O and NO (Clemens and Ahlgrimm, 2001). Therefore, NH3 abatement will result in decreasing N2O emissions caused by atmospheric deposition of NH3. However, investigatig the effects of control options that are available for European agriculture on the emissions of NH3, N2O and CH4, Brink et al. (2001) found that NH3 abatement may have an adverse effect on N2O emissions, while abatement of N2O results in a net decrease in NH3 volatilization. Abatement strategies for reduction of gaseous N emissions in grazed pastures should focus on reducing the gases emitted from animal excreta. A very simple measure to abate these emissions may be possible by reducing animal livestock and hence the amount of excreta. Therefore, a reduction of meat and fat consumption in the industrial world would help reduce animal stocks and also the emissions. Another mitigation option is to manipulate the N economy of the animal to reduce N excretion. A lower N content of pasture will reduce N excretion by animals and consequently NH3 volatilization loss. This may be achieved by reducing the level of N ferilizer application to pastures or substitution of grass by silage. Recent studies by Kebreab et al. (2001) show

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that excretal N could be reduced by using grass grown with moderate fertilzer application, and maize-based energy supplements, formulated to provide low degradable protein and with N intakes of less than 400 g d21 for average yielding cows. Gaseous emissions of N are much higher for grazing animals than for housed animals with effluent treatment using anaerobic lagoons (Mosier et al., 1998a,b), and restrictions on grazing can reduce emissions from dairy farming systems (Velthof and Oenema, 1997; Oenema et al., 1998). For example, the N2O emissions from aerobic effluent treatment systems appear to be 20 times higher than from anaerobic systems (Mosier et al., 1998a,b). However, this may result in higher NH3 volatilization losses from the field application of this manure (Velthof et al., 1996). Several techniques, such as incorporation, deep and shallow injection, slit injection, slury dilution, trailing shoe, band spreading, and sprinkling are available that reduce the amount of NH3 volatilization during and after field application of manure (Klimont, 2001). In excreta, microbial activity induces hydrolysis of urea resulting in NH3 emissions, while NO and N2O are emitted during nitrification and denitrification. Consequently, these emissions could be reduced if it were possible to control or influence the microbial processes in the excreta. New technologies employing CRFs and urease and NI can be used as effective mitigation alternatives to control environmental impacts of fertilization. The CRFs effectively decrease NO2 3 leaching, increase crop yields (Shoji et al., 2001) and reduce N2O emissions (Delgado and Mosier, 1996). NI have been proposed as management alternatives to reduce NO2 3 leaching and denitrification, and to provide greater N availability to the crop. NI are 2 compounds that delay the bacterial oxidation of NHþ 4 to NO3 in the soil for a certain period by depressing the activity of Nitrosomas. These NI can slow nitrification, decrease NO2 3 leaching (Cookson and Cornforth, 2002), increase N assimilation and yield (Freney et al., 1992; Yadvinder-Singh et al., 1994), and mitigate N2O (Bremner et al., 1981; Aulakh et al., 1984a; Bronson and Mosier, 1993; McTaggart et al., 1997; Castaldi and Smith, 1998). The use of dicyandiamide (DCD) NI in pastures has been shown to reduce N2O emissions by up to 80% (Velthof et al., 1996; McTaggart et al., 1997; Williamson and Jarvis, 1997). In very acid soils (pH 4.0), DCD was not effective in reducing emissions, probably because of its inactivation by binding to humic compounds (Mosier et al., 1998a,b). While hundreds of NI, including pyridines, pyrimidines, mercaptol compounds, succinamides, acetylenes, thiazoles, triazoles, triazines and carbon disulphide, have been evaluated worldwide (Prasad and Power, 1995), so far only two (DCD and Nitrapyrin) have gained importance for practical use. Furthermore, DCD is expensive for large-scale use in agriculture, and high application rates (25 kg DCD ha21) are required for significant nitrification inhibition (Merino et al., 2002). Nitrapyrin is seldom effective because of


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sorption on soil colloids, hydrolysis to 6-chloropicolinic acid, and loss by volatilization. It is also corrosive and explosive, and poses certain toxicology problems (Trenkel, 1997). Acetylene is a potent inhibitor, but being a gas it is difficult to introduce into the soil and maintain sufficient concentration to limit nitrification. A new nitrification inhibitor 3,4-dimethylpyrazol phosphate (DMPP; ENTEC), effective at low concentrations of 0.5 to 1.0 kg active compound ha21, has recently been developed in Germany (Zerulla et al., 2001). The practical advantages of NI for agriculture and for the environment are: † a significant reduction in NO2 3 leaching losses from ferilizers † a decrease in the emission of nitrogenous greenhouse gases, especially N2O † smaller N losses and the temporary ammonium nutrition of crops leading to yield increases † better utilization of N by plants † reduced workload of farmers due to more flexible timing of fertilizer applications. 2 Bolan et al. (1997) examined the distribution of NHþ 4 and NO3 ions in fresh field-moist pasture soil samples incubated with urea fertilizer (200 kg N ha21) in the presence and absence of DCD (25 kg DCD ha21) over 8 weeks. In the absence of DCD, the concentration of NHþ 4 increased for an initial period of 2 weeks and then decreased steadily. There was a corresponding increase in NO2 3 concentration after 2 weeks of incubation. The initial increase in NHþ 4 concentration resulted from the conversion of urea N to NHþ 4 ions. The 2 subsequent oxidation of NHþ 4 to NO3 (nitrification) in the absence of DCD þ caused a decrease in NH4 and an increase in NO2 3 levels. In the presence of DCD, 21 ) and there was however, the NHþ 4 concentration remained high (. 160 mg kg 2 no increase in NO3 concentration. More recent work (Cookson and Cornforth, 2002) suggests application of DCD in urine-amended plots resulted in a more 2 gradual decrease in soil NHþ 4 concentrations, significantly reduced peak NO3 2 concentrations, decreased the amount of NO3 leached, and hence decreased the potential for denitrification losses. Conversion from conventional to organic farming has been discussed as a possible way to reduce N dissipation. The most common argument in favour is that organic farming has lower N-inputs and therefore lower potential N losses. Greater rates of denitrification are usually observed with zero tillage compared with ploughed soils (Aulakh et al., 1984b; Linn and Doran, 1984; Staley et al., 1990). This increase is related to increased SOM and higher levels of available C in the upper part of the top soil, as well as to greater soil densities and decreased soil aeration (Aulakh et al., 1991). Moreover, no-till systems provide favourable living conditions for denitrifying bacteria (Doran, 1980). However, no differences were found in the rates of N2O emission between conventional

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tillage (CT) and no-till when measurements were made 7 years after the establishment of the tillage treatments (Choudhary et al., 2002).

IX. CONCLUSIONS AND FUTURE RESEARCH NEEDS Ammonia volatilization and denitrification are important components of the global N cycle, and play a major role in transferring the biologically and chemically fixed N to the atmospheric pool of N2. The significance of these processes of gaseous emission in N use efficiency in agricultural, grassland, and forest systems, and their implications for environmental quality are well recognized. While NH3 volatilization causes acidification of soil and aquatic environments, one of the products from denitrification, N2O, has been implicated in both global warming and stratospheric ozone depletion. Ironically, denitrification has also been used as a means to improve the efficiency of N removal from wastewaters and to protect water quality. Ammonia volatilization is purely a chemical process that occurs mostly under alkaline pH conditions, whereas denitrfication is largely a biological process. Studies on the ecology of denitrifying bacteria have enhanced our understanding of the denitrification process. Although denitrification is an anaerobic process, denitrifiers are generally facultative aerobes. The microorganisms can use NO2 3 as their electron acceptor to obtain energy from organic or inorganic compounds when O2 availability is limited. Ammonia volatilization is regulated by soil pH, CEC, temperature and wind velocity. Denitrification is regulated by C supply, NO2 3 -N concentration, aeration status, pH, and temperature. Plant growth, agricultural management practices, and weather conditions, can also regulate NH3 volatilization and denitrification in the field by affecting the basic factors that influence these two processes. The effect of individual parameters on these processes is well established. However, there is a lack of understanding of the interaction of the many factors affecting these processes in various soil environments. There has been a substantial development in methodology and instrumentation for quantification of NH3 volatilization and denitrification in recent years, and various methods of measurement are now available. The most common one uses an acid trap for NH3 volatilization and C2H2 as an enzyme inhibitor to block N2O reduction to N2. Denitrification can thus be measured as the amount of N2O produced in soil treated with C2H2. These techniques have been widely applied in the field using chambers and intact soil cores, and give acceptable results, although the methods present some problems. Research has now turned to the quantification of N loss through simultaneous NH3 volatilization and denitrification in field soils. While the potential NH3 volatilization rate can be measured using closed chamber techniques under


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alkaline conditions, the potential denitrification rate of a soil can be measured under non-limiting substrate and anaerobic conditions. The potential rates measured are generally higher than the actual rates of gaseous emissions measured in the field, since the conditions in the field do not always favour emission. High temporal and spatial variation confound the measurement of gaseous emission in the field, especially in grazed pasture, and reliable quantification of emission rates remains a goal to be achieved. The rates of gaseous emission in pasture soils obtained from a limited number of measurements vary. In addition to uneven distribution of animal excreta, which are the major sources of gaseous emission, the pasture soils have year-round root activity and hence O2 demand, and the presence of active roots also stimulates soil microorganisms through exudation of C compounds. This favours denitrification, as does the presence of animals with their consequent effects on soil structure and localised high concentrations of available N. On the other hand, denitrification is unlikely to be a major N loss due to high porosity in improved pasture soils. Pasture management practices such as fertilization, grazing management and irrigation may also have an impact on gaseous emission in pastures. The ultimate goal is to be able to estimate emissions accurately on a regional and national scale based on available climatic data, soil types, and grazing animals and their excretal N inputs. Field-scale mechanistic models can be used to estimate NH3 volatilization. However, the IPCC methodology used to estimate N2O emission has a number of limitations because it treats all agricultural systems as being the same under all climates, in all soils, in all crops and in all management systems (Mosier et al., 1998a,b), and ignores all site-specific controls. This highly empirical methodology is considered to be at the simple end of the spectrum of simulation models of N gas fluxes (Frolking et al., 1998). The process-based modelling approaches offer a solid beginning to this goal and a base for future development. The strength of these approaches is in their capacity to link N gas fluxes to soil, plant and animal processes of grazed pasture ecosystems, particularly those controlling N dynamics. Future testing of these mechanistic models at regional and national scales is essential in elucidating variations at scale relevant to global change. Given the current knowledge of NH3 volatilization and denitrification, we consider the following research areas should be pursued: † The major source of gaseous emission in grazed pasture is the deposition of urine and dung. However, not much work has concentrated on the relative contribution of urine and dung patches to overall gaseous N emission, although urea hydrolysis, NH3 volatilization losses and nitrification have been extensively studied during N fertilizer application in arable soils. † Little information is available on the ecology of denitrifiers. The denitrification enzyme activity (DEA) in soil is usually high, even in field soils in which the conditions (such as levels of C, NO2 3 -N, and O2) do not favour

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denitrification. Further work needs to establish how these bacteria can survive in such soils. † Currently there are inadequacies in our understanding of the spatial and temporal variability in gaseous emission of N in the field. More information about the causes of variability in these processes under various field conditions and management practices is required to enable better estimates of gaseous emission rates on a landscape scale. † One area of particular interest is the influence of animal grazing patterns on NH3 volatilization and denitrification in grazed pastures. In this area, it is also necessary to understand the relationship and relative importance of N loss through gaseous emission of N compared with the N loss through NO2 3 leaching. † Research on the relationship between gaseous N emission and management practices, such as fertilizer and manure application, soil amendments (e.g., liming), irrigation and tillage, is desirable to reduce N loss through gaseous emission. Information is also needed to minimize N loss through gaseous emission when plant residues and manures are used as nutrient sources.

ACKNOWLEDGEMENTS Our thanks to Anne Austin of Landcare Research, New Zealand, for editing; the New Zealand Ministry of Foreign Affairs and Trade for the Commonwealth Scholarship to Rita Bhandral; and Summit-Quinphos for financial assistance to Jagrati Singh.

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Williams, P. H., Hedley, M. J., and Gregg, P. E. H. (1990). The effect of preferential flow of dairy cow urine and simulated rainfall on movement of potassium through undisturbed topsoil cores. Aust. J. Soil Res. 28, 857–868. Williams, E. J., Hutchinson, G. L., and Fehsenfeld, F. C. (1992). NOx and N2O emissions from soil. Global Biogeochem. Cycles 6, 351–388. Williams, P. H., Jarvis, S. C., and Dixon, E. (1998). Emission of nitric oxide and nitrous oxide from soil under field and laboratory conditions. Soil Biol. Biochem. 30, 1885–1893. Williamson, J. C., and Jarvis, S. C. (1997). Effect of dicyandiamide on nitrous oxide flux following return of animal excreta to grassland. Soil Biol. Biochem. 29, 1575–1578. Wilson, J. D., Thurtell, G. W., Kidd, G. E., and Beauchamp, E. G. (1982). Estimation of the rate of gaseous mass transfer from a surface source plot to the atmosphere. Atmos. Environ. 16, 1861–1867. Wood, C. W., Marshall, S. B., and Cabrera, M. L. (2000). Improved method for field-scale measurement of ammonia volatilization. Commun. Soil Sci. Plant Anal. 31, 581–590. Xiu, W. B., Hong, Y. T., Chen, X. H., and Li, C. (1999). Agricultural N2O emissions at regional scales: a case study in Guizhou, China [in Chinese]. Sci. China 29, 115–117. Yadvinder-Singh, Malhi, S. S., Nyborg, M., and Beauchamp, E. G. (1994). Large granules, nests or bands—methods of increasing efficiency of fall-applied urea for small cereal-grains in NorthAmerica. Fert. Res. 38, 61–87. Yamulki, S., Jarvis, S. C., and Owen, P. (1998). Nitrous oxide emissions from excreta applied in a simulated grazing pattern. Soil Biol. Biochem. 30, 491–500. Yoshinari, T., Hynes, R., and Knowles, R. (1977). Acetylene inhibition of nitrous oxide reduction and measurement of denitrification and nitrogen fixation in soil. Soil Biol. Biochem. 9, 177–183. Zerulla, W., Barth, T., Dressel, J., Erhardt, K., von Locquenghien, K. H., Pasda, G., Radle, M., and Wissemeier, A. H. (2001). 3,4-dimethylpyrazole phosphate (DMPP)—a new nitrification inhibitor for agriculture and horticulture. Biol. Fert. Soils 34, 79–84. Zhang, Y., Li, C., Zhou, X., and Moore, B. (2002). A simulation model linking crop growth and soil biogeochemistry for sustainable agricultural. Ecol. Modelling 151, 75–108. Zhu, T., Pattey, E., and Desjardins, R. L. (2000). Relaxed eddy-accumulation technique for measuring ammonia volatilization. Environ. Sci. Technol. 34, 199–203. Zumft, W. G. (1997). Cell biology and molecular basis of denitrification. Microbiol. Mol. Biol. Rev. 61, 533 –543.

MODELING CADMIUM UPTAKE AND ACCUMULATION IN PLANTS L. Tudoreanu1 and C. J. C. Phillips2 Department of Clinical Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, UK

I. Introduction II. Empirical Models A. Root Uptake of Cadmium B. Empirical Relationships in Foliar Uptake of Cadmium III. Mechanistic Models A. Root Uptake Models B. Dynamic Foliar Uptake Models IV. Cadmium Uptake and Accumulation—A Modeling Perspective on the Main Processes and Phenomena Related to Uptake and Accumulation of Cadmium in Plants A. Cadmium Influx to the Root B. Foliar Uptake C. Accumulation Mechanisms in Plant Tissues D. Root Parameters Affecting Cadmium Accumulation by Plants E. Ion Competition F. The Influence of Symbiotic Fungi on Cadmium Uptake G. Short Distance Cadmium Transport H. Long Distance Cadmium Transport V. Summary and Conclusion A. Summary B. Conclusions References Models of cadmium uptake and accumulation by plants are potentially of value in evaluating both the soil and plant components, in order that limits can be established, particularly in relation to soil concentrations, to restrict cadmium in the human food chain. Although the theoretical pattern of uptake is believed to follow a Mitserlich function, the best estimates to date that are based on empirical data use only linear functions, due to a paucity of suitable 1 Present address: Department of Mathematics, Physics and Informatics, University of Agonomy and Veterinary Medicine, Bucharest, Romania. 2 Present address: School of Veterinary Sciences, University of Queensland, Gatton 4343, Queensland, Australia.


122

L. TUDOREANU AND C. J. C. PHILLIPS data, with r 2 values of 0.35 and 0.62 for maize and ryegrass, respectively. A feature of these empirical models is the strong dependence of cadmium uptake on the interaction between soil cadmium concentration and soil pH. Insufficient data currently exist to develop empirical models of foliar cadmium uptake. Mechanistic models are not well developed, but the most realistic models assume that ions are transported to roots by mass flow and diffusion and are absorbed at rates that depend on their concentration at the root surface, following Michaelis – Menten kinetics. However, the level of agreement with empirical data is unsatisfactory and further work is required to isolate the key variables contributing to the errors, in particular the role of ectomicorrhizal fungi on root uptake. The influences of root exudates and soil temperature on the solubility of different Cd species in the rhizosphere of apical root zones also require more detailed evaluation before incorporation into mechanistic models, and the absence of an accurate technique for estimating root surface area is an impediment. A further disadvantage of existing mechanistic models is the necessity for difficult and expensive root measurements, restricting their value for field predictions. Mechanistic foliar cadmium uptake models have been developed, but key variables such as translocation of heavy metals into the plant and the resuspension of the pollutants into the atmosphere have so far been ignored. Differential adherence of wet and dry particles to the leaves and the influence of soil splash on stem and leaf uptake remain to be effectively quantified. Although the parameters described so far may be generalized for a number of different soil and plant systems, the differences between genotypes on phytochelatin production and differential translocation rates cause major variation in accumulation rates and will ensure that both empirical and mechanistic models are genotype specific. Cadmium transport within the plant can be effectively dichotomized into short distance transport from the root to the stele, assumed to be a symplastic transport across the root cortex, and long distance transport to the shoots, mainly in the ionic form in xylem and phloem. Uptake into seeds is not well understood, even though it is of major importance for uptake into cereal grains. It is concluded that there is currently only a limited understanding and quantification of key parameters which would allow a comprehensive mechanistic model of Cd uptake by different plant genotypes to be constructed, and also that there is a limited number of empirical observations of key endpoints for an empirical model. Further work on these aspects is essential to facilitate the construction of effective models to control excessive Cd accumulation in the human food chain. q 2004 by Elsevier Inc.

I. INTRODUCTION Cadmium is a nonessential, toxic heavy metal, which accumulates in mammals. It occurs mostly as an impurity of zinc ore and phosphate fertilizers,

MODELS OF CADMIUM ACCUMULATION IN PLANTS

123

and is widely used in electroplating, pigments, plastic stabilizers and nickel – cadmium batteries, eventually ending up in sewage sludge or in municipal incinerators after product disposal. Accumulated cadmium in the offal of ruminants consuming contaminated herbage represents a significant source of intake for some consumers (MAFF, 1997). In many industrialized countries the cadmium content of sewage sludge has decreased in recent years (Smith, 1994), but even applying sewage sludge with low cadmium concentrations increases the adsorption of organic ligands to the soil and thereby increases heavy metal retention (Petruzzelli et al., 1992). Leaching of cadmium is slow in most soils, amounting to only approximately 0.1% of the total soil content per year (Holm et al., 1998). Phosphate fertilizers also add major quantities of cadmium to grassland, although some countries limit fertilizer cadmium concentrations. Cadmium can alter the uptake of minerals by plants through its effects on the availability of minerals from the soil, or through a reduction in the population of soil microbes (Moreno et al., 1999) and fungi (Plaza et al., 1998). However, many experiments demonstrating effects of cadmium on plant function employed provocative doses that exceed those found in polluted areas (e.g., Vassilev et al., 1998). Most experiments seeking to relate soil parameters to cadmium concentration in plants have been incapable of distinguishing the contributions of the soil and plant systems to cadmium accumulation in plant organs (Hamon et al., 1999). Following this, there is considerable disagreement regarding maximum permissible cadmium concentrations in soils (Piotrowska and Dudka, 1994) and the maximum loading rate for sewage sludge applied to agricultural land (Smith, 1994). For modeling purposes, the plant can be considered as an open system that exchanges mass, energy and information with the environment. Cadmium accumulation in the plant system can be simplified to the exchanges presented in Fig. 1.

Figure 1 Cadmium accumulation in the plant can be simplified to exchanges between the rhizosphere, plant tissues and the phylloplane

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L. TUDOREANU AND C. J. C. PHILLIPS

II.

EMPIRICAL MODELS

Empirical models are essentially descriptions of observational data. In plant science the main approach for empirical models is by fitting an equation or a set of equations to data. Empirical models of root uptake seek to relate bulk soil parameters to plant parameters by ignoring any contribution from other sources. It is theoretically possible to use either empirical or mechanistic models to relate suitable independent variables, in particular the total concentration of cadmium in soil, or extractable cadmium, to dependent variables such as cadmium concentration in plant tissues, but the success of either method is dependent on the quality and quantity of data available.

A. ROOT UPTAKE

OF

CADMIUM

Relevant empirical models use linear or nonlinear equations to relate total concentration of cadmium in soil, extractable cadmium and rate of deposition of cadmium/ha to cadmium concentration in plant organs (Table I). The plant response to the soil loading with cadmium has been described by the Mitscherlich function (Campbell and Keay, 1970; Bramley and Barrow, 1994), having the form: y ¼ a 2 b expð2cxÞ

ð1Þ

where y is the uptake or concentration of the pollutant in the plant; x the amount of pollutant supplied; a the maximum uptake or concentration; b the difference between a and the value of y when no pollutant is supplied; c a scaling term. Logan et al. (1997) were unable to fit first-order linear models to their data but they suggested that Cadmium concentrations in the ear, leaf and plant tissues were related to soil cadmium concentration by the Mitscherlich type equation: y ¼ B0 ð1 2 expðB1 xÞÞ þ B2

ð2Þ

where y is the plant tissue cadmium concentration (mg/kg DM); x the total soil cadmium concentration (mg/kg DM); B0 the asymptote (plateau) plant tissue cadmium concentration (mg/kg DM) above background; B1 the slope of the curve in the region between the asymptote and the intercept; B2 ¼ y the intercept/ background plant tissue cadmium concentration (mg/kg DM). The combined equation for all tissues was: y ¼ 5:3ð1 2 expð20:87xÞÞ þ 0:15

r 2 ¼ 0:82

ð3Þ

We recently reported the results of a meta-analysis based on a literature search performed using the databases BIDS, AGRICOLA and SilverPlatter. This identified papers published during the last 20 years containing information on

Reference

Plant type

Bell et al. (1997)

Leichardt soybean seed

Smith (1994)

Ryegrass (Lollium perenne cv Melle)

Soil type and position Seven soils with pHwater from 5.4 to 7.1 Org C: from 0.6 to 1.3% CEC(cmol/kg) from 2.2 to 16.4 Field experiment Harrogate (HA) site Swinton (SW)

Equation

Variables

N (no. of points)

R2

y ¼ 1:22x þ 0:1

y ¼ seed Cd (mg/kg) x ¼ 0.1 M CaCl2 extractable Cd

11

R2 ¼ 0:94

y ¼ 3:85ð^0:30Þ 2 0:42 ð^0:07Þx (for HA) y ¼ 0:81ð^0:09Þ 20:08ð^0:02Þx (for site SW) Log y ¼ 0:596ð^0:161Þ þ0:908ð^0:146Þlog x

y ¼ cadmium concentration in plant tissue (mg/kg) x ¼ soil pH

24 (HA) and 35 (SW)

R2 ¼ 0:59 (HA) and

y ¼ tissue concentration (?g/g dry weight) x ¼ total cadmium concentration in soil (?g/g soil dry weight) tc ¼ tissue concentration (?g/g dry weight) sc ¼ total cadmium concentration in soil (?g/g soil dry weight) –

Not reported

Not reported

Not reported

Not reported

34

R2 ¼ 0:089 R ¼ 0:91

Kuboi (1986)

Gramineea

Pot exp. Ichinomiya sand soil

Kuboi (1986)

Leguminosaeb

Pot exp. Ichinomiya sand soil

Log (tc) ¼ 0.059 (^0.304) þ0.986 (^ 0.082) log (sc)

Wells et al. (1993)

Maize

Samples from field cultures

Not reported

Erikson (1989)

Ryegrass

Clay Pot experiment Cd Cl2 added

y ¼ 0:007 þ 0:929x

y ¼ cadmium concentration in plants (mg/kg dwc) x ¼ Cd extractactable in NH4AcO, pH4.8(mg/kg soil)

R2 ¼ 0:29 (SW)

40

(continued)


Table I Linear Regressions for Soil and Plant Variables for Different Soil Types and Plants

125

126

Table I Continued Reference

Plant type

Soil type and position

Equation

Ryegrass


y ¼ 0:55 þ 1:45x

Erikson (1989)

Ryegrass


y ¼ 0:248 þ 1:23x

Erikson (1989)

Ryegrass

Sand Pot experiment Ca Cl2 added

y ¼ 0:015 þ 5:32x

Erikson (1989)

Ryegrass


y ¼ 20:013 þ 8:53x

Erikson (1989)

Ryegrass


y ¼ 0:323 þ 7:03x

y ¼ cadmium concentration in plants (mg/kg dwc) x ¼ Cd extractactable in NH4AcO, pH7(mg/kg soil) y ¼ cadmium concentration in plants (mg/kg dwc) x ¼ Cd extractactable in CaCl2 (mg/kg soil) y ¼ cadmium concentration in plants (mg/kg dwc) x ¼ Cd extractactable in NH4AcO, pH 4.8 (mg/kg soil) y ¼ cadmium concentration in plants x ¼ Cd (mg/kg dwc) extractactable in NH4AcO, pH7 (mg/kg soil) y ¼ cadmium concentration in plants (mg/kg dwc) x ¼ Cd extractactable in CaCl2 (mg/kg soil)

N (no. of points)

R2

40

R ¼ 0.96

40

R ¼ 0:93

40

R ¼ 0.91

40

R ¼ 0:97

40

R ¼ 0:97

Standard deviations are presented in brackets when available. a Oryza sativa L. cv Nihombare, Oryza sativa L. cv Hassakumochi, Triticum aestivum cv Norin Nr21, Hordeum distichum L emend Lam., Zea Mays L., Sorghum vulgarepers., Lollium multiflorum Lam. b Glycinemax (L) Merill, Pisumsativum L, Phaseolusvulgaris L, Trifoliumrepens L. c dw ¼ dry weight of plant tissue.


Erikson (1989)

Variables


127

cadmium uptake by maize and ryegrass plants (Tudoreanu and Phillips, 2002, 2004). Cadmium concentrations in both maize and ryegrass were negatively related to the product of cadmium in soil and pH, with similar coefficients for the two species. A positive coefficient between soil pH and cadmium in ryegrass may derive from ionic competition, for example, sodium has been demonstrated to increase plant cadmium (Chiy and Phillips, 1999a,b). We produced the following linear model for maize: Cdshoots ¼ 4:8ð^41:71ÞðP ¼ 0:91Þ þ 10:6ð^2:32ÞCdSoil ðP , 0:0001Þ þ 0:83ð^6:53ÞpHðP ¼ 0:90Þ 2 2 1:8ð^0:40ÞpHp CdSoil ðP , 0:0001Þðradj ¼ 0:35Þ

ð4Þ

where Cdshoots ¼ mean Cd concentration in plants (mg/g dry weight); pH is the nutrient solution pH; CdSoil the mean Cd concentration in soil (mg/g dry weight); pHpCdSoil the interaction term between soil pH and soil Cd concentration. The following model was produced for rye grass: Cdplant ¼ 281:6ð^20:36ÞðP , 0:0001Þ þ 13:3ð^3:42ÞpHðP ¼ 0:0001Þ þ 12:3ð^0:84ÞCdSoil ðP , 0:0001Þ 2 2 1:8ð^0:13ÞpHp CdSoil ðP , 0:0001Þðradj ¼ 0:62Þ

ð5Þ

Where Cdryegrass is the mean Cd concentration in ryegrass plants (mg/g dry weight); pH the soil pH; CdSoil the mean Cd concentration in soil (mg/g dry weight); pHpCdSoil the interaction between pH and Cdsoil. A further model (Tudoreanu and Phillips, 2002, 2004) of data generated in one experiment with soya beans (Glycine max) (Haghiri, 1974) demonstrated that other factors, such as soil temperature, have a major influence on uptake. It was concluded that the best indicator of cadmium concentration in maize and rye grass plants is the product of cadmium concentration in soil and soil pH. A positive coefficient for soil pH for accumulation in ryegrass may relate to different concentrations of competing ions that have an influence on soil pH, for example sodium (Chiy and Phillips, 1999a,b), which were not reported in the experiments. Also Eriksson (1990, cited by Andersson, 1992) found a weak linear relationship between cadmium in winter wheat grains and soil parameters such as pH, organic matter, clay fraction, total cadmium concentration in soil and total zinc concentration in soil. Chlopecka (1996) reported correlation coefficients for total cadmium concentration in soil and cadmium concentration in young and old maize leaves, maize shoots and grains. The correlation coefficients were 2 0.18 for old leaves, 0.05 for young leaves, 2 0.04 for shoots and 0.10 for grains ( p values were not reported for these coefficients). As the number of points used

128


to derive these coefficients was not reported, it is not possible to estimate if the correlations are significant. However, we may speculate that the high correlation observed between the soil-exchangeable cadmium and cadmium concentration in maize organs indicates that an adequate number of points were used for deriving the correlation. If, e.g., 12 points were used, the 0.10 correlation for maize grains is not significant. Correlation coefficients for the soil-extractable cadmium and cadmium concentration of the maize plant parts were between 0.90 and 0.95, demonstrating a strong linear trend between these two factors ðp , 0:05Þ: The r 2 does not confer enough evidence to conclude that the model is adequate (Mendenhall and Sincich, 1995), therefore it is recommended that more detailed statistical analyses of linear and multiple regression models should be presented in future.

B. EMPIRICAL RELATIONSHIPS IN FOLIAR UPTAKE OF CADMIUM The organic materials of the phylloplane are amino acids, carbohydrates and minerals. Saprophytic organisms, mainly bacteria and yeast-like fungi, live on the exuded nutrients, creating a complex environment. Leaf surface physical properties play an important role in the retention of the fluids or solid particles. There are three types of possible forms of deposition onto the plant leaves and stem: rain, aerosols and sewage sludge. For each, the rates of deposition, leaf surface physical properties and physiological activity as well as the physical and chemical properties of the deposits influence the transport of cadmium across the leaf surface. The physical properties of the aerosol and environmental factors such as air temperature, relative humidity, irradiance and wind speed are of major significance. A variety of experimental techniques and methods have been used to identify and quantify the atmospheric contribution to the total concentration of cadmium in plants: –

–

–

Isotope dilution analysis (e.g., Homand et al., 1983). Experimental soil is labeled with 109Cd to a measured specific activity (109Cd/total Cd) and then to make an indirect evaluation of the atmospheric contribution to the total cadmium concentration in plant organs. Rainfall simulation (e.g., Watmough et al., 1999). Stable isotopes of cadmium are applied to foliage by simulating rainfall under different pH regimes. Filtered air cabinets are used to generate a cadmium-free atmosphere. The difference between cadmium concentrations in plants grown in the filtered air cabinets and under field conditions is assumed to represent the contribution of aerosols and rain to the total concentration of cadmium in plants.


129

Adhesion of sewage sludge to leaves is a major contributor to cadmium accumulation by plants. Studies of short-term leaf surface adhesion of heavy metals following application of sewage sludge to grassland have been conducted to relate grass length (cm) and sewage sludge application rates (m3/ha) to concentrations of cadmium in and on the grass (Aitken, 1997). Cadmium speciation in the sludge plays an important role in these circumstances, as well as the physical and chemical properties of the leaf blades. Often rainfall on herbage reduces the metal concentration, but this effect is not consistent (Aitken, 1997). The leaf architecture and the intensity and droplet size of rainfall events are suspected to play an important role in washing the sewage sludge from the leaf. Plant growth is also an important factor, due to its dilution of metal contamination.

III. MECHANISTIC MODELS A. ROOT UPTAKE MODELS Thornley and Johnson (1990) believe that mechanistic modeling “follows the traditional reductionist method that has been so very successful in the physical sciences, molecular biology, and biochemistry.” Many mechanistic models have been proposed for the different plant physiological process. Over the last 20 years models have been proposed for solute transport across plant tissues and veins, water transport in the soil – plant system and nutrient uptake (Baldwin et al., 1973; Cushman, 1980; Barber and Cushman, 1981; Anghinoni et al., 1981; Itoh and Barber, 1983; Barber and Chen, 1990; Silva et al., 1991), but there are few mechanistic models for cadmium accumulation in plants. A simple model for cadmium uptake was developed by Palm (1994), who described cadmium uptake by plant roots as cadmium concentration in soil water multiplied by the root water uptake. Following this, Singh and Pandeya (1998) used a modified version of Baldwin et al.’s (1973) equation to predict cadmium uptake by Phaseolus vulgaris plants in sludge-treated soils. The classical nutrient uptake model conceived by Caassen and Barber (1974) and developed by Cushman (1980) has been used by Mullins et al. (1986) to evaluate cadmium and zinc uptake in maize. Finally, a mechanistic, dynamic model using differential equations has been proposed by Struck and Obstapczuk (1990) for calculating metal atmospheric depositions onto surfaces covered with plants. In 1973 Baldwin et al. developed a model to calculate the uptake of a solute by a multiple root system. First, they considered uptake associated with soil supply of nutrients by diffusion alone, with a constant density of regularly distributed

130


roots. The flux of solute ions F (mol/cm2 sec) was related to the root absorbing power a (cm/sec) and to the solution concentration at the root surface, Cla (mol/cm3 of solution). ð6Þ

F ¼ aCla

at a distance r from the root equal to the root radius a ðr ¼ aÞ: This relationship was restrictive, as it did not include any physiological influence on the root absorbing power and on the water flux at the root surface. The problem was to find the concentration of the solute in the soil solution at r ¼ a; as a function of time. They solved this by assuming that the rate of uptake equals the rate of loss (from the soil solution). The form of the equation was: 0 1 B B C l ¼ expB B C l1 @

C C !C C 2 1 aa x ðaa=DbÞ x A þ ln b 12 2 2 2 Db a x 2a 22paaLt

ð7Þ

where C l is the average concentration of solute in solution (mol/ml); Cl1 the initial concentration of solute in solution (mol/ml of solution); a the root radius (cm); a the root absorbing power (cm/s); x the distance from the root (cm); D diffusion coefficient of the solute (cm2/s); b the buffering capacity of soil; L the root density (cm/cm3); t the time (s). Subsequently, Baldwin et al. (1973) designed the following equation for ion supply by diffusion and mass flow at a constant density of regular roots, using the same parameters [v is the water influx (g/m2 s)]: 22ðav=DbÞ ! x 0 1 21 a C l a a B 2 C þ 12 ¼ ð8Þ @ 2 ! av A C la v v x 22 21 Db a The method presented by Baldwin et al. (1973) used the relation between the concentration at root surface, Cla ; and the mean soil solution concentration, C l ; to estimate the solute uptake as a time function in a root system of constant density and a random development. This was the first attempt to model solute uptake from a specified soil, linking plant properties (root demand coefficient, water influx, root geometry and growth) and soil properties (mean soil solution concentration and soil buffer power). Later, other models were developed using similar assumptions (Caassen and Barber, 1974; Barber and Cushman, 1981; Caassen et al., 1986). The Barber and Cushman (1981) model assumes that ions are transported to roots by mass flow and diffusion and are absorbed at rates that depend on their concentration


131

at the root surface, following Michaelis-Menten kinetics. In ¼ Imax ðCl 2 Cmin Þ=ðKm þ Cl 2 Cmin Þ

ð9Þ

where In is the net ion influx (mg/m2 s); Imax the maximum influx (mg/m2 s); Cl the concentration of the ion in the soil solution (mg/l); Cmin the solution concentration below which In ceases (mg/l); Km the concentration where the net influx is 0:5 £ Imax (mg/l). Mullins et al. (1986) tried to evaluate total cadmium uptake using the Barber– Cushman model, assuming Km ¼ 0.3 mmol/l for cadmium maize seedlings. This value was not experimentally derived, but was chosen largely because it was biologically plausible. However, the model overestimated total cadmium uptake, the predicted cadmium uptake being 1.4 times greater than the observed value during maize growth under optimal conditions in a growth chamber. A sensitivity analysis revealed that the influx kinetics parameter, Km , had a small influence on the total uptake (for an increase from 0.25 to 2.0 mmol/ l, uptake was mostly influenced by Cl). The sensitivities of the parameters in the model were in the following order: concentration of cadmium in soil solution . root growth . average root radius . water influx rate . soil buffering power . diffusion coefficient . maximum influx . half distance between the roots . Km. In 1998, Singh and Pandeya used a modified version of Baldwin et al.’s equation to predict cadmium uptake by P. vulgaris grown in a sewage sludge amended soil: 8 > >
> : b 1þ ln h D1 Ff 1:65r0

19 > = C> C C A> > ;

ð10Þ

where U is the uptake per unit volume of soil in time t (mol/cm3 soil); Ci the initial concentration (mol/cm3) of cadmium in soil solution; b the soil buffering power [the change in concentration of total labile forms (absorbed þ dissolved) (mol/cm3 soil) per unit change in concentration of the dissolved form (cm3 water soil solution)]; a the root absorbing power (uptake flux density, mol/cm2 root per concentration mol/cm3 soil solution); A1 the fractional area of soil solution (cm2 water/cm2 soil); r0 the root radius (cm); rh the half distance between roots (cm); Lv the root density (cm root/cm3 soil); t the time (s); D1 the cadmium diffusion coefficient in solution; F the volumetric water content (cm3 water/cm3 soil); f the conductivity factor (cm2 soil/cm2 water). The greatest disadvantage of the models presented is that they need expensive specific soil measurements. Moreover, experimental measurement of root parameters is difficult. In general, the purpose of uptake models is to estimate the quantity of cadmium taken up by plants from a given volume

132


of soil. This approach is particularly useful for predicting the mean cadmium quantity extracted by crop plants from the soil or the mean total quantity of cadmium accumulated by crops per hectare.

B. DYNAMIC FOLIAR UPTAKE MODELS Struck and Obstapczuk (1990) proposed a dynamic mechanistic model (Eq. 11) for foliar transport and accumulation of some metals using differential equations and approximating it to the total atmospheric deposition rate. They did not take into account either the translocation of heavy metals into the plant or the resuspension of the pollutants into the atmosphere and, therefore, their model is useful only as a guide to the maximum foliar accumulation. dqg =dt ¼ Ig 2 qg kgs

ð11Þ

where Ig is the trace metal deposition rate onto the plant surface (g/cm2 year); qg the trace metal content on the plant surface deposited from the atmosphere onto the plant surface (g/cm2); kgs the rate constant for grass surface to soil surface transfer (year21). For grass species, Struck and Obstapczuk (1990) proposed the following equation: kgs ¼

365 ln 2 tw

ð12Þ

where tw is the foliar weathering half time measured in days. The total deposition rate onto the plants Ig (g/m2) and onto the soil surface Is (g/m2) are directly proportional to the atmospheric total deposition rate w (g/m2), the area a exposed to atmospheric deposition (m2), and the fraction of the total deposition rate onto the grass fg ; or onto the soil fs : Ig ¼ wafg

ð13Þ

Is ¼ wafs

ð14Þ

fg þ fs ¼ 1

ð15Þ

Nielsen (1981) proposed that the interception factor fg for Italian ryegrass (Lolium multiflorum) is dependent on herbage density W (kg/m2) and on a retention coefficient v (m2/kg). fg ¼ 1 2 expð2vWÞ

ð16Þ ð17Þ

W ¼ aasg y=1000a 2

Where a is the grass density (g DW/m ); asg the soil surface area occupied by grass (m2); y the grass height (m); a the area of land under observation (m2).


133

The dry mass of the grass is a function of time depending on the height of the grass ðyÞ; which can be estimated using a growth function model, of which there are several available. The major limitations of this model are: (a) the translocation of heavy metals into the plant is not considered and the interception factor fg is considered independent of the leaf surface patterns and environmental factors affecting leaf adhesion of pollutants; (b) the interception factor does not take into account variation in leaf area during plant growth; (c) the deposition rates onto plants are considered constant, which is not true for most regions with atmospheric pollution; This model therefore has serious limitations if applied to total cadmium foliar uptake by plants.

IV. CADMIUM UPTAKE AND ACCUMULATION—A MODELING PERSPECTIVE ON THE MAIN PROCESSES AND PHENOMENA RELATED TO UPTAKE AND ACCUMULATION OF CADMIUM IN PLANTS A. CADMIUM INFLUX

TO THE

ROOT

New techniques and equipment for measuring ions fluxes along plant roots have been developed during the past decade. Among the most useful is the vibrating microelectrode, which has a high spatial and temporal resolution, being able to measure small Cd2þ gradients, as well as fluxes at specific locations along the root (Pineros et al., 1998). The Cd2þ flux profile of wheat, Thlaspi caerulescens and T. arvense, along roots has a characteristic spatial pattern (Pineros et al., 1998), with the Cd2þ influx being increased at the proximal region of the root apex. Similar flux profiles have been reported for Ca2þ and Mg2þ, with no significant Ca2þ influx at distances over 3 mm from the maize root apex (Ryan et al., 1990). Moreover, Ca2þ influx into Limnobium stoloniferum root hairs was localized close to the root hair apex (Jones et al., 1995). The magnitude and spatial patterns of Cd2þ flux profiles of T. caerulescens and T. arvense (Pineros et al., 1998) are similar, despite the fact that the two species differ in Cd2þ and Zn2þ tolerance and accumulation in roots and stems (Vasquez et al., 1992; Brown et al., 1995). For wheat, the concentration-dependent influx kinetics of 109Cd is characterized by smooth, nonsaturating curves that could be dissected into linear and

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saturable components (Hart et al., 1998). The saturable component probably characterizes the carrier-mediated cadmium influx across root –cell plasma membranes, and the linear cadmium uptake represents cell wall binding of 109Cd. Costa and Morel (1993) studied cadmium uptake by white lupin (Lupinus albus) from a hydroponic solution at low cadmium concentrations (0.05 nM – 5 mM). Up to 30% of the cadmium was passively absorbed, and was still observed in the presence of a metabolic inhibitor. The remaining 70% involved active absorption mediated by Hþ-ATPase. Cadmium absorption was reduced to 20% in the presence of calcium and zinc, which suggests that these two elements use the same carriers as cadmium across the cell membrane. The mechanisms describing the uptake of essential/nonessential heavy metals are not yet clearly defined. Membrane transporters such as (CPx-Type) ATP-ases, Nramp-the natural resistance-associated macrophage protein) and cation diffusion facilitator family (CDF) (Williams et al., 2000) are believed to play an important role in uptake mechanisms and in protecting cells from toxic effects. The root environment is influenced particularly by the root exudates. Mench et al. (1994a,b) found that for plants such as Nicotiana tabacum, Nicotiana rustica L. and Zea Mays the Cd extraction by root exudates was in order N. tabacum L. . N. rustica L. . Zea mays L., which is similar to Cd bioavailability in field plants. Their conclusion was that Cd solubility in the rhizosphere of apical root zones due to root exudates is likely to be an important cause of the relatively high Cd accumulation in Nicotiana spp. These findings add strength to the belief that Michaelis– Menten coefficients for plant cadmium uptake might be similar for plants belonging to the same specie, and that the differences between cultivars are mainly due to differences in accumulation at cellular level and long distance transport processes. A remaining task is still the identification and quantification of the main phenomena influencing cadmium solubility at root rhizosphere level. Discriminating between the uptake of ionic and complexed cadmium, as well as quantifying their relevant contributions to the total cadmium uptake, would be an important step forward in modeling the uptake of cadmium by plants.

B. FOLIAR UPTAKE Information about cadmium uptake by leaves is scarce, even though permeation of ions and low molecular-weight solutes throughout the leaf cuticle is well known (Marschner, 1995). Solutes with radii of , 44 nm (urea) but not larger than the molecules in synthetic chelates (e.g., FeEDTA) permeate through the hydrophilic pores within the cuticle (Marschner, 1995). Air particulates may contain Cd2þ while rain may contain cadmium species such as Cd2þ; CdCl2, Cd (OH)þ and organically bound cadmium. The hydrophilic pores have a diameter of less then 1 nm and are lined with fixed negative charges. The number of pores


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is increased around the guard cells and in trichomes. These pores are characterized by specific permeability (Levy and Horesh, 1984). Therefore, cadmium may be adsorbed to the negative charges of the hydrophilic pores and may also pass through these pores into the leaf apoplast. Rain pH appears to play an important role in cadmium foliar uptake. Greger et al. (1993) reported that a low pH in rain decreased the net uptake of cadmium in pea and sugar beet foliage, probably by an exchange reaction in the cutin and pectin of the cuticular membranes (Hþ – Cd2þ competition for the binding sites). Rain pH also influences leaf wetability (Percy and Baker, 1988) and thus influences the leaf rain retention time and uptake of some inorganic ions. At a cellular level the gradient of charge on matter is the driving force for solutes to enter the cell. In plants most of the membrane-bound transport proteins are energized indirectly through the action of plasma membrane Hþ-ATPases. The presence of a high density of Hþ-ATP-ases at trichome level may suggest that a Michaelis–Menten equation may describe cadmium uptake through leaves as well. The leaf cells take up many minerals from the apoplasm in a similar manner to the root cells, The foliar uptake process is affected by mineral concentrations in the solution applied to leaves, mineral valencies, temperature, pH and internal metabolic activity (Chamel et al., 1984). Minerals and cadmium are retranslocated at a limited rate to other plant parts due to the influence of the leaf cuticle thickness and run-off from (hydrophobic) leaf surfaces (Marschner, 1995; Watmough et al., 1999). It can be assumed that the foliar adsorption and active uptake of cadmium is likely to follow the same pattern as for the root cells. If this hypothesis is confirmed by experiments then the same modeling approach for cadmium uptake at root and foliar level might be used. The contribution of wet and dry deposition to cadmium concentration in leaves is still unclear. The extent to which sewage sludge, surface moisture and particles adhere to leaves is related to the surface chemistry of the cuticle and to surface roughness (wetability). Moreover pollutant depositions onto the leaves are affected by leaf surface wetness (Brewer and Smith, 1997). Although these facts have been reported by several authors, no attempts have been made to link cadmium accumulation in leaves to their physical properties. The influence of rain cadmium concentration and dry depositions on leaf cadmium concentration after sewage sludge application is still unclear. Soil type is a key influence in the quantity of soil splashed and the particle size distributions of the splash (Mermut et al., 1997). Organic matter and iron oxides are critically important factors in determining soil surface stability and erosion rate (Singer and Le Bissonnais, 1998). Mermut et al. (1997) found that the amount of soil splashed was about four times higher for Haploboroll type soils with high smectite than for Fragiudalf type soils, that are rich in Feoxyhydroxides. Increasing rain intensity was followed by an increase in the amount of the splashed material and sediment load for both soils, but soil splash decreased after soil surface wetting. The rate of soil splash had a steep decrease

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with increasing rainfall intensity. Despite these findings, soil splash contribution to cadmium accumulation in plants has been largely ignored by authors investigating cadmium accumulation in field grown plants (none of the 4280 papers in our endogenous database on cadmium accumulation in plants mentioned soil splash as a factor). Therefore, modeling soil splash contribution to cadmium accumulation in plants presents a new challenge.

C. ACCUMULATION MECHANISMS

IN

PLANT TISSUES

The role of class III metallothioneins in cadmium sequestration has been extensively researched. The class III metallothioneins or pytochelatines (PCs) are cadmium-binding peptides with a general structure of (EC)nG ðn ¼ 2; 3Þ for fission yeast (Kondo et al., 1984) and (EC)nG ðn ¼ 2 – 11Þ in higher plants (Grill et al., 1985). These small peptides, containing from 5 to 23 amino acids, are synthesized from glutathione (GSH) by a heavy metal-activated glutamyl-Cys dipeptidyl transpeptidase or PC synthase, EC 2.3.2.15 (Grill et al., 1989; Zenk, 1996). However, Salt and Wagner (1993) have demonstrated the presence of a Cd2þ/ þ H antiport transport of cadmium from the cytoplasm into the vacuolar sap. The process was Dp-dependent and exhibited saturation kinetics at Km , 5.5 mM. They concluded that this type of transport is a candidate for Cd2þ transport from the cytoplasm into the vacuolar sap under low as well as high Cd2þ exposure. A survey by Gekeler et al. (1989) over about 200 plant species ranging from algae to orchids found that heavy metals are sequestered by the specific metalcomplexing peptides, PCs or iso-PCs. Plants detoxify intracellular heavy metal ions by complexing them with PCs through thiolate coordination. For example, Grill et al. (1989) found that Cd ions activate the process in which PC synthase mediates the synthesis of PCs from GSH in Silene cucubalus. PC synthase genes have also been isolated in Arabidopsis (Vatamaniuk et al., 1999) and wheat (Clemens et al., 1999). Moreover homologous genes have been found in fission yeast and Caenorhabditis elegans (Inouhe et al., 2000), suggesting that PC synthase may be widespread and have more general functions in organisms, in addition to Cd-tolerance in plant cells (Howden et al., 1995a,b). Moreover Rauser (1995) suggested that the presence of the Cd-binding peptides contributes to the Cd tolerance of higher plants and fission yeast. Suspension cells from tomato root are reported to have a substantial tolerance to Cd (Inouhe et al., 1991). Inouhe et al. (2000) reported that isolated tomato root cells exhibit tolerance up to 100 mM Cd. They also identified that Vigna angularis suspension-cultured cells are deficient in PC synthase activity and thus very sensitive to Cd, concluding that the plant is Cd hypersensitive. On the other hand Klapheck et al. (1994) identified that in some plants, PCs ([-Glu-Cys]n-Gly) are replaced by Glu-Cys oligomers carrying a terminal Ser (iso-PC[Ser]).


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Moreover Meuwly et al. (1995) found (Glu (iso-PC[Glu]) oligomers and Kubota et al. (2000) found Gln (iso-PC[Gln]), collectively termed iso-PCs. Klapheck (1988) found that in Fabales, especially in Phaseoleae, GSH is replaced in several species by homoglutathione (hGSH), a homolog of GSH with the terminal amino acid Gly replaced by -Ala. After exposure to heavy metals, these plants produced homo-phytochelatins (hPCs; iso-PC[-Ala]) instead of PCs (Grill et al., 1986). Gekeler et al. (1989) showed that Cd2þ exposed plants (Phaseoleas) synthesize both sets of metal-complexing peptides, PCs and hPCs, simultaneously, which has been confirmed by Klapheck et al. (1995). Therefore, activated by heavy metal ions, hGSH will determine the formation of hPCs. The presence of hGSH have been confirmed in V. angularis (root extracts not treated with Cd2þ) (Oven et al., 2001), demonstrating that this legume (FabalesPhaseoleae) is using hPC for sequestering Cd. Therefore, it can be concluded that Cd-tolerance/resistance in plants may involve both the PC-dependent and hPCdependent processes. The PC-dependent tolerance/resistance process involves activation of PC synthase (Chen and Goldsbrough, 1994), GSH biosynthesis (Chen and Goldsbrough, 1994), sulphur assimilation (Nussbaum et al., 1988) and the accumulation of acid-labile sulphides (Reese et al., 1992). Thus there is a strong influence of sulfur on Cd accumulation in plants. Blinda et al. (1997) revealed that for barley plants (Hordeum vulgare, cv. Gerbel) cadmium is accumulated in the leaf apoplast for plants treated with cadmium and zinc at toxic concentrations (root growth was inhibited by 30%). The plants grown in nutrient solution containing 100 mmol/m3 of cadmium increased their leaf apoplast protein content to 1.55 mg/mm3 of the intracellular washing fluid (a diluted apoplast solution) compared to the controls. For provocative doses of cadmium it was found that the blades of 10 days old primary leaves of barley plants contains readily extractable apoplast protein, ionically bound proteins to the cell walls and covalent bound protein (Table II). Metallothioneins have been found in the soybean embryo, root and shoot apices for control and heavy metal treated plants (Chongpraditnun et al., 1991). They were localized in the same plant parts for control and treated plants, although treated plants had a higher metallothion in concentrations overall, suggesting that heavy metals do not play a major role in their localization. Cadmium-binding complexes have been found in the cytoplasmic fraction of maize roots and shoots for cadmium-treated plants (Inouhe et al., 1994). In the roots of maize, three families of peptides have been found that form the Cd-binding complexes: (gamma-glutamic acid-cysteine)ðnÞ-glycine [(gamma-Glu-Cys)ðnÞGly], and the phytochelatins, (gamma-Glu-Cys)ðnÞ, and (gamma-Glu-Cys)ðnÞ-Glu (Rauser, 1995). Chongpraditnun et al. (1991) suggests that phytochelatin production occurs virtually simultaneously throughout the plant.

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L. TUDOREANU AND C. J. C. PHILLIPS Table II Content of Apoplast Proteins in Leaves of 10 Days Old Barley Plants Protein content in mg/b fresh weight

Growth conditions Controls % 100 mmol/m3 Cd %

Apoplast protein 0.06 ^ 0.01a (0.4%) 0.27 ^ 0.08 (1.3)

Ionically bound proteins

Covalently bound proteins

Intracellular proteins

0.50 ^ 0.12 (3.5) 0.66 ^ 0.19 (3.4)

2.80 ^ 0.23 (19.8) 3.92 ^ 0.64 (19.9)

10.79 ^ 2,65 (76.3) 14.85 ^ 2.84 (72.5)

Data from Blinda et al. (1997). a Values ^ SD.

Cadmium concentrations in tissues, cadmium-binding complex characteristics and composition (high or low molecular weight) may vary considerably among organisms depending on the concentration of cadmium used, exposure time, and nutrients (Jackson and Alloway, 1991; Kneer and Zenk, 1992). The regulation of ionic Cd2 þ concentrations in the cytosol may involve at least two processes: (a) Cd2þ binding to phytochelatins (Grill et al., 1985) (b) Cellular compartmentation, particularly in the vacuole in which Cd is sequestered by PCs (Rauser, 1995; Vo¨geli-Lange and Wagner, 1990). Cadmium is also transported across the tonoplast into the vacuole of oat root cells, both as the free ion (Salt and Wagner, 1993) and in a complex with phytochelatins (Salt and Rauser, 1995). These findings support the incorporation of cadmium accumulation in plants by means of the PCs into a generic dynamic model (Tudoreanu and Phillips, 2002) for cadmium uptake and accumulation. Soil temperature exerts a major influence over cadmium accumulation in plants (Hooda and Alloway, 1993), not only in controlled experiments, but particularly in the field where there is considerable variation in the growing season and between different climatic regions. The main influence is on cadmium influx rate into plant roots (Cataldo et al., 1983; Barber, 1995). However, meteorological parameters are usually not included as factors in experiments for cadmium accumulation in fodder plants and therefore its inclusion in meta-analysis of literature data by regression models has not been possible. Nevertheless in the data of Haghiri (1974), temperature was the most significant factor of all those tested (Tudoreanu and Phillips, 2002, 2004). Plant genotype has a major role in cadmium partitioning between roots and shoots of maize plants (Florijn et al., 1993a,b). Florijn and Vanbeusichem


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(1993b) identified that maize plants could be classified as shoot cadmium excluders (mean 7.4 ^ 5.3 mg Cd/g shoot dry weight and 206.0 ^ 71.2 mg Cd/g root dry weight in roots) or nonexcluders (mean 54.2 ^ 3.4 mg/g shoot dry weight and: 75.6 þ /2 11.2 mg21 root dry weight). Similar differences between cultivars have been identified in Agrostis capillaris (Symeondis et al., 1985), P. vulgaris and Clycine max (Guo and Marschner, 1995; Guo et al., 1995; Guo and Marschner, 1996; Marchiol et al., 1996). Thus the internal distribution of cadmium, rather than its uptake, is significantly different in genotypes. The definition of the upper critical concentration in plant tissues is still controversial (Beckett and Davis, 1977; Davis and Beckett, 1978; Burton et al., 1986), with little agreement due to different assessment methods (Beckett and Davis, 1977; Davis and Beckett, 1978; Burton et al., 1986).

D. ROOT PARAMETERS AFFECTING CADMIUM ACCUMULATION BY PLANTS Root growth equations are used in different mechanistic models for the calculation of root surface area over which there is cadmium influx into the plant tissues. An accurate assessment of the superficial root area is essential for the calculation of the total cadmium uptake using the Michaelis– Menten approach. An equation for simple root growth was developed by Borg and Grimes (1986), presented by Rao (1994), using 150 field observations over the entire growth period of 48 crop species. The form of the equation is a sinusoidal function (Eq. 18) and it can accommodate conditions of slight to moderate root growth inhibition. DAP 2 1:47 ð18Þ RDðtÞ ¼ RDmax 0:5 þ 0:5 sin 3:303 DTM where RD(t) is the root length on the t-th day (m); RDmax the maximum root length (m); DAP the number of days after planting; DTM the number of days to maturity. The sinusoidal form of the root growth equation assumes an influence of soil temperature and moisture variations on root growth, but there is a need to verify this by appropriate field measurements and comparison with the classical exponential approximation of root growth proposed by Caassen and Barber (1974); Teo et al. (1995). No comparison of these primary growth equation models could be found for field situations with cadmium-polluted soil. The form of the root growth equation has not been widely questioned, and in situations where root growth is influenced by heavy metals the exponential growth function is usually adopted. However, for field-grown plants, soil compaction can differentially affect root distribution at varying soil depths, influencing water and mineral uptake as well as root and shoot growth

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(Tardieu, 1990). Plants usually invest between 20 and 50% of their total weight in roots and under water stress roots can reach up to 90% of total plant mass (Salisbury and Ross, 1992). The roots of hydroponically grown plants represent only 3 –5% of the total plant biomass (Bugbee and Salisbury, 1998 cited by Salisbury and Ross, 1992), as they develop under no physical constraints or stress. Florijn et al. (1993a) found that for hydroponically grown maize plants the root radius and length was not affected by cadmium contamination. However in field conditions, root mass is highly variable and dependent on symbiotic relationships with, for example, the hyphae of vesicular arbuscular mycorrhizae (AM) (Cooperband et al., 1994; Miller et al., 1995) and nitrogen-fixing bacteria (Olesniewicz and Thomas, 1999). The sensitivity analysis (Mullins and Diggle 1995) of the Barber and Cushman (1981) model, which was based on Michaelis-Menten kinetics for metal influx, confirmed that root radius is one of the most important variables influencing cadmium uptake by plants. If it assumed for modeling purposes that roots are smooth cylinders (of constant radius) with a density of 1 g/cm3, the total superficial area of roots is usually underestimated, compared with that for field grown plants. The root rhizosphere represents a complex interface, which has its own particular physical and chemical characteristics. Krishnamurti et al. (1996) reported that the rhizosphere pH values of 2-week wheat plants was smaller than the pH values of the corresponding bulk soil, and as a result more cadmium was complexed with low molecular-weight organic acids. Mullins and Sommers (1986) reported a decrease in rhizosphere pH for maize seedlings grown in a nutrient solution over the first 10 days after transplanting. This influenced the influx rate of cadmium, even though the experiment used a mixed resin system to maintain constant concentrations of nutrients and cadmium in the flowing solution.

E. ION COMPETITION Ion competition will occur inside the plant tissues as well as outside the root. Cadmium can alter the uptake of minerals by plants through its effects on the availability of the minerals from the soil, or through a reduction in the population of soil microbes (Moreno et al., 1999) and fungi (Plaza et al., 1998). However, many experiments demonstrating effects of cadmium on plant function employed provocative doses that exceed those found in polluted areas (e.g., Vassilev et al., 1998). Essential micronutrients such as Cu2þ, Zn2þ, Mn2þ, Fe2þ, Ni2þ and Co2þ and nonessential metals such as Cd2þ, Hg2þ and Pb2þ may become toxic when present in excess. Ion competition may occur in the transport of a range of essential and potentially toxic metals (such as Cu2þ, Cd2þ, Zn2þ, Pb2þ) across the cell membrane. Moreover the influence of cadmium on sulfate uptake in maize roots


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was shown to be due to the high rate of cadmium-induced phytochelatin synthesis as a response to the high sulfur demand during PC synthesis. (Nocito et al., 2002) The P-ATPases are involved in most metal transports across the cell membrane (Ca2þ-ATPase, Hþ- ATPase). Williams et al. (2000) consider the CPx-ATPases as candidates for transporting metals across the tonoplast. The CPx-ATPases (Solioz and Vulpe, 1996) are P-type ATPases sharing a common feature of a conserved intramembranous cysteine –proline – cysteine, cysteine – proline – histidine or cysteine – proline – serine motif which was denoted as the CPx-motif. The Cd2þ/Hþ antiport mechanism discovered in the vacuolar fraction of the oat root might be a lower affinity metal transporter analogous to Ca2þ/Hþ antiporter. It is still unclear if the D pH-dependent cadmium transport in the oat roots is a novel Cd2þ/Hþ antiporter or whether cadmium is transported by the Ca2þ/Hþ antiporter. In support of the latter, several experiments demonstrate that cadmium competes with calcium and zinc for uptake (Jarvis et al., 1976; Chiy and Phillips, 1999b). Uptake of sodium, rubidium and calcium as well as cadmium was mediated by LCT1 in yeast, and LCT1 cloned from wheat was suggested to mediate the uptake of cadmium (Clemens et al., 1998). Besides these mechanisms, other mechanisms that might be affected by ion competition have been identified to contribute to cadmium transport into the plant cell. White (1998) suggested that at least two major classes of Ca2þ channels reside in the plasma membrane. The relatively nonselective cation channels with a high single-channel conductance are called maxi-cation channels (White, 1993, 1994). The more cation selective channels or voltage-dependent cation channels (White, 1994; Pineros and Tester, 1995, 1997) exhibit a smaller single-channel conductance. Although both classes of ion channel have been characterized most thoroughly in cereal roots, it is clear that Ca2þpermeable channels exist in a variety of other cell types and tissues, including carrot and parsley suspension cultures (Thuleau et al., 1993; Zimmermann et al., 1997), Arabidopsis mesophyll and root cells (Ping et al., 1992; Thion et al., 1996).

F. THE INFLUENCE OF SYMBIOTIC FUNGI CADMIUM UPTAKE

ON

Hyphae of ectomycorrhizal fungi (AM) may bind cadmium and protect against heavy metal uptake, whilst facilitating the uptake of essential metals like K, P and Mg, thereby providing benefit to the host plant (Kaldorf et al., 1999). Toxic metals are sequestered in vacuoles (Turnau et al., 1993) and prevented from entering the plant This is not, however, a universal finding (Weissenhorn and Levyal, 1995; Weissenhorn et al., 1995a,b), perhaps because of the varied ability of AM to sequester heavy metals with metalothionein-like peptides (Galli et al., 1994). AM cannot protect the plants from significant uptake if there is a high cadmium concentration in soil solution. A better understanding

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of the quantitative relationship between root colonization by mycorrhizae and cadmium concentration in plants is needed for mechanistic models. Guo et al. (1996) attempted to estimate the contribution of mycorrhizal fungus to the uptake of cadmium in maize plants but found that, regardless of mycorrhizal colonization, the concentration of cadmium was higher in the roots than in the shoots. Cadmium in soil solution has toxic effects on mycorrhizal growth, which was completely surpressed at 10 mg Cd/l of soil solution in the study of Weissenhorn et al. (1995a,b). This may be partly responsible for the yield reductions observed in response to cadmium applications (Buysse and Merckx, 1995). Obbard et al. (1994) detected AM associated with a wheat crop in soils containing 20 mg Cd/ kg and other high concentrations of toxic metals, demonstrating that AM can develop tolerance to high concentrations of heavy metals. Microbial biomass and enzyme activity are reduced at concentrations of cadmium in soil as low as 50 mg/kg, especially in a sandy loam (Dar, 1996). However, a review by Smith (1996) suggested that the critical level for adverse effects of cadmium on soil rhizobium bacteria is about 4 mg Cd/kg soil.

G. SHORT DISTANCE CADMIUM TRANSPORT The pathway of cadmium movement within the root to the stele is assumed to be a symplastic transport across the root cortex. Cadmium transport across the stele system is comparable to solute transport across a porous adsorptive media. Hart et al. (1998) proved that interactions with the apoplast must be considered when characterizing metal-ion influx into the symplast. Desorption experiments carried out on 109Cd uptake by Triticum turgidum L. var durum and T. aestivum L. indicated that a small amount of 109Cd was not completely removed from roots (100 mm Cd for 15 min). It was assumed that “the undesorbed fraction probably consisted of Cd bound to reactive sites within the apoplast.” A 15-minute desorption period was sufficient to remove all easily desorbable Cd. Similar kinetics of binding in the root apoplast have been reported for Zn2þ (Lasat et al., 1996), and other divalent ions. Moreover the amount of Cd removed by the desorption experiments was proportional to the Cd concentration in the nutrient solution and the kinetics of Cd desorption from wheat roots were similar to those reported for Zea mays (Rauser, 1987; Florijn et al., 1993b) and roots of A. gigantea (Rauser, 1987). An important finding of Hart et al.’s experiment (1998) was that the differences between the two cultivars in adsorption of cadmium to the apoplast did not influence the net cadmium uptake into the symplast. Hart et al. also found that the apoplasmic cadmium binding process was temperature dependent, confirming that temperature plays an important role in cadmium accumulation, at least at this level. It was also suggested that


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the differences between cultivars in cadmium accumulation at root level may be explained by the differences between the two cultivars in apoplasm-Cd interactions, but the factors responsible for a higher level of cadmium binding in the bread wheat cultivar are not known.

H. LONG DISTANCE CADMIUM TRANSPORT Translocation of Cd to shoots (Florijn et al., 1993a; Salt et al., 1995) is not influenced by Cd2þ binding to phytochelatins, and therefore vacuolar compartmentation of Cd may be a more effective mechanism for inhibiting long-distance transport within the plant. Hart et al. (1998) found that cadmium accumulation in durum wheat grains is not correlated with seedling-root influx rates or root-to-shoot translocation, but may be related to phloem-mediated cadmium transport to the grain. The transport of cadmium in the xylem and phloem is believed to be governed by mass transport, supported by the sap flow (Marschner, 1995). Thus the transport of cadmium via xylem is probably driven by the gradient in water potential. Inconsistent evidence has been found for the rates of cadmium transport in the phloem. When mature wheat plants were injected with solutions of 0.1, 1.0, and 10 mM CdCl2 to measure transport of cadmium in the phloem, only a small quantity of cadmium was removed from phloem by the grains (Herren and Feller, 1997). However, in such research it is important to know if the injected cadmium concentrations are below or above the critical limit for the studied plant variety. Most of the research on transport of cadmium in xylem relates to the influence of cadmium on other substances in the xylem sap, and does not involve the major agricultural crops, such as maize or ryegrass (Aidid and Okamoto, 1992; Trivedi and Erdei, 1992; Senden et al., 1992, 1994, 1995a). For example, quantitative information about the transport of low molecular weight polypeptides sequestering cadmium by xylem sap flow comes from the characterization of cadmium-binding macromolecules in pumpkins (Przemeck and Haase, 1991). Although it is very important for characterizing accumulation throughout the human food chain, there is relatively little information available concerning the movement of Cd into developing seeds. A study by Popelka et al. (1996) on cadmium translocation into developing peanut fruits provided evidence that cadmium accumulation occurred predominantly via the phloem. Hart et al. (1998) suggested that “Cd that has been loaded in immature grains may be less likely to be remobilized out of grains, which would imply that symplastic transport processes are of primary importance in understanding Cd accumulation in wheat grains.” Moreover the small difference between wheat cultivars (T. turgidum L. var durum and T. aestivum L.) in root Cd2þ-uptake kinetics, corroborated with the low rates of root-to-shoot Cd translocation in the durum

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variety, suggest that root Cd2þ uptake and xylem translocation are not responsible for excess Cd accumulation in grains of durum wheat. In one of the few pieces of research involving maize, Florijn et al. (1993b) found that only 0.01– 0.1% of cadmium was transported in a complexed form in the xylem sap of maize plants, concluding that the xylem loading process is an important process, but that cadmium is mostly transported in an ionic form.

V. SUMMARY AND CONCLUSION A. SUMMARY The overwhelming majority of the experiments report only the analyses of variance of different levels of the treatment, and some later experiments report linear regressions between one soil parameter and one plant parameter. Linear multiple regression models (Andersson, 1992) which contain as independent variables only soil bulk parameters are not successful in predicting cadmium concentration in wheat grains. Anderson also commented that: “The coefficient of correlation is relatively low ðr 2 ¼ 0:35Þ but it should be remembered that important variables like amount of precipitation, yield, variety, etc., are omitted.” The applicability of regression equations is restricted to the interval of the independent variable for which the model was created. For example the linear regression, found by Eriksson et al., 1996, for estimating cadmium uptake by ryegrass for extractactable cadmium in NH4AcO at pH 7 is: y ¼ 20:013 þ 8:53x If soil-extractable cadmium is less than 0.03 mg/kg soil, cadmium accumulation in plants is negative. Probably this was due to the minimum soilextractable cadmium concentration in the data being 0.03 mg/kg soil, but a negative value could also be interpreted as an efflux of cadmium from the plant system towards its environment. Physically this process would be similar to desorption of cadmium adsorbed by the root cell walls. Such an interpretation would only be valid if confirmed by experiments, and it is important not to extrapolate beyond the range of the data. Large number of soil factors, atmospheric factors and plant factors are usually influencing cadmium uptake by plants, moreover plant variety plays an important role in cadmium partitioning between roots and shoots for maize plants (Florijn and van Beusichem, 1993b). Apparently conflicting results are obtained in studies concerning the effect of liming on cadmium uptake by plants (Andersson, 1992; Eriksson, 1989). It is usually observed that increasing soil pH by liming


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will decrease cadmium absorption by plants (Smith, 1994), other factors being equal. However, this may be an oversimplification since the phenomena that are taking place at the root – soil interface are complex. In these circumstances the valid conclusion is that, for a particular situation, there is a linear trend between soil pH and cadmium uptake by plants. Element interactions are particularly important in understanding cadmium uptake and transport. There is evidence of competition between calcium and cadmium for root uptake (Jarvis et al., 1976; McLaughlin et al., 1998) and sodium and cadmium compete for trans-membrane carriers. Moreover appear to be available to plants cadmium complexes such as CdCl22n n (Smolder and McLaughlin, 1996) and may contribute to the amount of cadmium available for uptake by plants. Also there is evidence of cadmium influence on sulfate transport in maize related to the changes in the levels of sulfate and nonprotein thiols during Cd-induced phytochelatin (PC) biosynthesis (Notcito et al., 2002). Mechanistic models have been constructed to estimate mineral root uptake, which usually assume that ions are transported to roots by mass flow and diffusion and are absorbed at rates that depend on their concentration at the root surface, following Michaelis-Menten kinetics. The accuracy of such models is not high, partly because accurate estimates of root surface area are essential but difficult to achieve. Other important parameters are the cadmium concentration in the soil solution and root growth. A large number of models are considering nutrients uptake (Silberbush and Barber, 1983, 1984; Silva et al., 1991), solute transport within plants and water uptake and short or long transport in plants (Flowers and Yeo, 1992; Steudle and Henzler, 1995; Steudle and Peterson, 1998). Other than the Michaelis-Menten parameters for cadmium uptake for maize and soyabean plants no other specific parameters for cadmium transport in plants were found. Soil temperature variations of more than 158C occur over the growing season but little attention has been paid to this factor, which has a major impact on cadmium influx into the roots and leaves. Other factors, such as the presence of competing ions, symbiotic fungi (AM), bacteria and temperature play an important role in cadmium uptake but these are mainly unquantified. The sewage sludge deposition onto the leaves is known to contribute to heavy metals accumulation in plants but no attempts have been made to model sewage sludge contribution to cadmium accumulation in plants, relating this contribution to environmental factors and plant leaf physical properties. Soil splash (Amaral et al., 1994) may play an important role in the contamination of crops which have the edible parts within 30– 40 cm above the soil surface. For sand and simulated rain, soil splash has been modeled by Salles and Poesen (2000), with the most relevant physical parameters responsible for sand splash being raindrop diameter and momentum.

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The contribution of wet and dry deposition also plays an important role in heavy metal accumulation in plants, but little attention has been paid to cadmium accumulation throughout the phylloplane.

B. CONCLUSIONS Even though it is not fully exploited, the most common empirical modeling method is the simple linear regression. Because an r 2 statistic does not confer enough evidence to conclude that the model is adequate (Mendenhall and Sincich, 1995), it is recommended that more detailed statistical analyses of linear and multiple regression models should be presented in future. High correlation does not imply causality (Mendenhall and Sincich, 1995; Lewis and Trail, 1999) and “it is incorrect to conclude that a change of the independent variable ðxÞ causes a change of the dependent variable ðyÞ: The only valid conclusion is that linear trend may exist between x and y:” (Mendenhall and Sincich, 1995). Sometimes two variables have a high positive or negative correlation because each of them is related to a third common variable. Many comparisons may be complicated by this kind of error. The stepwise regression (using software such as SAS/STAT or JMP) will be of great help for choosing the significant factors to be included in a multiple regression model. No such statistical approach was found in any report and no paper was found reporting simultaneously a large number of environmental and plant factors suspected to influence cadmium accumulation and uptake. Empirical models, while presenting a less satisfactory biological model compared to mechanistic models, are based on observations, which ensures a degree of accuracy that is not necessarily present in mechanistic models. The presence of cadmium in the food chain is primarily affecting humans, rather than food animals or crops, because of the longevity of humans and the accumulation of cadmium through the food chain. Therefore, it is essential that empirical models for plant accumulation are linked to similar models for animals and humans, such as that for accumulation in sheep derived from a meta-analysis of literature data (Prankel et al., 2004). However, before this can be achieved, further work is required to understand each species’ influence on the model parameters. Survey data of field-grown plants might help to elucidate different aspects of the relationship between soil parameters and cadmium accumulation in plants (Smith, 1994). Mechanistic or phenomenological dynamic models of cadmium accumulation in plants have not been yet reported. Modeling cadmium uptake is difficult due to problems in measuring specific cadmium uptake parameters and plant parameters (such as total root superficial area). Stepwise regression analyses could provide evidence for all the relevant parameters to be included in empirical or mechanistic models, in particular when considering soil splash and sewage sludge contributions to cadmium uptake by plants. Object oriented programming (OOP) languages are an ideal tool for


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modeling complex systems, enabling the development of modular structured models (Tudoreanu and Phillips, 2002). Each module may therefore be independently developed, updated and run.

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VARIABLE CHARGE SOILS: THEIR MINERALOGY, CHEMISTRY AND MANAGEMENT Nikolla P. Qafoku,1 Eric Van Ranst,2 Andrew Noble3 and Geert Baert4 1

Battelle-Pacific Northwest National Laboratory, Richland, Washington USA 2 Ghent University, Gent, Belgium 3 International Water Management Institute (IWMI), Bangkok, Thailand 4 Hogeschool Gent, Gent, Belgium

I. Introduction II. Mineralogy of Variable Charge Soils A. Mineralogy in General B. Highly Weathered Soils C. Volcanic Ash Soils III. The Chemistry of Variable Charge Soils A. Chemical Characteristics in General B. Soil Particles and Their Surface Charge C. Sorption D. Chemical Reactions at Solid: Aqueous Interfaces in VCS IV. The Management of Variable Charge Soils A. Chemical Degradation of Variable Charge Soils B. Management of Variable Charged Soils Acknowledgements References Soils in the Oxisols, Ultisols, Alfisols, Spodosols and Andisols orders that are rich in constituents with surface reactive groups with amphoteric properties are considered variable charge soils (VCS). They have developed under intensive weathering in subtropical and tropical regions or from volcanic ash parent material. The magnitude and sign of the surface charge of variable charge constituents depend on the chemistry of the contacting solution (pH and ionic strength). The mineralogical, physical and chemical

Abbreviations: AFM, atomic force microscopy; BE, background electrolyte; BES, background electrolyte solution; CEC, cation exchange capacity; EXAFS, extended X-ray absorption fine structure; EDL, electrical double layer; GCS theory, Gouy–Chapman–Stern Theory,; HWS, highly weathered soils; IEP, iso-electric point; IS, ionic strength; PZC, point of zero charge; PZNC, point of zero net charge; PZSE, point of zero salt effect; PZNPC, point of zero net proton charge; SC, surface complexation; SOM, soil organic matter; VAS, volcanic ash soils; VCS, variable-charge soils; XSW, X-ray standing wave. 159 Advances in Agronomy, Volume 84 Copyright q 2004 by Elsevier Inc. All rights of reproduction in any form reserved. DOI 10.1016/S0065-2113(04)84004-5

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N. P. QAFOKU ET AL. characteristics of these soil systems are different from those observed in soil systems of temperate regions. In this chapter, the mineralogy, chemistry and management of VCS are reviewed and discussed, focusing on the chemistry of these systems. q 2004 by Elsevier Inc.

I. INTRODUCTION Soils rich in constituents with amphoteric surface reactive groups in the Oxisols, Ultisols, Alfisols, Spodosols and Andisols orders are considered variable charge soils (VCS) (Theng, 1980). Vast areas of the world are covered by these soils, which have developed either under intensive weathering and leaching or from volcanic ash parent material. The world distribution of some of the VCS is presented in Table I. In the group of VCS are included soils with a wide spectrum of morphological, mineralogical, chemical, physical, biological, and genetic characteristics. However, they have one property in common; the magnitude and sign of their amphoteric surface charge depends on the chemistry of the contacting solution, i.e., pH and ionic composition and concentration (Sumner, 1995b). The variable charge component is usually developed on surfaces of organic soil constituents with carboxyl, phenolic, or amino reactive groups, as well as on surfaces of inorganic soil constituents with hydroxyl reactive groups. The variable charge is generated because of adsorption or desorption of ions that are constituents of the solid phase, such as Hþ, and ions that are not constituents of the solid phase. VCS are heterogeneous charge systems. The coexistence and interactions of soil particles and colloids with net opposite surface charges confer a quite interesting, and much more complex pattern with respect to soil physical and chemical behavior compared to homogeneously charged soil systems of temperate regions. A great deal of time and effort has been spent over the last 80 years to elucidate different aspects of their behavior, and many prominent soil scientists, such as Uehara, Mattson, Schofield, van Olphen, Sumner, Thomas, Gillman, Wada, Barrow, Bowden, Bertsch, and Sposito have made illustrious contributions towards a better understanding of these fascinating soil systems. The following chapter is divided into three sections in which topics on mineralogy, chemistry and management of VCS are reviewed and discussed. The use of new and advance laboratory techniques over the last few years have contributed to a better understanding of the chemical behavior of variable charge minerals and soils. For this reason, the chemistry section occupies the major part of this chapter.

VARIABLE CHARGE SOILS

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Table I Global Areas and Percentages of Suborders of the Soil Orders with Variable Charge Soils Orders

Suborders

Area [km2 ( £ 103)]

Proportion (%)

Alfisols

Aqualfs Cryalfs Ustalfs Xeralfs Udalfs

836 2518 5664 897 2706 12621

0.7 1.9 4.3 0.7 0.2 9.6

Subtotal Andisols

Cryands Torrands Xerands Vitrands Ustands Udands

255 2 32 281 63 279 912

0.2 0.01 0.01 0.2 0.1 0.2 0.7

Aquox Torrox Ustox Perox Udox

320 31 3096 1162 5201 9810

0.2 0.01 2.4 0.9 4 7.5

Aquods Cryods Humods Orthods

169 2460 58 667 3354

0.1 1.9 0.01 0.5 2.5

Aquults Humults Udults Ustults Xerults

1281 344 5540 3870 19 11054

1 0.3 4.2 3 0.01 8.5

Subtotal Oxisols

Subtotal Spodosols

Subtotal Ultisols

Subtotal

Data from USDA-NRCS, Soil Survey Division, World Soil Resources, 1998 (modified after Wilding, 2000 (24)).

II. MINERALOGY OF VARIABLE CHARGE SOILS A. MINERALOGY

IN

GENERAL

The most important mineralogical components in VCS are: kaolinite, Fe oxides and gibbsite in Oxisols (Herbillon, 1980) with quartz being an important

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component as well (Weaver, 1975; Eswaran and Stoops, 1979); kaolinite, hydroxy-interlayered vermiculite, muscovite, smectite, and Fe and Al oxides in Ultisols (quartz in the sand and silt fractions) (Carlisle and Zelazny, 1974; Gallez et al., 1975; de Alwis and Pluth, 1976; Eswaran and Sys, 1976; Smith et al., 1976); kaolinite and smectite in the highly weathered Alfisols (mica and Fe oxides in smaller abundances and quartz and feldspars in the coarse fractions) (Jungarius and Levelt, 1964; Gallez et al., 1975; de Alwis and Pluth, 1976); minor amounts of mica, chlorite, kaolinite and vermiculite in the clay fraction of Spodosols (orthoclase, plagioclase, mica, pyroxene, and amphibole in the sand fraction, and quartz and traces of plagioclase in the silt and sand fraction) (McKeague, 1965; McKeague and Brydon, 1970; Kapoor, 1972; Righi and De Coninck, 1977); allophane, imogolite, poorly crystalline Fe oxides (probably ferrihydrite), volcanic glass (which is a mixture of aluminosilicates and traces of ferromagnesian minerals), and secondary Si minerals (opaline silica) in Andisols (Shoji and Masui, 1971; Bleeker and Parfitt, 1974; Mizota, 1981; Parfitt et al., 1983; Wada and Kakuto, 1985; Wada et al., 1986; Shoji et al., 1987; Wada, 1987; Mizota et al., 1988; Parfitt et al., 1988; Delvaux et al., 1989, 1990; Childs et al., 1991; Dahlgren et al., 1993). The clay fraction mineralogy of variable charge subsoils is mostly dominated by the quintet kaolinite, gibbsite, goethite, and hematite, and amorphous minerals (mostly allophane, imogolite or ferrihydrite) (Uehara and Gillman, 1981; Gillman and Sinclair, 1987). It is important to emphasize, however, that the contents and proportions of mineralogical constituents, particle size distribution, and specific surface areas are different in different soils. As a result, they manifest a significant diversity in their properties. Variable charge subsoils are likely to have one of the following five mineralogical characteristics when they reach the apparent steady-state during their development (Qafoku et al., 2000b): (1) Large amounts of kaolinite and crystalline and less reactive Fe and Al oxides, mainly hematite and gibbsite (typical examples are Oxisols from Australia); (2) large amounts of kaolinite and very reactive Fe and Al oxides, mainly goethite and gibbsite (typical examples are Ultisols from the Southeastern United States and South Africa); (3) large amounts of extremely reactive amorphous minerals such as allophane, imogolite and ferrihydrite (typical examples are Andisols); (4) almost monophase mineralogy dominated by kaolinite and small amounts of Fe oxides (typical examples are some Ultisols from Southeastern United States and Brazil, and some Oxisols from Hawaii; (5) almost monophase mineralogy dominated by not very reactive Fe and Al oxides, and in some cases, Ni oxides; typical examples are some Oxisols from New Caledonia and Jamaica. The mineralogical characteristics of highly weathered soils (HWS) from the humid tropical regions (mainly Oxisols and Ultisols) and volcanic ash soils (VAS) (mainly Andisols and Ultisols) are treated in greater detail below.


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B. HIGHLY WEATHERED SOILS The mineralogy of the sand, silt and clay fractions of HWS is characterized by the presence of thermodynamically stable primary and secondary minerals. Most oxic and argillic horizons have mineralogical assemblages in which a few major constituents often make up as much as 90% of the total soil mass (Herbillon, 1980). Among these minerals are 1:1 layer silicates of the kaolin group, Fe, Al and Ti oxides and some highly resistant minerals either inherited or transformed from the parent rock such as quartz, muscovite and probably hydroxyinterlayered vermiculite. The common occurrence of muscovite in soils derived from micaceous parent rocks suggests that muscovite is resistant to weathering under base-depleted conditions, such as the ones prevailing in the HWS (Murali et al., 1974; Gallez et al., 1975; Herbillon, 1980). Although the list of major mineralogical constituents appears to be rather limited, this does not preclude a relatively broad diversity. Differences may be due either to a variation in the proportions of the major minerals or variable characteristics within the same mineral type (Smith et al., 1975; Van Ranst, 1995). The dominant clay mineral is kaolinite (Fripiat, 1959). Among the Fe oxides, goethite and hematite are the most important minerals in highly weathered tropical soils (Segalen, 1971). Kaolinite crystals from HWS show several important differences to kaolinites from natural geological deposits (Table II). These crystals may be very small compared to the “classical” crystals of kaolinites, having a much higher reactive surface area (Herbillon et al., 1976; Mestdagh et al., 1980). In addition, kaolinite crystals from HWS appear to have a higher structural Fe content. Oxisols from South Brasil were found to have up to 2% Fe-rich kaolinite (Palmieri, 1986), which corroborates other earlier reports (Mestdagh et al., 1980). It also appears that kaolinite from HWS is less crystallized compared to kaolinites from geological deposits (Mestdagh et al., 1980). The incorporation of Fe in the kaolinite crystals formed in Fe-rich environments of the humid tropics affects crystal development and surface reactivity (Mestdagh et al., 1980).

Table II Some Properties of Kaolinite Crystals from Highly Weathered Tropical Soils and from Geological Deposits Kaolinite crystals Properties

Oxic soil materials

Geological deposits

Size Surface area Structural Fe

Range of 0.1 mm 100–250 m2/g Up to 2% Fe2O3

Micrometer range Few m2/g Extremely low

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Although known for some time (Norrish and Taylor, 1961), it has only recently been realized that Al-substitution in Fe oxides seems to be the rule rather than the exception (Biais et al., 1972; Davey et al., 1975; Bigham et al., 1978; Golden et al., 1979; Mendelovici et al., 1979), and that the degree of substitution in HWS may reach the maximum possible extent (Fitzpatrick and Schwertmann, 1982; Schwertmann and Ka¨mpf, 1985; Schwertmann and Herbillon, 1992). Al-for-Fe substitutions generally result in a lower degree of crystallinity, smaller particle size and, above all, a significant increase in the reactive surface area of the oxidic material (Janot and Gilbert, 1970; Plancon and Tchoubar, 1977; Anand and Gilkes, 1987). The activity of soluble Al in the environment of the developing goethite crystals may be an important factor in determining the degree of Al substitution in goethite, and can be influenced by pH and Si concentration. Soil maturity, landscape position and horizon are important determinants affecting the degree of Al substitution in Fe oxides (Fitzpatrick and Schwertmann, 1982). For example, in a deep laterite profile from Cameroon it was found that the Al-for-Fe substitution of goethite increased in the order: Fe-rich nodules (10 –15 mol%) , red clay matrix (15 –20 mol%) , yellow clay matrix (20 –25 mol%) (Muller and Bocquier, 1985) (remark: Al-for-Fe substitution in goethite is usually expressed in mole percent substitution). Low substitutions in goethites (0 –10 mol%) were found in hydromorphic environments, whereas high values (greater than 33 mol%) occurred in association with gibbsite (Schwertmann and Ka¨mpf, 1985). An Al-for-Fe substitution in goethite of up to 28 mol% was found in a Xanthic Ferralsol from Lower Congo (Baert et al., 1999). Among the common 2:1 silicate minerals in HWS with argillic horizons, namely mica, vermiculite and smectite, dioctahedral mica (muscovite) is the most widespread mineral found in the clay fraction (Murali et al., 1974; Gallez et al., 1975). The occurrence of small to moderate amounts of mixed-layer clay minerals and smectites is also common in many strongly acidic soils with argillic horizon (Odell et al., 1974). Vermiculite is a relatively uncommon clay mineral found only in well weathered soils in the humid tropics (Juo, 1980).

C. VOLCANIC ASH SOILS These soils undergo gradual changes as a result of weathering of the primary minerals that are present in volcanic deposits. Two trends in their development are likely to be distinguished (Wada, 1980; Yoshinaga, 1986; Dahlgren et al., 1993; Van Ranst et al., 1993): 1. Fresh volcanic ash material ! 2:1 phyllosilicates þ free Fe constituents ! 1:1 phyllosilicates þ free Fe constituents ! free Al þ Fe constituents; 2. Fresh volcanic ash material ! Al-rich constituents þ free Fe constituents ! 1:1 phyllosilicates þ free Fe constituents ! free Al þ Fe constituents.


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The first sequence needs a parent material rich in basic cations and/or a slow removal of weathering products. The second sequence requires a very rapid removal of the weathering products (Shoji et al., 1982; Shoji and Fujiwara, 1984; Van Ranst et al., 1993). The rate of weathering depends on numerous factors such as amount, size, porosity, chemical and mineralogical composition of the weatherable primary minerals, especially volcanic glass (Mizota, 1976, 1981; Yamada and Shoji, 1983; Shoji, 1986; Van Ranst et al., 1993). Other factors include time since the deposition occurred, climate that determines primarily the possibility for export of the constituents released during weathering, composition of the deeper layers that determine the rate of transport of the soil solution, and presence or absence of a water table (Lowe, 1986; Yoshinaga, 1986; Shoji et al., 1988; Ugolini et al., 1988; Dahlgren et al., 1993). The constituents formed from weathering products most probably are free Feoxides, hydroxides or (oxy)hydroxides, secondary 2:1 phyllosilicates containing basic cations both in the lattice and in the interlayer space, constituents characterized by high Al-contents, including short range order minerals (allophanes, imogolite), constituents with ill-defined structure and composition (allophane-like constituents), organo-Al complexes (gibbsite), 1:1 phyllosilicates with a regular organization (kaolinite, halloysite), and free Al constituents with crystalline structure (gibbsite – boehmite) (Wada, 1980; Wada, 1985; Wada, 1987; De Coninck and Sutanto, 1990; Van Ranst et al., 1990; Dahlgren et al., 1993). Mineralogical analyses of sands and silts from VAS show that they are largely composed of light materials, in which volcanic glass and feldspars are most abundant, with, in general, greater or lesser amounts of silica minerals (quartz and cristobalite), mica and weathered pumice grains as minor components (Yoshinaga, 1988). Heavy minerals account for only a part of the fine sands and most frequent are hypersthene, opaques, augite and hornblende (Jackson, 1964; Loughan, 1969; Shoji, 1986). Olivine is of relatively rare occurrence, because of its high weatherability (Jackson, 1964; Loughan, 1969). Nevertheless, olivine with or without colored volcanic glass can be abundant in basaltic ash (Shoji et al., 1975). The clay components of particular importance in VAS are allophane and imogolite (Yoshinaga and Aomine, 1962a,b). Other important clay minerals are non-crystalline iron hydroxides, which may or may not be ferrihydrite (Parfitt et al., 1988; Childs et al., 1991). Besides these minerals, they contain 2:1 and 2:1:1 type minerals and their integrades, halloysite, gibbsite, opaline silica, etc., usually in minor amounts but occasionally in substantial or dominant amounts (Wada, 1985; Van Ranst et al., 1993). Interstratified 1:1 –2:1 phyllosililcates may also be present (Herbillon et al., 1981; Wada et al., 1987; Delvaux et al., 1990; Fiantis et al., 1998). Studies in the last 30 years have established that VAS are characterized by the formation of short-range-order minerals, such as allophane and imogolite, and

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related materials from volcanic ash (Parfitt et al., 1983, 1984; Wada, 1987; Parfitt and Kimble, 1989). Imogolite coexists with allophane, but the content is generally lower (Wada and Harward, 1974; Shoji et al., 1988; Wada, 1989). However, in environments rich in organic matter, formation of such clay materials is limited and inhibited by the formation of stable Al – humus complexes whose accumulation in the surface horizons constitutes another characteristic in the development of these soils (Shoji et al., 1982; Shoji and Fujiwara, 1984; Saigusa and Shoji, 1986; Parfitt and Kimble, 1989). The formation of allophane and imogolite in the surface horizon of VAS can be hindered in organic matter rich soils since Al will form strong complexes with organic matter resulting in a decline in its activity in the soil aqueous phase (Dahlgren and Ugolini, 1989). The rate of co-precipitation with Si to form allophane or imogolite decreases as well. These circumstances may promote Si precipitation in the form of opaline silica (Wada, 1980). Opaline silica occurs more abundantly in younger than in older VAS, and in humus-rich A and buried A horizons than in the underlying B and C horizons (Shoji and Masui, 1971; Wada, 1980). Such occurrence indicates that the opaline silica is formed early during soil development where weathering release of Si from ash is abundant, and that it is a component alienated by the formation of Al– humus complexes (Shoji et al., 1982; Shoji and Fujiwara, 1984; Shoji et al., 1985). This implies that the formation of opaline silica and that of Al –humus complexes proceed in parallel. However, opaline silica is not formed when allophane and imogolite are formed (Wada, 1985). Halloysite is found, usually, in old and buried ash and pumice layers where Si is supplied abundantly by percolating water (Wada, 1980, 1989). In VAS with dry water regimes and where water movement is restricted halloysite rather than allophane and imogolite, is formed in surface horizons (Iseki et al., 1981; Parfitt et al., 1984; Lowe, 1986; Wada, 1987). The formation of halloysite is governed primarily by the availability of Si in the soil solution (Parfitt et al., 1983; Singleton et al., 1989). Iron in VAS is present mostly in the form of non-crystalline hydroxides and partly as Fe – humus complexes (Wada and Higashi, 1976; Subardja and Buurman, 1980; Yoshinaga, 1986; Supriyo et al., 1992). The former may or may not be ferrihydrite (Parfitt et al., 1988; Childs et al., 1991), a short-rangeorder Fe hydroxide mineral. Layer silicates such as vermiculite, smectite and their intergrades with chlorite and mica are frequently found in VAS (Wada, 1980; Yamada and Shoji, 1983; Delvaux et al., 1989). Their content in general is low but in some VAS they constitute a substantial or even the dominant part of the clay fraction (Wada, 1980). Reports on clay mineralogy of VAS from arid and semiarid tropical areas are rather limited (Wielemaker and Wakatsuki, 1984). The clay mineralogical features of such soils appear to be quite different from those of humid regions. Allophane and imogolite are scarce or absent and the major, or one of the major,


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clay constituents in reportedly siliceous Fe oxides (Wielemaker and Wakatsuki, 1984) associated with embryonic halloysite (poorly ordered halloysite) (Wada and Kakuto, 1985), or Si- and Fe-rich allophanes (Wada and Wada, 1977; Parfitt et al., 1980; Goodman et al., 1985; Shimizu et al., 1988), and curved smectite (Van der Gaast et al., 1985). It is presumed that such clay minerals, together with embryonic halloysite, may have a more widespread distribution in VAS in tropical dry areas (Wada and Kakuto, 1985).

III. THE CHEMISTRY OF VARIABLE CHARGE SOILS A. CHEMICAL CHARACTERISTICS

IN

GENERAL

Studies on the electrochemical characteristics of VCS have been conducted around the world over the past 70 years and a great deal of time and effort are currently being spent in investigating these fascinating soil systems. These studies have shown that HWS and VAS have unique chemical properties, which set them apart from other soils (Van Raij and Peech, 1972). The most typical chemical properties are the following (Stoop, 1980): a point of zero charge at pH where plant roots may grow normally (Van Raij and Peech, 1972; Keng and Uehara, 1973); a relatively large anion adsorption capacity (Hingston et al., 1967; Kinjo and Pratt, 1971; Hingston et al., 1972; Hingston et al., 1974; Charlet and Sposito, 1987; Charlet and Sposito, 1989; Bellini et al., 1996; Qafoku et al., 2000b; Qafoku and Sumner, 2002); high lime or gypsum requirement to achieve neutral pH (Sumner, 1993); considerable sorption affinity for cations such as Ca and Mg, which may form both inner- and outer-sphere surface complexes although inner-sphere surface complexes are found to be more important (Charlet and Sposito, 1987). With respect to the most extremely weathered VCS, Oxisols, a negligible permanent charge is present and therefore, the point of zero net charge (PZNC) equals the point of zero net proton charge (PZNPC) (Charlet and Sposito, 1987). In a collection of variable charge subsoils from all over the world, the PZNC varied between pH values of 3 and 5.4 (Qafoku et al., 2000b).

1.

Aqueous Phase Chemistry

Aqueous phase properties, especially soil solution pH and ionic strength (IS) (which includes the effect of both ionic concentration and composition) are important determinants in the chemical behavior of VCS. Even minor changes in the magnitude of these aqueous phase properties may have a profound influence on surface charge and colloid generation and transport in these Fe oxidedominated systems (Seaman et al., 1995). The soil solution of VCS is usually

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very dilute because of the intensive leaching they have undergone (Sumner and Davidtz, 1965; Le Roux and Sumner, 1967; Gillman and Bell, 1978; Gillman and Sumner, 1987). For example, soils in North Queensland in Australia are reported to have an IS upper limit of approximately 0.005 (Gillman and Bell, 1978). In general, the soil solution is more dilute in the subsoils of Oxisols and Ultisols than in their corresponding topsoils, but this trend may be reversed in less weathered Alfisols (Le Roux and Sumner, 1967). They usually have a slightly acidic to acidic soil solution pH, which is close to either PZNC or point of zero salt effect (PZSE) of the soil (Qafoku et al., 2000b). 2.

Solid Phase Chemistry

VCS usually undergo isoeletric weathering and eventually reach a stage of zero net charge during their development (Matson, 1932; Sumner, 1963b; Qafoku et al., 2000b). The concept of “isoelectric weathering” appears to have been introduced more than 70 years ago (Matson, 1932). Amphoteric colloids of these soils possess a tendency to alter their composition in such a way that the soil iso-electric point (IEP) coincides with the prevailing pH. They are characterized by high abundances of minerals with a PZNPC at neutral or slightly basic pH, the most important being Fe and Al oxides and allophane. Under acidic conditions, the surfaces of these minerals are net positively charged. In contrast, the surfaces of dual-charge phyllosilicates are negatively charged regardless of ambient conditions. Therefore, VCS are characterized as being isoelectric mixed charge systems.

B. SOIL PARTICLES

AND

THEIR SURFACE CHARGE

Based on their surface charge characteristics, the soil particles are of two different types: dual-charge particles (phyllosilicates and allophane) and variable-charge particles (metal oxides). Because these minerals are found in significant abundance in VCS, they usually control the chemical properties of the bulk soil. But even in cases where they constitute a minor fraction of the total soil or sediment mass, the surface chemical properties of soils and sediments may be completely dominated by secondary minerals or grain coatings (Davis et al., 1988).

1. Dual-Charge Sorbents Dual-charge soil minerals, such as phyllosilicates, usually develop permanent and variable charge on different surfaces of the same particle. These soil minerals are also called permanent or constant charge minerals. The siloxane ditrigonal


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cavity of the phyllosilicate siloxane surfaces may develop a localized permanent negative charge as a result of isomorphic substitutions in their internal crystal structures (Sposito, 1984). Importantly, the magnitude of this surface (permanent) negative charge does not depend on pH and IS of the contacting solution. In contrast, the edges of these particles develop variable charge, hence the name dual-charge particles. The variable charge on particle edges is pH and IS dependent. The most common dual-charge minerals in VCS is kaolinite. Because allophane may have permanent structural charge in addition to surface variable charge (Harsh et al., 2002), it may be considered as a dualcharge soil mineral. (a) Kaolinite: Kaolinite is a 1:1 phyllosilicate with a relatively low specific surface area (between 5 and 39 m2 g21) and, commonly, a pseudohexagonal plate shape. It has an Al octahedral sheet and a Si tetrahedral sheet. Oxygen (O22) connects the Al centers of the octahedral gibbsite sheet and the Si centers of tetrahedral siloxane sheet (Wieland and Stumm, 1992). The cohesion energy between adjacent kaolinite sheets is estimated to be 18.64 kcal per unit cell (Wiechowski and Wiewiora, 1976). Each sheet of kaolinite has two surfaces namely, a surface of oxygens on the Si tetrahedral sheet and a surface of hydroxyls on the Al octahedral sheet. Both these surface groups are fully chargesatisfied and have low reactivity. However, the edges of kaolinitic particles have single coordinated aluminol and silanol variable charge groups with unsatisfied charge that are quite reactive. Due to isomorphic substitution of Si by Al, (Si –O – Si) groups are replaced by negatively charged (Si –O – Al) groups in the surface lattice structure of the siloxane layer causing a permanent (constant) structural charge (Schofield and Samson, 1954; Bolland et al., 1976; Van Olphen, 1977; Sposito, 1984). Small amounts of 2:1 phyllosilicates attached to the siloxane layers of kaolinite particles may also increase the magnitude of the surface negative charge of these layers (Lim et al., 1980). However, kaolinite has the lowest surface charge (about 1– 5 cmol(c) kg21) among common dual-charge clay minerals because of the relatively small number of isomorphic substitutions in its structure. The PZNC of a specimen of Georgia kaolinite is approximately 3.6 and the PZNPC is between pH values of 5 and 5.4 (Schroth and Sposito, 1997). Although acid/base properties of dual charge minerals and Si oxides are not very well understood and related studies are relatively rare in the literature (Zachara and McKinley, 1993; Kraepiel et al., 1998; Kraepiel et al., 1999; Dixit and Van Cappellen, 2002), convincing evidence has been presented to show that in addition to the permanent charge generated on surfaces, the edges of kaolinite particles carry a variable charge (Schofield and Samson, 1954; Cashen, 1959; Quirk, 1960; Rand and Melton, 1977; Wieland and Stumm, 1992). The kaolinitic particle is composed of three morphological surfaces of different chemical composition: the gibbsite and the siloxane surfaces, both denoted as basal surfaces and a complex oxide of the two constituents Al(OH)3 and SiO2 at

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the edge surface (Wieland and Stumm, 1992). Kaolinitic particles have the following terminal oxo and hydroxo groups in their surfaces that may be involved in complexation reactions with protons, metal ions, and ligands: Al – OH – Al and yAlOH groups at the gibbsite layer, Si – O –Si and ySiOH groups at the siloxane layer, and yAlOH and ySiOH groups at the edge surface (Wieland and Stumm, 1992). Chemisorption of water molecules on edge Al sites results in the formation of Lewis acid sites which are acidic and act only as proton donor sites (Sposito, 1984). A three-site model may be used to describe the acid/base characteristics of kaolinite (Wieland and Stumm, 1992). The coordinative surface groups engaged in surface complexation and ion exchange reactions are the aluminol groups at INT INT ¼ 6:5; pKa2 ¼ 8:5; the aluminol groups at the gibbsite the edge with pKa1 INT INT surface with pKa1 ¼ 3:4; and pKa2 ¼ 8:4; and the yXO negatively charged sites of the siloxane surface where ion exchange occurs (Wieland and Stumm, 1992). (b) Allophane: Under the name of allophane are included a group of aluminosilicate minerals with primarily short-range structural order that occur as spherical nanoparticles 3 –6 nm in diameter, with a chemical composition of silica and alumina (Qafoku et al., 2003). The specific surface area measured by ethylene glycol monoethyl ether (EGME) varies between 700 and 900 m2 g21 (Egashira and Aomine, 1974). Allophane may have both permanent and variable surface charge but the relative predominance of permanent versus variable charge depends upon mineral structure (Harsh et al., 2002). As an example, in silica rich environments Al occurs in fourfold coordination via isomorphic substitution for tetrahedral Si. Under these conditions, Al is more likely to substitute for Si than to form separate octahedral units (Harsh et al., 2002). The variable charge results from protonation and dissociation of surface aluminol and silanol functional groups, with aluminol groups having negative, neutral or positive charge and the more acidic silanol groups having either neutral or negative charge. As allophane is a dual-charge soil mineral, the PZNPC is not equal to the PZNC.

2. Variable Charge Sorbents VCS generally have a high proportion of variable charge (or constant surface potential) colloids of metal oxides (Keng and Uehara, 1973), in particular Fe and Al oxides. Oxides have surface reactive groups with amphoteric properties; these groups are protonated (positively charged) under acidic conditions or deprotonated (negatively charged) under basic conditions. In general, the oxide surfaces have a net positive surface charge when pH of the contacting solution is below the PZNPC, which varies between pH ¼ 7 and 9 for common oxides. The surface charge density of variable-charge oxides is pH and IS dependent. Modest changes in IS of the soil solution are equally as important in their effect on cation exchange capacity as are changes in pH (Gillman, 1981). Studies suggest that


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surface charge density and adsorption properties of amphoteric surfaces are altered by solutes in contact with them (Wann and Uehara, 1978). (a) Fe and Al Oxides: Fe and Al oxides are the most important variable charge sources in tropical soils. Their amphoteric surfaces are capable of sorbing and desorbing protons depending on pH and IS of the soil solution, and as a result, they may have positive, negative, or no surface charge. They usually have a net positive surface charge under acid conditions typical for VCS. Although Fe and Al oxides are found in almost all soils, they are present in VCS in greater quantities because they are one of the end products of the weathering processes in soils. They form particles as small as a few nm across (e.g., ferrihydrite) and have specific surfaces as high as several hundred m2 g21. Even crystalline Fe oxides (e.g., goethite) may have specific surfaces of several tens of m2 g21 (Qafoku and Amonette, 2003). The surface functional groups form complexes with cations and anions from the aqueous phase. Oxyanions (e.g., phosphate) are particularly strongly bound as they form inner-sphere complexes in which the anion becomes part of the oxide surface structure. One very important surface property of oxides is that there are very few charges present at PZNPC and most of the surface is covered with uncharged hydroxyl groups (Hunter, 1993). Goethite and hematite are the most important Fe oxides in HWS. The substitution of Al for Fe in goethite is more frequent in these soils. This affects surface charge as it generally results in a lower degree of crystallinity, a smaller particle size and a significant increase in surface area and sorption capacities. The PZNPC values reported in the literature for goethite vary between 7.5 and 9.4 (Kosmulski, 2002); carbonate adsorption and/or surface morphology are thought to account for this wide range (Gaboriaud and Ehrhardt, 2003). The PZNPC values reported in the literature for hematite vary in quite a similar range of 7 –9.2 (Kosmulski, 2002). The positive charge generated on these Fe and Al oxide surfaces may be electrostatically attracted to the permanent negative charge on layered aluminosilicate clay minerals (Qafoku and Sumner, 2002; Qafoku et al., 2003). Formation of electrostatic bonds between oxide and phyllosilicate minerals promotes the formation of soil aggregates and stabilizes them, especially in highly weathered variable-charge soils. This would explain the non-dispersive nature and formation of stable aggregates in subsoils from the southeastern US (Miller et al., 1990). Fe oxides also buffer the oxidation –reduction activity of soils (Qafoku and Amonette, 2003). The reduction potential for the aqueous Fe3þ/Fe2þ couple (þ 0.77 V) is situated in the middle of the limits for aqueous chemistry (i.e., 2 1.1 to þ 1.8 V), and Fe3þ in poorly ordered oxides serves as a terminal electron acceptor for microorganisms once oxygen and nitrate are consumed. The crystalline Fe oxides are less susceptible to reductive dissolution and can retain some of these mobile Fe2þ cations on their surfaces, where they become

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effective reductants for environmental contaminants (Stumm, 1992; Stumm and Morgan, 1996).

C. SORPTION 1.

Solid-Like and Solid-Unlike Potential Determining Ions; Their Competitive Sorption Behavior

The net charge and the resultant electrostatic potential on variable charge surfaces relative to the surrounding aqueous phase, is strongly dependent on the balance of Hþ and OH2 concentrations in solution (Hunter, 1993). For this reason, Hþ and OH2 are called potential determining ions (p.d.i.). These ions are components of all variable charge surfaces in soils and surface potential is a direct function of the extent of their adsorption. In addition to being adsorbed in response to changes in their own aqueous concentrations, Hþ and OH2 are also adsorbed on soil variable charge surfaces in response to a change in the background electrolyte (BE) concentration (or IS) of the contacting solution. They are driven to the surface to keep the surface potential constant when the BE concentration changes (Hunter, 1993). If the bathing solution pH is below the PZNPC of the variable charge surface, protons are adsorbed when BE concentration is increased. If the bathing solution pH is greater than the PZNPC, hydroxyls are adsorbed onto the variable charge surfaces when BE concentration is increased. One may think that similar to Hþ or OH2, other non-lattice cations and anions may act as solid-unlike p.d.i., and may form inner-sphere complexes with the surface reactive groups. From a chemical perspective, the distinction between solid-like and solid-unlike p.d.i. is somewhat arbitrary because in both cases, chemical bonds between surface reactive groups and anions are formed. One should expect, therefore, that if these ions are present in the soil solution in sufficiently high concentrations, such cations or anions may, respectively, compete with Hþ or OH2 for surface reactive sites, when BE concentration is increased at a constant pH. Cations, however, are less likely to behave as solidunlike p.d.i. because they are quite different from protons. Clearly the distinction between hydroxyls and oxyanions that are adsorbed via ligand exchange is less pronounced. Besides being oxyanions, similar to OH2, these anions increase the negative charge of the oxide surface and competition among them for surface sites is determined by the anion ability to give the oxide a negative charge (Hingston et al., 1967, 1972; Hingston et al., 1974; Bowden et al., 1980). In addition, they may also decrease the PZNPC of the sorbents (Stoop, 1980; Goldberg et al., 1996). It is quite possible therefore, that these anions may serve as solid-unlike p.d.i. and their adsorption extent may increase as a result of changes in the BE concentration at pH values greater than the PZNPC.


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A vast array of bibliographical references provides evidence of different anions behaving as solid-unlike p.d.i. on variable charge surfaces. Adsorption of phosphate by goethite as a function of BE concentration (NaCl in this case) is well pronounced at basic pH values as high as 9 (Barrow et al., 1980a). At such a basic pH, the variable charge surface is not positively charged and phosphate should not be electrostatically attracted to the surface. Other examples include: 1. Sorbed P not only lowers the PZC of an Oxisol, but also increases surface charge density at any pH above the soil PZC (Wann and Uehara, 1978). 2. When concentration of the BE solution, in this case KNO3, is increased from 0.01 to 0.5 M, PO4-adsorption to goethite increases as well; the magnitude of adsorption increases as pH is increased to approximately 10, that is higher than the IEP of goethite (Geelhoed et al., 1997). 3. Boron adsorption to pyrophyllite edges at basic pH is affected by the NaNO3 BE concentration (Keren and Sparks, 1994); significantly more B is adsorbed at pH ¼ 9 as compared to that adsorbed at pH ¼ 7 for all BE concentrations tested in these studies. It appears that as the surface charge on goethite changes from positive to neutral and then negative, P and B adsorption unexpectedly increases. At basic pH boron is mostly present as borate (B(OH)2 4 ) and forms inner sphere surface complexes with goethite, gibbsite and kaolinite (Goldberg et al., 1993). Quite interestingly, Cl may behave like a solid-unlike p.d.i. in addition to oxyanions. Ba2þ and Cl2 co-adsorption is observed on negatively charged hematite surfaces at pH 10.4 in experiments where Cl concentration is an order of magnitude greater than the OH concentration (Pochard et al., 2002). The adsorption of Cl increases with increasing BaCl2 concentration in the contacting solution. Specific adsorption of Cl may occur on the freshly prepared hematite surfaces shifting the IEP to lower pH values (Penners et al., 1986). Even though other explanations are given in the literature, such as the increase in PO4 adsorption at high BE concentrations and pH values above the IEP, can be explained by the less negative potential in the plane of adsorption (Barrow et al., 1980b), the examples presented above clearly indicate that anions may serve as a solid-unlike p.d.i. when variable charge surfaces are negatively charged. An indirect means of assessing whether an ion has the ability to form inner-sphere surface complexes is by studying adsorption of that ion as a function of the BE concentration at a solution pH greater than the PZNPC for anions, or lower than PZNPC for cations. One should also be aware and consider the changes in sorbate speciation as a function of pH, because the increase in adsorption as BE concentration increases at different basic pH may be attributed in some cases to differences in solute speciation at these different basic pH. The BE concentration effect on

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B adsorption was smaller at pH 7 than at pH 9, consistent with a decrease in B(OH)2 4 activity in the equilibrium solution at pH 7 and the low affinity of the clay for B(OH)3 (Keren and Sparks, 1994).

2. Co-Adsorption Co-adsorption occurs when the adsorption of an aqueous ion facilitates or causes the adsorption of another aqueous ion. Co-adsorption appears to be a common phenomenon in variable charge surfaces. For example phosphate adsorption increases the adsorption of aqueous cations, which may be attributed to a shift in the PZC to lower pH’s (Hingston et al., 1967; Hingston et al., 1972; Breeuwsma and Lyklema, 1973; Hingston et al., 1974; Parfitt and Atkinson, 1976), neutralization of surface positive charge (Hingston et al., 1972), or electrolyte imbibition (Thomas, 1960). Adsorption of metal ions onto the reactive surfaces in soils in contact with solutions of strong indifferent electrolytes is thought to occur without the involvement of the electrolyte ions. However, in cases where the metal ion forms a strong aqueous complex with the electrolyte anion, such as CdClþ or PbClþ, the metal and the electrolyte anions adsorb simultaneously (Criscenti and Sverjensky, 1999). Macroscopic sorption studies with Al oxide conducted to evaluate the effect of strongly sorbing Se(IV) and weakly sorbing Se(VI) oxyanions on Co(II) sorption to g-Al2O3, show that Se(IV) significantly altered Co(II) sorption as a function of Co(II) surface coverage, while Se(VI) adsorption has no effect on Co(II) sorption (Boyle-Wight et al., 2002a). The effect of Se(IV) on Co(II) sorption is a function of the Se(IV) surface coverage (Boyle-Wight et al., 2002b). In an EXAFS study, Cd(II) adsorption on goethite is strongly enhanced in the presence of PO4 or SO4 ions in the BE solution (Collins et al., 1999). The mechanism of Cd(II) adsorption appears to be solely electrostatic, i.e., the adsorption of negative anions onto the surface reduces positive charge on the surface, and thus increases the attraction of cations (Cd2þ) to a positively charged surface. No evidence of the formation of ternary complexes is reported in this study as is suggested elsewhere (Hoins et al., 1993). In addition, the sulfur and phosphate ions are absent from the coordination environment of Cd2þ bound to the surface of goethite, which also suggests that the presence of Cd-sulfate or Cd-phosphate surface precipitates is unlikely and indicating that ligands were sorbed to surface sites other than those occupied by Cd(II). This is an example of co-adsorption that reveals the importance of surface potential in adsorption. Salt adsorption (Thomas, 1960; Wada, 1984; Mercano-Martinez and McBride, 1989; Alva et al., 1991b; Bolan et al., 1993; Bellini et al., 1996; Pearse and Sumner, 1997; Qafoku and Sumner, 2001), may be considered a specific case of


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co-adsorption. The equivalent sorption of Ca2þ and SO22 4 with little or no net release of cations and anions into the soil solution provides evidence for salt adsorption (Alva et al., 1991a,b). Studies have also shown salt adsorption by kaolin group minerals and Andisols when suspended in salt solutions (Wada, 1984). The proposed mechanism in Andisols is the simultaneous development of cation and anion holding sites on variable charge surfaces (Wada, 1984). It is suggested that both ions formed inner-sphere surface complexes releasing equivalent amounts of OH and H ions, which react to form water. Simultaneous sorption of Ca2þ and SO22 has also been reported by other researchers 4 (Mercano-Martinez and McBride, 1989) in Oxisols during equilibration in batch reactors with CaSO4, with the mechanism of simultaneous adsorption based on the formation of surface ion-pairs of these two ions. However, the formation of surface ion-pairs does not fully explain salt adsorption, i.e., the adsorption of anions and cations of an electrolyte in equivalent amounts with no net release of other ions into the soil solution (Qafoku et al., 2000a; Qafoku and Sumner, 2001, 2002).

3.

Co-Adsorption and Competition of BE Ion for Surface Sites

Transition and heavy metal adsorption on goethite and gibbsite with dielectric constant in the range 10 – 22 is best described by surface complexes of the metal and the indifferent BE anions. Experimental evidence of such complexes when NaNO3 is used as a BE has been reported from pressure-jump relaxation experiments with Pb; this is described by the metal adsorbed in the 0-plane and nitrate ions in the b-plane (Hayes and Leckie, 1986): 2þ ySOHz þ M2þ þ NO2 2 NO2 3 O ySOHM 3

ð1Þ

However, in the case when both NaCl and NaClO4 are used as BE, both the metal and the respective BE anion adsorbed on the 0-plane (Criscenti and Sverjensky, 1999): þ ySOH þ M2þ þ ClO2 4 O ySOHMClO4

ð2Þ

ySOH þ M2þ þ Cl2 O ySOHMClþ

ð3Þ

Adsorption of bivalent metal ions on quartz and silica with dielectric constants between 4 and 5 is best described by the metal and indifferent electrolyte anion ClO4 adsorption; when NaNO3 and NaCl BE solutions are used metal adsorption occurred as ySOH and ySOMOH. Under these conditions, the low dielectric constant of the solids results in large Born salvation free energies opposing adsorption of the BE anions (Criscenti and Sverjensky, 1999). BE anions may also compete for surface sites created by p.d.i. adsorption when BE concentration is increased. The same increase in BE concentration can

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be achieved by increasing the concentration of either one electrolyte or those of a mixture of electrolytes. In the latter case, the anions of electrolytes may compete for the newly charged sites created as a result of the p.d.i. adsorption in response to the increase in BE concentration. For example, sorption of chromate, sulfate, and selenate are affected by the background solution concentration, in this case NaNO3; especially, chromate adsorption in the low pH region is affected by the NaNO3 concentrations (Wu et al., 2000). This indicates that these ions are adsorbed in the same plane as NO3, which competes with them when BE concentration, i.e., NO3 concentration, is increased. In contrast, sorption of molybdate and selenite does not show any noticeable differences when NaNO3 concentration is increased (Wu et al., 2000). A review of experimental data on adsorption of Cd2þ, Pb2þ, Co2þ, UO2þ 2 , 2þ Zn , Cu2þ, Ba2þ, Sr2þ, and Ca2þ, on the surfaces of many soil minerals contacted with NaNO3, KNO3, NaCl, and NaClO4 solutions over a wide range of BE concentrations (0.0001 –1.0 M), revealed that transition and heavy metal adsorption as a function of BE concentration depends on the type of electrolyte (Criscenti and Sverjensky, 1999). There was little or no dependence on BE concentration when NaNO3 was used. However, when NaCl was used the metal adsorption decreased significantly with increase in the BE concentration and, when NaClO4 was used as the contacting electrolyte metal adsorption exhibited little increase with increasing IS (Criscenti and Sverjensky, 1999).

D. CHEMICAL REACTIONS AT SOLID: AQUEOUS INTERFACES IN VCS 1. Direct Probing of the Electrical Double Layer (EDL) Structure Although macroscopic experiments allow estimation of the capacitance, potentials, and binding constants appropriate to the model by fitting titration experimental data of a particular model, this approach does not allow direct determination of the structure and nature of surface complexes and the structure of the double layer (Westall and Hohl, 1980). In situ molecular-scale microprobes are needed to provide direct information on the surface complexes and structure of the EDL (Brown and Parks, 2001). Different models have been proposed to describe the distribution of ions in the solid –liquid interface (Bowden et al., 1977; Goldberg, 1992), and electrokinetic measurements provide a means to measure the surface potential at the plane of shear (Hunter, 1981; Johnson et al., 1999). However, relatively little is directly known about the molecular-scale structure of the EDL at the mineral –aqueous solution interface (Sturchio et al., 1997; Fenter et al., 2000a). This is because the microscopic significance and interpretation of the parameters from the models


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are often in question and such models suffer from lack of direct structural confirmation (Fenter et al., 2000a). In most cases, our understanding of the EDL has been hindered by a lack of quantitative molecular-scale experimental data that can be used to independently test available EDL models (Fenter et al., 2000a). Measuring the surface charge and potential, as well as the distribution of ions within the EDL, however, is a particularly challenging task. Especially challenging is the unraveling of the boundaries between the condensed and diffuse layers of the EDL and the position and distribution of ions within these two sub-layers (Fenter et al., 2000b). An additional major challenge in mineral – fluid interface studies is to relate the results from macroscopic field and laboratory measurements to molecular scale processes (Fenter et al., 2000b). Progress is being made by application of new experimental techniques, such as atomic force microscopy (AFM), and synchrotron X-ray methods that are capable of probing single-crystal solid – fluid interfaces in situ at the molecular level (Wang et al., 1992; Toney et al., 1994; Sturchio et al., 1997; Brown et al., 1999). AFM (Fenter et al., 2000c, 2001; Wang and Bard, 2001) appears to have been successfully used to probe the solid – liquid phase interface and gather direct information on surface charge (Wang and Bard, 2001), surface potential (Considine and Drummond, 2001), interactions between charged surfaces (Kekicheff et al., 1993; Swartz et al., 1997; Giesbers et al., 2002), adsorption (Kreller et al., 2002) and the distribution of ions at solid/liquid interfaces. In addition to AFM, X-ray techniques such as X-ray standing wave (XSW) (Sturchio et al., 1997; Fenter et al., 2000a) and X-ray reflectivity (Sturchio et al., 1997; Fenter et al., 2000b,c, 2001) promise a means to elucidate the structure and composition of the EDL for the following reasons (Fenter et al., 2000a): the weakly interacting nature of hard X-rays enables them to probe in situ the solid – liquid interface structure; the measurements are truly quantitative because the interaction of the X-ray with matter is well understood at a fundamental level; ˚ this technique also naturally probes over the length scales from 1– 104 A normally present in an EDL. The XSW technique was used in experiments to directly measure the EDL structure at the rutile (110) – water interface and to probe the distribution of ions near a mineral –fluid interface (Fenter et al., 2000a). It appears that this technique may be successfully used to measure the precise location of ions in the condensed sub-layer of the EDL, and the partitioning of ions between the condensed and diffuse sub-layers of the EDL (Fenter et al., 2000a). 2.

Modeling the Interfaces in VCS

Although electrokinetic techniques (Hunter, 1981; Johnson et al., 1999) may be successfully used to determine surface potential at the plane of shear,

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surface potential in different planes of adsorption is invariably difficult to measure (Schindler and Sposito, 1991). For this reason, surface chemical models that describe the structure of the electrified interface have been proposed to calculate surface potential from the surface charge measured experimentally. The surface potential values are then used to correct the conditional stability constants of surface complexation reactions as in the cases presented below. The clay fraction mineralogy of VCS is usually dominated by the quintet: kaolinite, allophane, gibbsite, goethite, and hematite (Qafoku et al., 2000b, 2003). VCS may have monophase mineralogy when a single mineral dominates the clay fraction; however, the majority of VCS have different contents and proportions of the aforementioned clay minerals. As a result, they manifest a significant diversity in their particle interactions, surface charge, particle size distribution, and specific surface areas, which makes the prediction of their behavior difficult. Nevertheless, models are being proposed and, to some extent, successfully used to predict the response of variable charge surfaces to different management strategies (Bowden et al., 1980). (a) Single Sorbent VCS Systems Dominated by One Dual-Charge Mineral (Kaolinite or Allophane): A multiple-site adsorption model may be used to describe surface complexation reactions on all reactive surfaces of kaolinite (Schindler et al., 1987). The term yMOH groups is used to represent all amphoteric surface OH groups, i.e., OH groups at the edge and the basal surfaces of the kaolinite particle, with a variable charge usually referred to as the net proton surface charge, which may act as the terminal ligands for proton equilibria and metal complexation (Wieland and Stumm, 1992). The other term, yXO groups, refers to the negatively charged sites of the siloxane layer which are involved in exchange reactions with cations in solution, such as Hþ, Naþ, Ca2þ, Mg2þ, and Al3þ, and therefore act as terminal groups for these cations. Under acidic conditions that usually exists in VCS, and in the presence of an appreciable amount of Al, the protonation/deprotonation reactions and ion exchange equilibria involving the most common ions in these systems, such as Hþ, Naþ, Ca2þ, Mg2þ, and Al3þ, may be written as follows (Wieland and Stumm, 1992): þ yMOHþ 2 O yMOH þ H

ð4Þ

yMOH O yMO2 þ Hþ

ð5Þ

yXOH þ CatðxÞ O yXOCatðx21Þ þ Hþ

ð6Þ

ayXOH þ bAl3þ O ðyXOÞa Alb ðOHÞcð3b2ðaþcÞÞþ þ ðb þ cÞHþ

ð7Þ

where Cat(x) represents all possible exchangeable cations, and a, b, and c are stoichiometric coefficients. The conditional equilibrium constants and the intrinsic


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equilibrium constants of a hypothetically neutral surface, are (Wieland and Stumm, 1992): K1 ¼

{yMOH}½H þ {MOH2þ }

K1 ¼ K1ðINTÞ eðFC=RTÞ

ð8Þ

K2 ¼

{yMO2 }½H þ {yMOH}

K2 ¼ K2ðINTÞ eðFC=RTÞ

ð9Þ

K3 ¼

{yXOCatðx21Þ }½H þ {yXOH}½CatðxÞ

ba;b;c ¼

ð10Þ

{ðXOÞa Alb ðOHÞcð3b2ðaþcÞÞ þ }½H þ ðbþcÞ {yXOH}a ½Al3þ b

ba;b;c ¼ ba;b;cðINTÞ eð3b2ðaþcÞFC=RTÞ

ð11Þ

The conditional equilibrium constants are usually corrected for the Coulombic energy of the charged surface of the soil mineral. As a result, intrinsic equilibrium constants of the hypothetical uncharged surface are calculated from the relations presented in Eqs. (8), (9) and (11). In these equations, C represents the surface potential, and F; R; and T are the Faraday’s constant, the molar gas constant and the absolute temperature, respectively. It should be noted that surface equilibria given by Eqs. (4) – (7) are valid if the following assumptions are considered (Wieland and Stumm, 1992): 1. Amphoteric surface hydroxyl groups yMOH account for the variable or net proton surface charge at the kaolinite surface. 2. Ion exchange reactions occur at permanent negatively charged surface sites yXO at the siloxane surface. 3. The concentration of the weak surface complexes yMONa and yMOAl2þ formed at the gibbsite surface and edge can be neglected under acidic conditions. In order to correct the conditional stability constants, surface chemical models are used to calculate surface potential from the surface charge measured experimentally. The simplest, self-consistent model of the diffuse-ion swarm near a planar charged surface is the modified Gouy –Chapman theory (Sposito, 1992). The basic principles of electrical double layer models are carefully reviewed in other references (Van Olphen, 1977; Carnie and Torrie, 1984). In some of these references (Carnie and Torrie, 1984) thorough comparisons of model results with those from Monte Carlo simulations which are based on statistical mechanics were made. Other most frequently used models are the constant capacitance model (Schindler et al., 1976; Stumm et al., 1976, 1980), diffuse layer model (Stumm et al., 1970; Dzombak and Morel, 1990), and triple layer model (Davis et al., 1978).

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For a review of these models and their applications to soils the reader is referred to other references (Goldberg, 1992). The single-layer and multiple-layer models differ in their perception of how DGADS (see below) is split into DGINT and DGCOUL (Schindler and Sposito, 1991). The relationship between surface charge and surface potential in one of the most popular models, namely constant capacitance model, is given by the following expression (Wieland and Stumm, 1992):

s¼C£C

ð12Þ

or Q ¼ ðs=FÞ £ s ¼ ðs £ C=FÞ £ C

ð13Þ

where s is the specific surface area (m2 kg21) and C is the integral capacitance of the flat double-layer which is usually treated as an adjustable parameter during calculations. Although none of the models in the literature may be used as a substitute for experimental data (Pochard et al., 2002), it would be interesting to test such models against more demanding data sets, e.g., involving surface-charging behavior at different IS (Kosmulski, 2002), or during particle – particle interactions (Qafoku and Sumner, 2002). In addition, recent studies have concluded that one cannot obtain an adequate estimate of the diffuse double-layer charge via Gouy – Chapman –Stern (GCS) theory (Wang and Bard, 2001). The failure of the classical GCS theory to describe the electrical double layer is probably because it does not account for the ion correlation and ion condensation effects at surfaces. Ion condensation, which occurs when a fraction of excess counterions remains in the close proximity to the charged surface of particle, even if the solution in which it is suspended becomes infinitely dilute (Sposito, 1992), may also be common in VCS. More on counterion binding and ion condensation theory can be found in the following references (Manning, 1979; Groot, 1991). (b) Systems Dominated by Metal Oxides: The surface ionization reactions responsible for the amphoteric behavior of metal oxide surfaces are given by the reactions (4) and (5). The conditional equilibrium constants and the intrinsic equilibrium constants of a hypothetically neutral surface, are given by expressions (8) and (9) (Dzombak and Morel, 1990; Wieland and Stumm, 1992). Finding the right values for the equilibrium constants for surface group protonation and deprotonation reactions is very important when modeling the surface complexation reactions of other aqueous species with reactive surface groups. For this reason, attempts have been made in the CD-MuSiC model to calculate proton affinity of individual surface groups on oxide surfaces based on the under-saturation of the surface oxygen valence (Hiemstra et al., 1996; Rietra et al., 1999).


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The equilibrium constant for the surface protonation reactions can also be expressed in terms of the inverse of the dielectric constant of the solid and an average Pauling bond strength per angstrom for the solid (Sverjensky and Sahai, 1996). Each individual oxide or silicate mineral should have its own unique surface characteristics, depending on bonding in the bulk crystal structure connected to the surface. Therefore, bonding in surface protonated species is probably far more analogous to that in the bulk crystal structure than to bonding in protonated aqueous species (Sverjensky and Sahai, 1996). (c) Multiple Sorbent Systems: Much of the knowledge on the reactivity and behavior of colloids and/or nanoparticles is derived from extensive experimentation with monophase model systems. Although these investigations have significantly increased our understanding of the physical and chemical properties of individual colloids, this information unfortunately, cannot be readily extrapolated to complex colloidal assemblages such as soils. The surface charging mechanisms operative in complex mineral assemblages cannot be predicted based on the bulk mineralogy or by considering surface reactivity of less abundant mineral phases based on results from model systems (Bertsch and Seaman, 1999). In addition, the reactivity of surface functional groups and their charging mechanisms operative in complex assemblages of colloids and nanoparticles cannot be adequately predicted by considering individually the phases that are present in the system. The interactions between charged micro- and nano-scale colloidal particles in aqueous electrolyte solutions are important in many areas, particularly in colloid and soil science. Emphasis has been placed recently on the role of colloids in facilitating contaminant transport (McCarthy and Zachara, 1989). The electrostatic interactions between oppositely charged surfaces primarily control the formation of microaggregates and coagulation in a mixed charge colloidal system. For highly charged surfaces, such as soil clays, electrostatic interactions govern phase equilibria in the system. They also control the extent of such important phenomena as ionic adsorption and colloidal mobility and transport in porous media. Few studies have been published on the colloid surface chemistry of VCS (Chorover and Sposito, 1995) and the effect of particle interactions on adsorption is not well understood (Qafoku and Sumner, 2002). The behavior of like particles in aqueous solutions is well described by the DLVO (Derjaguin –Landau – Verwey – Overbeek) theory, although some researchers claim that this theory hypothesizes strictly repulsive long-range interactions among like-charged particles but the long-range Coulombic attractive force among like particles cannot be explained quantitatively or qualitatively by this theory (McBride and Baveye, 2002). The interactions among particles of different types and the effect they might have on adsorption are not well studied and understood. In addition, application of the SC concept to adsorption of ions by soils and sediments are relatively rare due to the complexity of natural systems

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(Davis et al., 1988). Quantification of Coulombic correction factors for the electrical double layer on the surfaces of particles is equally complex (Davis et al., 1988). Interacting double layers of heterogeneous particles (Prieve and Ruckenstein, 1978), the formation of surface coatings and the competitive adsorption of many different ions and species cause significant changes in the electrical properties of mineral –water interfaces (Davis et al., 1988). Interactions among like particles are common in VCS and: “…in fact, kaolinite could even adsorb itself (by edge-face attraction)” (Thomas, 1977). The zwitterionic nature of kaolinite makes its aggregation behavior complicated (Aurell and Wistrom, 2000) because the edge and plane may carry a net charge of opposite sign at acid pH, which may promote aggregation through edge-to-face associations of different kaolinite particles (Van Olphen, 1977; Frenkel et al., 1978). This electrostatic edge-to-face interaction is not observed at solution pH values greater than 7.8 (Aurell and Wistrom, 2000). The edge-to-face interactions may depend on the BE concentration of the contacting solution. The Poisson –Boltzmann equation is solved for a thin cylindrical disk shape smectite particle with a positive change on edges and a negative charge on faces of the particles (Secor and Radke, 1985). For low BE concentrations the negative electrostatic field emanating from the particle face spills over into the edge region; as a result, the positive charge edge exhibits a negative electrostatic field which results in a repulsive electrostatic potential for interparticle edge-face interactions and for solution anion-particle edge interactions (Secor and Radke, 1985). Another possible phenomenon in colloidal suspensions is the counterionmediated attraction between like particles (Ise, 1999; Ise et al., 1999), which is quite possible in VCS as well. Interactions among unlike particles also appear to be common in VCS. Schofield was the first to propose that acid soils contain two distinct materials on which electrical charges are carried (Schofield, 1949). These are Fe and Al oxides that may carry positive surface charge and clay particles that may carry permanent negative charge (Schofield, 1949). Variation in soil positive and negative charge magnitude with pH was studied initially in 1965 (Sumner and Davidtz, 1965). In natural systems, the arrangement of the nano- and microscale sized particles into microaggregates influences the character of charge manifested by the soil particle assemblages. Small quantities of Fe oxides (, 4% by mass) were acting as surface coatings on microsize quartz particles, shifting their PZNC from below 3 to approximately 8.1, a value which is similar to that observed in pure Fe oxides systems (Hendershot and Lavkulich, 1983). (d) Particle Interaction Effect on Surface Charge and Adsorption: The complex nature of electrostatic interactions between oppositely charged particles has hampered the development of models to describe and represent the behavior of surface reactive groups in mixed charge colloidal systems. For this reason


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the interactions among oppositely charged surfaces and the subsequent effect of these interactions on the reactivity of surface groups have not been comprehensively covered in the literature. Under acidic conditions, the ditrigonal cavities of the phyllosilicate siloxane surfaces may react individually or collectively not only with positively charged ions and inorganic or organic hydroxyl-polymers (Sposito, 1984), but also with clusters or nanoparticles of oxides which may coat the phyllosilicate siloxane surfaces. The degree of interactions between oppositely charged surfaces will strongly depend on pH, IS and the interfacial concentration of inorganic or organic ions of the bathing electrolyte solution. It is quite likely that the extent of ionic adsorption will depend on the degree of interactions between the solid surfaces that are present in these systems. In addition, the oxide nanoparticle mobility and transport will also depend on the degree of interaction among different surfaces, which in turn depend on pH, IS and composition of the bathing solution. Studies have indicated that in Fe-chemistry-dominated soils and sediments, a chemical perturbation, such as a plume of organic ligands, is likely to induce Fe colloid release initially via electrostatic repulsion (Liang et al., 2000). Metal oxides, such as Fe or Al oxides, may be: 1. Chemically bonded to Si-oxide surfaces such that only attack on the bonds by a suitable ligand or a proton could free the Fe-oxide particle, or 2. held in a weaker manner to the surface through interparticle forces, e.g., in a shallow energy well, so that bringing higher negative charge density onto the Fe oxide could impart repulsive energy, freeing the particle (Liang et al., 2000). In the first case, when a positively charged metal (Fe) oxide colloid is attached to the negatively charged quartz surface through a chemical bond (ySi – O –Fey), ligand adsorption on the Fe oxide via surface complexation induces overall surface charge reversal on Fe oxide surfaces and promotes bond breaking leading to Fe oxide colloid mobilization. In the case when the Fe oxide colloid is attached to the surface through surface interaction energy, anion adsorption via ligand exchange on Fe oxide induces again surface charge reversal from positive to negative increasing the repulsive force and promoting colloid mobilization (Liang et al., 2000). Contact solution pH and IS control the degree of interactions between oppositely charged particles and, for this reason, they also control the extent of ionic adsorption, the colloidal stability and nanoparticle mobility in a mixed charge colloidal system. Contrary to mono-charge colloidal systems, mixed charge colloidal systems are characterized by the presence of micro- and nano-scale colloids with net opposite charges on their surfaces. These colloidal systems will probably become stable as pH of the contacting electrolyte solution increases.

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Because the PZNPC of variable charge nano-colloids (i.e., oxides) is at slightly basic pH values, their amphoteric surfaces will have a net neutral or negative charge at circum-neutral and basic pH. On the other hand, the negative charge on phyllosilicate surfaces is pH-independent. Electrostatic repulsion between like-charge particles will most likely stabilize the colloidal system under these conditions. This will invariably affect the extent of adsorption of inorganic or organic solutes (contaminants, radionuclides, etc.) and particle mobility and transport. At constant pH, IS controls the magnitude of the surface charge of amphoteric (variable charge) surfaces. When pH is acidic, an increase in the contact solution IS will increase the positive charge density of variable charge surfaces. The degree of binding of phyllosilicate particles with nanometer-scale colloids of metal oxides which coat their surfaces will most likely decrease, affecting the system stability and probably, the extent of ionic adsorption. On the other hand, when IS decreases a bond linkage between phyllosilicate and oxide surfaces are promoted. In this case, the particle –particle interactions will be not solely electrostatic. Ionic composition of the bathing solution may also control the colloidal stability in a mixed charge system. Ions with a high energy of adsorption and affinity for phyllosilicate or oxide surface sites may stabilize an unstable mixed charge colloidal system, mobilizing oxide nanoparticles. Ions of the bathing electrolyte solution will be adsorbed on the respective opposite charge sites on the surfaces of phyllosilicate and oxides thus decreasing the electrostatic attraction between particles. A very dense layer of counterions is usually built immediately next to the surface which may induce an electrostatic repulsive effect on the “adsorbed” nanoparticle, increasing their mobility and potential for transport. Interactions between phyllosilicates and oxides in a mixed charge system depend on the type of the phyllosilicate mineral. When isomorphic substitution of Al3þ by Fe2þ and Mg2þ occurs in the octahedral sheet, the resulting excess negative charge can distribute itself (principally) over the 10 surface oxygen atoms of the four tetrahedra that are associated through their apexes with a single octahedron in the layer (Sposito, 1984). This distribution of negative charge enhances the Lewis base character of the ditrigonal cavity and makes it possible to form complexes with cations as well as with dipolar molecules. Consequently, sorbed ions are more likely to form outer-sphere complexes, and oxides will be loosely “sorbed”. On the other hand, if isomorphic substitutions of Si4þ with Al3þ occur in the tetrahedral sheet, excess negative charge can distribute itself primarily over just the three surface oxygen atoms of one tetrahedron, and, because of this localization of charge, much stronger complexes with cations (inner-sphere complexes) and oxide nanoparticles is possible. It is quite likely that in the acid variable charge subsoils from the humid regions of southeastern US the surface charge on negatively and positively


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charged soil surfaces and particles is not equal to the counter-ion charge, i.e., the sum of the charges of individual ions adsorbed as outer-sphere complexes or in the diffuse layers, under conditions of very low BE concentrations in the soil solution (Qafoku and Sumner, 2002). In order to describe the adsorption of BE indifferent ions and to explain how the particle charges on soil surfaces would be balanced under these conditions, a mechanism based on particle – particle interactions was proposed. It is quite possible, however, that other mechanisms may operate to balance the surface charge under different conditions (Wada, 1984; Schulthess and Sparks, 1988). The proposed mechanism is likely to operate in variable charge subsoils from southeastern United States, with clay-fraction mineralogy dominated by kaolinite and Al/Fe oxides. These HWS that have apparently reached the “advanced stage” of the Jackson –Sherman weathering sequence, are characterized by the removal of Na, K, Ca, Mg, Fe(II) and the presence of Fe oxides and Al-hydroxy polymers (Jackson and Sherman, 1953; Jackson, 1965; Gillman and Bell, 1978; Sposito, 1989; Seaman et al., 1995). The Fe and Al oxides most likely coat the clay particles. The long-range electrical forces appear to keep the particles together in very stable aggregates, and dispersion is usually not observed even when they are leached over an extended period with DI-water. The small particle sizes of Fe and Al oxides, which are the end products of the long weathering process in the humid climate of the southeastern US, appear to have never really collapsed on the clay particles. The extremely small, almost massless but very reactive individual particles or polymers with polycation-like structures seem to preserve their identities, i.e., they may be separated from the clay surfaces under the effect of strong deflocculating chemical agents. The schematic presentation of this reality in simple and generalized terms is presented in Fig. 1. The point of zero charge (PZC) of kaolinite is between 2.8 and 2.9, while that of Al/Fe oxides is between 8 and 9. The negative surface charge on the cleavage faces of kaolinite (Fig. 1a) is caused by the isomorphic substitutions in the crystal lattice (Hunter, 1993). The positive charges on the surfaces of Fe/Al oxides, is a result of protonation and deprotonation of hydroxyl groups on the surfaces of the colloids. The positive charge developed on the kaolinite particles edges is usually balanced by a portion of the negative charge on surfaces of other kaolinite particles when they are arranged in the card-house structure (Hunter, 1993). As a result, kaolinite particles have surface excess negative charge and Fe and Al oxides have a net positive surface charge at pH 4 to 6, which may be balanced by counter-ions present in the soil solution (Fig. 1a). Intensive leaching promotes the dilution of the soil solution. The ions in the double layers are likely to diffuse into the soil solution and oppositely charged double layers may expand and overlap with one another (Fig. 1b). The spatial separation of negatively charged silicate and positively charged sesquioxides is likely to facilitate mutual particle charge neutralization. Under such conditions, the ions in the overlapping regions of the diffuse double layers are no longer

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Figure 1 (a) Interactions among positively charged Fe oxides and negatively charged phyllosilicates in Fe-rich soils. (b) Interactions among positively charged Fe oxides and negatively charged phyllosilicates in Fe-rich soils. (c) Interactions among positively charged Fe oxides and negatively charged phyllosilicates in Fe-rich soils. (d) Interactions among positively charged Fe oxides and negatively charged phyllosilicates in Fe-rich soils.


Figure 1

(Continued)

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needed to balance the respective particle charges, so that they are free to leave the system (Fig. 1c). This may cause the double layer thickness to further increase with even greater mutual neutralization of the particle charge on the surfaces of oppositely charged particles. As a result, the magnitude of the counter-ion charge decreases further (Fig. 1d). When an indifferent electrolyte is added to such extremely leached subsoil, the reverse phenomenon may occur, that is cations and anions of the added electrolyte salt may be depleted from the soil solution because they may be adsorbed into the respective oppositely charged diffuse layers while compressing them. The interpenetration or overlapping of the double layers around the positively charged Fe/Al oxides and negatively charged silicate minerals, and resultant mutual neutralization of positive and negative charge in VCS is not a new concept in the literature. It has been successfully used to interpret experimental data from studies conducted over the last 37 years with VCS and subsoils (Sumner, 1963b,a; Sumner and Davidtz, 1965; Singh and Kanehiro, 1969; Reeve and Sumner, 1971; Barber and Rowell, 1972; Ji, 1997; Ji and Li, 1997; Zhang and Zhao, 1997; Qafoku et al., 2000a). However, from recent studies it appears that overlapping of diffuse layers on oppositely charged soil particles and the salt adsorption phenomenon observed frequently in VCS and subsoils are related to one another (Qafoku and Sumner, 2002). The magnitude of salt adsorption is greater in leached acid subsoils and quite possibly, salt adsorption of indifferent electrolytes is caused by the simultaneous adsorption of their ions in oppositely charged diffuse layers, when they compress in response to the increase in BE concentration of the soil solution. The association of phyllosilicate and Fe oxides particles is clearly presented in the SEM micrographs taken in some HWS (Fig. 2). In addition, it is quite interesting that in the subsoil with the smallest salt adsorption magnitude from New Caledonia, the surface of a kaolinitic particle is clean of Fe oxides (Fig. 3). Other evidence from the literature supports the overlapping mechanism and relates it to the salt adsorption phenomenon in VCS. The concentration of salts in the soil solution remained rather low even when salt was added because the soil acted both as a cation-exchanger and as a salt-sorber (Thomas, 1960). Even two alcohol washings (10 ml) were sufficient to cause a severe drop in the measured positive and negative charges in equivalent amounts (Sumner, 1963a). Some soils from Australia were dominated by variable charge components and at soil pH contained sufficient positive charge to reduce exchangeable cations to near zero, despite the presence of soil minerals with permanent surface charge (Gillman, 1984). Allophanic soils from Japan adsorbed significant quantities of Naþ and Cl2, but neither aluminum hydroxide nor silica alone exhibited any salt sorption behavior (Wada, 1984). This strongly suggests that salt adsorption occurs only when two oppositely charged solid phases are present. Salt adsorption was more frequently observed in soils with a low or very low soil solution concentration and the magnitude depends strongly on the initial IS of


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Figure 2 The association of phyllosilicate and Fe and/or Al oxides in some HWS from: A. Australia, B. Brazil, C. Southeastern USA.

the soil or subsoil solution (Wada, 1984; Pearse and Sumner, 1997). The depletion of the added salt from the soil solution was observed in many subsoils collected from Georgia and other tropical and subtropical regions (Qafoku and Sumner, 2001). The magnitude of salt adsorption was larger in subsoils where both, kaolinite and Al/Fe oxides were present in appreciable amounts, which indicates that this phenomenon occurs when two types of oppositely charged colloids are present (Qafoku and Sumner, 2001). An L-type NO2 3 isotherm was observed in the Cecil subsoil at low IS suggesting that more than one mechanisms may be responsible for NO3 sorption at low concentrations in variable charge

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Figure 3 TEM micrographs of a kaolinite particle (A– D) and next to it, an Fe-rich microaggregate (E) in a variable charge subsoil from New Caledonia.

subsoils (Qafoku et al., 2000a). Other discussions on the surface charge, electrical potential and overlapping may be found in other references (Xin et al., 2000; Alkafeef et al., 2001). (e) Surface Effective Charge in Mixed Sorbent Systems: The ionic adsorption potential can be expressed as a contribution to the Gibbs free energy of adsorption (Brown and Parks, 2001). For each counter-ion or co-ion the contribution of each


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component to the free energy of adsorption (DGADS) is (Bowden et al., 1977; Hunter, 1987; Lyklema, 1991): DGADS ¼ DGCOUL þ DGCHEM þ DGSOLVATION

ð14Þ

where DGCOUL is the free energy associated with the long-range coulombic or eletrostatic interaction at the location where the ion is adsorbed, DGCHEM is the free energy associated with formation of a chemical bond, such as the covalent bond, between the ion and the reactive surface group, and DGSOLVATION is the free energy associated with solvation (Brown and Parks, 2001). The first component in expression 14 is the coulombic component (DGCOUL) which simply represent the electrostatic interaction between a point charge and an electric field; it depends only on the sorbent’s charge; if this is the only component of the adsorption free energy of an ion, then this ion will only adsorb on charged surfaces; ions of like charge should adsorb in proportion to their activities in solutions. This component of the free energy of adsorption is equal to (Schindler and Sposito, 1991): DGCOUL ¼ zFC

ð15Þ

Therefore, DGCOUL is defined as the energy required to bring a charge of zF Coulombs from the solution to a surface site of potential C (Schindler and Sposito, 1991). The second chemical component (DGCHEM) which can be positive, negative or zero, describes the specific interaction of the ion with the surface; the binding forces have their origin in the electronic nature of the sorbate and sorbent and are composed of coordination, Van der Waals and polarization forces. Ions with a large DGCHEM component can adsorb on uncharged surfaces and, if the DGCHEM component is sufficiently large, they may sorb against the electrostatic forces of repulsion that operate on like charge surfaces. The third component, DGSOLVATION is the free energy associated with solvation, which is a function of the charge and radius of solvated ion, and the dielectric constant of water in the interfacial region of the EDL (Brown and Parks, 2001). Some progress has been made recently towards an understanding of how the magnitude of the components of the free energy of adsorption changes in mixed sorbent systems. For example, the behavior of binary systems has been studied in a few recent publications (Anderson and Benjamin, 1990b,a; Meng and Letterman, 1993). However, many questions remain, including: † Do particle interactions in a mixed sorbent system affect the magnitude of the surface potential (and charge) on the respective individual sorbent surfaces? † To what degree do particle interactions affect the extent of ionic adsorption of ions with different DGCHEM?

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† Is the value of the dielectric constant of water in the overlapping region of the double layers different from that in the double layers when overlapping does not occur? † Does ion condensation occur in VCS and to what extent? † Does ion condensation affect the extent of ionic adsorption? † How many of the surface reactive sites on soil minerals become non reactive as a result of opposite charge particle interactions? † Can Al/Fe oxide nanoparticles, which are the end products of the weathering process in VCS, compete for surface adsorption sites with aqueous ions? † Is the extent of ionic adsorption affected by this competition? † How much and under what conditions is the extent of ionic adsorption affected by particle – particle interactions? † Is the charging of variable charge surfaces in response to changes in pH and IS affected by particle –particle interactions and ion condensation? † Is it possible to model these systems and predict the extent of ionic adsorption under different conditions of pH and IS? † Is it possible to develop an adsorption model to account for all possible phenomena that may simultaneously or sequentially occur in VCS? In these soil systems where particle interactions may play a predominant role in refining the chemical properties of the bulk soil, the general approach should be to develop a model to express the surface effective charge in terms of the amount of ions adsorbed and not in terms of the amount of surface reactive groups, i.e., the surface charge density. The following equation describes the net total surface charge of an individual particle (sP) (Sposito, 1984):

sP ¼ s0 þ sH þ sIN þ sOS

ð16Þ

where s0, sH, sIN, and sOS, are permanent structural charge, the net proton charge, inner-sphere complex charge, and outer-sphere complex charge, respectively. The arithmetic addition operator (þ ) does not represent the sign of the charge components in Eq. (13). Because the permanent structural charge is usually negative, and the other components of the equation of surface charge may be negative or positive, a more precise algebraic formulation of Eq. (16) would be: ð^ÞsP ¼ ð2Þs0 þ ð^ÞsH þ ð^ÞsIN þ ð^ÞsOS

ð17Þ

The net total surface charge of an individual particle is balanced by the diffuseion swarm charge (sD): ð^ÞsP ¼ ð^ÞsD

ð18Þ

where sD should be equal in magnitude and opposite in sign to sP. However, the magnitude of the surface charge components in Eq. (16) and that of sD in


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Eq. (18) might not be the same in binary or multiple colloidal systems because of particle –particle interactions. It is quite likely that the diffuse-ion charge may have a smaller magnitude than the particle charge (Barber and Rowell, 1972; Qafoku and Sumner, 2002). In addition, results from other studies (Anderson and Benjamin, 1990b,a; Meng and Letterman, 1993) have shown that particle interactions caused changes in particle size distribution, surface charge, and adsorption characteristics in binary systems of Al or Fe, and Si oxides. Even the assumption made to derive the principal equation of the double layer theory (Hunter, 1993) that the total charge, per unit area of surface, in the diffuse layer is obtained by summing the volume charge density through the whole region from distance 0 to 1, does not hold true in binary or multiple colloidal systems. Definitely, much more research is needed in this area in order to increase our understanding of these multiple colloidal systems.

IV.

THE MANAGEMENT OF VARIABLE CHARGE SOILS

Highly weathered VCS pose a particular challenge to resource managers in view of the low values of exchangeable basic cations, acidic reaction, and their ability to adsorb and fix anionic species (Gillman and Sumpter, 1986). In their natural state, these soils often maintain highly productive and diverse ecosystems that are dependent on efficient resource utilization. A characteristic of these systems is their reliance on soil organic matter (SOM) to cycle nutrients from the soil through the plant and hence back to the soil through plant debris. Soil organic matter (SOM) effectively acts as a slow release nutrient delivery system that mediates the cycling of nutrients and chemical attributes of soils. However, when these ecosystems are disturbed through continuous cultivation, the productivity of many strongly weathered variable charged soils often declines rapidly due to a loss in SOM (Kang and Juo, 1986; Aweto et al., 1992; Willett, 1995), accelerated soil acidification (Gillman et al., 1985; Plamondon et al., 1991) and a reduction in the CEC thereby limiting the ability of the soil to hold nutrients such as Ca2þ, Mg2þ, and Kþ, which are rapidly lost through leaching. In addition, physical changes occur that are manifest in the development of surface crusts and accelerated soil loss through erosion (Kooistra et al., 1990; Van der Watt and Valentin, 1992). Hence, sustainable management of VCS is contingent on effectively manipulating soil attributes that influence surface charge characteristics. The following section briefly highlights soil chemical degradation associated with changed land use and outlines selected management strategies to overcome these constraints.

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A. CHEMICAL DEGRADATION

OF


Changes in SOM, CEC and cation depletion associated with changed management of variable charged soils that are dominated by low-activity clays and iron and aluminum oxides significantly influences the productive potential. Quantification of these changes is succinctly demonstrated when comparing the properties of an Oxisol cleared of climax rain forest 53 years previously and currently under tea production in north Queensland (Noble et al., 2001). Soil pH declined by approximately 0.3– 0.6 units irrespective of depth, from that of the undisturbed forest (Table III). This decline in soil pH is in part attributed to the acidifying effects of nitrogenous fertilizers used in the growing of crops and the increased mineralization of soil organic matter associated with land clearing (Rowell and Wild, 1985; Aweto et al., 1992). Declines in exchangeable basic cations associated with crop export and leaching is clearly evident (Table III). The loss of

Table III Mean (Standard Error of the Mean in Parentheses) for pH, Exchangeable Cations, Exchangeable Acidity, Effective Cation-exchange Capacity (ECEC), and Organic Carbon (OC) for Selected Depth Intervals for Soil Collected from a Climax Tropical Forest Site and Tea Sites in North Queensland (Noble et al., 2001) Depth(cm) Characteristic

Site

pHw

Forest Tea Forest Tea Forest Tea Forest Tea Forest Tea Forest Tea Forest Tea Forest Tea

Ca2þ (cmolc/kg) Mg2þ (cmolc/kg) Kþ(cmolc/kg) Naþ (cmolc/kg) Al3þHþ (cmolc/kg) ECEC (cmolc/kg) OC (mg/g)

0–10

10–20

20–30

30– 50

50–70

5.26(0.05) 4.98(0.04) 1.35(0.38) 0.24(0.03) 1.02.02(0.15) 0.17(0.02) 0.23(0.02) 0.26(0.06) 0.09(0.002) 0.04(0.005) 0.25(0.01) 0.15(0.02) 2.94(0.54) 0.85(0.10) 66.2(2.6) 35.4(1.0)

5.26(0.04) 4.63(0.06) 0.49(0.16) 0.05(0.01) 0.48(0.10) 0.06(0.01) 0.16(0.01) 0.06(0.01) 0.06(0.007) 0.05(0.006) 0.14(0.03) 0.14(0.02) 1.32(0.29) 0.36(0.02) 48.8(3.9) 31.2(1.3)

5.25(0.04) 4.61(0.04) 0.22(0.05) 0.04(0.01) 0.22(0.05) 0.04(0.003) 0.08(0.01) 0.04(0.01) 0.04(0.003) 0.03(0.004) 0.10(0.03) 0.01(0.006) 0.69(0.13) 0.17(0.01) 33.8(3.8) 23.8(1.2)

5.24(0.06) 4.67(0.06) 0.09(0.02) 0.03(0.01) 0.09(0.03) 0.02(0.003) 0.03(0.01) 0.03(0.02) 0.02(0.002) 0.03(0.004) 0.08(0.02) 0.01(0.005) 0.32(0.06) 0.12(0.02) 21.0(0.9) 15.6(0.5)

5.24(0.06) 4.75(0.07) 0.05(0.01) 0.02(0.01) 0.04(0.01) 0.01(0.003) 0.01(0.002) 0.03(0.01) 0.01(0.001) 0.03(0.003) 0.04(0.02) 0.02(0.01) 0.16(0.03) 0.11(0.02) 15.6(0.9) 12.2(0.7)


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soil organic carbon from the tea site amounted to an equivalent of 58.1 t ha21 over a 0– 20 cm depth (Table III). This dramatic decline in soil organic carbon had a significant impact on the soils ability to retain cations and hence the inherent fertility of the disturbed site as evident in the charge fingerprints from each of the sites for the 0 – 10 cm depth interval (Fig. 4). However, with depth, differences between the disturbed and undisturbed systems declined so that at 50 cm there were no differences between systems (Fig. 4). In addition, low CEC in the subsoil of variable charged soils will limit crop root development making plants incapable of using subsoil moisture during drought periods (Sumner, 1995a; Paul et al., 2003). On the other hand, these soils develop appreciable anion exchange capacity (AEC) under acidic conditions, which retain otherwise leachable anions such as nitrate and sulfate particularly in subsoils (Wong et al., 1990). Studies have shown that adsorption of low affinity cations, such as Ca, reduced surface charge and even resulted in charge reversal (Bolan et al., 1999). Due to these intrinsic characteristics, surface charge properties are of central importance in the management of VCS.

B. MANAGEMENT

OF

VARIABLE CHARGED SOILS

Of importance in the management of VCS is the ability to manipulate the surface charge characteristics in order to control the retention of cations and anions. Since variable charge within soils is predominantly depended on the pH of the soil solution, treatment of soils with amendments has frequently been used to control the reactions of nutrient ions and toxic heavy metals (Bolan et al., 1999). In addition, the application of electrically charged materials such as exchange resins, permanently charged clays, silicate materials and organic matter will increase the retention of cations and anions in soils thereby enhancing the productive potential of these often degraded soils.

1.

Managing Soil pH

Soil acidity causes detrimental effects to both plants and soil organisms that are important for various mediated soil reactions (Robson and Abbott, 1989). In excessively acidic soils (pH , 4) the growth of most plant species of agronomic significance are drastically reduced. Soil microbiological activities are drastically reduced, resulting in the inhibition of biological nitrogen fixation, by legumes and decomposition of organic matter (Bolan et al., 2003).

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Figure 4 Charge fingerprints for the 0–10 cm (a), 20–30 cm (b) and 50–70 cm (c) of soils collected from a tea () and adjacent climax tropical rain forest (B) collected from north Queensland. CECT is represented by the dotted lines and CECB by the solid lines (from Noble et al., 2001).


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The application of liming materials is the most common management practice used to neutralize acidity and increasing pH thereby influencing the surface charge properties of variable charged components in the soil (Barrow, 1984; Mora and Barrow, 1996). An increase in pH increases the net negative charge (CEC) and a decrease in pH increases the net positive charge (AEC). In addition, increasing soil pH have been shown to reduce phytotoxic levels of exchangeable 22 acidity (Al3þ), decrease the retention of anions (e.g. SO22 4 ) and HPO4 (Marsh et al., 1987; Bolan et al., 1988; Naidu et al., 1990) and increase the ability of soils to retain nutrient ions and potential toxic heavy metals (Adams, 1984; Alloway and Jackson, 1991; Helmke and Naidu, 1996). Most plants grow well within a pH range of 5.5 – 6.5 and therefore a liming program should be aimed at maintaining the pH in this range (Bolan et al., 2003; Paul et al., 2003). However, in order to increase the soil pH to 6 or above, as is often advocated in permanently charged temperate soils, large inputs of lime are required which is inefficient because of the high buffering capacity in these soils and may result in micronutrient deficiencies. By maintaining these soils at a pH of 5.5 phytotoxic Al is eliminated from the exchange complex and a significant amount of negative charge is generated (Noble et al., 2000; Noble and Hurney, 2000). Therefore it is of practical importance to maintain the pH of VCS at levels sufficiently high to precipitate aluminium and to increase CEC especially in Ultisols of the humid tropics that contain 2:1 clay minerals. Andisols are generally characterized by low amounts of exchangeable Al and over-liming them commonly results in Mn and Zn deficiencies. When applying management techniques that aim at changing the pH of the soil an increase in the CEC of soils occurs with a corresponding decrease in AEC. An increase in CEC would help agricultural production, but the corresponding decrease in AEC would decrease the capacity of soils, especially subsoils, to retain contaminant anions such as nitrate. There are a range of liming materials that are available for agricultural use. These include calcite (CaCO3), burnt lime (CaO), slaked lime (Ca(OH)2), dolomite (CaMg(CO3)2) and slag (CaSiO3). The amount of liming material required to rectify soil acidity depends on the neutralizing value of the liming material and the pH buffering capacity of the soil. The potential value of other Ca-containing compounds in overcoming problems associated with acidification has been assessed (Dick et al., 2000). These materials include phosphate rock, fluidized gas gypsum, fluidized bed boiler ash, fly ash and lime stabilized organic composts. In addition, the application of basic rock dust acts as both a liming material and slow release source of Ca and Mg (Gillman, 1980; Gillman et al., 2001). Frequent regular applications of lime are advocated to achieve maximum productivity on highly weathered VCS (Noble and Hurney, 2000).

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2. Organic Matter Management Soil organic matter represents a key indicator of soil quality, both for agricultural (i.e. productivity and economic returns) and environmental functions (i.e. carbon sequestration). Organic matter, and the biological activity that it generates, have a major influence on the physical and chemical properties of variable charged soils. Soil organic matter occupies numerous functional roles within ecosystems ranging in scale from the molecular such as complexation of otherwise toxic cations in the soil solution, to global, where soils serve as an important sources, sinks and buffers of greenhouse gasses (Woomer et al., 1998). The CEC and amounts of nutrients stored in highly weathered and volcanic ash topsoils are mainly related to the SOM content. Soil organic matter content decreases progressively with time in these soils and the loss of organic matter through oxidation or erosion occurs especially during prolonged cropping. This reduces the ability to supply nitrogen, phosphorus and sulfur and to retain cations in exchangeable form (Van Ranst, 1995). Agricultural practices aiming at increasing SOM content and decreasing SOM removal through erosion are therefore important. However, under humid tropical conditions increasing soil organic matter and maintaining it is problematic as it is rapidly mineralized. Converting a continuous sugarcane cropping system to a 6 year pasture ley resulted in an increase in total soil organic carbon from 19.9 t/ha under the continuous cane to 34.6 t/ha under the pasture ley over the 0– 10 cm depth interval, indicating a 14.7 t/ha difference in total organic C between the systems over this period (Noble et al., 2003a). Concomitant with this increase in organic carbon there was a corresponding increase in surface charge characteristics (Fig. 5). Increase in crop biomass through the introduction of new varieties as well as through agronomic management, such as nutrient management (nitrogen management) and crop rotations can significantly increase organic inputs to soils. Implementation of conservation agriculture, zero tillage and crop residue management on VCS will increase SOM and reduce losses associated with mineralization (Lal, 1997).

3.

Phosphate, Silicate and Addition of Permanently Charged Clays to Variable Charged Soils

22 The application of specifically adsorbed anions such as HPO22 4 and SiO4 has been used to increase the CEC of variable charged soils (Noble et al., 2003b). The reduced HPO22 sorption in a Typic Gibbsihumox (Fox, application of SiO22 4 4 1978). Other researchers (Wann and Uehara, 1978) suggested that the application of HPO22 4 fertilizers added to soils not only increases the nutritional component of the soil but in addition increases the CEC of VCS. This is associated with a shift in the PZC due to a decline in pH (Hingston et al., 1972; Wann and Uehara,


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Figure 5 Changes in surface charge characteristics associated with the establishment of a pasture ley system with respect to a continuous sugarcane cropping systems for the (a) 0 –10 cm and (b) 10– 20 cm depth intervals (Noble et al., 2003a,b).

1978), neutralization of positive charge (Hingston et al., 1972), and electrolyte inhibition (Thomas, 1960). Although P fertilizer application has been proposed as a management tool to increase the CEC of variable charged soils, large quantities of fertilizer are required to cause a significant increase in CEC (Bolan et al., 1999).

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Figure 6 Effect of Ca-silicate additions on charge capacity in the top 0 –10 cm of an Oxisol from north Queensland 12 months after application [modified from Noble et al. (2003b)].

Figure 7 Surface charge characteristics of an Oxisol after the addition of varying rates of bentonite (Noble et al., 2002).


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The application of Ca –silicate slags and calc-alkaline pyroclastic materials added to HWS have shown that the negative surface charge may increase in these soils (Van Ranst, 1995; Fiantis et al., 2002; Noble et al., 2003b). In the latter case this is associated with (1) a breakdown of bonds in silicates; (2) hydrolysis of Si – O2; (3) adsorption of silicate anions on positively charged sites with a possible decrease of the overall PZNPC (Van Ranst, 1995). The application of relatively small amounts of Ca-silicate slag increased the CEC at pH 5.5 of a degraded Oxisol from 2.57 to 4.33 cmolc kg21 2 years after treatment (Fig. 6). In addition, significant increases in the production of sugarcane production were achieved that in part was associated with elevated Si levels (Noble et al., 2003b). This approach may be a viable and inexpensive method of increasing the CEC of degraded soils. Through the addition of cation beneficiated bentonite to a degraded Oxisol, significant responses in yield and permanent changes in the charge characteristics may be achieved (Fig. 7) (Noble et al., 2001). Selected management options for VCS are presented in Table IV.

Table IV Constraints and Management Options for Variable Charge Soils Constraint Soil acidity– aluminium toxicity

Management options Routine prophylactic applications of calcitic or dolomitic limestone applied and incorporated. Soil pH should be maintained at pH 5.5 to reduce the risk of Al3þ toxicity. If Mn toxicity is suspected pH should be raised to 6.0. Over-liming decreases the availability of P, B, Zn and Mn and results in yield declines. In addition, there is a decline in soil structure. Judicious use of acidifying nitrogenous fertilizers will minimize acid generation through the conversion 2 of NHþ 4 to NO3 . Alternatively, the use of NO3 based sources of nitrogen would eliminate any acid generation associated with mineralization. Retention of crop residues and organic matter to increase the pH buffering capacity. Application of organic materials with high ash alkalinity is an alternative source of alkalinity where conventional liming materials are not available. Sub-soil acidity can be corrected through a combination of growing deep rooted acid tolerant grass species (Andropogen spp.) and in combination with leaching and nitrate fertilizations will result in the remediation of sub-soil acidity. (continued)

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Constraint

Management options

Low cationic retention from fertilizers

Strong fixation of anionic fertilizers such as P.

Low nutrient supplying capacity

Regular small amounts of inorganic fertilizer should be applied to reduce the risk of leaching loss and increase efficiency. In addition, fertilizer additions will increase the ionic strength thereby increasing the surface charge. Increasing the negativity of the exchange complex can be achieved through increasing the soil pH or decreasing PZNPC. Lowering of PZNPC can be achieved by sorption of large anions onto particle surfaces, thereby masking a portion of the positive charge. Continued regular applications of organic matter will increase the CEC of soils as well as effectively lower the pH0. In situations where increasing organic matter levels are not possible, inorganic soil amendments such as phosphate and silicates could be used to lower PZNPC. When increasing the negative charge of these soils, the anion exchange capacity will decline thereby reducing the ability of these soils to retain anionic species such as nitrate. Reducing the reactivity of surfaces for PO4. This could be achieved by increasing the amounts of colloids with low affinity for PO4 fixation, the addition of other anions that compete with PO4 and the application of organic matter. In addition, sources of silica, ground basalt, volcanic ash and Ca-silicate can be used. Banded applications of inorganic P fertilizers and the use of rock phosphate under acid conditions will improve P nutrition. The application of superphosphate may promote the release of nutrients through the breakdown of silicate minerals through the formation of H3PO4. Si deficiency on highly weathered soils can be rectified through the addition of silicated materials.

ACKNOWLEDGEMENTS Pacific Northwest National Laboratory (PNNL) is operated for the DOE by Battelle Memorial Institute under Contract DE-AC06-76RLO 1830. We would like to recognize the contributions made to this paper by Alice Dohnalkova for the SEM and TEM analyses conducted in some variable charge subsoils. The SEM and TEM analyses were performed in the Environmental Molecular Sciences Laboratory, a national scientific user facility sponsored by the U.S. Department of Energy’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory in Richland, WA.


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UNDERSTANDING AND REDUCING LODGING IN CEREALS P. M. Berry,1 M. Sterling,2 J. H. Spink,3 C. J. Baker,2 R. Sylvester-Bradley,4 S. J. Mooney,5 A. R. Tams5 and A. R. Ennos6 1

ADAS High Mowthorpe, Duggleby, Malton, North Yorkshire YO17 8BP, UK 2 School of Engineering, The University of Birmingham, Edgbaston, Birmingham B15 2TT, UK 3 ADAS Rosemaund, Preston Wynne, Hereford HR1 3PG, UK 4 ADAS Boxworth, Boxworth, Cambridge CB3 8NN, UK 5 School of Life and Environmental Science, University of Nottingham, University Park, Nottingham NG7 2RD, UK 6 School of Biological Sciences, University of Manchester, Oxford Road, Manchester M13 9PT, UK I. Introduction II. Observations of Lodging A. Types of Plant Failure B. Temporal Patterns C. Spatial Patterns III. Effects of Lodging on Cereal Yield and Quality A. Yield B. Quality IV. Mechanics of Lodging A. Bending Moments B. Stem Failure C. Anchorage Failure D. Models of Lodging V. Avoidance Through Crop Management A. Cultivations B. Sowing Date, Rate and Depth C. Nutrition D. Growth Regulators E. Summary of Management Factors VI. Avoidance Through Plant Breeding A. Effects of Dwarfing Genes B. Potential for Further Progress VII. Lodging-Proof Ideotype A. Quantifying a Lodging-Proof Ideotype B. Can Cereals Be Made Lodging-Proof? VIII. Conclusions A. Progress in Understanding Lodging During the Last 30 Years B. Further Understanding Required References


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Improved lodging resistance has contributed significantly to the dramatic increase in cereal yields observed in many countries during recent decades. Several advances in understanding lodging have been made since the last major review of lodging in 1973. These include: (1) a more thorough quantification of the effects of lodging on grain yield and quality, (2) collaborative studies by biologists and engineers have elucidated the mechanisms of stem and anchorage failure and the way in which cereal shoots interact with the wind and rain, (3) the development of models of the lodging process and (4) explanations for how crop husbandry decisions affect lodging. This review collates the new understanding of lodging and attempts to set out cultural and genetic-based approaches for the continued reduction of lodging risk in high-yielding cereals. The review demonstrates that the prospects for continuing to reduce lodging risk through the selection of shorter genotypes may be limited because there appears to be a minimum crop height that is compatible with high yields. There does appear to be significant scope for increasing lodging resistance by strengthening the stem and the anchorage system by exploiting the wide genetic variation in these plant characters and through crop management decisions. q 2004 by Elsevier Inc.

I. INTRODUCTION The process by which the shoots of small grained cereals are displaced from their vertical stance is known as lodging. This usually occurs only after the ear or panicle has emerged and results in the shoots permanently leaning or lying horizontally on the ground. This can reduce yield by up to 80% and causes several knock-on effects including reduced grain quality, greater drying costs and slower harvest. It is a problem that limits cereal productivity in both developed and developing countries. Lodging is a complicated phenomenon that is influenced by many factors including: wind, rain, topography, soil type, previous crop, husbandry and disease. It is frequently associated with conditions that promote plant growth such as an abundant supply of nutrients. Great strides were made during the 1960s and 1970s to reduce lodging risk by the introduction of semi-dwarf varieties. The yield of these varieties was greater than the traditional varieties for two reasons: (1) reduced stem growth rates during the development of the ear resulted in more fertile florets and more grains per square metre and (2) they could respond to greater amounts of fertilizers because they were less susceptible to lodging (Fig. 1). For these reasons the introduction of semi-dwarf varieties was perhaps the most significant reason for the steady improvement in grain yields starting in the late 1960s, which has resulted in cereal yields

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Figure 1 The response to fertilizer by dwarf wheat cultivars (A—Sonora 64, £ —Lerma Rojo) and a traditional wheat cultivar (K—C-306) in the irrigated plain of the Pacific North-West of Mexico. Adapted from Conway (1997).

increasing by as much as 1 t ha21 per decade in western Europe and 0.5 t ha21 in many American and Asian countries (Conway, 1997). The continued improvement in yields in some countries has been significantly aided by the use of plant growth regulators (PGRs) that further reduce crop height making cereals even more resistant to lodging. Three major types of PGRs have been introduced including: chlormequat chloride during the mid-1960s, ethephon during the late 1980s and trinexapac-ethyl during the mid-1990s. In France, Germany and the UK, which have among the highest cereal yields in the world, PGRs are now applied to more than 70% of wheat area (Rademacher, personal communication). Dwarfing genes and PGRs have been very effective tools for reducing lodging risk and maintaining steady improvements in yield. However, they have not eradicated lodging and there is evidence that farmers will not be able to rely on these tools for further reductions in lodging risk in order to counter the escalating lodging risk resulting from continued yield increases. An analysis of the effects of several dwarfing genes on wheat yield by Flintham et al. (1997) showed that the minimum crop height for optimum yield was 0.7 m (fully described in Section VI). PGR use may become restricted if maximum residue limits of chlormequat in grain are reduced to below the levels at which PGRs are currently detected in treated crops (Juhler and Vahl, 1999). It therefore seems likely that alternative strategies for reducing the lodging risk of cereals must be sought.

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Since the last comprehensive review of lodging (Pinthus, 1973), several advances in understanding lodging have been made. There has been a more thorough quantification of the effects of lodging on grain yield and quality, so the impact of lodging on productivity can now be better assessed. Collaborative studies by biologists and engineers have elucidated the mechanisms of stem and anchorage failure and the way in which cereal shoots interact with the wind and rain. These studies have culminated in models of the lodging process. Many studies have also explained how variety, sowing date, seed rate, nitrogen fertilizer and PGRs affect lodging. This improved understanding offers the prospect of designing a lodging-proof ideotype for cereals, which may be achievable through a combination of husbandry and conventional breeding, in tandem with new genetic techniques. This review collates the new understanding of lodging and attempts to set out cultural and genetic-based approaches for the continued reduction of lodging risk in high-yielding cereals.

II. OBSERVATIONS OF LODGING A. TYPES

OF

PLANT FAILURE

Until recently, wheat, barley and oats were perceived by many farmers, together with their supporting industries, to lodge as a result of buckling of the lower internodes (stem lodging) (e.g., Thomas, 1982). For example, cultivars with good lodging resistance are often described as “strong strawed” and PGRs described as “straw stiffeners”. However, the scientific literature has recognised that lodging can also result from failure of the anchorage system (root lodging) since 1908 (Mulder, 1954) and Pinthus (1973) concluded that root lodging was probably the predominant form on a world scale. The misconception amongst practitioners that stem failure is the main cause of lodging probably arises from difficulties with observing the point of failure in lodged crops because the plant bases tend to be covered by fallen plants. Root lodged crops also tend to have a proportion of plants with buckled stems (Easson et al., 1992). It is also possible that displacement of the shoots may begin with anchorage failure, and then the increased base bending moment of the shoot, arising from its displacement, may lead to stem failure. The scientific literature reports both stem and root lodging, and the consensus must be that both forms of lodging can occur in farmers’ fields. In wheat, barley and oats, stem lodging is usually caused by one of the bottom two internodes buckling (Neenan and Spencer-Smith, 1975; Mulder, 1954) and results in the upper stem and ear lying horizontally (Fig. 2). Buckling of the middle internodes, commonly known as “brackling” (Fig. 3) is common in barley (Neenan and Spencer-Smith, 1975) and oats (White et al., 2003). White (1991) showed that susceptibility to brackling increased towards harvest. Buckling of


Figure 2

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Close view of stem lodging in winter wheat (Laude and Pauli, 1956).

the peduncle just below the ear, commonly known as “necking”, is a particular problem in barley. Greater applications of nitrogen delayed the onset of necking and there were significant differences between cultivars (White, 1991). In theory, it is unlikely that stem lodged plants can lean at angles of less than 908 from the vertical without being supported by neighbouring plants (see Section IV.B for explanation). Root lodging has been observed in wheat (Crook and Ennos, 1993; Easson et al., 1993), barley (Graham, 1983) and oats (Mulder, 1954). It results in permanent displacement of the cereal stems without any observable stem

Figure 3

Brackling in winter barley.

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Figure 4 Root lodging in winter barley.

buckling. This can result in plants leaning at less than 908 from the vertical or lying horizontally (Sterling et al., 2003) (Fig. 4). During root lodging, Crook and Ennos (1993) observed the soil on the leeward side of the plant subsiding slightly, but not moving appreciably on the windward side. Pinthus (1973) observed cracks parallel to the planting rows on the windward side of root lodged plants. Easson et al. (1992) reported clear evidence of “plants pulling away from the soil” during root lodging. The authors of the present review have also observed the oscillating stems to produce a slot in the soil next to the plant base.

B. TEMPORAL PATTERNS The severity with which a region experiences lodging depends upon the season. For example, the UK experienced widespread lodging in 1980, 1985, 1987, 1992, 1997 and 1998, during which it was estimated that about 16% of the wheat area lodged (Berry et al., 1998). These years were often associated with wetter than normal summers. However, wet summers did not always result in widespread lodging and it is clear that summer rainfall is not the sole determinant of a widespread lodging year. Winter wheat has been observed to lodge any time from the emergence of its ear until its grains have matured (Fischer and Stapper, 1987; Easson et al., 1993). These developmental stages may span 3 months in cool climates. Lodging can also begin as early as the emergence of the ear or panicle in other cereal species, although published evidence for this is difficult to find. Lodging tends to be more common close to harvest, which indicates that cereal plants become more lodging prone as they develop.


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Witness accounts describing the process of lodging are very rare. This is probably because it often occurs in relatively hostile weather conditions. This is one of the reasons why the mechanism of lodging and the factors that determine it are poorly understood. Winter wheat, grown on a sandy clay loam soil, has been observed to root lodge over a period of several hours (Easson et al., 1992). During this time, the crop, constantly moving due to the action of wind, initially returned to the vertical from each movement and then began to be displaced a few degrees from the vertical before gradually becoming fully lodged. This study showed that this lodging frequently occurred during the same 24 h period that rain fell and could occur following as little as 4 mm of rainfall. It was shown to be associated more with the occurrence than the amount of rainfall. Wind speed appeared to play a secondary role with one lodging event occurring when the wind speed did not exceed 5 ms21 (a gentle breeze). The direction of lodging was variable and bore no correlation with the wind direction. Berry (1998) also found that root lodging in winter wheat could be associated with as little as 4 mm of rain and that it was not associated with “windier than average days”. However, during a drier summer, stem lodging was observed on four occasions after less than 1 mm of rain had fallen. These lodging events were associated with higher than normal wind speeds. Wind tunnel experiments by Sterling et al. (2003) showed that root lodging could occur within 5 min when the soil was saturated and the crop was subjected to a mean wind speed of 8 ms21 and gusts of 10 ms21. Stem lodging, however, was observed to occur almost instantaneously once a threshold wind speed had been exceeded, in agreement with Neenan and Spencer-Smith (1975).

C. SPATIAL PATTERNS On a spatial scale, there are evident patterns of lodging at several levels, including between regions, between farms, between fields and within fields. Regional variation may be caused by different weather during crop growth or at the time of lodging, or by different soil types. Variation between farms may be caused by different husbandry. A farm may apply large quantities of animal manures or the farmer may be particularly skilled at choosing cultivars or using PGRs. Field-to-field differences may be associated with different cropping histories or topographical variation, which affect local wind speeds. Perhaps the field had previously been a permanent pasture and therefore had a high organic matter content, promoting lush growth. Within a field, the margins frequently show lodging. Plants next to the wheel-ways (tramlines), which are caused when agro-chemicals are applied, tend to remain upright. Berry et al. (1998) described the spatial patterns of lodging in winter wheat during a widespread lodging year (1992) in the UK. Out of 340 fields that were surveyed, at nine locations within England, 309 (91%) experienced some lodging. Altogether, 456 ha out of 2865 ha were lodged. The percentage area

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Figure 5 Aerial photos of wheat fields in which the lodged area is denoted by the light shading. (a) Lodging at the junction between the field margin and the main body of the field. (b) Whole margin and small parts of the main body of the field lodged. (c) More than 50% of the field area lodged, but most of the tramlines are unlodged.


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lodged varied from 9 to 29% between locations and there was a tendency for the sites in the south and south-west to have more lodging. However, this was not associated with greater rain or wind. The percentage area that a field lodged could vary from 10 to 90% at a particular site. This was an important observation that demonstrated that lodging severity could vary by a large amount at individual sites, even though each field probably experienced similar weather conditions. Within each field, distinct patterns of lodging could be recognised for different lodging severities. For low lodging severity (, 10% area lodged), the lodging was usually confined to the field margin and often involved the junction between the margin and the main body of the field (Fig. 5a). Seed drilling and fertilizer applications tend to overlap on this part of the margin, so these patches are likely to be associated with greater plant density and/or fertilizer. For fields with moderate lodging (10 – 50%), most of the margin was lodged with the lodged area extending into the central part of the field, between the tramlines (Fig. 5b). In severely lodged fields, the entire margin tended to lodge, with lodging occurring evenly over the rest of the field leaving the tramlines standing (Fig. 5c). Several reasons for the high lodging resistance of the plants next to the tramlines can be put forward. These include: improved anchorage caused by vehicles compacting the soil surrounding the plant roots, reduced plant density resulting in less mutual shading and stronger stems and roots, or sturdier plant growth stimulated by vehicles brushing against the plants.

III. EFFECTS OF LODGING ON CEREAL YIELD AND QUALITY A. YIELD Lodging can reduce cereal yield by reducing the grain size and number or by reducing the amount of crop that can be recovered by the combine harvester. This section deals only with physiological reductions in yield associated with lodging. The greatest lodging-induced reductions in potential grain yield occur when crops are lodged flat at anthesis or early on in grain filling. Yield reductions from this type of lodging have been reported to reduce yields of wheat by 31% (Weibel and Pendleton, 1964) to 80% (Easson et al., 1993), barley by 28– 65% (Sisler and Olsen, 1951; Stanca et al., 1979; Jedel and Helm, 1991) and oats by 37% (Pendleton, 1954). All the above studies, apart from Easson et al. (1993), artificially lodged the plants. This was achieved by growing the plants through wire netting, then moving the wires to effect lodging. This method has the advantage of lodging the crops at specific dates and at different angles, but may induce damage not normally incurred with natural lodging. Easson et al. (1993)

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compared the yields of crops grown at high seed rate, which lodged naturally, with those at low seed rate, which experienced negligible lodging. Smaller yield losses have been observed when the angle of lodging is less than 908 from the vertical. Lodging at 458 causes between one-quarter and one-half of the yield losses incurred from 808 lodging in wheat (Fischer and Stapper, 1987), barley (Sisler and Olsen, 1951) and oats (Pendleton, 1954). Smaller yield losses also occur when lodging occurs at a later stage of development. Artificial lodging at the ear emergence, milk, soft dough and hard dough stages reduced yield by 31, 25, 20 and 12%, respectively (Weibel and Pendleton, 1964). Stapper and Fischer (1990) supported these observations by showing that about 0.5% of the potential yield was lost for each day of the grain filling period that a crop was lodged flat. Crops which lodge before anthesis often have smaller yield losses than crops that lodge soon after anthesis (Fischer and Stapper, 1987). This appears to be associated with the upper one or two internodes bending upwards to partially re-erect the crop. Crops that lodge after anthesis have completed stem extension and are unable to re-erect themselves. In natural situations, the re-erected crops are very unstable and are usually re-lodged by unexceptional weather (Easson et al., 1993). A number of mechanisms by which lodging reduces the yield of cereals have been postulated. These have been reviewed by Hitaka (1968) and include reduced translocation of mineral nutrients and carbon for grain filling, increased respiration, reduced carbon assimilation within the canopy, rapid chlorosis and greater susceptibility to pests and diseases. The most likely mechanism appears to be reduced carbon assimilation. Setter et al. (1997) showed that lodging reduced the yield of rice by increasing the amount of self-shading by neighbouring leaves which, in turn, reduced the rate canopy photosynthesis. This work indicated that the main limitation was inefficient light interception and use by the horizontal leaf and panicle layers of the lodged plants. A model of light distribution and photosynthesis in field crops (Monteith, 1965) predicts that, for crops with a leaf area greater than five experiencing high irradiance, canopy photosynthesis decreases as leaves become more horizontal. This is because the upper leaf layers proportionately intercept more light, but are unable to use it efficiently because they are either close to, or above, their light saturation point. This mechanism of yield loss may explain why partially re-erected crops can sometimes reduce lodging-induced yield losses.

B. QUALITY One of the most important quality criteria of wheat grain is its bread-making quality. This is measured in terms of its Hagberg falling number (HFN), and a HFN of at least 250 s is required for good quality bread. In the UK, the severe lodging in 1992 (described in Section II.C) was associated with a drop in HFN


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from a 5 year national average of 287 to 254 s, thus significantly reducing the amount of bread-making grain produced in this year. Also in 1992, the specific weight of wheat grains dropped from 77 to 73 kg hl21, the number of small grains (, 2.0 mm) increased from 1.9 to 2.6% and the percentage of grain samples with more than 11.5% protein increased from 19 to 29% (HGCA, 1997). Artificial lodging has also been observed to cause similar effects on grain quality (Table I). In this experiment, lodging was induced by pushing the plants through 908 in the direction of drilling at five growth stages: ear emergence (growth stage 59 (Tottman, 1987)), mid-anthesis (growth stage (GS) 65), early grain filling (GS75), late grain filling (GS83) and pre-harvest (GS90). Wheat plants were able to partially re-erect themselves after artificial lodging at GS59 and GS65 by bending at the uppermost 1 or 2 nodes. These treatments remained partially reerected until harvest, which explains their smaller reductions in grain quality in response to lodging. Lodging during early grain filling affected grain quality the most by reducing the HFN, thousand grain weight and specific weight, and increasing the protein content. Lodging after this developmental stage caused smaller effects on quality. The small grains and low specific weight indicate that lodging reduced the supply of assimilates to the grains, and this increased the concentration of protein. Similar effects on grain size, specific weight and protein content have also been observed in wheat (Laude and Pauli, 1956; Weibel and Pendleton, 1964), barley (Day and Dickson, 1958; Stanca et al., 1979) and oats (Mulder, 1954). HFN is reduced by the accumulation of alpha amylase predominantly as a result of two mechanisms: pre-maturity alpha amylase accumulation in the absence of sprouting and post-maturity sprouting (most common). Pre-maturity alpha amylase accumulates when grain dries from 40 to 20% moisture in cool damp conditions (Gale et al., 1983). Either high humidity or a large diurnal

Table I Grain Quality of Artificially Lodged Winter Wheat (cv. Riband) Sown in the UK (52.18N, 2.58W) on 16/8/95

Unlodged control Lodged at GS59 GS65 GS75 GS83 Preharvest P-value SED (22 df)

Hagberg falling number (s)

Thousand grain weight (g)

Specific weight (kg hl21)

Protein (% at 85% dry matter)

289 271 216 114 114 258 ,0.001 20.0

42.2 42.3 41.4 37.2 41.7 42.1 ,0.001 0.99

70.3 69.4 68.2 65.8 68.0 70.3 ,0.001 0.93

10.6 11.0 12.0 12.1 11.1 10.8 ,0.001 0.24

Each treatment was replicated five times. Unpublished data.

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temperature range may be required to initiate this response. The chance of postmaturity sprouting increases with delays in harvesting because the optimum temperature at which dormancy is broken increases to more than 108C and therefore becomes more likely (Lunn, personal communication). Lodging can promote the production of alpha amylase through either mechanism by keeping the grains moist for longer periods and delaying harvest. The likelihood that lodged crops will reduce HFN depends upon a complex interaction with weather conditions. Table I shows that a lodged crop does not automatically result in a low HFN. On the other hand, even a small delay in harvest can be critical, with rates of reduction for HFN of 25 s per day possible once dormancy is broken. Lodging in barley can also increase alpha amylase (Mabuchi, 1993) and this was shown to reduce the amount of malt that could be extracted from the barley grain during brewing (Day and Dickson, 1958). The humid atmosphere surrounding lodged crops also increases the likelihood of fungal infections that contaminate the grain with mycotoxins. This has been demonstrated in wheat, barley and oats, with the P. verrucosum toxin ochratoxin A and F. graminearum toxin deoxynivalenol most common (Langseth and Stabbetorph, 1996; Scudamore, 2000). Animal health and productively can be adversely affected when they are fed grain containing high levels of these toxins.

IV. MECHANICS OF LODGING A. BENDING MOMENTS The wind-induced force acting on the upper sections of a shoot or plant results in a bending moment at the plant’s base. This can be described as the shoot leverage. If the bending moment of a shoot exceeds the strength of the stem base then stem lodging is expected. If the bending moment of all the shoots belonging to a plant exceed the strength of the root/soil system (expressed in terms of its restoring moment) then root lodging would be expected (see Section IV.C for further details). Hence, a key parameter for understanding the mechanics of lodging is the wind-induced base bending moment experienced by an individual shoot and a whole plant. Crook and Ennos (1995) approximated this bending moment to the “self-weight moment” of a shoot. This proved useful for estimating lodging risks, but did not account for the dynamic nature of the parameter. The coherent waving of cereal shoots, apparent even in light winds, provides striking evidence that cereal shoots are subjected to varying forces and hints at the importance of including the shoot’s motion in any calculation of the applied base bending moment. Baker (1995) attempted to account for the dynamic nature of shoot movement by considering the forces that act on an idealised shoot (Fig. 6).


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Figure 6 The wind-induced forces on an idealised wheat shoot. Shoot movement is modelled as a damped harmonic oscillator.

Baker (1995) showed that the wind-induced base bending moment, B could be expressed as B ð1 2 b4 2 Þ ¼ lX PX a2 12aþb 4 2 þ ð1 2 gÞb4 4 tan lX

ð1Þ

where

42 ¼

ð2pnÞ2 X g

lX mgX 2 tan lX k mg l2 ¼ EI Hg b¼ kX mgX g¼aþ k a¼

P¼

1 2

rACd Vg2

P is the wind-induced force, X the height at the centre of gravity of a shoot, n the frequency at which the shoot oscillates, g the acceleration due to gravity, m the mass of the shoot’s canopy, E and I the Young’s modulus and second moment of area of the stem, respectively, r the density of air, A the projected ear area for an individual shoot, Cd the drag coefficient of an ear and Vg the wind speed. Finally, the parameters H and k represent the rotational stiffness of the root – soil complex. Baker (1995) showed that for a typical cereal plant the value of b is

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sufficiently small so that this term can be neglected. This allows Eq. (1) to be greatly simplified, the magnitude of which can be expressed as 2 g 1þ B ð2pnn Þ2 X ð2Þ PX ¼ ( 2 !2 )1=2 n n 2 12 þ 2d nn nn where nn is the shoot’s natural frequency and d the damping ratio (which represents the efficiency with which the shoot is dissipating energy between each oscillation). The importance of Eq. (2) can be appreciated by referring to Fig. 7. When the frequency at which the base bending moment is applied is less than the natural frequency of the shoot, the non-dimensionalised magnitude of the bending moment takes a relatively constant value of the order of 1.6. When the loading frequency approaches the shoot’s natural frequency the effect is marked and increases the non-dimensionalised magnitude to approximately 10. It should be stressed that this large increase occurs purely as a result of altering the loading frequency and is independent of wind speed. The wind flow over a plant canopy is complex and comprises a variety of scales of motion each with varying degrees of frequency (see Finnigan, 2000 for an in-depth review). The motion of the shoots within a canopy will affect the coherent structures present in the air flow, which will, in turn, affect not only the loading frequencies experienced by the shoot, but also alter the gustiness of the wind flow. Since the base bending moment is directly proportional to the square of gust velocity, the dynamics of the shoot may significantly affect the base bending moment. Hence, it is imperative that any model that attempts to represent the lodging process takes into account the dynamics of the shoot.

Figure 7 A graphical representation of Eq. (2), with nn ¼ 1 Hz, X ¼ 0.5 m and d ¼ 0.08.


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The turbulent structures present within the air flow encompass a wide spectrum of length and time scales. One important question that must be addressed is: what is the maximum base bending moment (Bm) that a shoot will experience for a given gust velocity averaged over the time (t) that such a gust may exist? Using a simplified form of Eq. (1), Baker (1995) was able to demonstrate that the answer to this question can be expressed as Bm g 2pd sinðpnn tÞ ¼ 1þ 1 2 e ð3Þ pnn t PX ð2pnn Þ2 X Fundamental in the derivation of Eq. (3) are a number of key assumptions, in particular that the damping ratio is relatively small and that the shoot can be considered to act as a damped harmonic oscillator. These assumptions were validated during experiments in which a portable wind tunnel (Fig. 8) was used to test the aerodynamic properties of field-grown wheat (Berry et al., 2003a; Sterling et al., 2003). Despite the potential restrictions of such an approach, the wind tunnel generated conditions that mimicked natural conditions sufficiently well, thereby ensuring that the shoots within the tunnel experienced realistic wind loading. During each test a number of calibrated strain gauges were attached to the base of some of the shoots enabling a direct measurement of the base bending moment imposed by the shoot’s movement. An ultrasonic anemometer was placed directly above an instrumented shoot and sampled simultaneously with the strain gauges. This allowed the wind-induced base bending moment to be directly correlated with the corresponding gust velocity.

Figure 8 Portable wind tunnel capable of producing wind gusts of 10 ms21. Adapted from Sterling et al., 2003.

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Equation (3) is most applicable to a wheat crop, since such crops typically fail at or near the base of the stem. The situation is rather more complicated for barley and oats since they can lodge by stem buckling at either the bottom, mid-point or, in the case of barley, at the top of the stem. Also, barley and oats are structurally different to wheat due to the presence of awns and panicles, respectively. Both structures will increase the surface area that is subjected to wind loading, but the extent to which this is transmitted to the plant base will depend on the flexibility of the awns, panicle and upper stem. The flexural rigidity of barley stems has also been measured to be three times less than that of wheat (Graham, 1983), which indicates that less wind-induced force will be transmitted down the stem. Awns and panicles may also trap more water than a wheat spike. It is hypothesised that a lodging model for barley and oats could be developed along similar lines to that of wheat. However, it would be important to specify the distribution of extreme bending moment along the entire length of stem rather than just at the base. This distribution would need to be combined with a corresponding distribution of the structural properties of the stem, thus allowing buckling to be simulated anywhere along the stem.

B. STEM FAILURE The flexibility of cereal stems typically results in the plants undergoing relatively large deflections. However, experiments by Neenan and Spencer-Smith (1975) have shown that the stems of wheat and barley buckle at a certain critical ratio of radius of curvature to outside diameter of the stem. Buckling was shown to occur suddenly with negligible amounts of plastic deformation. The Young’s modulus of wheat and barley was shown to remain reasonably constant for a range of stem curvatures, which indicates that negligible plastic deformation occurs and that the limit of proportionality between the applied stress and corresponding strain is seldom exceeded. These observations indicate that fields with widespread stem lodging must result in shoots lying horizontally on the ground and stem lodged shoots may only “lean” when there are sufficient nonbuckled stems nearby to support them. Assuming that a typical stem can be considered to be analogous to a cylinder, Baker (1995) showed that the stem failure moment (BS) can be expressed as ! spa3 a2t 4 12 ð4Þ BS ¼ a 4 where s is the stem failure yield stress (material strength), a the external radius of the stem and t the wall thickness. This formula assumes that the pith in the centre of the stem does not contribute to the structural properties of the stem. Solid stemmed varieties of wheat have often been linked with greater lodging resistance. However, Ford et al. (1979) found no qualitative anatomical


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differences between solid and hollow stems. The “pith” of the solid stems was undifferentiated parenchyma, whose cells were thin walled. Hence this tissue would not be expected to contribute significantly to the stem’s structural integrity. Graham (1983) also showed that the so called “solid” stemmed varieties had a lower flexural rigidity than hollow stemmed varieties because they had a smaller diameter.

C. ANCHORAGE FAILURE 1. Root Failure An understanding of how the root –soil complex fails in cereal plants is vital, however, much conjecture exists as to its exact mechanism. Uncertainty about how roots fail lies in the obvious difficulties associated with observing the process within its natural environment. This has resulted in previous studies encountering a number of problems. For example, the trenching method originally used by Coutts (1983, 1986) to observe the mechanism of failure in Sitka spruce, cannot allow the lodging process to be observed under natural conditions. Extracting root –soil cores from the field runs the risk of disturbing the soil and artificial lodging may not result in the same failure mechanism as natural lodging. It has also been noted that plants grown in glasshouses have weaker roots than field-grown plants (Graham, 1983). Ennos (1991) showed that anchorage failure of spring wheat involved bending of the crown roots and resistance to axial movement through the soil. Crook and Ennos (1993) showed that anchorage failure of winter wheat occurred when the root –soil cone rotated at its windward edge, the soil inside the cone moving as a block and compressing the soil beneath. This idea supported earlier observations by Pinthus (1967), who showed that a wider angle of root spread was related to greater resistance to root lodging. Easson et al. (1992) suggested that winter wheat roots acted like ropes to withstand root lodging and that anchorage strength would therefore be a function of the tensile strength of the roots on the windward side of the plant. Finally, Ennos et al. (1993) showed that plants with a large number of widely spread roots, such as sunflowers, fail by a “hinge” mechanism similar to that of Sitka spruce (Coutts, 1983, 1986). This mechanism may become more likely in cereals as the use of low seed rates by commercial growers becomes more common. The model developed by Crook and Ennos (1993), which assumes that the mechanism of failure in wheat is rotational movement of the root –soil cone, has been tested and calibrated with field experiments by Griffin (1998) and Baker et al. (1998). This yielded the following equation for anchorage strength (BR) BR ¼ 0:43d3 s

ð5Þ

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where d is the spread of the root plate and s the shear strength of the surrounding soil. The size of the root plate is identified by the parts of the crown roots that are surrounded by a rhizosheath. The rhiozsheath is a dense mat of hairs that cover the upper sections of crown roots. These sections of roots have been shown to have an outer ring of lignified tissue in addition to the lignified central stele (Crook and Ennos, 1993), which is why the rhizosheath is used to estimate the length of root that provides anchorage. However, potential deficiencies have been recognised with this model including its applicability on frictional soil types, its failure to account for root bending or soil slippage between the roots and the fact that it does not account for progressive failure of the anchorage system.

2.

Soil Strength

When soil yields under stress it most commonly fails in shear, tangentially acting forces causing it to deform and possibly fracture. Shear strength increases nearly linearly with increasing normal load, that is; S ¼ C þ N tan f

ðMohr-Coulumb0 s equationÞ

ð6Þ

where S is the maximum shearing stress, C the shear stress at zero load (called cohesion or apparent cohesion), N the normal load (stress perpendicular to shearing stress) and f the angle of internal friction (shearing resistance). N also includes a component due to water suction which pulls soil particles together. As a result N can be broken down to ðss 2 uw Þ; where ss is the total stress and uw the pore water pressure (also known as the matrix potential). So, soil strength is a combination of cohesive strength and shearing resistance. The relative proportion that each component contributes to soil strength will depend upon the nature of soil failure. The process of anchorage failure is likely to involve small normal loads because only the surface layer of soil is involved and because the windinduced load of a cereal shoot is relatively small compared with the normal loads induced by other factors such as traffic. Therefore, cohesive forces will be relatively important. Soil texture, moisture content and compactness each affect C and f, and are therefore expected to be important determinants of soil shear strength and resistance to anchorage failure. In clay, cohesive forces are strong because the individual particles are held together by surface tension when moist, and strong electrostatic and other bonding when dry. Cohesive forces are weak in sand because there is no significant attraction between grains. However, sand has a greater shearing resistance than clay, so its shearing strength increases proportionally more when a normal load is applied. Increasing bulk density increases the number of particle –particle contacts of both sand and clay, and thus enlarges the binding force between elementary particles. Cohesive forces decrease between the lower


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and upper plastic limit as water content increases. Changes in water content have a large effect on the shear strength of clays, but only a small effect on sands. It must also be emphasised that the effects of bulk density and water content on soil strength are confounded because bulk density varies with water content due to swelling and shrinking properties (Guerrif, 1994). Easson et al. (1995) experimentally determined the tensile properties of mature wheat roots and the forces necessary to remove the roots from undisturbed soil at a range of soil water contents. Increasing the volumetric soil water content from 17 to 26% reduced the peak load from 5.2 to 3.5 N. Averaged over the two soil moisture contents, the peak loads for sandy clay loam and sandy loam soils were 4.8 and 3.9 N, respectively. There was no interaction between soil water content and soil type in the peak load. A model of soil strength developed by Baker et al. (1998) showed that variation in clay content, moisture content and compaction that is normally found within farmers’ fields could each be expected to alter the soil shear strength by several fold. This indicates that the state of the soil is likely to be of paramount importance for determining lodging as it has been predicted to be directly proportional to anchorage strength [Eq. (5)]. However, the results from this soil strength model must be interpreted with caution because it has not yet been widely tested and does not account for possible interactions between the soil factors.

D. MODELS

OF

LODGING

Few studies have attempted to interrelate all the elements which interact to cause lodging. Farquhar and Meyer-Phillips (2001) and Crook and Ennos (1994) developed “safety factors” against lodging from a comparison of the strength of the stem and root structures with the load they must bear. These have proved useful for assessing the effects of plant structure on lodging risk, but cannot predict lodging quantitatively because they do not provide a mechanism for considering the effects of wind and rain. Baker et al. (1998) considered weather, plant form and soil in a model of wheat lodging. This model assumes that the dominant parameter affecting lodging is the wind-induced bending moment at the stem base. The value of this bending moment relative to the failure moment of the stem and the failure moment of the root – soil complex indicates whether or not lodging will occur. The base bending moment of a single shoot (stem, ear and leaves) is calculated from the wind speed acting upon the ear, the area and drag of the ear, together with the shoot’s natural frequency, height at centre of gravity and damping ratio [Eq. (3)]. The base bending moment of the whole plant equals the product of the shoot base bending moment and the number of shoots per plant. Stem failure moment is calculated from the stem radius, wall width and failure yield stress

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[Eq. (4)]. Anchorage failure moment is calculated from the spread of the root plate and the shear strength of the surrounding soil [Eq. (5)]. Soil strength is calculated from the moisture content to the depth of the root plate, as determined by rainfall, and the soil’s clay content and bulk density. More recently Berry et al. (2003a) further developed the model of Baker et al. (1998) to account for spatial non-uniformity between plants and temporal changes in plant structure during the growing season. Predictions of how the percentage area lodged increased during the summer season using inputs describing the plant characteristics at ear emergence and daily weather compare favourably with observations of lodging in the same fields. A sensitivity analysis using this model shows that the risk of stem lodging is influenced most by changes in stem diameter and the risk of root lodging is affected most by changes to the spread of the root plate (Fig. 9). In these analyses, the risk of lodging is measured in terms of the wind speed required to cause lodging, which is termed the “stem” or “root” “failure wind speed”. The large effect on the chance of lodging caused by small changes in the failure wind speed is illustrated by the probabilities of experiencing different wind speeds above a UK wheat crop (Fig. 10). It must be emphasised that this model requires more testing, particularly on different soil types. Nevertheless, it seems likely that a similar approach to that used in wheat could be used to develop models of the lodging process in other cereal species. More sophisticated models may be required, however, to calculate the wind-induced bending moment of barley and oats more accurately (see Section IV.A).

V.

AVOIDANCE THROUGH CROP MANAGEMENT A. CULTIVATIONS

The use of minimal cultivations to prepare seed beds have been shown to reduce lodging compared with more traditional methods which usually involve ploughing to about 20 cm depth (Ellis et al., 1978). This section investigates whether these effects on lodging are caused directly by changes to the strength of the soil, or indirectly due to changes in root and shoot growth arising from the different soil conditions. There is little doubt that direct drilling increases soil strength, but the magnitude of the increase and its duration vary. For example, Schjonning and Rasmussen (2000) showed that direct drilling increased the shear strength of the top 8 cm of a silty loam at plant emergence by 18 to 49%, but only small increases were observed on sandy soils. Finney and Knight (1973) showed that the bulk density of the top 5 cm of a sandy loam, which had been ploughed and cultivated, was about 0.9 g cm23 compared with a bulk density of greater than


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Figure 9 Failure wind speeds after 7 mm rain for (a) internode 1 and (b) anchorage. The ranges (0–1) are judged to represent the combined genetic and environmental range of each parameter within a high-yielding wheat crop. Adapted from Berry et al. (2003a).

1.1 g cm23 after direct drilling. However, these differences became smaller after 2 or 3 months. Goodman and Ennos (1999) demonstrated the large influence that bulk density has on shear strength by showing that increasing bulk density of a sandy loam from 1.0 to 1.4 g cm23 doubled its shear strength. Direct drilling has been shown to reduce the rate of elongation of the seminal roots of winter wheat, but had no effect on the number, elongation and diameter of the crown roots. Bingham and Bengough (2003) supported these observations

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Figure 10 Probabilities of experiencing wind gusts independent of rainfall (—) and wind gusts with $7 mm daily rain ( – – – ) between mid-June and mid-August within the main wheat growing regions of the UK. Adapted from Berry et al. (2003a).

by showing that greater soil strength significantly restricted the extension of the main seminal roots in spring barley but not in spring wheat, and had no effect on the density of lateral roots for either plant. Crook (1994) also found that compacting the seed bed did not affect the length, number and bending strength of crown roots belonging to wheat. Shoot growth has been shown to be unaffected by changes in bulk density between 0.9 and 1.4 g cm23 (Finney and Knight, 1973; Goodman and Ennos, 1999). However, more severe compaction is likely to impede root elongation to the extent that water and nutrient extraction is impaired and shoot growth is retarded. It therefore seems likely that observations for direct drilling or minimal cultivations to reduce lodging are mainly caused directly by increased soil strength resulting from greater bulk density. The common observations for high bulk density to impede root extension and increase root thickness (Wilson and Robards, 1977; Materechera et al., 1991) appear to be restricted to sections of the cereal root system that play little part in anchorage, namely, the seminal roots or the distal sections of the crown roots. Changes in soil strength associated with different cultivation methods appear to have little effect on the biomechanical properties of the upper 30 to 50 mm of the crown roots that are important in anchorage and are seldom large enough to retard shoot growth. Rolling to consolidate the soil is another management practice that has been shown to reduce lodging (Kopecky, 1970; Pinthus, 1973; Crook, 1994; Berry et al., 2002). This can be done immediately after the primary cultivations or in


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spring to re-consolidate the top-soil after it has been loosened by cycles of freezing and thawing. Berry et al. (2002) showed that rolling a sandy loam in the spring increased shear strength in the top 5 cm by 25% and this effect persisted until harvest. No effects were observed on the biomechanical properties of the wheat roots. This study also showed that rolling before GS30 reduced lodging, but rolling after GS31 had no effect on lodging. It was hypothesized that this treatment damaged the extending stems, which encouraged extra tillering, and these extra shoots countered the effects of the stronger soil. This theory was supported by rolling experiments to break cereal stems by Peltonen and Peltonen-Sainio (1997).

B. SOWING DATE, RATE

AND

DEPTH

The lodging risk of wheat is almost always reduced by delaying sowing (Green and Ivins, 1985; Fielder, 1988; Stapper and Fischer, 1990; Berry et al., 2000; Spink et al., 2000a). Published evidence for similar observations in other cereals is scarce. Pinthus (1973) cites two studies that show reduced lodging in barley when it is sown later, but Fielder (1988) observed that early sowings could reduce or increase lodging in barley. In wheat, the reduction in lodging caused by delayed sowing can be very large (Fig. 11). Even a delay of only 2 weeks can reduce the amount of lodging by as much as 30%. Reducing the number of plants established also causes a large reduction in the lodging risk of wheat (Lowe and Carter, 1972; Stapper and Fischer, 1990; Easson et al., 1993; Webster and Jackson, 1993; Berry et al., 2000; Spink et al., 2000b) and barley (Kirby, 1967).

Figure 11 Effect of sowing date on the percentage area of lodging (mean of six cultivars) (Spink et al., 2000a).

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Reducing the number of plants within a row or using wider row spaces both reduce lodging. Figure 12 shows that reducing the number of plants established from about 400 plants m22 to about 100 plants m22 can reduce the amount of lodging from 100% to negligible amounts. Deeper sowing has also been found to reduce lodging in barley (Pinthus, 1973), but in general published evidence for sowing depth effects are scarce. In addition to this, Easson et al. (1992) found that the direction of drilling did not affect the severity of lodging. It is envisaged that the husbandry effects described above are caused by changes to the structure of the crop. Berry et al. (2000) showed that sowing winter wheat 6 weeks earlier increased both root and stem lodging risk by increasing the base bending moment of the shoot by about 30% and by reducing the strength of the stem base and the anchorage system by about 50%. Stapper and Fischer (1990) have shown that early sowing results in a greater number of extended internodes, and this probably caused the longer stems which gave rise to the greater base bending moment. More tillers resulting from the early sowing (Green et al., 1985a) also contribute to a greater base bending moment. The stems were weaker because they were narrower and had thinner walls (Berry et al., 2000). The mechanism by which weak stems develop is thought to be due to a greater number of shoots competing for limited photo-assimilate during early stem extension, which reduces the dry matter per unit length of the lower internodes (Berry, 1998). The reduction in anchorage strength appeared to be partly due to greater establishment associated with the early sowing. However, it also seems likely that the plant’s shade avoidance response, triggered by the low

Figure 12 Effect of plant population on the percentage area lodged at harvest (—) cv. Apollo from Easson et al. (1993); ( – – –) cv. Cadenza from Spink et al. (2000b). Both cultivars had an equal rating to lodging resistance (HGCA, 1994).


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ratio of red light to far-red light in the denser canopy of the early sown crops, may play a part. In response to shade, Kasperbauer and Karlen (1986) showed that wheat partitioned a greater proportion of the assimilate to the extending shoots and away from the root system. Establishing 200 plants m22 compared with 400 plants m22 reduced lodging risk by increasing the strength of the anchorage system by more than 50% and the strength of the stem base by 15% (Berry et al., 2000). The increase in anchorage strength more than compensated for the increase in shoot number in these plants. The greater anchorage strength has been attributed to several morphological changes including more roots per plant (Easson et al., 1993), stronger and thicker roots (Easson et al., 1995) and a wider and deeper root plate (Berry et al., 2000). Sparsely populated plants have many tillers (Whaley et al., 2000), each of which develop up to four crown roots from each of their subterranean nodes. Therefore, it should be of no surprise that establishing fewer plants results in plants with more crown roots. Thicker and stronger roots may be caused by the absence of a strong shade avoidance response by the plant, which stimulates a greater proportion of assimilate to be partitioned to the roots. The explanation for stronger stems on sparsely populated plants is thought to be the same as for the effect of delayed sowing described above. Contrary to common perception, reducing the plant population density from 400 plants m22 to 200 m22 did not affect the base bending moment of the shoot (Berry et al., 2000). Reductions in plant height were shown to be small and were countered by a larger ear area. Earlier sowing and greater plant density may also increase the prevalence of stem base diseases, which may increase lodging by weakening the stem. Scott and Hollins (1974) showed that wheat crops with a greater incidence of sharp eyespot (Rhizoctonia), brought about through inoculation, had more lodging. Our unpublished data showed that sowing 4 weeks earlier increased the amount of Fusarium foot rot (Fusarium) on the stem base from a disease index of 6 to 16 (out of 100) ðP , 0:01Þ and increased sharp eyespot from a disease index of 6 to 13. Establishing 400 plants m22 compared with 200 plants m22 increased the Fusarium index from 18 to 24 ðP , 0:01Þ. Figure 13 shows that severe levels of either disease can reduce the failure moment of the lower internodes by 30 – 40%, thus increasing the likelihood of stem lodging. Interestingly, slight or medium levels of disease did not appear to weaken the stems. The scarcity of literature showing deeper drilling to reduce lodging is probably caused by the plant’s ability to adjust its crown depth to about 40 mm for sowing depths of between 40 and 70 mm (Kirby, 1993). This is achieved by altering the length of the sub-crown internode (Kirby, 1993). This means that sowing depths over this range are unlikely to affect the depth of the structural roots. However, drilling more shallowly than 40 mm may be expected to raise the crown and its structural roots, thus weakening anchorage. Evidence that altering crown depth can affect lodging may be deduced from the seed treatment Baytan (triadimenol). This chemical can increase crown depth by shortening the sub-crown internode

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Figure 13 Effect of Fusarium foot rot (Fusarium) (closed columns) and sharp eyespot (Rhizoctonia) (open columns) on the failure moment of internode 2 of winter wheat at GS87. Error bars are ^SED (8 df). Disease severity was according to Jones and Clifford (1978). Measurements carrried out at ADAS Rosemaund, UK in 1995.

(Montfort et al., 1996) and has been shown to reduce lodging (Anon, 1993). However, it has also been shown to reduce establishment, which could also explain the reduction in lodging.

C. NUTRITION Plant-available nitrogen (mainly NO2 3 ions) can either be supplied to the crop from the mineralization of plant residues or from chemical fertilizers. An increased supply of available nitrogen from either source has frequently been shown to increase lodging in wheat (Bremner, 1969; Pandey et al., 1997; Berry et al., 2000), barley (Widdowson, 1962; White, 1991) and oats (Chalmers et al., 1998). In wheat, the greatest increase in lodging is usually observed in response to early applications of nitrogen fertilizer before the onset of stem elongation (Mulder, 1954; Miller and Anderson, 1963; Berry et al., 1998), with applications after anthesis having no effect (Webster and Jackson, 1993). Contrary to this, Chalmers et al. (1998) found that lodging in winter oats was reduced by applications of nitrogen before the onset of stem extension compared with later applications at GS30/31. It is commonly perceived by parts of the farming industry that high rates of nitrogen increase lodging by making plants taller. However, increasing


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applications of fertilizer from 160 to 240 kg N ha21 only increased the height of wheat by 2 to 3% (Crook and Ennos, 1995). In barley, increasing applications of fertilizer from 80 to 200 kg N ha21 increased height by 10% (White, 1991). Mulder (1954) showed that increasing nitrogen supply to oats increased the length of the bottom internodes, but actually shortened the upper internodes, to effect a relatively small reduction in overall height. It therefore seems unlikely that an increase in height is the main cause of lodging in response to more nitrogen. Both Crook and Ennos (1995) and Berry et al. (2000) showed that increasing the nitrogen supply to winter wheat, through either greater amounts of residual nitrogen at sowing or larger applications of fertilizer in the spring, reduced the strength of the stem base and the anchorage system. Reductions in stem strength could be as much as 50% when high levels of residual nitrogen were combined with applications of fertilizer early in the spring (Berry et al., 2000). Reductions in anchorage strength tended to be smaller, but still larger than the effects on crop height. It appears that changes to several plant characteristics cause the nitrogeninduced changes to stem and anchorage strength. A greater nitrogen supply almost always decreases the dry weight per unit length of the basal internodes of wheat (Crook and Ennos, 1995; Berry et al., 2000), barley (White, 1991), oats and rye (Mulder, 1954). In relation to this, stem diameter and stem wall width are also frequently reduced. Mulder (1954) showed that plants with deficient supplies of nitrogen actually had thinner stem bases than adequately supplied plants. However, these deficient plants had a lower lodging risk, possibly because the weight of the shoot and ear were reduced by more than the strength of the stem base. Berry et al. (2000) showed that high levels of residual nitrogen reduced the strength of the stem wall material, but only for early sown crops. These findings were supported by Crook and Ennos (1995) who showed that a component of material strength, Young’s modulus, was also reduced by more fertilizer in spring. The cause of these effects may have been elucidated by Mulder (1954), who showed that an increased supply of nitrogen reduced the amount of lignified tissue within the sclerenchyma zone and the thickness of the sclerenchyma cell walls. Mulder (1954) demonstrated that nitrogen affected the structure of the stem base both directly and indirectly as a result of the larger canopy increasing shading. Elongation of the lower internodes was entirely due to shading, whereas reductions in stem diameter, wall width and lignification resulted from a combination of shading and a direct nitrogen effect. Reductions in anchorage strength in response to more nitrogen can be linked with fewer roots, which are thinner with smaller bending and tensile strengths (Crook and Ennos, 1995; Easson et al., 1995). Mulder (1954) showed that the crown roots of oat plants supplied with large amounts of nitrogen were practically free from lignified cells beneath the epidermis, in contrast to plants supplied with

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moderate amounts of nitrogen. The amount of lignification within the stele was also reduced. The effects of potassium, phosphorus and trace elements are less pronounced than that of nitrogen. Pinthus (1973) cites literature that mainly reported a reduction in lodging in response to potassium. However, other studies give mixed results about the effect of potassium. On potassium-deficient soils, Mulder (1954) showed that applying 100 kg K ha21 mostly reduced lodging in wheat and rye, but could also increase lodging or have no effect. No further effects were observed when an extra 200 kg K ha21 was applied. Gaspar et al. (1994) also found no consistent reduction in lodging in oats after applying potassium to soils which already had an adequate supply. Repairing a potassium deficiency was shown to increase the diameter of the stem and stem strength (Mulder, 1954; Pinthus, 1973). However, no effect of excessive amounts of potassium was observed on stem strength (Mulder, 1954). It therefore seems likely that potassium fertilizers will reduce the risk of stem lodging on soils with a potassium deficiency. An increase in the supply of phosphorus has been shown to promote lodging of wheat (Miller and Anderson, 1963). On phosphorus-deficient soils, phosphorus increased oat lodging but had no effect on wheat (Mulder, 1954). Reduced breaking strength of stems was reported by Miller and Anderson, whereas stronger roots have been reported by Spahr (1961) in response to phosphorus. Of the trace elements, only silicon is reported to affect lodging with any regularity. Improvements in lodging resistance have been reported in wheat and rice in response to applications of silica to soils with both low and high levels of silicon (Wong et al., 1994; Uchimura et al., 2000). The latter study showed that the breaking strength of rice stems was increased in response to silicon. In our consideration of nutrition we must differentiate between effects that result from repairing a deficiency and effects resulting from super-optimal supply. For example, it appears that an increase in nitrogen will increase lodging risk, but the mechanism by which this occurs will depend on the level of nitrogen supply. If a nitrogen deficiency is being repaired then lodging risk increases because the leverage of the shoot and ear increase. It seems likely that the stem strength, and possibly the anchorage strength, will be increased by correcting the deficiency but these effects are outweighed by the greater leverage. Additional nitrogen increases the shoot leverage by progressively smaller amounts, but lodging risk continues to rise because the strength of the stem base and root system begins to decrease as a result of the indirect effects of shading. It is possible that phosphorus behaves in a similar way to nitrogen. However, potassium might be different as the evidence (Mulder, 1954; Pinthus, 1973; Gaspar et al., 1994) indicates that it can reduce lodging when repairing a deficiency and additional amounts have no effect. This may be due to the important role that this element plays in regulating the turgor of plant tissues.


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D. GROWTH REGULATORS PGRs are synthetic compounds, which are used to reduce the shoot length of plants. This is mainly achieved by reducing cell elongation, but also by decreasing the rate of cell division. PGRs can be classified into two main groups: inhibitors of gibberellic acid biosynthesis and ethylene-releasing compounds. In cereals, PGRs are used to reduce lodging. They are most commonly used for this purpose in north and western European countries and in Canada and the USA. In the UK, 84% of the winter wheat is treated with PGRs (Garthwaite and Thomas, 2000). The most commonly used inhibitors of gibberellic acid biosynthesis in cereal crops are chlormequat chloride, mepiquat chloride and trinexapac-ethyl. Chlormequat chloride and mepiquat chloride block the early steps of gibberellic metabolism, whereas trinexapac-ethyl blocks a later step (Rademacher, 2000). Ethephon is the most commonly used ethylene-releasing compound used on cereals (Rademacher, 1993).

1. Lodging There is no doubt that PGRs are a very cost-effective method of reducing the incidence of lodging. PGRs applied before the emergence of the ear reduced lodging in almost all the vast numbers of published experiments that have studied their effect and in which lodging occurred. The reduction in the percentage area lodged can be anything up to 70%. For example, Herbert (1982) showed that applying chlormequat and choline chloride to winter wheat at the beginning of stem extension could reduce the percentage area lodged from about 73% to less than 8%. However, it must also be noted that PGRs do not eliminate lodging in highly susceptible crops. Berry et al. (1998) applied an identical PGR to that used by Herbert (1982) to a very lodging-prone crop and only reduced the percentage area lodged from 93 to 88% at harvest. It should be noted, however, that this treatment did delay the onset of lodging, which would reduce the amount of yield lost (Section II.A). Therefore, it is clear that the lodging susceptibility of a crop has a large influence on the amount that PGRs can reduce lodging by. Small reductions in the percentage area lodged should be expected for crops, which have either a very high or a very low risk to lodging, because the crop will remain close to either 100 or 0% lodged, respectively. The extent to which PGRs reduce lodging is also determined by the ability of the chemicals to alter the morphology of the plant in a way that reduces lodging risk. The next sections describe the factors which determine the effect of growth regulators on the plant characteristics associated with lodging.

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2.

Plant Height

Growth-regulating chemicals have been shown to reduce plant height by between 0 and 40% (Tables II and III). This variation is probably caused by interactions between the type of active ingredient, the cereal species together with the stage of plant development and the environmental conditions when the chemical is applied. Chlormequat has been shown to be effective at reducing lodging in winter and spring wheat, oats and rye, but less effective on barley (Humphries, 1968; Matthews and Thompson, 1983). It appears that translocation of chlormequat to its biochemical target(s) is less efficient in barley compared with other cereals (W. Rademacher, personal communication). On the other hand, barley undergoes large height reductions in response to a mixture of ethephon and mepiquat chloride (Stanca et al., 1979; Herbert, 1982). These effects are illustrated in Tables II and III, where chlormequat is shown to reduce the height of winter barley by 2 – 3%, but ethephon can reduce height by 4– 17%. Chemical applications appear to be more effective after the onset of stem elongation than before it, e.g., Leitch and Hayes (1990) found that chlormequat effected the greatest height reduction in oats when applied at GS32. This should be expected because most growth regulators are only active for a few days after application and can therefore shorten internodes most effectively when applied during their extension. Optimum temperatures for the growth regulators vary greatly, but are generally above 58C. Therefore applications of PGRs early in the plant’s development, when temperatures are cooler, may also result in lower activity. Several workers have shown that dwarf and semi-dwarf cultivars of oats and wheat undergo proportionately less shortening in response to chlormequat (Lowe and Carter, 1972; Abbo et al., 1987; Evans et al., 1995; Rajala and Peltonen-Sainio, 2002). Peltonen-Sainio and Rajala (2001) actually report that chlormequat increases elongation in dwarf oats. Perhaps this should be expected given that both Rht genes and chlormequat reduce height via their effects on gibberellic acid. However, Stanca et al. (1979) observed no such effect in barley when a mixture of ethephon and mepiquat chloride was applied. This may mean that semi-dwarf plants respond weakly to the PGRs that block the biosynthesis of gibberellic acid, but not to those that produce ethylene. Despite appearing to be less responsive to certain growth regulators, the lodging risk of semi-dwarf cultivars continues to be effectively reduced by the widespread use of chlormequat (HGCA, 2003).

3.

Other Traits Associated with Lodging

In addition to shortening crops, PGRs are frequently claimed to reduce lodging risk by altering other parts of the plant. These claims usually centre around traits that are, or could be, associated with strengthening the stem base

Species

Timing

Final height reduction (%)

Grain yield change (%)

Ear number (m22)

" 15 ¼ ¼ ¼ ¼ ¼

" ¼ ¼ ¼ ¼ ¼ " and ¼

2

" 0 –10 ¼ ¼ " 15 –25 ¼ " 15 –20 ¼

GS13-14 GS31 GS32

0 0– 7 0– 11

" 7 ¼ " 0 –13

WO WO WO WO

GS23 GS30 GS32 GS21 and 32

0– 10 0– 10 24–31 20–30

WT

GS23

16–25

SB SB SB SB SB SB

GS13 GS13 GS13 GS30 GS31 GS39

WB WB WB WB WB WB WB

GS13 GS13 GS14/23 GS23 GS30 GS30 GS30-31

SO SO SO

12 1–6 0 1–13 0 0– 7 3

Grains per ear

Grain weight

Reference

Location

¼ ¼ ¼ ¼ ¼ ¼

¼ ¼ ¼ ¼ ¼

Matthews and Thompson (1983) Ma and Smith (1992) Rajala and Peltonen-Sainio (2002) Ma and Smith (1992) Rajala and Peltonen-Sainio (2002) Ma and Smith (1992)

UK Canada Finland Canada Finland Canada

Matthews and Thompson (1983) Green et al. (1985b) Bragg et al. (1984) Matthews and Thompson (1983) Green et al. (1985b) Matthews and Thompson (1983) Koranteng and Matthews (1982)

UK UK UK UK UK UK UK

¼ ¼

# ¼ ¼ #

¼ ¼ "

¼ ¼ ¼

¼ ¼ ¼

Rajala and Peltonen-Sainio (2002) Rajala and Peltonen-Sainio (2002) Peltonen-Sainio and Rajala (2001)

Finland Finland Finland

¼ ¼ ¼ # 7–11

¼ ¼ ¼ ¼

¼ ¼ ¼ ¼

¼ ¼ ¼ #

Leitch and Hayes (1990) Leitch and Hayes (1990) Leitch and Hayes (1990) Leitch and Hayes (1990)

UK UK UK UK

" 0–13

¼

"

#

Naylor (1989)

UK

¼ " "

247

(continued)


Table II Effect of Chlormequat on Grain Yield and Yield Components in the Absence of Lodging

248

Table II Continued Species

Timing GS13 GS15 GS16 GS30/31 GS31-32 GS32/33

WW WW WW WW WW WW WW WW

GS13 GS13/21 GS23 GS30 GS30 GS30-31 GS30-31 GS30/31

3– 9 30 –40 10–23 8 –16 1–29 6 0 2 –24 12–16 6 3 –15


Ear number (m22)

Grains per ear

Grain weight

Reference

Location

Rajala and Peltonen-Sainio (2002) Humphries and Bond (1969) Humphries et al. (1965) Harris (1978) Rajala and Peltonen-Sainio (2002) Lowe and Carter (1972)

Finland UK UK UK Finland Australia

Kettlewell et al. (1983) Bragg et al. (1984) Matthews and Caldicott (1981) Gill et al. (1974) Page (1973) Matthews and Caldicott (1981) Herbert (1982) Berry (1998)

UK UK UK UK UK UK UK UK

¼ " 0 –15 ¼ " 4 # 8 ¼

¼ " " ¼ ¼ ¼

¼ " ¼

# # ¼

¼ ¼

# ¼

¼ ¼ ¼ ¼ ¼ " 5 ¼ ¼

" ¼ ¼

¼ ¼ ¼

¼

¼

¼ ¼ ¼ # # ¼

¼

¼

¼

SB, spring barley; WB, winter barley; SO, spring oats; WO, winter oats; WT, winter triticale; SW, spring wheat; WW, winter wheat.

P. M. BERRY ET AL.

SW SW SW SW SW SW

Final height reduction (%)

Table III Effect of Ethephon on Grain Yield and Yield Components in the Absence of Lodging Final height reduction (%)


SB SB SB SB SB SB SB SB SB SB SB SB SB

GS13 GS13 GS13 GS30 GS32 GS39 GS39 GS39-45 GS40 GS43 GS43 GS45 GS39

0 – 10 0 2 –5 0 – 10 3–8 1 – 30 8 – 17 8 – 12 10 – 13 4– 17 ? 11 – 29 4– 10

¼ " and ¼ ¼ # 0 – 30 ¼ # 0 – 50 ¼ # 0 – 11 ¼ ¼ # and ¼ # 40 # and ¼

WB WB WB WB WB WB

GS32 GS33 GS35-45 GS39 GS39 GS45-47

um 5 –8 um um 4 – 17 14 – 17

SO SO SO

GS13 GS39 GS39-40

SW SW SW

GS13 GS39 GS40

Ear number (m22)

Grains per ear

Grain weight

Reference

Location

¼ ¼

# ¼

¼ ¼ # # ¼ # ¼

" " ¼

¼ # # # ¼

¼ ¼ ¼ # ¼

Ma and Smith (1992) Rajala and Peltonen-Sainio (2002) Lauer (1991) Ma and Smith (1992) Lauer (1991) Ma and Smith (1992) Lauer (1991) Bridger et al. (1995) Bulman and Smith (1993) Foster and Taylor (1993) Foster et al. (1991) Taylor et al. (1991) Rajala and Peltonen-Sainio (2002)

Canada Finland USA Canada USA Canada USA Canada Canada Canada Canada Canada Finland

" 15 " 12 # 5– 10 ¼ ¼ # 0– 5

" um ¼ "

# # um

"

#

¼ um um # #

Matthews and Thompson (1983) White (1995) Moes and Stobbe (1991a,b,c) Matthews and Thompson (1983) Stanca et al. (1979) Stobbe et al. (1992)

UKa UKa Canada UK UKa Canada

0 0 – 12 0 – 13

¼ # 0 – 17 # 5

¼ ¼ ¼

# ¼

¼ #

Rajala and Peltonen-Sainio (2002) Peltonen-Sainio and Rajala (2001) Rajala and Peltonen-Sainio (2002)

Finland Finland Finland

0– 6 1 – 14 2 – 12

¼ ¼ ¼

¼ ¼ ¼

¼ ¼ ¼

¼ ¼ ¼

Rajala and Peltonen-Sainio (2002) Rajala and Peltonen-Sainio (2002) Khan and Spilde (1992)

Finland Finland USA

¼ ¼ ¼ " ¼ " " "

249

SB, spring barley; WB, winter barley; SO, spring oats; SW, spring wheat. a Ethephon applied as a mixture with mepiquat chloride.

#


Timing

Species

250

P. M. BERRY ET AL.

and the anchorage system. However, only two published studies have measured these parameters directly with and without PGRs (Crook and Ennos, 1995; Berry et al., 2000). These showed that a mixture of chlormequat and choline chloride applied to winter wheat at the beginning of its stem extension did not affect the strength of either the stem base or the anchorage system. An additional application of ethephon and mepiquat chloride at GS39 also had no effect. More studies have investigated the effects of PGRs on other characteristics of the stem and root system. Care must be taken when interpreting these results because changes in these parameters will not necessarily result in changes to the strength of the stem base and anchorage system. The next two paragraphs consider studies relating to the stem and roots in turn. Berry et al. (2000) showed that chlormequat reduced the material strength of the stem slightly. Crook and Ennos (1995) showed that the Young’s modulus (a component of the material strength of the stem) of wheat stems was reduced by a combination of chlormequat followed by ethephon and mepiquat chloride. Sanvicenti et al. (1999) found that a combined application of chlormequat, imazaquin and ethephon to winter barley at GS31 reduced the amount of metaxylem and the number of vasular bundles in the stem base. This may also be evidence of a reduction in material strength. Gibberellins are known to stimulate the differentiation of fibre cells (Aloni, 1987), which provide mechanical support. Therefore, blocking the biosynthesis of gibberellic acid with chlormequat could reduce the strength of the stem material. Against this, Knapp et al. (1987) found that chlormequat applied to winter wheat at GS31 and ethephon applied to winter barley at GS45 had no effect on the content of cellulose, hemicullose and lignin in the stem base. Inconsistent results have been observed on the stem dry weight per unit length, with White (1995) observing a decrease in winter barley following ethephon and mepiquat chloride at GS33 and Sanvicenti et al. (1999) an increase. No consistent PGR effects have been found on the diameter and wall width of the stem of oats or wheat (Gendy and Hofner, 1989; Crook and Ennos, 1995; Berry et al., 2000) Crook and Ennos (1995) observed an increase in crown root number after chlormequat was applied at the beginning of stem extension. However, neither Crook and Ennos (1995) nor Berry et al. (2000) observed any effects of this treatment on the spread of the root plate and rigidity of the surface roots. These root observations were supported by Easson et al. (1995) who found no effect on the breaking load, cross-sectional area or Young’s modulus of the top few centimetres of individual winter wheat roots following separate applications of chlormequat at GS30 and ethephon with mepiquat chloride at GS32. Many other studies have reported effects of growth regulators on cereal root growth, but these usually either include the distal roots, that play no role in anchorage, or report effects during early growth stages that are not maintained until maturity. For example, field experiments by Bragg et al. (1984) showed that chlormequat applied before the onset of stem extension increased the mass of winter barley


251

roots below 0.4 m depth and increased winter wheat roots during stem extension, but this effect had disappeared by harvest. Other studies have also observed positive effects on root growth after the application of PGRs. Twenty days after treatment, a mixture of chlormequat and imazaquin increased the dry matter and surface area of the whole root system of winter wheat by 8% (Blouet et al., 1991). However, it is uncertain whether these effects would have persisted. Naylor et al. (1986) reported a reduced shoot:root ratio, 33 days after chlormequat was applied to barley at GS13-15. However, it is not known whether the shoot:root ratio was reduced by an increase in root growth or a reduction in shoot growth. Evidence that PGRs affect root growth may be deduced from investigations of cereal growth under drought conditions. However, reviews of this literature by Green (1986) and Humphries (1968) show that chlormequat can improve, reduce or have no effect on the ability of cereals to withstand drought. Other studies have shown no or negative effects of PGRs on roots. Rajala et al. (2002) showed that neither chlormequat, tri-nexypacethyl nor ethephon affected the extension of seminal roots of wheat, barley or oats when applied during the seedling stage. Ethephon actually retarded root extension of barley and oats when applied above commercial rates. Woodward and Marshall (1987, 1988) also observed that ethephon alone, and with mepiquat chloride, inhibited the root growth of barley 3 weeks after its application. There is little evidence in scientific publications to support claims that PGRs can strengthen either the stem base or the anchorage system. However, it must be recognised that only two studies have investigated the effects of PGRs by directly measuring stem and anchorage strength. More studies must be undertaken to investigate the effects of a wider range of PGRs, application rates and timings on the relevant plant characters before strong conclusions can be drawn about whether they can strengthen stems and anchorage.

4.

Grain Yield in the Absence of Lodging

Yield improvements are nearly always observed after PGRs have been used to reduce lodging. This should be expected given the large reductions in potential yield that are caused by lodging (described in Section II.A). Herbert (1982) observed yield increases of up to 40% following applications of chlormequat to reduce the amount of lodging in wheat. In the absence of lodging, the effect of PGRs on yield is more variable and appears to be determined by the type of PGR, timing of application, cereal species and growing conditions. Chlormequat has been shown to increase yield in 10 studies, decrease yield in two studies and have no effect in 23 studies (Table II). The reports of yield increases exist for almost all the major cereal species and can occur in response to PGR applications before or after the onset of stem elongation. Yield increases

252

P. M. BERRY ET AL.

could be as much as 25%, but were more commonly less than 15%. In several cases, the yield increases were associated with an increase in ear number. A survey of 45 commercial trials between 1973 and 1980 by Woolley (1981), in which chlormequat chloride was applied to winter wheat, and in which there was no lodging, showed that the average yield improvement with chlormequat was only 0.07 t ha21. Caldicott (1978) found that, in the absence of lodging, chlormequat increased yield by at least 0.3 t ha21 in one out of three trials. Across all trials, this resulted in a yield increase of 0.18 t ha21. In general, it appears that in some circumstances chlormequat has the potential to cause small yield increases in the absence of lodging, but the economic benefits derived will be marginal. Several mechanisms by which chlormequat could increase yield in the absence of lodging have been postulated and these are comprehensively reviewed by Rajala and Peltonen-Sainio (2000). Of the yield components, ear number is most frequently associated with chlormequat induced yield increases. Therefore, understanding how ear number is altered may help explain the variation in yield responses. Chlormequat has been shown to increase both tiller production (Wunsche, 1973) and tiller survival (Humphries, 1968; Koranteng and Matthews, 1982; Kettlewell et al., 1983). Green (1986) reviewed this literature and concluded that increased tiller survival was more common/likely and discussed two mechanisms by which chlormequat could cause this. These were through the reduction of apical dominance that results in more uniform tiller size (Matthews et al., 1982) or through delayed ear emergence (Humphries, 1968; Lowe and Carter, 1972). Increasing the ear number will only increase grain yield when the source of assimilates is not limiting. If it is limiting then either fewer grains will be set or/and the grains will be lighter and the effect of greater ear numbers will be countered. Several studies have shown that chlormequat reduces grain weight (Table II), which may be the evidence of the above theory. In the absence of lodging, ethephon has been shown to increase yield in three studies, decrease yield in 10 studies and to have no effect in 12 studies (Table III). The reports of yield decreases appear to be most frequent for spring or winter barley grown in north America when the ethephon was applied after the emergence of the flag leaf. The yield reductions could be as much as 50% and were caused by decreases in the number of grains per ear and grain weight, that outweighed increases in ear number. Evidence of similar yield reductions in Europe are more rare, although reductions in barley yields have been observed in the UK following the application of a mixture of ethephon and mepiquat chloride at GS39 (Woolley, 1981). The reduction in grains per ear has been attributed to both the promotion of late-appearing shoots with relatively few grains, and the abortion of distal florets on the main stems and early appearing tillers. The latter effect may be caused by ethephon’s gametocidal properties (Moes and Stobbe, 1991c; Bulman and Smith, 1993). Lauer (1991) suggested that the reduced grain weight was also due to more late-emerging tillers. Ethephon applications before


253

GS39 result in far fewer cases where yield is reduced (Table III). In the UK, rare yield improvements were observed in winter barley when ethephon and mepiquat chloride were applied before GS39 (Matthews and Thompson, 1983; White, 1995).

E. SUMMARY

OF

MANAGEMENT FACTORS

It is clear that most aspects of crop management result in large changes in lodging risk. The surprise is that many of these effects are not brought about by shortening the plant, but by increasing the strength of the stem base and anchorage system. Furthermore, the strengths of the stem base and anchorage system are often changed by different amounts for any change in management. This means that certain types of management would be expected to reduce one type of lodging more than the other. The effects of six types of management on the risk of stem and root lodging have been summarised by Berry et al. (2003b) in terms of changes to the failure wind speed (Table IV). This shows that stem lodging is best reduced by sowing on soils with less residual nitrogen and by reducing and delaying the amount of fertilizer applied in spring. Root lodging is best reduced by establishing fewer seeds and by rolling in spring to consolidate the soil. Delayed sowing and growth regulators were estimated to reduce stem and root lodging by equal amounts. The large effect on the chance of lodging caused by small changes in

Table IV Effect of Crop Management on the Wind Speed Required to Cause Stem or Root Lodging

Factor Less soil residual N (116–71 kg N ha21) Delayed sowing (per week, between 20 Sept and 1 Nov) Less plants established (per 100 plants m22, between 400 and 200 plants m22) PGRs (split chlormequat @ GS30/31) Delayed and less fertiliser N (target GAI of 5) Spring rolling (pre-GS30) Adapted from Berry et al. (2003a,b,c). a At 400 plants m22.

Increase in stem failure wind speed ms21

Increase in root failure wind speed ms21

2.3 (3.9a)

1.3

0.5

0.5

0.8

1.8

1.4

1.4

1.4

0.8

0

0.8

254

P. M. BERRY ET AL.

the failure wind speed is illustrated by the probabilities of experiencing different wind speeds above a UK wheat crop described in Fig. 10.

VI. AVOIDANCE THROUGH PLANT BREEDING A. EFFECTS

OF

DWARFING GENES

The Rht (reduced height) alleles began to be introduced into UK wheat varieties during the 1970s and are now part of the germplasm of most highyielding semi-dwarf varieties. The Rht alleles cause insensitivity to gibberellic acid, which reduces elongation of the internode cells and results in shorter plants. More extreme dwarfing alleles may reduce the number of internode cells. The Rht alleles do not appear to be expressed above the collar node (Lenton et al., 1987) and therefore have no direct effects on grain number and size. Rht1 and Rht2 alleles have made a vital contribution to the improvement of yields by enabling greater amounts of fertilizer to be used without causing an excessive risk to lodging. Pleiotropic effects for an increased harvest index have further added to the yield improvements associated with these alleles. Reduced stem growth rates allow more resources to be allocated to the developing ear, which results in a greater number of fertile florets and grains per ear. Greater competition for resources during grain filling usually results in smaller grains, but this seldom outweighs the effect of the greater number of grains, and yield is usually greater. In UK and German wheats, Rht1 and Rht2 alleles can reduce height by 14 – 17% independently of each other and by 42% when in combination (Flintham et al., 1997). Rht3 can reduce height by 59%, but has not yet been used in commercial varieties. In the UK, the Rht1 and Rht2 alleles have helped to reduce the height of wheat cultivars from over 1 m to about 0.7 m between the early 1970s and the mid-1990s (Shearman, 2001). Using the methodology described in Section VII.A, this height reduction can be estimated to reduce the leverage of a shoot from 320 to 115 Nmm. When the associated increases in grain yield (2.5 t ha21) and harvest index (0.1) over this period (Shearman, 2001) are also accounted for, the leverage is reduced by about 25%. Crook and Ennos (1994) and unpublished data indicate that breeders have not significantly altered stem and anchorage strength during the last few decades. It therefore appears that UK breeders have improved the lodging resistance of wheat through the reduction in height. This reduction in leverage has enabled the amount of nitrogen fertilizer applied to wheat to be increased from less than 100 kg ha21 in the early 1970s to nearly 200 kg ha21 in the 1990s (Gooding and Davies, 1997) without a dramatic increase in the incidence of lodging. In oats, the variety S172, released in 1939, has been reported to be Europe’s first dwarf cereal variety (Valentine et al., 2003). However, dwarfness in this and


255

several derived varieties was associated with small grains and a yield penalty. During the 1990s, shorter winter oat varieties have been released; e.g., in the UK cv. Gerald is 122 cm tall, which is approximately 20 cm shorter than many of its contemporary varieties (HGCA, 2003). This variety is thought to be responsible for much of the recent yield increases in this country. However, the genetic basis for its short straw is not known. Recently a dwarf line cv. Buffalo, has been released in the UK which is only 92 cm tall and is 5% higher yielding than cv. Gerald (HGCA, 2003). This variety contains the DW-6 dwarfing gene, which was discovered in a mutation programme in Canada (Brown et al., 1980) and has been shown to shorten the peduncle (Milach et al., 2002). This gene has been shown to reduce height by 20 – 75 cm, have thicker straw and to reduce lodging by large amounts (Valentine et al., 1997). Milach et al. (2002) showed that dwarf lines containing this gene responded to exogenously added gibberellic acid, so it does not appear to reduce height by the same mechanism as the Rht genes. Major dwarfing genes are common in spring barley. The ari-eGP dwarfing gene was found in cvs Golden Promise and Midas, which comprised over 70% of the Scottish barley crop from the mid-1970s to early 1980s. The ari-eGP gene was then superseded by the sdw1 dwarfing gene, such that by 1989 the percentages of certified seed carrying the sdw1 and ari-eGP genes were 74 and 8, respectively (Thomas et al., 1991). Currently, sdw1 cultivars are estimated to occupy over 85% of the certified seed but the ari-eGPs have fallen to 1.5%. There are no known major dwarfing genes in winter barley cultivars, so it seems likely that the height reduction in this species has come about as the result of accumulating minor genes (W. Thomas, personal communication).

B. POTENTIAL 1.

FOR

FURTHER PROGRESS

Conventional Breeding

There is great potential to continue increasing lodging resistance through further height reductions via the introduction of more extreme dwarfing genes such as Rht3 in wheat. However, several studies have shown that yield is reduced when crops are shortened too much (Allan, 1986; Kertesz et al., 1991; Baylan and Singh, 1994; Miralles and Slafer, 1995; Flintham et al., 1997). The reduction in yield appears to be exacerbated by high temperatures or drought stress. Flintham et al. (1997) showed that extreme dwarfs accumulated less overall biomass and had much lighter grains. Miralles and Slafer (1995) showed that dwarf wheat had more prostrate leaves that may reduce the efficiency with which light is converted into dry matter. The spread of foliar disease is also more rapid in short plants (Parker et al., 2002). Also, the ears of extreme dwarfs do not always fully emerge from the sheath of the flag leaf. As a result of one or a combination of these observations, Flintham et al. (1997) showed that the minimum height for

256

P. M. BERRY ET AL.

optimum grain yields is already being approached in UK and German wheats. A similar situation also seems likely for modern wheat varieties grown in other countries. There is evidence that the same problem could occur in oats because the DW-6 dwarfing gene has been associated with small grains, low kernal content and poor extrusion of the panicles from the flag leaves (Valentine et al., 1997). It therefore seems unlikely that much further improvement in lodging resistance can be made by continuing to shorten wheat crops and there may be only limited further shortening possible in other cereal species. As a result, breeders must target other plant traits to improve lodging resistance and counter greater yields. A model of wheat lodging (Berry et al., 2003a) has shown that changes in the strength of the stem base and anchorage system have a large effect on lodging risk. Large differences amongst wheat varieties have been observed for both these traits (Crook and Ennos, 1994; Berry et al., 2003b; Spink et al., 2003). The latter study showed that anchorage strength could vary from 206 to 587 Nmm and stem strength could vary from 122 to 175 Nmm between varieties. These differences were caused by a combination of wider, deeper root plates and stiffer roots for anchorage strength, and wider, thicker walled stems with a greater material strength for overall stem strength. In barley, differences in culm wall thickness have frequently been positively correlated with varietal differences in lodging resistance (Tandon et al., 1973; Jezowski, 1981; Dunn and Briggs, 1989). However, the study of Stanca et al. (1979) did not support these findings. The thickness of sclerenchyma cell walls has also been positively correlated with differences in lodging resistance between barley varieties (Cenci et al., 1984). It should be noted that these studies mainly focused on the stem characteristics and further studies may find genetic differences in the anchorage strength of barley. White et al. (2003) showed that plant height was not well related to the lodging resistance of winter oats, so it seems possible that varietal differences in stem and anchorage traits are also important in this cereal species. If oats and barley have a similar level of genetic variation in stem and anchorage strength as has been observed in wheat then there appears to be significant scope for breeders to improve the strength of the stems and anchorage systems of cereals.

2.

New Technologies

As outlined above, recent work has identified considerable genetic variation for stem failure moment and anchorage failure moment within the wheat cultivars. However, time-consuming measurements probably explain why these traits are seldom selected directly by breeders. New instrumentation for rapidly measuring these traits in the field, such as that recently developed by Berry et al. (2003c), could help over come this problem. Also, great potential lies in the identification of genetic markers for the strength characteristics since breeders


257

could use these to assist and hasten the selection of lodging-resistant lines in any environment. Several studies have identified Quantitative Trait Loci (QTL) for the incidence of lodging in wheat (Keller et al., 1999; Borner et al., 2002; Ma et al., 2002) and barley (Backes et al., 1995; Hayes et al., 1995; Larson et al., 1996). However, the most important QTLs identified by the studies were often associated with height differences and it is not possible to relate them to stem or anchorage strength. The only study of direct relevance to biophysical properties has been by Bruce et al. (2001) who provided the first clue of genes associated with anchorage strength in maize. This study discovered genes that have homology with a cytochrome P450 and an impedance-induced protein were expressed more in the root tissue of maize lines with high root lodging resistance. Other studies, which have investigated the genetic control of drought resistance, may also provide clues about the genetic control of anchorage. For example, QTLs have been detected for root-penetration ability, root thickness and root number in rice by Zheng et al. (2000) and Price et al. (2000), and in maize by Tuberosa et al. (2002). Studies with Arabidopsis mutants have shown that decreased stem strength is caused by deficiency in: cellulose deposition in the secondary wall (Turner and Somerville, 1997), differentiation of interfascicular fibers (Zhong et al., 1997) and lignin (Jones et al., 2001). Thus, the material strength of the stem wall is likely to be affected by several genes. Less is known about the genetic control of the geometric components of stem strength, stem diameter and stem wall width, although QTLs have been found for stem diameter in Populus (Bradshaw and Stettler, 1995).

VII. LODGING-PROOF IDEOTYPE A. QUANTIFYING

A

LODGING- P ROOF IDEOTYPE

In order to assess how to minimise lodging in the future it would be useful to describe a lodging-proof ideotype that could form the target for agronomists and breeders. This section attempts to do this for wheat because most is known about the lodging mechanism of this cereal species. If we assume that yield will continue to increase and the minimum crop height compatible with high yields is already being approached then there appears to be limited potential for avoiding lodging by minimising the base bending moment of the shoot. This is because two of the most important components of bending moment (Section IV.A): height at the centre of gravity of the shoot and ear area, are closely related to height and yield respectively. There may be some prospects for increasing shoot natural frequency by increasing the stem flexural rigidity. However, natural frequency has been shown to be negatively correlated with height at centre of gravity (Berry et al., 2000), so the overall reduction in leverage is likely to be small. It should be

258

P. M. BERRY ET AL.

possible to quantify the maximum base bending moment from the maximum wind gust possible above cereal-growing areas and from predictions of future yield and crop height. This will then determine the structural requirements of the stem base and anchorage system for lodging avoidance. Section IV.A has described how the base bending moment of a wheat shoot can be successfully calculated from several engineering parameters that describe the shoot, namely the height at centre of gravity, natural frequency and ear area. This section outlines and tests a method for calculating these parameters from crop height, grain yield and harvest index. This is then used to help define a lodging-proof ideotype. The components of height at centre of gravity (X) are stem length (SL), stem and leaf fresh weight (SW), ear fresh weight (EW) and ear length (EL). Berry (1998) showed that in theory these can be combined to calculate height at the centre of gravity [Eq. (7)] if the weight distributions of the shoot and ear are both assumed to be uniform X¼

ðSL SW þ 2SL EW þ EL EW Þ 2ðSW þ EW Þ

ð7Þ

Equations (8) –(10) show how the components of Eq. (7) can be calculated from crop attributes that are more commonly measured by crop physiologists, namely, grain yield, crop height, harvest index and ear number m22 EW ¼

Y=ð1 2 aÞ En

ð8Þ

SW ¼

EW ð1 2 aÞ 2 EW Hi

ð9Þ

SL ¼ h 2 E L

ð10Þ 22

In Eqs. (8) – (10), Y is grain yield (g m ), En the number of ears per metre square, a the ratio of chaff dry weight to total ear dry weight, Hi the harvest index and h the crop height to the tip of the ear (m). It is assumed that all plant tissues have a moisture content of 15% at harvest. The authors of the present paper have tested these equations by measuring Y, Hi, a, h, En and EL in crop samples taken from 0.72 m2 quadrats and X on 10 shoots taken from the same plot, but outside the quadrat. These measurements were taken at harvest time on seven winter wheat cultivars, each replicated three times. Figure 14 shows that these equations correctly account for differences in height at centre of gravity, but under-predict the measurement by about 7%. This is probably because dry matter was not uniformly distributed along the shoot, with more at the base than the top. The height at centre of gravity of shoots without their ear was shown to be 45% along their length (from the base). The natural frequency (nn) of the shoot can now be estimated from the height at centre of gravity using the empirical equation described by Berry et al. (2000).


259

Figure 14 Predicted and measured height at centre of gravity at harvest for seven winter wheat cultivars grown in the UK (52.58N, 1.38W) in 2002. Plant height ranged from 0.67 to 0.86 m, grain yield ranged from 6.9 to 12.0 t ha21 and harvest index ranged from 0.44 to 0.55. (—) 1:1 line. Best fit line, y ¼ 0:83x þ 0:14; R2 ¼ 0:82).

This has been modified to account for the developmental change in natural frequency between the stage when Berry et al. (2000) took measurements and harvest (Berry et al., 2003a). nn ¼

X 21:5 þ 0:3 4

ð11Þ

Our unpublished data has also shown that EW (g) can be related to ear area (A) (cm2) by A ¼ 3:3 þ 3EW

ð12Þ

Equation (12) was calculated from 450 pairs of data points measured on 15 winter wheat cultivars grown in the UK in 2002. The best fit line through the points had an R 2 value of 0.87 ðP , 0:001Þ: Thus, Eqs. (7) –(12) have shown how height at centre of gravity, natural frequency and ear area can be calculated from plant height, harvest index and yield. These parameters can now be used in Eq. (3) to estimate how changes to plant height, harvest index and yield affect the base bending moment of the shoot. If we define lodging proofness as a structure that can withstand the strongest wind likely to occur over a cereal crop once every generation (18 ms21) (Berry et al., 2003a), then the base bending moments described in Fig. 15 represent the minimum strength of the stem base required for lodging proofness. The anchorage strength required for lodging proofness must consider the number of shoots borne by the plant. In order to calculate Hi we assume that 0.5 m high crops have a straw weight (at 85% dry matter) of 6 t ha21,

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Figure 15 Effect of changes in grain yield on the base bending moment of a wheat shoot subjected to a 18 ms21 wind gust. Crop heights are 0.5 m (—), 0.7 m ( – – –) and 0.9 m (_).

0.7 m crops have 8 t ha21of straw, 0.9 m crops have 10 t ha21of straw and the ratio of chaff weight to ear weight (a) is 0.2.

B. CAN CEREALS

BE

MADE LODGING- P ROOF?

The strongest stem bases and anchorage systems that have been published for wheat are in the region of 200 and 550 Nmm, respectively (Berry et al., 2002). These anchorage systems supported 2– 3 shoots. Agronomic strategies for further strengthening these plants are quite limited because techniques for producing robust crops were employed by Berry et al. (2002). These included using one of the most lodging-resistant varieties used in the UK, establishing about 200 plants m22 in early October, and applying economically optimum amounts of nitrogen fertilizer after the onset of stem elongation. Opportunities for further strengthening the plants, whilst maintaining high yields, include reducing the number of plants established to about 100 m22 and rolling the soil before the onset of stem elongation. If we assume that the plant population effects observed by Berry et al. (2000) continue linearly below 200 plants m22 then reducing the plant population could be expected to increase the stem strength by 10% and the anchorage strength by 25%. Rolling could increase the anchorage strength by 25% (Berry et al., 2002). These changes could increase anchorage strength to more than 800 Nmm, however, the stronger anchorage would be partially countered by the increase in shoots per plant (to 3– 4) resulting from fewer plants per square metre. We estimate these structures will almost provide lodging


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proofness for 0.7 m tall crops yielding 8 t ha21, which is the current average wheat yield for many countries in north-west Europe. It therefore appears unlikely that future high-yielding crops can be made lodging proof using agronomic methods alone. This means that the large amount of genetic diversity already identified for stem and anchorage strength (Spink et al., 2003) must be exploited to help avoid lodging in the future. Progress can be made along this route using conventional breeding techniques, but there is also potential to hasten this process by using molecular genetic techniques to understand the genetic control of these traits. If it is assumed that current rates of yield improvement remain at 1 t ha21 decade21 then we estimate the strength of the stem base and anchorage system must increase by about 1% p.a. to counter the increased lodging risk. This seems achievable given the high level of variation in stem and anchorage strength already observed between modern wheat varieties. In addition to improving strength, it would be useful if further research could also investigate how crops can be made shorter whilst maintaining their yield potential. Studies must focus on designing a canopy architecture that enables maximum light interception and most efficient conversion to dry matter, whilst restricting the spread of splash borne diseases and successfully competing against weeds.

VIII. CONCLUSIONS A. PROGRESS

IN

UNDERSTANDING LODGING THE LAST 30 YEARS

DURING

Since the last major review of lodging in cereals (Pinthus, 1973), there have been several areas relating to lodging where understanding has improved significantly. (1) The recognition by the farming industry that lodging occurs due to both buckling of the stems and overturning of the anchorage system has been a major step forward for improving lodging control. Whilst Pinthus (1973), and previous researchers, had observed both forms of lodging it appears that much of the farming industry perceived that stem lodging was the main problem. As a result of this controls were not specifically targeted at reducing root lodging (Section II.A). (2) One of the most improved areas of understanding has resulted from a collaboration between biologists and wind engineers. This partnership enabled the interaction between the wind and the wheat canopy to be modelled and as a result the wind-induced bending moment (leverage) on the base of the plant can now be calculated (Section IV.A).

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(3) A significant amount of research has focussed on elucidating the mechanism of anchorage failure during root lodging. This has resulted in more than one model for anchorage failure which identify the importance of several root and soil parameters in this process (Section IV.C). (4) Improved understanding of the lodging mechanisms have enabled the development of a comprehensive and realistic model of wheat lodging. This has been used to show that relatively few plant characters determine the lodging risk of wheat. These include the height at centre of gravity, natural frequency and ear area of a shoot, the stem diameter, wall width and material strength of the stem base and the spread and depth of the root plate. This approach also developed a new term for measuring lodging risk—“failure wind speed”. This term has the advantage of quantifying differences in the lodging risk of crops irrespective of their environment (Section IV.D). (5) The effects of crop husbandry on lodging is now more fully understood (Section V). This is particularly true for wheat where models have been used to explain lodging observations in terms of which plant characters are influenced. This showed that husbandry can affect lodging risk by changing the leverage of the shoot, or stem strength or anchorage strength. Interestingly, this showed that PGRs reduce lodging risk by reducing plant height and there is very little evidence that they strengthen stems or anchorage systems (Section V.D). (6) Over the last 30 years, breeders have countered the greater lodging risk caused by heavier yielding crops by breeding shorter plants. However, there is evidence that the minimum height that is compatible with high yield is being approached in some cereals. Therefore, breeders must exploit the large amount of genetic variation in the strength of the stem and anchorage system to continue producing lodging-resistant varieties.

B. FURTHER UNDERSTANDING REQUIRED (1) To date, most lodging research has concentrated on wheat. This has enabled models of the lodging mechanism to be developed, which have been used to identify the critical plant characters, quantify the effects of factors on lodging and elucidate the mechanisms by which these effects are caused. Understanding about lodging in other cereals, such as barley and oats, lags far behind wheat. In order to replicate the advances made in wheat, the next step must be to model the lodging mechanisms in these cereals. This will not be a trivial task. For example in barley, greater stem flexibility, the presence of awns and the fact that stems can buckle at any point mean that a barleylodging model will be significantly different from wheat.


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(2) In wheat, it appears that the greatest improvement in lodging risk can be made by strengthening the stem base and anchorage system. This review showed that there is considerable genetic variation in these plant characters that has not yet been exploited by breeders. For this to happen, rapid assessment techniques must be developed. These may be via the identification of genetic markers or through the development of novel instrumentation for rapidly measuring stem and anchorage strength. (3) So far, lodging research has concentrated on the time period when crops can lodge. As a result, there is no way of predicting the likelihood of lodging from earlier stages of crop development. Therefore, further research must study the development of the lodging-associated plant characters with the objective of predicting lodging from early assessments of the crop. Any prediction scheme must predict lodging risk before, or soon after, the onset of stem elongation to enable growers to alter their husbandry tactics (PGRs, fertilizer, rolling) accordingly. (4) This review has demonstrated the importance of soil strength in affecting the risk of root lodging. However, models for predicting soil strength are largely inadequate because they are either applicable to a narrow range of soil types, do not account for all the major factors and their interactions or are based on remoulded soils. Further work must quantify the effects on soil strength of texture, water content, bulk density, organic matter as well as quantifying any interactions. (5) The progressive nature of root lodging must be investigated to improve the predictive ability of lodging models. (6) PGRs reduce lodging risk by shortening crops, but there is little published evidence that they can strengthen the stems and anchorage system. Further research should investigate the effect of existing PGRs on stem and anchorage strength as well as focusing on discovering new growthregulating chemicals that strengthen these traits.

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ALTERING FATTY ACID COMPOSITION IN OIL SEED CROPS Joe W. Burton,1 Jerry F. Miller,2 B. A. Vick,2 Rachael Scarth3 and C. Corley Holbrook4 1

USDA-ARS, Soybean & Nitrogen Fixation Unit, Raleigh, North Carolina, USA 2 USDA-ARS, Northern Crop Science Laboratory, Fargo North Dakota, USA 3 University of Manitoba, Faculty of Agricultural & Food Science, Manitoba, Canada 4 USDA-ARS, Crop Genetics and Breeding Unit, Tifton, Georgia 31793, USA

I. Soybean A. Introduction B. Unsaturated Fatty Acids C. Saturated Fatty Acids D. Genetic Engineering Soybean Oil with Novel Fatty Acids II. Sunflower A. Introduction B. Nusun Sunflower Oil C. Reducing Saturated Fatty Acids in Sunflower Oil D. Tocopherol Role in Nusun Sunflower Oil III. Brassica A. Intraspecific and Interspecific Crosses B. Mutagenesis C. Transformation D. Production of Modified Oil Cultivars IV. Peanut A. Introduction, Breeding Objectives, and Rationale B. Increasing Oleic Acid References World consumption of vegetable oils increased steadily in the last decade, from 62.6 million metric tons (MMT) in 1993 to 87.8 MMT in 2000 (Goblitz, 2002). This demand has been primarily due to increased use of edible oils in food preparation. Yet, vegetable oils are being used in many industrial products including fuels. Part of this has resulted from alteration of the fatty acid composition of vegetables oils making them more versatile in their uses. The four major oilseed crops are soybean (Glycine max L. Merr.), sunflower (Helianthus annuus L.), rapeseed (Brassica), and peanut (Arachis hypogaea L.). The seed oil of these has been genetically altered through standard plant breeding methodology and molecular genetic engineering. The following


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I. SOYBEAN A. INTRODUCTION Oil from soybeans is in high demand and is the most plentiful seed oil being produced. Each year, consumption nearly equals production. Even though soybean oil is generally considered to have lower intrinsic quality than other vegetable oils, production and use increased each year in the last decade. Currently, soybean oil accounts for about 44% of edible vegetable oil produced. About 1/3 of the oil produced is consumed in the US. Increased demand for soybean meal is a major reason for the increase in soybean oil production. Some will argue that soybean should be considered a protein-seed rather than an oil-seed because the amount of protein meal produced is about four times the oil produced. In this sense, soybean oil is a valuable byproduct of meal production, and continued demand for high quality soyprotein meal insures the production of a large supply of soybean oil. Because production and consumption of soybean oil is so large, there has been a desire to improve the nutritional and functional quality of the oil through genetic alteration of the soybean seed lipids. Most of this work has been done using traditional plant breeding methods. More recently, molecular genetic engineering has also been used. While there are no popular cultivars today with radically different oil quality, considerable progress has been made over the past 20 years in the development and release of improved germplasm with altered oil composition. Breeding goals vary, but the following would be considered by most oil users to be improvements: 30 g kg21 or less linolenic acid, 70 g kg21 or less total saturated fatty acids, and 550– 650 g kg – 1 oleic acid. There is also research to increase saturates, stearic and/or palmitic acids. There is germplasm with both traits. If a higher saturated soybean oil proves to be useful to the food industry, then this trait might be added as a breeding objective. Transgenic research is being used to bring fatty acids that are different from those normally found in soybean oil.

B. UNSATURATED FATTY ACIDS 1.

Decreasing Linolenic Acid Concentration

Reduction of linolenic acid in soybean oil was proposed by Howell et al. (1972) over 30 years ago. They cited evidence that linolenic acid is broken down

ALTERING FATTY ACID COMPOSITION IN OIL SEED CROPS 275

by enzymes or spontaneous oxidation to form secondary products that give the oil a bad odor and flavor. At that time, cooking oil was routinely hydrogenated in processing to lower the concentration of linolenic acid. Thus, reduction of hydrogenation costs in oil processing was the primary benefit associated with a genetically altered soybean oil. Today, because of public concern about trans fatty acids produced in the hydrogenation process, oil processors want a more stable oil that requires less hydrogenation. Results from initial breeding research suggested that concentrations of unsaturated fatty acids in soybean oil were polygenic traits (Howell et al., 1972). Therefore, C.A. Brim (USDA-ARS, NC State University) applied recurrent mass and within half-sib family selection to a population that had two plant introductions (PI90406 and PI92567) in the parentage. Both of these lines had relatively higher oleic acid and lower linolenic acid than standard cultivars. Because linolenic acid results from the consecutive desaturation of oleic acid and linoleic acid, concentrations of oleic acid and linolenic acid are negatively correlated. Brim selected for higher oleic acid concentration as a way to indirectly decrease linolenic acid concentration. In this experiment, oleic acid was increased from 227 to 416 g kg21 in eight cycles of selection, and linolenic acid decreased from 87 to 59 g kg21 (Carver et al., 1986). This increase in oleic acid had very little effect on the saturated fatty acids. A line, N78-2245, derived from the fifth cycle of this experiment was the source of genes for higher oleic acid in subsequent research. Work with N78-2245 showed that the low-linolenic phenotype was quite sensitive to environmental differences (Carver et al., 1983). To stabilize this trait, N78-2245 was mated with PI123,440, a plant introduction with low linolenic acid concentration compared with other accessions in the soybean germplasm collection, for maturity groups V to VIII. This mating produced progeny in the F3 generation that ranged from 3.4 to 10.9% linolenic acid. Because the extremes in this phenotypic distribution were transgressive segregates when compared with either parent, a combination of at least two different gene loci, one from N78-2245 and one from PI123,440, must have been responsible. Because N782245 had a relatively high oleic acid concentration, it was thought that the gene or genes from that parent were responsible for less desaturation of oleic acid (Wilson and Burton, 1986). The gene contributed by PI123,440 was thought to cause less desaturation of linoleic acid. Further work with these materials led to the development and registration of the germplasm line, N85-2176, which has 44% oleic and 3.3% linolenic acid (Burton et al., 1989). Linolenic germplasms have also been developed through mutagenesis. Wilcox et al. (1984) treated seeds of the cultivar “Century” with the mutagen, ethyl methanesulfonate (EMS). In screening 5000 M2 plants, one was found that had oil with 34 g kg21 linolenic acid and in this case, oleic acid was not unusually high, 22 g kg21, compared to 191 g kg21 for Century. This line was designated C1640. Subsequent studies of the inheritance of this trait revealed it to be controlled

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by a single recessive gene (Wilcox and Cavins, 1985) and the gene symbol fan was assigned to the mutant (Wilcox and Cavins, 1987). The heterozygote Fan/fan was found to be intermediate to the two homozygotes (Table I). They also found that the low-linolenic trait segregated among F2 seeds from a single F1 plant indicating that it was under embryonic rather than maternal control. Another low linolenic acid germplasm line, A5, was developed through mutagenesis by Hammond and Fehr (1983). They treated seeds of a line FA9525, with EMS. This line had lower linolenic acid and higher oleic acid than standard cultivars. The line A5 (3.9% linolenic acid) was selected from the M4 generation. A fourth source of low linolenic acid germplasm, PI361088B, was identified by Rennie et al. (1988). Rennie and Tanner (1989, 1991) have shown that the three sources, (PI123,440, A5, and PI316088B) carry genes that are either allelic or identical to the fan allele in C1640 (Table I). Variation in phenotype among the three suggests that background genotype is also influential in actual oil composition. Other mutations at this locus have been reported. One was found in Japan by X-ray irradiation of seeds of the cultivar Bay (Rahman et al., 1996b). This mutant in line M-5 has 51 g kg21 linolenic acid. The other mutation was developed in Canada by EMS mutagenesis of C1640. This mutant allele in

Table I Sources of Soybean Germplasm with Reduced Concentration of Linolenic Acid in Seed Lipids, Their Phenotype, and Alleles Associated with the Germplasm Genotype Germplasm Centurya C1640 PI123,440 PI361,088B A5 A23 A16 RG10 M5 M-24 Bayb A29 a

Locus 1

Locus 2

Locus 3

Linolenic acid (g kg21)

Reference

fan3/fan3

72 52 32 49 38 51 56 22 ,25 51 24 61 92 13

Wilcox and Cavins (1985) Wilcox and Cavins (1985) Wilcox and Cavins (1985) Wilson and Burton (1986) Rennie et al. (1988) Fehr et al. (1992) Fehr et al. (1992) Fehr et al. (1992) Stojsin et al. (1998) Rahman et al. (1998) Rahman et al. (1998) Rahman et al. (1998) Rahman et al. (1998) Ross et al. (2000)

Fan/Fan Fan/fan fan/fan fan/fan fan/fan fan/fan fan/fan fan-b/fan-b fan/fan fan/fan Fan/Fan Fan/Fan fan/fan

fan2/fan2 fan2/fan2 Fanx/Fanx fanxa/fanxa fanxa/fanxa Fanx/Fanx fan2/fan2

Century is a cultivar which was mutagenized to produce C1640 fan/fan genotype. It is presumably wild-type at the second locus. b Bay is a cultivar which was mutagenized to produce M5 and M-24.


soybean line RG10 further lowers linolenic acid to , 25 g kg21. This allele has been designated fan-b (Stojsin et al., 1998). A second locus, fan2 was discovered by Fehr et al. (1992) in the line A23, which had been selected for its high palmitic acid content. When both recessive loci are combined in the homozygous condition in the line A16 ( fan/fan fan2/fan2), linolenic acid is reduced to 2.2% (Fehr et al., 1992). Combining recessive alleles at a third locus, fan3, with fan/fan and fan2/fan2 reduced the linolenic acid to 13 g kg21 (Ross et al., 2000). In Japan, Rahman et al. (1998) have also discovered a gene locus independent of fan that reduces linolenic acid. This gene was also mutagenized by irradiating seeds of cultivar Bay. This gene that they designated, fanxa, in combination with fan produces 2.4% linolenic acid. Because soybean is an ancient diploidized tetraploid, there are many duplicate gene loci. Thus, it is likely that fan2 and fanxa are mutations at the same locus. Most of the linolenic acid in soybean oil is synthesized by a mircosomal omega-3 desaturase that catalyzes desaturation of 18:2-PC (linolenic acid esterified to phosphotidylcholine) to 18:3-PC. A single gene, FAD3, has been cloned that encodes an omega-3 desaturase. Using Southern blot analysis, Byrum et al. (1997) has shown that the cDNA encoding the omega-3 desaturase from the A5 mutant, has a DNA fragment missing. This suggests that the low-linolenic phenotype in A5 is at least partially due to a deletion in the FAD3 gene. Thus, fan is probably a FAD3 gene. The other locus, fan2, showed no DNA polymorphism between the mutant and wild-type. However, because soybean genomes possess more than one isoform of the FAD3 gene, it is possible that the fan2 locus corresponds to a second copy of the omega-3 desaturase gene that was mutagenized in A23. Blocking the FAD3 gene expression, via gene silencing molecular techniques, which should suppress the activity of all FAD3 isoforms, soybean lines with , 1.5% linolenic acid were produced (Kinney, 1995).

2.

Increasing Linolenic Acid Concentration

Oils with high levels of polyunsaturates would have application in the manufacture of lubricants and drying oil. Also, linolenic acid is an omega-3 fatty acid, which is essential in mammalian diets. So there is some interest in a high linolenic acid oil from a nutritional standpoint. It would seem, however, that the instability of such an oil would require that the high-linolenic soybean be consumed as a vegetable or as tofu or some other soyfood. Two sources of increased linolenic have been reported. One was developed by Takagi et al. (1989) through mutagenesis using X-ray irradiation of seeds of the cultivar Bay. This mutant B739, has 130 g kg21 linolenic compared with Bay at 90 g kg21. Some plant introductions in the wild soybean collection have elevated

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levels of linolenic acid (Pantalone et al., 1997). One of these, PI424031, has 150 g kg21 linolenic. Crosses between G. max and G. soja yielded a line with 13 g kg21 linolenic.

3. Increasing Oleic Concentration As previously mentioned, oleic acid was increased in a recurrent selection experiment (Carver et al., 1986). Continued recombination and selection of these higher oleic materials have resulted in a . 550 g kg21 oleic phenotype (Wilson et al., 2003). The inheritance of this oleic phenotype is being determined, and it is being incorporated into higher yielding materials. Two higher oleic mutants have been created in Japan through irradiation of the cultivar Bay (Rahman et al., 1996a). These mutants M23 and M11 have 530 and 390 g kg21 oleic acid, respectively. Segregation analysis of F1, F2, and backcrosses between the two mutants and between the two mutants and Bay, shows that a single locus is involved. They have designated the allele in Bay as Ol, the allele in M23 as ol, and the allele in M11 as ola. The gene Ol is partially dominant to ol, and ola is completely dominant to ol. They found no maternal or cytoplasmic effects. Desaturation of oleic to linoleic acid is catalyzed by microsomal omega-6 desaturases. There are at least two of these, FAD2-1 and FAD2-2. FAD2-1 is expressed only in the seeds and the other, FAD2-2, is expressed constitutively in all tissues (Heppard et al., 1996). Silencing the FAD2-1 gene in somatic embryos and subsequent regeneration into plants has resulted in transgenic soybean lines with very high . 800 g kg21 oleic acid content (Kinney, 1995). These single gene manipulations are successful in dramatically changing oleic acid. But previous research suggests that the end phenotype in a field situation may be under a more complex genetic control. For instance, it has been shown that oleic acid can be influenced by the maternal genotype. Brim et al. (1968) and Erickson et al. (1988a) have demonstrated this effect with reciprocal crosses between low and mid-oleic lines. This effect was further demonstrated using reciprocal grafts between mid-oleic line N78-2245 and the cultivar Essex (Carver et al., 1987). When “Essex” as scion was grafted to a N78-2245 stock and then defoliated after pods had set, the fatty acid concentrations of Essex seeds became more similar to those of N78-2245 seeds. For instance, oleic acid of Essex seeds changed from 17.8 g kg21 as an autograft to 38.3 g kg21 as a defoliated scion N78-2245. Likewise, the oleic acid of N78-2245 decreased from 50.1 g kg21 as an autograft to 27.6 g kg21 as defoliated scion. Because this effect was greatest when the scion was defoliated, it was concluded the maternal influence on fatty acid composition is expressed via translocated factors that probably originate in leaf tissue.


Several experiments have shown that temperature affects unsaturated fatty acid synthesis. An experiment by Howell and Collins (1957) showed shifts in linolenic acid of 4.3 percentage points in day temperatures that range from 21 to 298C. Heppard et al. (1996) looked at the affect of temperature on transcription levels of both FAD2-1 and FAD2-2 genes. They studied plants of the soy cultivar Rye at temperatures from 32/28 to18/128C. In both leaf and seed tissues, linoleic and linolenic acid decreased as temperature increased, however transcript levels of FAD2-1 and FAD2-2 were relatively constant in developing soybean seeds at the different growth temperatures. Thus, temperature must be acting at the translational or post-translational levels, perhaps by altering desaturase enzyme activity or stability.

C. SATURATED FATTY ACIDS 1.

Reducing Saturated Fatty Acids Concentrations

Medical studies have shown diets high in saturated acyl components, palmitic and stearic fatty acids may contribute to increased blood serum cholesterol levels. High blood cholesterol increases the risk of coronary heart disease. Accordingly, substantial markets have emerged for low saturate oils, with FDA labeling regulations requiring that a “low-saturated” vegetable oil must contain , 70 g kg21 total saturates. Although soybean oil is relatively low in total saturates (120 – 140 g kg21), a 50% reduction in saturated fat is needed to enhance the utility of soybean oil in this new market. When one considers the large amount of soybean oil annually consumed in the US (< 12 million pounds), a 50 g kg21 reduction in the saturated fats of soybean oil would have a significant impact on saturated fat consumption of our population without dietary change. Of the two saturated fatty acids in soybean oil, palmitic and stearic, palmitic is of the greatest concentration and has received the most attention. In fact from a health standpoint, palmitic has been identified as the more problematic of the two. Studies have shown that a minimum of two loci control the low palmitic acid trait in soybean. The additive allele, fap1, was obtained as a mutation following EMS treatment of seeds of the cultivar “Century” (Erickson et al., 1988b). Inheritance studies showed a 12 g kg21 decrease in palmitic acid with each additional copy of fap1. Fehr et al. (1991) developed a mutant line, A22, containing the fap3 allele, which segregates independently of fap1. Palmitic acid concentration in A22 is approximately 70 g kg21 (Stoltzfus et al., 2000). Another low palmitic genotype, N78-2077-12, (Burton et al., 1994) was selected from the 5th cycle of recurrent selection for increased oleic acid (Table II). A critical step in biosynthesis of palmitic acid in soybean seeds is release of free palmitic acid from 16:0-ACP in the plasmid, followed by its transport into the cytoplasm where it becomes esterified to CoA. The enzyme involved

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Table II Sources of Soybean Germplasm with Reduced Concentrations of Palmitic Acid in Seed Lipids, Their Phenotype, and Alleles Associated with the Germplasm Genotype Germplasm Century C1726 N79-2077-12 C1943 N94-2575 A8

Locus 1

Locus 2

Palmitic acid (g kg21)

Reference

Fap1/Fap1 fap1/fap1 Fap1/Fap1 fap1/fap1 fap1/fap1 fap1/fap1

Fap3/Fap3 Fap3/Fap3 fapnc/fapnc fapnc/fapnc fapnc/fapnc Fap3/fap3

111 84 60 40 39 44

Erickson et al. (1988b) Erickson et al. (1988b) Burton et al. (1994) Burton et al. (1998) Burton et al. (1998) Fehr et al. (1991)

is the 16:0-ACP thioesterose, which is encoded by the Fat B gene. Southern blot analysis has shown that N78-2077-12 has a deletion in one isoform of the Fat B gene (Wilson et al., 2001). Segregation analysis has shown the gene, fapnc, to be allelic to fap3. However, Southern analysis has shown that unlike fapnc, fap3 is not a Fat B deletion (Wilson et al., 2001). Nevertheless, either fap3 or fapnc in combination with fap1 reduces palmitic to 4% or less (Fehr et al., 1991; Wilcox et al., 1994). Another interesting part of this picture is that even though the biosynthetic pathways for fatty acids and triacylglycerol are well understood, heritable genetic variation for modifiers that affect reduced saturated fatty acid content can be found. Rebetzke et al. (1998) developed lines from a single cross that were homozygous for normal and reduced palmitic acid alleles. Palmitic acid ranged 19 g kg21 in the first and 15 g kg21 in the second. Heritabilities of this variation were 83 and 86. Results for stearic acid were similar with heritabilities of 85 and 89. Another set of materials from a different cross yielded similar results (Rebetzke et al., 1998). Thus attempts to move the reduced palmitic trait into cultivated soybean should be made emphasizing selection for alleles of major and minor effect.

2.

Increasing Saturated Fatty Acids Concentrations

In the US, concerns about heart disease risk by consumers prompted food industries to sharply decrease their use of tropical oil due to their high-palmitic acid content. Because saturated fats (solid fats) are needed for many food products, cottonseed oil has been substituted for tropical oil. Soybean oil is also hydrogenated to increase the saturated fatty acids. It has been suggested that soybean oil with high stearic acid might be used instead as a replacement for tropical oils and decrease the need for hydrogenation. Stearic acid does not pose the same health risk for coronary heart disease that palmitic acid does and would

ALTERING FATTY ACID COMPOSITION IN OIL SEED CROPS 281 Table III Sources of Soybean Germplasm with Increased Concentration of Stearic Acid in Seed Lipids, Their Phenotypes, and Alleles Associated with the Germplasm Genotype Line

Locus 1

Locus 2

Stearic acid (g kg21)

FA8077 A81-606085 A6 FA41545

Fas/Fas fas/fas fasa/fasa fasb/fasb

? ? ? ?

43 187 304 155

Reference Graef et Graef et Graef et Graef et

al. al. al. al.

(1985) (1985) (1985) (1985)

thus have a definite advantage if it had the processing qualities needed by the food industry. There are three alleles at a single locus that cause an increase in stearic acid concentration, fas, fasa and fasb (Graef et al., 1985). All three were developed by chemical mutagenesis. The fas and fasb alleles (Hartman et al., 1997), both increase stearic acid about 4-fold, fasa causes a 7-fold increase (Table III). There is evidence that another locus may be involved (Bubeck et al., 1989; Rahman et al., 1997). There are also mutants that cause increases in palmitic acid (Table IV; Erickson et al., 1988b; Bubeck et al., 1989; Stoltzfus et al., 2000). These may be useful if it is determined that the optimum saturated fatty acid content for solid products such as margarine and shortening require some combination of increased palmitic and stearic acid. One locus with two alleles, fap and fap2-b, cause increases of palmitic acid from 120 to 180 and 210 g kg21, respectively. A second locus, fap4, causes increases to 180 g kg21. Combining fap2-b and fap4 raises the concentration of palmitic acid above 250 g kg21 (Schnebly et al., 1994). Three other loci, fap5, fap6, and fap7 have been identified (Stoltzfus et al., 2000) which separately have palmitic acid concentrations between 140 and 160 g kg21 (Table IV). These loci can act additively to increase palmitic acid. A line homozygous for fap2-b, fap4, fap5, and fap7 alleles had 402 g kg21 palmitic acid.

D. GENETIC ENGINEERING SOYBEAN OIL NOVEL FATTY ACIDS

WITH

Because the biosynthetic pathways for fatty acid and triacylglycerol synthesis in oil seeds are well understood, and many of the genes cloned, they can be manipulated using molecular genetic techniques. Given the large number of fatty acids that exist in the oil of exotic oil seed species, A.J. Kinney of DuPont Agricultural Products says “there should be no theoretical barriers to producing exotic fatty acids in temperate oil seed crops” (Kinney, 1997). One exotic species

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Table IV Sources of Soybean Germplasm with Increased Concentration of Palmitic Acid in Seed Lipids, Their Phenotypes, and Alleles Associated with the Germplasm Genotype Line

Locus 1

Locus 2

Locus 3

Locus 4

Palmitic Locus 5 acid (g kg21)

Century Fap2/Fap2

86

C1727

fap2/fap2

173

A21

fap2-b/fap2-b

200

A24

fap4/fap4

180

A19

fap2-b/fap2-b fap4/fap4

.280

A27

fap5/fap5

A25

162 fap6/fap6

A30 fap2-b/fap2-b fap4/fap4 fap5/fap5

159 fap7/fap7

146

fap7/fap7

402

Reference Erickson et al. (1988b) Erickson et al. (1988b) Schnebly et al. (1994) Schnebly et al. (1994) Schnebly et al. (1994) Stoltzfus et al. (2000) Stoltzfus et al. (2000) Stoltzfus et al. (2000) Stoltzfus et al. (2000)

of interest “meadow foam” (Limnanthes douglasii) has a high content of C20 and C22 fatty acids with D5 unsaturation. Eicosenoic acid (20:1 D5) accounts for 60% of the total fatty acids. This oil is useful in cosmetics, surfactants and lubricants. Using particle bombardment, Cahoon et al. (2000) transformed soybean somatic embryos with cDNAs of a D5-desaturase gene and a FAE1 (fatty acid elongase) homolog, with a strong seed specific promoter. The desaturase and elongase genes were expressed in the somatic embryo, and in some embryos, eicosenoic acid accumulated to amounts 18% of the total fatty acid. In another example, Kinney reports transferring an epoxy fatty acid gene from Vernonia to soybean and producing soybean oil containing 10% D12 epoxy fatty acids. These oils are useful for PVC plasticizer application. A third example involves the production of conjugated double bond fatty acids, a class of fatty acids in which the double bonds are not separated by a methylene group as is found with conventional fatty acids. These are the fatty acids in tung oil and are the drying agents in paints and inks. Cahoon et al. (1999) isolated a class of cDNAs which represent a divergent form of the D12-oleic acid desaturase found in Momordica charantia and Impatiens balsamina tissues that accumulate a-eleostearic (18:3 D9cis11trans13trans) and a-parinaric (18:4 D9cis11trans13trans15cis) acids. Soybean somatic embryos transformed with


these cDNAs accumulated both a-eleostearic and parinaric acids to a combined level of 17% of the total fatty acids. While all of the above genetic alterations of soybean oil hold promise, the percentage of the novel fatty acid produced within the soybean is much lower than is observed in the native species in which these fatty acids are found, and their yields need to be increased significantly before such products can become commercially viable. Suboptimal substrate specificities of the cognate acyltransferases in the lipid biosynthetic pathways or lipase activities may be limiting the accumulation of the novel fatty acids into soybean triacylglycerols. Furthermore, the process of getting these materials from the lab to the farm to the processor to the end user is complicated. Strong economic incentives are needed before new oil products are developed and commercialized. Health claims or labeling regulations represent additional complicating factors. For the farmer, a new oil cultivar must have very good yielding ability or they will probably be unwilling to produce it. Even so, reducing saturates, increasing oleic acid and decreasing linolenic should make cooking oil that is superior in quality and functionality to current standard soybean oil. If the demand by oil users for this type of oil continues to increase, eventually there may be large scale commercial production of soybeans with this type oil.

II. SUNFLOWER A. INTRODUCTION Traditional high-linoleic sunflower (Helianthus annuus L.) oil has been viewed as a healthful vegetable oil with desirable flavor and is considered a premium oil in world markets because of its high percentage of polyunsaturated fatty acids. Its popularity in European and East Asian countries for salad oil, cooking oil, or for margarine production was based on its oil composition and the absence of cholesterol. Selection of an oil for frying purposes depends on several criteria: (1) oxidative stability, (2) product flavor, (3) product texture, (4) mouth feel, (5) availability, (6) cost, (7) nutritional needs, and (8) consumer issues (Gupta, 1998). Most important of these criteria are oxidative stability and product flavor. Unlike soybean and canola oils, sunflower oil has negligible linolenic acid, which is highly susceptible to oxidation. Thus, when soybean and canola oils are used as frying oils, they typically require partial hydrogenation to eliminate linolenic acid. Hydrogenation leads to the formation of trans fatty acids, which are dietary risk factors for cardiovascular disease. Increasing the oleic acid concentration of sunflower oil increases its oxidative stability without the need for hydrogenation, thus eliminating trans fatty acids and any related consumer issues regarding this

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Table V Fatty Acid Composition of NuSun Sunflower Oil, Traditional Sunflower Oil, and Olive Oil Oil type Fatty acid

NuSun sunflower (g kg21)

Traditional sunflower (g kg21)

Olive (g kg21)

Oleic Linoleic Saturated Linolenic

630 270 90 10

230 720 130 10

770 80 140 10

subject. However, a threshold level of linoleic acid must be maintained for acceptable product flavor. A low saturated fat concentration would be beneficial to consumers concerned with dietary requirements and cardiovascular disease. A report by USDA-ARS scientists (Miller et al., 1987) creating a mid-oleic level of oleic acid prompted E.D. Campbell of Archer Daniels Midland Co. in Decatur, IL, and M.K. Gupta, formerly with the Frito Lay Co. in Plano, TX, to recognize the potential of oleic-enhanced sunflower oil for the frying industry. In meetings with the National Sunflower Association (Bismarck, ND), a task force was formulated to investigate the creation of a mid-oleic sunflower oil, which would be given the trademark NuSun. The composition of NuSun sunflower oil was defined as 550– 650 g kg – 1 oleic acid, 200 –280 g kg21 linoleic acid, less than 90 g kg21 saturated fatty acids, and 1 g kg21 linolenic acid. Comparisons of NuSun to traditional sunflower oil and olive oil are made in Table V. The objectives of the USDA-ARS Sunflower Research Unit were to investigate the genetic inheritance of oleic acid concentration in sunflower oil and to initiate hybrid trials testing the feasibility of NuSun hybrids in sunflower production areas of the US. Also, studies to lower the saturated fatty acid level of sunflower oil were initiated. The feasibility of changing the homologue of tocopherol from a-tocopherol presently in sunflower oil to g-tocopherol is also a breeding objective. With stronger antioxidant properties than a-, g-tocopherol in combination with mid-oleic fatty acid levels could significantly increase the oxidative stability of the oil.

B. NUSUN SUNFLOWER OIL 1.

Inheritance

The development of a sunflower with a high oleic acid concentration was first reported by Soldatov (1976). Seed of the variety VNIIMK 8931 was treated with a 0.5% solution of dimethyl sulfate, a chemical mutagen. Seed was advanced to the M3 generation and screened for differing levels of oleic acid. The individual


seeds that were selected contained about 500 g kg21 oleic acid. By bulking the superior plants with high-oleic concentration, the Pervenets variety was created and released to producers in Russia by the VNIIMK research center (Pukhalsky and Dvoryadkin, 1978). Seed of this cultivar grown in North Dakota averaged 699 g kg21 with individual plants having as high as 900 g kg21 of oil (Miller et al., 1987). Oil from seed of 46% of the plants had . 800 g kg21 and 21% had , 600 g kg21 oleic acid concentration. In 1978, Russian scientists reported that they had created breeding lines with oleic concentrations as high as 895 g kg21 (Pukhalsky and Dvoryadkin, 1978). Seed of the Pervenets variety (PI 483077) was planted in the 1982 spring greenhouse of the USDA-ARS Sunflower Research Unit at Fargo, ND, and plants were self-pollinated. Plants were harvested and the fatty acid composition of the self-pollinated seed was determined by capillary gas chromatography. Ten selections were made, each having an oleic acid concentration greater than 850 g kg21, and analysis of single seeds of these plants confirmed that they were homozygous for oleic acid concentration. Four of these plants, designated Pervenets 302, 304, 305 and 306, were utilized to determine the inheritance of the high oleic acid trait in sunflower. Plants of the inbred line HA 89, a traditional high-linoleic sunflower line, were hand-emasculated and pollinated with the Pervenets selections. At maturity, seed of the parental self-pollinated plants and F1 crosses were harvested and fatty acid composition was determined. The seed oil of the Pervenets selections averaged 846 g kg21 of oleic acid, whereas HA 89 averaged 110 g kg21 (Table VI). The average oleic acid concentration of the F1 crosses was 520 g kg21 of oil when the high-oleic Pervenets selections were used as the female parent. This cross was

Table VI Average Oleic Acid Concentration in Seed Oil of Parents and Reciprocal F1 Crosses Grown in the Field at Fargo, ND

Parent or cross High-oleic Pervenets selections Range HA 89 Range F1 seed, high-oleic/HA 89 Range F1 seed, HA 89/High-oleic Range

Oleic acid concentration (g kg21) 846 790–894 110 102–181 520 427–634 390 370–491

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J. W. BURTON ET AL.

the first mid-oleic or NuSun sunflower hybrid created (Miller et al., 1987). When the high-oleic Pervenets 306 was used as male parent in the cross, the F1 seed averaged 390 g kg21, indicating maternal influence but not complete maternal inheritance. The F1 plants of the cross between Pervenets 306 and HA 89 were selfpollinated and F2 seed were grown in the field nursery at Fargo, ND. Analysis of F2 seed showed a trimodal distribution for oleic acid concentrations (Table VII). An intermediate class was clearly evident, ranging in oleic concentration from 480 to 720 g kg21. The high-oleic class ranged from 820 to 920 g kg21, whereas the low-oleic class was similar to HA 89 and ranged from 110 to 180 g kg21. The number of seeds in the intermediate class was too large to support a single, dominant gene theory. A Chi-square analysis for goodness of fit of segregation 3:9:4 high:intermediate:low was proposed and accepted for the four crosses, for the pooled families, and the heterogeneity analysis (Table VII). The study confirms the presence of a single, dominant gene, designated Ol. This gene produced seed with oleic composition levels of 500 –700 g kg21. A second gene, designated Ml, appears to modify the oleic concentration upward. When in the recessive form mlml and combined with the gene Ol, oleic levels in seed were 820 g kg21 or higher. Therefore, the theoretical genotype Ol_Ml_ would produce oleic acid concentrations desirable for NuSun. F3 progeny tests were conducted on intermediate F2 seeds. These F2 seeds produced very few high-oleic F3 segregants, as expected with the two-gene model proposed. Since this study, Fernandez-Martinez et al. (1989) proposed a three-gene model, further supporting the modifier gene aspect of mid-oleic sunflower oil.

Table VII Distribution of Seed in Oleic Classes and Chi-Square Analysis for Goodness of Fit of Segregation Observed in F2 Seeds (Derived on F1 Plants) Involving High- and Low-Oleic Acid Parents No. of seeds in oleic classes Pedigree F2 population (3:9:4 ratio tested) HA 89/Pervenets Sel 302 HA 89/Pervenets Sel 304 HA 89/Pervenets Sel 305 HA 89/Pervenets Sel 306 Pooled Chi-square Heterogeneity Chi-square a

High

Intermediate

Low

Pa

6 18 11 13

15 42 26 31

9 30 13 13

0.50– 0.80 0.20– 0.50 0.50– 0.80 0.50– 0.80

48

114

65

0.05– 0.20 0.50– 0.80

Probability of a larger x2 value due to chance.


2.

Methods of Producing NuSun Sunflower Hybrids

Based on the inheritance studies, there are four basic methods of producing NuSun sunflower hybrids with a mid-oleic level of oleic acid. At present, most seed industry companies are utilizing the first two strategies, with a few companies applying the third strategy. (a) High £ Low Crosses or Low £ High Crosses: Crossing a high-oleic female parent (OlOlmlml) with a low-oleic male parent (traditional linoleic) (ololMlMl) produces hybrid seed with the genotype OlolMlml. Planting of seed with this genotype has produced sunflower seeds which generally average 520 – 620 g kg21 oleic acid. The crossing of a low-oleic female parent (ololMlMl) with a high-oleic male parent (OlOlmlml) also produces hybrid seed with the genotype OlolMlml. However, planting of seed of this cross has typically produced a sunflower crop that averages 500 – 560 g kg21. This result is due to the maternal influence factor, or the influence of the genotype of the maternal parent on the resulting oleic concentration of seed produced on that plant (Miller et al., 1987). It appears that the high-oleic female parent continues to influence the oleic concentration of seed produced on that plant. (b) Modified Single-Crosses [(High £ Low Female) £ High Male]: Crossing a high-oleic female parent (OlOlmlml) with a related low-oleic, female parent (ololMlMl) produces a cytoplasmic male-sterile hybrid plant of mid-oleic phenotype (OlolMlml). This male-sterile hybrid could then be crossed with a high-oleic male (OlOlmlml), producing a mixture of male-fertile genotypes with varying oleic acid concentrations in the producer’s field. This cross appears to produce a sunflower crop that averages 600 – 680 g kg21 oleic acid content, much higher than the strict single-cross hybrid. (c) Mid-oleic £ Mid-oleic Crosses: The crossing of a true-breeding mid-oleic female parent (OlOlMlMl) with a true-breeding mid-oleic male parent (OlOlMlMl) produces a hybrid with the mid-oleic trait because the genotype of the hybrid is also OlOlMlMl. Seed of this plant should be more stable than high £ low or low £ high crosses. However, the breeding effort appears much more involved and it is difficult to create these genotypes. The obstacle may lie in the number of modifier genes having an effect on the oleic concentration. Hybrids must be tested extensively to confirm that specific modifier genes are the same in both genotypes, ensuring that the correct mid-oleic level will be produced by the hybrid. An industry breeder must have two programs, both male and female, for the selection of specific mid-oleic genotypes. (d) High-oleic £ High-oleic Crosses with Differing Numbers of Modifier Genes: The crossing of a high-oleic female parent having 800 – 820 g kg – 1 oleic acid and possessing a modifier gene with a slight effect on oleic concentration (OlOlml1ml1Ml2Ml2ml3ml3) with a high-oleic male parent possessing a different modifier gene, also with a slight effect on oleic concentration (OlOlml1ml1ml2ml2Ml3Ml3), would produce a genetically complex hybrid

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J. W. BURTON ET AL.

(OlOlml1ml1Ml2ml2Ml3ml3). Planting of seed with this genotype has produced a sunflower crop which generally averages 700 – 780 g kg21 oleic acid. This result is due primarily to the small effect of each of the different modifier genes on the Ol gene, lowering the oleic concentration from a potentially high level. Several hybrids of this type were produced by the sunflower seed industry and USDAARS when the female line HA 341 was used as a female parent in experimental hybrids.

3.

Progress of Industry

Acceptance of NuSun hybrids by industry and producers has been excellent, and steady progress has been made in 2002 and 2003. According to the National Sunflower Association, 2003 hybrid sunflower production was approximately 60 – 70% converted to NuSun sunflower hybrids. This is an outstanding feat when considering that the idea was just proposed to companies during the year 1995. The company of Proctor & Gamble, Cincinnati, OH, completely converted their original Pringles Potato Crisp frying line to NuSun sunflower oil. North Central regional companies Old Dutch and Barrel O’Fun also use NuSun sunflower oil in producing potato chips (National Sunflower Association, Bismarck, ND, www. sunflowernsa.com). Producer acceptance has been enhanced by the performance of the seed industry’s NuSun hybrids (Table VIII). Trials of NuSun sunflower hybrids have

Table VIII Yield, Oil Content, and Oleic Acid Concentration of NuSun Sunflower Hybrids and Traditional Check Hybrids Grown at Five Locations in the US from 1996 to 2000 Yield (kg ha21)

Oil (g kg21)

Oleic acid (g kg21)

Casselton, ND NuSun hybrids, 1996–2000 Traditional checks, 1996– 2000

2457 2366

463 467

596 225

Brookings-Gettysburg, SD NuSun hybrids, 1996–2000 Traditional checks, 1996– 2000

2146 2049

464 472

612 279

Colby, KS NuSun hybrids, 1996–2000 Traditional checks, 1996– 2000

2416 2428

452 459

636 277

Minot, ND NuSun hybrids, 1996–2000 Traditional checks, 1996– 2000

2475 2584

470 484

571 158

Location and year grown


been grown since 1996 at three locations in the US: Casselton, ND, BrookingsGettysburg, SD, and Colby, KS. A trial at Minot, ND, was later added to test NuSun hybrids in a more northern location requiring earlier maturing hybrids. The maturation of these hybrids at Minot in a cooler environment puts downward pressure on oleic concentration. As expected, the oleic concentration of NuSun hybrids was higher at the Kansas and South Dakota locations due to higher growing degree day effects on oil composition. However, the difference between oleic composition in hybrids grown in southern and northern locations was smaller than expected, indicating that NuSun oleic values are more stable than high-oleic hybrids. NuSun hybrid yield performance was nearly the same as the traditional linoleic check hybrid performance, enhancing the acceptance of NuSun hybrids by producers. However, the oil content of NuSun hybrids has been lower, indicating that industry needs more effort to improve present hybrids in this characteristic.

4.

Identity Preservation

Identity preservation of NuSun hybrid seed versus traditional linoleic hybrid seed has been a major challenge to the sunflower industry. A National Sunflower Association committee was organized specifically to address this problem. The country elevator was targeted as the point at which identity should be made, with the elevator binning the two types separately. In 2000, nearly all country elevators were equipped with a small oil press to extract approximately 5 ml of oil from random samples taken throughout a truck load. The oil was then placed on a hand-held refractometer. The refractometer will not provide an exact numerical oleic concentration number but it will clearly show if the seed has produced a traditional linoleic concentration or NuSun sunflower oil. The North Dakota Grain Inspection Service provides sample bottles of NuSun oil with the oil used to calibrate the hand-held refractometer. The 2001 minimum oleic concentration level acceptable for NuSun processors was 550 g kg21.

C. REDUCING SATURATED FATTY ACIDS

IN

SUNFLOWER OIL

Reducing the saturated fatty acid concentration of NuSun sunflower oil would benefit the sunflower industry through increased consumer preference for a low saturated sunflower product. This factor is very important to industries using NuSun oil for frying as consumers become more aware of labeling requirements on food products. In a project designed to reduce saturated fatty acids in sunflower oil, two USDA maintainer inbred lines, HA 821 and HA 382, and two USDA pollen

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fertility restorer inbred lines, RHA 274 and RHA 801, were selected for mutagenesis treatment (Miller and Vick, 1999). Two chemical mutagens (NMU and EMS) were evaluated at rates of 1 and 2 g kg21. Rates of 4, 6, and 8 g kg21 of both mutagens were found to be lethal for sunflower seed. A total of 56,000 seeds were treated, or 14,000 seeds per inbred line and 3500 per mutagen treatment (two levels of two mutagens). The fatty acid concentration of approximately 6800 M5 lines was analyzed by gas chromatography. Sixteen of the 6800 M5 lines analyzed showed significant deviation in fatty acid concentration from their respective parental genotypes. Five lines were lower in palmitic acid concentration, seven lines were lower in stearic acid concentration, two lines had over 800 g kg21 oleic acid, and one line was classified as a mid-oleic genotype (525 g kg21). Only one line had an elevated level of a saturated fatty acid, with the palmitic acid concentration reaching 132 g kg21, compared with 59 g kg21 in the original HA 382 genotype. Also found was a mutant line of RHA 274 having a high linoleic acid concentration of 786 g kg21, in comparison with 646 g kg21 for the parental genotype. No significant reductions were found in the arachidic (20:0), behenic (22:0), or lignoceric (24:0) saturated fatty acids. Two M5 lines, HA 821 LS-1 and RHA 274 LS-2, had lower stearic acid concentration (41 and 20 g kg21), and one M5 line, RHA 274 LP-1, had lower palmitic acid concentration (47 g kg21) than their respective parental lines. Segregation ratios of F2 and testcross progeny indicated that the low stearic acid concentration in HA 821 LS-1 was controlled by one gene, designated fas1, with additive gene action. The low stearic acid concentration in RHA 274 LS-2 was controlled by two genes with additive gene action. The first gene was designated fas2, and the second gene was temporarily designated fasx. The allele fap1 was identified in RHA 274 LP-1 to control palmitic acid concentration with additive gene action. Incorporation of the fas1, fas2, fasx, and fap1 genes into NuSun hybrids will require extensive testing in early generation breeding material for development of parental inbred lines. Utilizing half-seed analysis of segregating seeds derived from one sunflower head will be feasible. For example, a genotype homozygous for the fas1 fas1 fas2 fas2 fap1 fap1 alleles should be easily discerned from a genotype with heterozygous alleles at any locus. The key to selection is testing sufficient numbers of seeds to find the desired genotype. Marker assisted selection would be a new tool to identify genotypes with the three alleles. The combination of the alleles providing low stearic acid concentration with alleles providing low palmitic acid concentration could substantially reduce the saturated fatty acid concentration of NuSun seed oil. On the basis of results of this study, a sunflower hybrid could be produced with a total saturated fatty acid concentration of less than 80 g kg21, including the 20:0, 22:0, and 24:0 saturated fatty acids.


D. TOCOPHEROL ROLE

IN

NUSUN SUNFLOWER OIL

NuSun oil stability during use and storage can be enhanced by increasing the natural antioxidants contained in the oil. Tocopherols (Vitamin E) are the most powerful of the natural fat-soluble antioxidants (Demurin, 1993). They exist in four homologues: alpha, beta, gamma, and delta. Each homologue differs in antioxidant activity. Cultivated sunflower contains a high concentration of alpha tocopherol (97% of total tocopherol), which has the lowest antioxidant property of the four homologues.

1.

Inheritance of Tocopherol in Sunflower

A mutation breeding program was initiated by the VNIIMK (Krasnodar, Russia) research group working on sunflower oil quality. They found a line, LG15, with an oil tocopherol composition of 50% beta homologue and 50% alpha homologue. This tocopherol composition was determined to be controlled by a recessive gene, tph1 (Popov et al., 1988; Demurin, 1993) (Table IX). Another mutant line, LG-17, was found to contain 95% gamma tocopherol and 5% alpha tocopherol. The gene controlling the high gamma tocopherol composition was also recessive and named tph2. The genes tph1 and tph2 were non-allelic and unlinked, and neither was linked with the Ol gene controlling high oleic acid concentration in the cultivar Pervenets. The epistatic action of the tph2 gene on the tph1 gene results in approximately 84% of total tocopherol being the gamma homologue, 8% alpha tocopherol, and 8% delta tocopherol (Table IX). Expressivity of the tph1 and tph2 genes depends both on seed maturity and temperature during maturation. An increase in temperature from 20 to 308C during seed maturation resulted in an increase of the

Table IX The Content of Tocopherols in the Seeds of Sunflower Lines Tocopherol homologue (% of total tocopherol) Line VK373 LG15 LG17 LG24

Genotype

Alpha

Beta

Gamma

Delta

Tph1, Tph1, Tph2, Tph2 tph1, tph1, Tph2, Tph2 Tph1, Tph1, tph2, tph2 tph1, tph1, tph2, tph2

97 ^ 1 50 ^ 5 5^2 8^2

0 50 ^ 5 0 0

3^1 0 95 ^ 2 84 ^ 5

0 0 0 8^4

Demurin, 1993.

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alpha homologue of tocopherol. Combining both genes with the high-oleic gene increased the stability and shelf life of sunflower oil dramatically. 2. Altering Tocopherol Homologues in NuSun Sunflower Sunflower breeders in the US are currently incorporating the tph2 gene into parental lines of NuSun sunflower hybrids. Since the gene control is recessive, the tph2 gene must be incorporated into both the female and male parents of all NuSun hybrids. Molecular marker technology will be beneficial in identifying genotypes which have the tph2 gene in early generation selection.

III. BRASSICA The development of the new technologies for trait modification has opened the possibility of engineering a wide range of new oil profiles in Brassica. The new Brassica oil qualities provide the opportunity to assess the effect of fatty acid composition on the nutritional or functional properties of the oil. Cultivars with modified oil profiles are being developed by Brassica breeding institutions worldwide to compete with other modified oilseeds for a share in the world vegetable oil market. The categories of modified oils are as follows: low erucic acid oil, high and super high erucic acid oil, reduced saturate and elevated saturate (saturates defined as the sum of palmitic acid C16:0 þ stearic acid C18:0 þ arachidic acid C20:0 þ behenic acid C22:0), low-linolenic oil (, 35 g kg21 C18:3), mid-oleic oil (between 650 and 750 g kg21 C18:1) and high-oleic oil (over 750 g kg21 C18:1). These categories are not mutually exclusive as a change in one fatty acid is accompanied by changes in other fatty acids and in other minor components. However, these categories do represent separate germplasm developments that may then be combined to produce new oil profiles. The modified oil profiles have been grouped in this review according to the method used to produce the new fatty acid composition: intraspecific crosses and interspecific crosses, mutagenesis and transformation.

A. INTRASPECIFIC 1.

AND INTERSPECIFIC

CROSSES

Low Erucic Acid Oil

Brassica napus and Brassica rapa. The term canola oil is used in this review to describe the oil profile of the B. napus and B. rapa cultivars which produce oils


with very low levels of erucic acid (less than 10 g kg21 C22:1), equivalent to the terms low erucic acid rape or rapeseed (LEAR) and colza. The typical canola oil profile can be represented as 70 g kg21 saturated fat, 610 g kg21 C18:1, 210 g kg21 linoleic acid C18:2 and 110 g kg21 C18:3. This fatty acid composition represents the original modified oil profile in both B. napus and B. rapa. The reduction in erucic acid was achieved through crossing and selection, after the discovery of the variation in an accession of forage rapeseed Liho (Stefansson et al., 1961). The LEAR profile was released first in the B. napus cultivar Oro and was subsequently transferred through interspecific crossing into B. rapa with the first LEAR cultivar Span. Other Brassica and related species. The isolation of a B. juncea selection with low levels of erucic acid (Kirk and Oram, 1981) has led to the development of mustard germplasm with canola quality oil after crossing and selection. The low erucic acid trait has also been established in B. carinata and in Sinapis alba at two breeding organizations: AAFC Saskatoon and the University of Idaho, USA.

2.

High Erucic Acid Oil

B. napus cultivars with very high levels of erucic acid C22:1 provide a valuable source of C22:1 and its derivatives for industrial applications including high temperature lubricants, surfactants, plasticisers, surface coatings and solvents (McVetty and Scarth, 2002). There are also pharmaceutical and food applications. The economics of extracting C22:1 from the oil for these applications improves significantly when the erucic acid levels are increased over 500 g kg21. The level of C22:1 in unselected B. napus germplasm is between 350 and 400 g kg21. Selection following intraspecific crossing with B. napus germplasm containing elevated C22:1 produced the high erucic acid (HEAR) cultivar strain Hero (Scarth et al., 1991). The recently released HEAR cultivars Castor and Millenium 01 have oil profiles with 550 g kg21 C22:1. (McVetty et al., 1998a,b).

3.

Super High Erucic Acid Oil

Market applications for erucic acid would increase significantly with further increases in the level of erucic acid. However, no Brassica germplasm has been identified with erucic acid levels exceeding 660 g kg21 (McVetty and Scarth, 2002). The substrate specificity of the Brassica acyltransferase LPAAT preferentially inserts C18:1 in the middle position (sn-2) of the glycerol molecule, excluding the longer chain fatty acids including C22:1 and limiting the maximum expression of erucic acid content to 660 g kg21 (Luhs et al., 1999).

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Accessions of B. oleracea and B. rapa have been identified which esterify erucic acid in the sn-2 position (Taylor et al., 1995; Taylor, personal communication). This germplasm was used to resynthesize B. napus by interspecific crossing followed by chromosome doubling. However, the erucic acid levels expressed in the resynthesized B. napus did not exceed 660 g kg21 (McVetty, personal communication) A similar approach using interspecific crosses to resynthesis high eruric B. napus was reported by Luhs and Friedt (1995).

4. Reduced Saturate Oil Quality Canola oil contains a very low level (. 71 g kg21) of total saturates, and only 40 g kg21 of the saturated fatty acids identified as contributing to elevated blood cholesterol levels, i.e., lauric acid C12:0, C14:0 and C16:0. The labeling regulations in the US and Canada allow oils with less than one gram of saturated fat per 14 g of total fat or less than 70 g kg21 saturated fatty acid content in the oil to be identified as low in saturated fatty acids. It is this trait that distinguishes canola oil from the competing vegetable oils in the North American market such as corn, soy, and peanut oil. Consumer preference for low saturate oils as a salad oil and in cooking and frying applications has established a significant market share for canola oil (Fitzpatrick and Scarth, 1998). Defense of this market share requires at a minimum the maintenance of the 70 g kg21 limit on saturated fat. Breeding institutions in Canada have focused on the reduction of saturates initially below 70 g kg21, with the long-term objective of achieving reductions in the sum of C16:0 þ C18:0 below 40 g kg21. Significant reductions in saturated fatty acids are not available in current B. napus canola cultivars. B. napus germplasm has been developed from interspecific crosses between B. rapa and B. oleracea strains, with levels comparable to B. rapa (less than 60 g kg21 of the total saturated fatty acids) (Raney et al., 1999a).

B. MUTAGENESIS 1. Low-Linolenic Oil Quality Linolenic acid and linoleic acid are both essential fatty acids for human health. Linolenic acid has a role in reducing plasma cholesterol levels (Eskin et al., 1996). The ratio of C18:3/C18:2 in canola oil (1:2) is also regarded as nutritionally favorable. However, vegetable oils high in C18:3 such as canola have poor oxidative and flavor stability. The use of hydrogenation to reduce the polyunsaturated fatty acids results in the formation of trans fatty acids. Nutritionists are concerned with the trans isomers of cis-fatty acids raising the serum low-density lipoprotein cholesterol (LDL-C) levels and reducing the serum


high-density lipoprotein cholesterol (HDL-C). Elevated levels of LDL-C and reduced levels of HDL-C are associated with enhanced risk of CVD. The current recommendation from nutritionists is that the current levels of trans fatty acid in the diet should not be increased (Fitzpatrick and Scarth, 1998). One solution is the reduction of C18:3 to increase stability without the need for hydrogenation. Low-linolenic oils with . 35 g kg21 C18:3 have shown increased stability under conditions of accelerated storage with no changes in overall odor intensity or pleasantness. There were also significantly lower levels of free fatty acids during frying with low-linolenic canola oil with better flavor quality of the French fry product (Eskin et al., 1996). The reduction in C18:3 is typically accompanied by an increase in C18:2 and C18:1. Many breeding institutions worldwide have developed low-linolenic B. napus cultivars. The low-linolenic profile is being developed in zero-erucic acid spring turnip rape B. rapa at the University of Helsinki and Boreal Plant Breeding in Finland. Current levels of linolenic acid are 70 g kg21 with a 1:4 ratio of C18:3/C18:2, achieved through selection (Laakso et al., 1999). The most reported method used to reduce C18:3 content has been mutagenesis applied to imbibed seeds or to developing microspores. The low-linolenic trait was produced by seed mutagenesis of the B. napus cultivar Oro, which led to the isolation of a mutation line, M11 with an altered C18:3/C18:2 ratio (Raney et al., 1999b). A program of backcrossing to the adapted cultivar Regent, combined with selection, led to the release of the first low linolenic cultivar Stellar with approximately 30 g kg21 C18:3 in the seed oil (Scarth et al., 1988).

2.

Mid- and High-Oleic Oil Quality

Comparative studies of genetically modified oils for frying performance or life of the oil, shelf-life, dietary benefits and sensory properties of end product identified the optimum oil profile as 50– 70 g kg21 saturate, 670 –750 g kg21 C18:1, 150 – 220 g kg21 C18:2 and . 30 g kg21 C18:3. The role of C18:2 in enhanced sensory properties was noted as C18:1 levels over 750 g kg21 results in a reduction in sensory properties (flavor and taste) and an increase in off-odors (Warner and Mounts, 1993). Mid-oleic oils with increased C18:1 levels in combination with reduced C18:2 and C18:3 provide stability without the requirement for partial hydrogenation (Fitzpatrick and Scarth, 1998). Enhanced C18:1 levels have been produced through mutagenesis, applied both to seed and to microspore derived embryos. The University of Go¨ttingen Institute fur Pflanzenbau und Pflanzenzuchtung has produced high-oleic quality in winter rapeseed developed from mutagenic lines from cv. Wotan and other high-oleic lines. A study of the influence of the environment on

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the high-oleic trait showed a high genetic heritability, but with a significant environment and GXE component (Schierholt and Becker, 1999). High-oleic oils (over 750 g kg21) are targeted for industrial end-use in the oleate market or can be blended with conventional oils to lower oleic levels. The competing oils in this market are the mid- and high-oleic sunflower oils. Seed mutagenesis followed by crossing and selection resulted in Brassica genotypes with . 850 g kg21 oleic and reduced levels of linoleic and linolenic acid (Wong et al., 1991). The oil profile with oleic acid levels over 800 g kg21 has been protected through patent.

3. Reduced Saturate Oil Quality Doubled haploid B. rapa lines with reduced saturate levels have been developed from microspore mutagenesis conducted at the Plant Biotechnology Institute in Saskatoon. This low saturate variation is being introduced into B. napus, to produce low saturate germplasm for further cultivar development (McVetty and Scarth, 2002). Raney and Rakow (2002) have also used mutagenesis to produce B. napus germplasm with reduced saturate levels.

C. TRANSFORMATION 1.

High Saturate Oil Quality Including Novel Fatty Acids

Oils with high levels of saturated fat have applications in the production of solid fat products such as shortenings and margarines where unmodified liquid oils cannot be used. Canola and soybean oils with high saturated fatty acid levels can replace animal fats and offer the benefit of domestic production for temperate countries, reducing dependence on tropical high saturate oils. Transgenic modification using the Agrobacterium-mediated system has been used to increase the total saturated fatty acid content of canola. High laurate C12:0 oil canola was the world’s first transgenic oilseed crop in commercial production. The high C12:0 trait was the result of the insertion of the acyl-ACP thioesterase (TE) isolated from California Bay Laurel (Umbellularia californica). The typical analytical value of Lauricale oil profile is 380 g kg21 C12:0, 40 g kg21 C14:0, 30 g kg21 C16:0, 310 g kg21 C18:1, 110 g kg21 C18:2, 70 g kg21 C18:3 and 60 g kg21 other fatty acids. The Lauricale product has applications in the food industry in products such as confectionary, simulated dairy products, icings and frostings. Overexpression of the oleate preferring acyl-ACP TE from soybean (Glycine max) increased the sum of C16:0 and C18:0 to approximately 200 g kg21 in transgenic lines of the canola cultivar Westar (Hitz et al., 1995). Levels of C16:0


have been increased to over 30 g kg21 by transformation with TE from elm (Ulmus americanca) and nutmeg (Myristica fraganceae) (Voelker et al., 1992). Transgenic lines with TE from Cuphea lanceolata have been characterized with 160 g kg21 C14:0 and 430 g kg21 (C14:0 þ C16:0) (Rudloff et al., 1999).

2.

Mid- and High-Oleic Oil Quality

High-oleic canola (. 860 g kg21 C18:1, , 70 g kg21 C18:2, , 25 g kg21 C18:3) has been produced using seed specific inhibition of microsomal oleate desaturase and microsomal linoleate desaturase gene expression, either through co-suppression or antisense technology. Co-suppression has been used in combination with mutation treatments to produce modified fatty acid profiles (Debonte and Hitz, 1996).

D. PRODUCTION

OF

MODIFIED OIL CULTIVARS

The effect of modifying oil quality on the other quality traits, including oil and protein content, and on agronomic performance is a critical factor in the successful production of the modified oil quality. In general, the performance of the modified oil cultivars is not different from the non-transgenic parent cultivar used in the original crosses, mutagenetic treatment or transformation event. The challenge for the successful production of these cultivars is to achieve the performance of the current conventional cultivars with the optimum expression of the modified oil quality. The stability of the modified oil trait over different production environments is another important factor.

IV. PEANUT A. INTRODUCTION, BREEDING OBJECTIVES,

AND

RATIONALE

In the US, peanut (Arachis hypogaea L.) is primarily used as a food crop, however, peanut is one of the five most important oilseeds produced in the world (Carley and Fletcher, 1995). About two thirds of the world’s peanut crop is utilized for oil production (Savage and Keenan, 1994). The fatty acid composition of peanut is an important quality attribute whether it is used as a food or a source for oil. Two fatty acids, oleic (O) and linoleic (L), can account for up to 80% of the oil content of peanut (Young and Waller, 1972). Oleic acid is an 18-carbon monounsaturated (18:1) precursor to linoleic acid (18:2). Oleic acid is less reactive

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with oxygen and therefore more stable. A commonly used index of the quality of groundnut is the ratio of oleic to linoleic fatty acids (O/L ratio). A higher ratio of oleic to linoleic acid in peanut oil and other peanut products is considered an indicator of a more stable product. Fatty acid composition of peanut oil is influenced by cultivar, degree of maturity, and environmental conditions (Ahmed and Young, 1982). In the US, approximately 70% of the peanuts are runners (small-seeded types of var. hypogaea), 20% are virginias (large-seeded types of var. hypogaea), 10% are spanish (var. vulgaris) and less than 1% are valencia (var. fastigiata) market types, respectively (Knauft and Gorbet, 1989). Oil from seeds of different botanical types of peanuts differ in their tendency to develop oxidative rancidity or undesirable odors and flavors. Virginia botanical-type peanuts (var. hypogaea) produce oil with slightly lower linoleic percentage and therefore tend to have greater oil stability than spanish or valencia botanical types (Norden et al., 1982). During seed maturation the proportion of oleic acid increases and the proportion of linoleic acid decreases (Sanders, 1980a,b; Sanders et al., 1982). Peanuts produced in the northern regions of the US peanut production areas often have relatively low O/L ratios resulting in inferior oxidative stability (Worthington et al., 1972; Brown et al., 1975). Holladay and Pearson (1974) observed that higher temperatures during the last 4 weeks before harvest resulted in peanuts with a higher proportion of oleic acid.

B. INCREASING OLEIC ACID 1.

Breeding History

Historically, standard peanut cultivars have averaged 550 g kg21 oleic acid and 250 g kg21 linoleic acid (Knauft et al., 1993). Norden et al. (1987) examined the fatty acid composition of 494 genotypes and identified a breeding line (F435) with 800 g kg21 oleic acid and 20 g kg21 linoleic acid. This was a major deviation from previously known levels of fatty acid composition in peanut. Moore and Knauft (1989) found that inheritance of the high-oleate trait was controlled by duplicate recessive genes, ol1 and ol2, and therefore, easily transferable to existing cultivars through backcrossing. F435 differed at both loci from a virginia-type line but at only one locus from a runner line. Knauft et al. (1993) found the trait to exhibit monogenic inheritance in crosses with 12 additional cultivars and breeding lines of the runner market-type. A cross with a virginia market-type segregated in a 15:1 ratio typical of recessive digenic inheritance. These results led the authors to conclude that one of the recessive alleles occurs with high frequency in peanut breeding populations in the US and that the other allele is rare. Isleib et al. (1996) examined five different cultivars of virginia-type peanut cultivars and found that four were either Ol1Ol1ol2ol2 or


ol1ol1Ol2Ol2 and one was Ol1Ol1Ol2Ol2. When only one gene transfer is required, Isleib et al. (1998) were able to identify heterozygotes based on linoleate levels. This will allow breeders to identify carriers of the recessive allele in successive cycles of backcrossing without intervening generations of selfing and decrease the time required to achieve the desired number of backcrosses. Lopez et al. (2001) examined the inheritance of the high oleic acid in six Spanish market-type peanut cultivars. Segregation patterns indicated that two major genes were involved. However, the presence of low-intermediate O/L ratio genotypes indicated that other genetic modifiers may be involved in the expression of the O/L ratio in these genotypes. Isleib et al. (1998) also observed an effect of other loci on fatty acid concentrations.

2.

Progress

SunOleic 95R was the first peanut cultivar having the high-oleic trait (Gorbet and Knauft, 1997). This was followed by the release of Flavorunner, GK7 High Oleic, and SunOleic 97R (Gorbet and Knauft, 2000). Oil from higholeic peanut has a composition similar to olive oil with low levels of polyunsaturates. In comparison to standard peanut oil, the high-oleic oil has a much longer shelf-life before exhibiting rancidity (O’Keefe et al., 1993). This increase in oil stability is achieved without chemical hydrogenation, which introduces undesirable trans fatty acids. Rancidity is also delayed in whole peanuts which are high-oleic (Mugendi et al., 1998) resulting in increased shelf life for some peanut products. Pattee and Knauft (1995) evaluated four high oleic acid breeding lines and observed no change in roasted peanut attribute intensity in comparison to Florunner. Pattee et al. (2001) observed that high-oleic cultivars and breeding lines derived by backcrossing with Sunrunner had a high positive breeding value for the roasted peanut attribute. It is not clear if this is a real genetic effect or an artifact of the sensory evaluation since the protocol requires a storage period during which some oxidation of linoleic acid in the Sunrunner seeds may occur that may produce off-flavors The first peanut cultivars containing high oleic acid were extremely susceptible to tomato spotted wilt tospovirus (TSWV) (Culbreath et al., 1997) and performed poorly in areas with high TSWV pressure. Moderate levels of resistance to TSWV have been reported in the mid-oleic cultivars Florida MDR98 (Culbreath et al., 1997) and ViruGard (Culbreath et al., 2000). Recently, higholeic breeding lines have been produced with acceptable levels of resistance to TSWV (Culbreath et al., 1999). Several in vitro studies have indicated that fatty acid composition could either directly or indirectly affect aflatoxin contamination (Fabbri et al., 1983; Passi

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et al., 1984; Doehlert et al., 1993; Burrow et al., 1997). Holbrook et al. (2000) evaluated the effect of altered fatty acid composition on preharvest aflatoxin contamination in peanut, but observed no measurable effect of reduced linoleic acid composition on preharvest aflatoxin contamination. They concluded that the products of the lipoxygenase pathway that have been shown to affect aflatoxin biosynthesis in vitro may not be present in sufficient quantities in developing peanut seed. However, under conditions that simulated post-harvest conditions, Xue et al. (2003) observed an increased ability of high-oleic lines to support production of aflatoxin in comparison to normal-oleic lines. They urged special care in handling and storage of high-oleic peanuts to prevent the growth of Aspergillus spp. Ray et al. (1993) determined that the high-oleic phenotype was due to reduced activity of microsomal oleoyl-phosphatidylcholine (PC) desaturase. Jung et al. (2000b) isolated two cDNA for this microsomal oleoyl-PC desaturase, ahFAD2A and ahFAD2B. The amount of ahFAD2B transcript was markedly reduced in plants with the high-oleic trait (Jung et al., 2000a), and this decreased activity was consistent with the observed inheritance of the high-oleic phenotype. Comparison of the base sequences of the reading frames of the ahFAD2A and ahFAD2B genes showed 11 base pair differences resulting in four differences in amino acids (Jung et al., 2000a). The change of aspartate at position 150 to asparagine was a change in a residue that is absolutely conserved among other desaturases. Brunner et al. (2001) used site-specific mutagenesis to change the aspartate in the high activity enzyme to asparagine and to change asparagine in the lower activity enzyme to aspartate. Subsequent expression in yeast resulted in nearly complete loss of activity of the previously more active desaturase and restored activity to the previously less active desaturase indicating that this mutation is the molecular basis of the high-oleic phenotype in peanut. Lopez et al. (2000) observed a similar polymorphism in Spanish market-type lines with the high-oleic trait. It is not clear how widely accepted the high-oleic characteristic will be in the US peanut industry. The trait should be valuable in the northernmost production areas since undesirable fatty acid profiles have historically been a problem in peanuts from these regions. This trait adds much less value to peanuts produced in the southern production areas. The value of this trait is also dependent on the end product of the peanuts. An extended shelf life would be of great value for some peanut products whereas for other products, such as peanut butter, stabilizers are already used to extend shelf life. Negotiations are ongoing to determine the cost for using this trait and who will bear these costs. The University of Florida has been granted three patents related to this trait (Knauft et al., 1999, 2000a,b). These patents encompass peanut seed, oil, and products.


REFERENCES Ahmed, E. M., and Young, C. T. (1982). Composition, quality, and flavor of peanuts. In “Peanut Science and Technology” (H. E. Pattee and C. T. Young, Eds.), pp. 655–688. American Peanut Research and Education Society, Yoakum, TX. Brim, C. A., Schutz, W. M., and Collins, F. T. (1968). Maternal effect on fatty acid composition and oil content of soybeans, Glycine max (L.) Merr. Crop Sci. 8, 517–518. Brown, D. F., Cater, C. M., Mattil, K. F., and Darroch, J. G. (1975). Effect of variety, growing location and their interaction on the fatty acid composition of peanuts. J. Food Sci. 40, 1055–1060. Brunner, A. C., Jung, S., Abbott, A. G., and Powell, G. L. (2001). The naturally occurring high oleate oil character in some peanut varieties results from reduced oleoyl-PC desaturase activity from mutation of aspartate 150 to asparagine. Crop Sci. 41, 522– 526. Bubeck, D. M., Fehr, W. R., and Hammond, E. G. (1989). Inheritance of palmitic and stearic acid mutants of soybean. Crop Sci. 29, 652–656. Burrow, G. B., Nesbitt, T. C., Dunlap, J., and Keller, N. P. (1997). Seed lipoxygenase products modulate Aspergillus mycotoxin biosynthesis. Mol. Plant-Microbe. Interact. 10, 380–387. Burton, J. W., Wilson, R. F., Brim, C. A., and Rinne, R. W. (1989). Registration of soybean germplasm lines with modified fatty acid composition of seed oil. Crop Sci. 29, 1583. Burton, J. W., Wilson, R. F., and Brim, C. A. (1994). Registration of N78-2077-12 and N87-2122-4, two soybean germplasm lines with reduced palmitic acid in seed oil. Crop Sci. 34, 313. Burton, J. W., Wilcox, J. R., Wilson, R. F., Novitzky, W. P., and Rebetzke, G. J. (1998). Registation of low palmitic acid soybean germplasm lines N94-2575 and C1943. Crop Sci. 38, 1407. Burton, J. W., Wilson, R. F., Novitzky, W. P., and Pantalone, V. R. (2003). Registration of N984445A. Crop Sci. 43. Byrum, J. R., Kinney, A. J., Stecca, K. L., Grace, D. J., and Diers, B. W. (1997). Alteration of the omega-3 fatty acid desaturase gene associated with reduced linolenic acid in the A5 soybean genotype. Theor. Appl. Genet. 94, 356– 359. Cahoon, E. B., Carlson, T. J., Ripp, K. G., Schweiger, B. J., Cook, G. A., Hall, S. E., and Kinney, A. J. (1999). Biosynthetic origin of conjugated double bonds: production of fatty acid components of high-value drying oils in transgenic soybean embryo. PNAS 96, 12935–12940. Cahoon, E. B., Marilla, E. F., Stecca, K. L., Hall, S. E., Taylor, D. C., and Kinney, A. J. (2000). Production of fatty acid components of meadow foam oil in somatic soybean embryo. Plant Phys. 124, 243–251. Carley, D. H., and Fletcher, S. M. (1995). An overview of world peanut markets. In “Advances in Peanut Science” (H. T. Pattee and H. T. Stalker, Eds.), pp. 554–577. American Peanut Research Education Society, Stillwater, OK. Carver, B. F., Burton, J. W., and Wilson, R. F. (1983). Influence of maturity date on the oil content of soybeans with genetically altered fatty acid composition. Soybean Genet. Newslett. 10, 93–95. Carver, B. F., Burton, J. W., Carter, T. E. Jr., and Wilson, R. F. (1986). Cumulative response to various recurrent selection schemes in soybean: oil quality and correlated agronomic traits. Crop Sci. 26, 853 –858. Carver, B. F., Burton, J. W., and Wilson, R. F. (1987). Graft-transmissable influence on fatty acid composition of soybean seed demonstrated by grafting. Crop Sci. 27, 53 –56. Culbreath, A. K., Todd, J. W., Gorbet, D. W., Shokes, F. M., and Pappu, H. R. (1997). Field response of new peanut cultivar UF 91108 to tomato spotted wilt virus. Plant Dis. 81, 1410–1415. Culbreath, A. K., Todd, J. W., Gorbet, D. W., Brown, S. L., Baldwin, J. A., Pappu, H. R., Holbrook, C. C., and Shokes, F. M. (1999). Response of early, medium, and late maturing peanut breeding lines to field epidemics of tomato spotted wilt. Peanut Sci. 26, 100–106. Culbreath, A. K., Todd, J. W., Gorbet, D. W., Brown, S. L., Baldwin, J., Pappu, H. R., and Shokes, F. M. (2000). Reaction of peanut cultivars to spotted wilt. Peanut Sci. 27, 35–39.

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Index A

stock reduction 99 treading 65, 70 anion exchange capacity (AEC) 195 anthropogenic nitrous oxide emissions 86, 97 – 8 anti-carcinogens 19 – 20 aqueous phase chemistry, variable charge soils 167–8 aqueous– solid interfaces 176– 93 Arachis hypogaea see peanut ari-eGP dwarfing gene 255 arsenic 11 – 13, 45 – 6 atmospheric cadmium deposition on leaves 128 atomic force microscopy (AFM) 177

abiotic transformations 52 – 3 accumulation, cadmium in plants 121– 47 acetylene inhibition method 79 – 82 acidification, soil 95 – 6 acid rain 95 – 6 acid soil denitrification rate 72, 75 adsorption, variable charge soil interface models 182– 90 AEC see anion exchange capacity aeration, soil 69 – 70 aerosols 128 aflatoxin contamination 299– 300 AFM see atomic force microscopy agricultural pollution 4, 94 agro-chemicals, soil pollution 4 Alfisols see variable charge soils allophane 165– 6, 170, 178– 80 alpha amylase 227– 8 aluminium geo-medical issues 11 substitution in iron oxides 164 aluminium oxides 162, 171– 2 aminization 49 ammonia environmental effects 94 volatilization 53 – 63, 67 – 9, 76 – 9, 83 – 6, 102– 4 ammonification 49 – 50 ammonium-based fertilizers 50, 54, 97 ammonium fixation 52 anaerobic environments 65 anchorage failure 220, 233– 5 anchorage strength nitrogen 243– 4 plant breeding 256 plant growth regulators 250– 1 sowing date, rate and depth 240– 1 Andisols see variable charge soils animals excreta 43 – 4, 54, 97 – 8 nutrition 10 – 11

B

background electrolytes (BE) 172– 6, 182 bacteria, denitrifying 64 Bangladesh, arsenic poisoning 12 – 13 Barber – Cushman model 130, 131 base bending moment 228– 32, 258– 60 bioavailability of soil mineral elements 7– 8 biochemical process-based models, gaseous nitrogen emission 89 biological nitrogen fixation 40 – 2, 54, 97 biological treatment of farm effluents 46 –7 biotic transformations 48 – 52 blood cholesterol 279, 294 boron 5, 13 brackling 220– 1 Brassica 292– 7 erucic acid oil 292– 4 intraspecific and interspecific crosses 292– 4 linolenic oil 294–5 modified oil cultivar production 297 mutagenesis 294– 6 novel fatty acids 296– 7 oleic acid 295– 7 saturated fatty acids 294, 296– 7 307

308

INDEX

bread-making grain 226–8 breeding lodging avoidance 254– 7, 262 objectives for peanut 297–8 buckling 220– 1, 232

C

cadmium accumulation in plants 121– 47 empirical plant uptake models 124–9, 146 foliar uptake empirical relationship 128– 9 mechanistic models 132– 3 processes and phenomena 134– 6 geo-medical issues 13 – 14 influx to roots 133–4 ion competition 140– 1 long-distance transport 143–4 mechanistic plant uptake models 129– 33, 145 modeling plant uptake and accumulation 121–47 occurrence and use 122– 3 plant tissue accumulation mechanisms 136– 9 root uptake influx 133– 4 models 124– 32 parameters 139– 40 sewage sludge 123, 128– 9, 135 short-distance transport 142– 3 transport 142– 4 uptake in plants 121– 47 cadmium-binding complexes 137– 8 calc-alkaline pyroclastic materials 201 calcium, geo-medical issues 14 – 15 calcium – silicate slags 200– 1 camps, stock 44 cancer 19 – 20 canola oil 292– 7 carbon assimilation 226 availability and denitrification rate 72 – 4

carbonic acid 95 Carnegie – Ames – Stanford (CASA) Biosphere model 93 – 4 cation exchange capacity (CEC) 68, 194– 6 cattle excreta deposition 43– 4, 54 CD-MuSiC model 180 CEC see cation exchange capacity CENTURY ecosystem model 90, 93 – 4 cereals, lodging 217– 63 cerium 15 chamber techniques 81 charge fingerprints 195– 6 chemical degradation, variable charge soils 194– 5 chemoheterotrophs 64 chlorine 15 – 16 chlormequat 219, 245– 8, 250– 2 cholesterol 279, 294 chromium 16 clay fraction in variable charge subsoils 162 geophagia 6 permanently charged 198–202 volcanic ash soils mineralogy 166– 7 climate ammonia volatilization 68 –9 denitrification 75 – 6 global change 94, 96 – 8 Intergovernmental Panel on Climate Change methodology 86 –8 closed chamber techniques 82 clover, nitrogen fixation 40 – 1 co-adsorption 174– 6 cohesive forces, soil 234– 5 compaction of soil 65, 70 competition, ion 140–1 constant capacitance model 179– 80 contaminated land policies 27 –8 controlled-release fertilizer 98 conventional breeding, lodging 255– 6 copper 11, 16 – 17 core technique, acetylene inhibition method 81 – 2 Coulombic attractive force 181– 2

INDEX crop management, lodging 236– 54, 262 cropping, exhaustive 5 crown depth 241– 2 cultivations, lodging 236– 9

309

dynamic foliar cadmium uptake models 132– 3

E D

dairy cattle see cattle dairy effluents 46 – 7 DAYCENT 90, 92 – 4 DCD see dicyandiamide decomposition 89 – 90 degradation 194– 5 denitrification 52, 60, 63 –7, 69 – 76, 79 – 82, 102– 4 Denitrification and Decompostion (DNDC) model 89 – 94 denitrifying bacteria 64 denuder technique 78 deposition of cadmium on leaves 128– 9, 135– 6 Derjaguin – Landau– Verwey – Overbeek (DLVO) theory 181 detoxification of cadmium in plants 136 developing countries, geo-medical issues 5, 26 – 7 dicyandiamide (DCD) 100– 1 diffuse layer model 179–80 3,4-dimethylpyrazol phosphate (DMPP; ENTEC) 101 direct drilling 236– 8 direct probing 176–7 diseases, geophagia 6 – 7 distal regulators 60, 69 DLVO see Derjaguin – Landau – Verwey – Overbeek DMPP see 3,4-dimethylpyrazol phosphate DNDC see Denitrification and Decompostion model drilling 236– 8 drinking water nutrients 3 dry soils and infant mortality 9 – 10 dual-charge sorbents 168– 70 DW-6 dwarfing gene 255– 6 dwarfing genes 219, 254– 5

ear area 258– 9 ectomycorrhizal fungi 141– 2 EDL see electrical double layer effluent irrigation 45 – 8, 54 electrical double layer (EDL) structure 176– 7 elephantiasis 7 emissions see also nitrogen, gaseous emission from grazed pastures nitrous oxide 57 – 9, 66 – 7, 71, 82, 86 – 8, 96 – 8 empirical models, cadmium plant uptake and accumulation 124–9, 146 enclosure methods 76 – 7 ENTEC see 3,4-dimethylpyrazol phosphate environmental implications gaseous emissions of nitrogen 94 – 8 manure-by-products land application 45 – 6 epoxy fatty acids 282 erucic acid oil 292– 4 esophageal cancer 19 – 20 ethephon 245– 6, 249–50, 252–3 ethylene-releasing compounds 245 exchange capacity 194–6 excreta 43 – 4, 54, 97 – 8 exhaustive cropping 5 exudates 134

F

failure wind speed 236– 7, 262 fan loci 276– 7 fatty acids 273– 300 feldspars 165 fertilizers ammonium 50, 54, 97 controlled-release 98 15 N-labeled 79 – 80

310

INDEX

nitrate 54 nitrogen cereal lodging 242– 3 denitrification 65 environmental effects 94 – 5, 97 – 8 grazed pasture inputs 41 – 3, 54 phosphate 13 urea 54, 75, 97 variable charge soils management 201– 2 field margins 225 flowing helium atmosphere system 80 fluorine 17 fluxes 133– 4 foliar uptake cadmium empirical relationship 128– 9 cadmium mechanistic models 132– 3 cadmium processes and phenomena 134– 6 food chain 8 – 9 fungi cadmium uptake 141– 2 cereal lodging 228

G

gaseous emission see nitrogen, gaseous emission from grazed pastures genetic engineering 281– 3 genotypes, cadmium accumulation in plants 138– 9 geo-medical issues aluminium 11 animal nutrition 10 – 11 arsenic 11– 13 bioavailability of soil mineral elements 7 –8 boron 5, 13 cadmium 13 – 14 calcium 14 – 15 cerium 15 chlorine 15 – 16 chromium 16 contaminated land policies 27 – 8 copper 11, 16– 17

current trends in soil-related studies 3 –6 fluorine 17 food chain nutrient supply 8 – 9 geographical dimension 9 – 10 geophagia 6 – 8 iodine 2 – 3, 9, 18 iron 17 – 18 lead 9, 18 – 19 magnesium 22 – 3 malnutrition 26– 7 manganese 19 – 21 mercury 21 mineral elements deficiencies and excess 10 –11 mineral nutrients supply 6 – 9 molybdenum 21 nitrogen 23, 27 phosphate 21 – 2, 27 phosphorus 21 – 2 pollution 3 – 4, 27 – 8 potassium 22, 27 radon 5– 6 selenium 24 – 5 sodium 24 soil ingestion 6 –8 soil-related 1 –29 soil-to-man chain in mineral nutrients supply 6 – 9 under-nutrition 26 – 7 zinc 25 – 7 geophagia 6 – 8 gibberellic acid biosynthesis inhibitors 245 gibbsite 161– 2 global climate change 94, 96 – 8 global food production 39 global warming 94, 96– 8 Glycine max see soybean goethite 162, 164 goitre 18 Gouy – Chapman theory 179 Gouy – Chapman– Stern theory 180 grain cadmium accumulation 143– 4 quality 226– 8

INDEX yield base bending moment 260 chlormequat effect 247– 8, 251– 2 ethephon effect 249, 252– 3 lodging 218– 19, 225– 6, 247– 9, 251– 3 plant growth regulators 247–9, 251– 3 grasses dynamic foliar uptake model 132– 3 grazed pastures gaseous nitrogen emission 37 – 104 greenhouse gas emissions 93, 95 groundwater contamination 45 growth regulators see plant growth regulators

H

Hagberg falling number (HFN) 226– 8 halloysite 166 height at center of gravity 258– 9 plant growth regulators 246– 9 reduction through plant breeding 254– 7 Helianthus annuus see sunflower helium atmosphere system 80 herbage density 132– 3 HFN see Hagberg falling number highly weathered soils (HWS) 163– 4, 193 human health see also geo-medical issues soil pollution studies 3 – 4 trends in soil-related studies 3 – 6 humidity, lodging 227– 8 HWS see highly weathered soils hybrids NuSun sunflower identity preservation 289 NuSun sunflower production methods 287– 8 hydrolysis of urea 61 – 2 hydrophilic pores 134– 5 hydroxyls 172

311 I

identity preservation, NuSun sunflower hybrids 289 ideotype, lodging-proof 257– 61 immobilization 51 imogolite 165– 6 industrial pollution 4, 27 – 8 infant mortality 9 – 10 influx, cadmium to plant roots 133–4 ingestion, mineral nutrients soil-to-man chain 6 – 8 inheritance NuSun sunflower oil 284– 6 tocopherol in sunflower 291– 2 intensive farming 4 – 5 interfaces, variable charge soils 176– 93 Intergovernmental Panel on Climate Change (IPCC) methodology 86 – 8 inter/intraspecific crosses, Brassica 292– 4 iodine 2 – 3, 9, 18 ion competition, cadmium uptake and accumulation 140– 1 ionic composition, colloidal stability 184 IPCC see Intergovernmental Panel on Climate Change iron 17– 18 iron oxides mineralogy of variable charged soils 161– 2 phyllosilicate interactions 185–90 variable charged sorbents 171– 2 irrigation, effluent 45 –8 isoelectric weathering 168

J

Japan, cadmium 14

K

kaolinite dual-charge sorbents 169– 70

312

INDEX

mineralogy of variable charged soils 161– 3 variable charge soil interface models 178– 80 Kyoto Protocol 86

L

leaching 52 – 3, 186, 188 lead 9, 18 – 19 legumes and nitrogen fixation 40 – 1, 97 – 8 liming 197 linear regression, cadmium models 124– 6 linolenic acid Brassica 294– 5 peanut oil 297– 9 soybean oil 274– 8 sunflower oil 283– 5 linolenic germplasm 275– 7 liquid – solid interfaces 176– 93 lodging anchorage failure 220, 233– 5 bending moments 228– 32 cereals 217– 63 crop management 236– 54, 262 cultivations 236– 9 lodging-proof ideotype 257– 61 mechanics 228– 36 models 235– 6, 262 nutrition 242– 4 observations 220– 5 plant breeding 254– 7, 262 plant failure types 220– 2 plant growth regulators 245– 54 quality effects 226– 8 root failure 220– 2, 233– 4 soil strength 234– 5 sowing date, rate and depth 239– 42 spatial patterns 223– 5 stem failure 232– 3 temporal patterns 222– 3 yield effect 225– 6, 247– 9, 251– 3 lodging-proof ideotype 257–61 long-distance cadmium transport 143– 4

M

macronutrients see mineral nutrients magnesium 22 – 3 maize, cadmium uptake 127– 8 malnutrition 26 – 7 managed pastures world productivity 39 manganese 19 –21 manure application 45 – 8, 54, 65 – 6, 97 – 8, 100 by-products 45 – 6 mass balance approach 76 – 9 measurement techniques ammonia volatilization 76 –9 denitrification 79 – 83 nitrous oxide 82 mechanics of lodging 228– 36 mechanistic models of cadmium uptake and accumulation in plants 129– 33, 145 membrane transporters 134 mercury 21 metallothioneins 136– 7 metal oxides 180– 1, 183 Michaelis – Menten equation 134– 5 micrometeorological methods ammonia volatilization 77 –8 denitrification 80 mineralization, nitrogen 48– 50, 60 mineral nutrients see also geo-medical issues animal nutrition 10 – 11 bioavailability 7 – 8 deficiencies and excess 4– 6, 10 – 11 food chain 8 – 9 indirect supply 8 – 9 soil-to-man chain 6 – 9 mineralogy highly weathered soils 163– 4 variable charge soils 161– 7 volcanic ash soils 164– 7 mineral – aqueous interfaces 176– 93 mining pollution 4 mitigation, gaseous nitrogen emission 98 – 102 Mitscherlich function 124

INDEX mixed sorbent systems 190– 3 MJD see Mseleni Joint Disease modeling ammonia volatilization 83 – 6 cadmium, uptake and accumulation in plants 121–47 interfaces in variable charge soils 177– 93 lodging 235– 6, 262 nitrous oxide emissions 86 – 94 moisture content ammonia volatilization in soil 69 denitrification in soil 69 – 71, 76 soil/infant mortality correlation 9 – 10 soil strength 235 molybdenum 21 Mseleni Joint Disease (MJD) 20 multiple-site adsorption model 178– 80 multiple sorbent systems 181– 2 mutagenesis, Brassica 294– 6 mycotoxins 228

N 13

N, denitrification measurement 80 N-labeled fertilizer 79 – 80 15 N-labeled gases 79 – 80 natural frequency, lodging 258–9 NDVI see Normalized Difference Vegetation Index necking, stem lodging 221 new technologies, lodging 256– 7 New Zealand Denitrification and Decompostion model (NZ-DNDC) model 89 – 91 Nitrapyrin 100– 1 nitrates denitrification rate 70 fertilizers 54 leaching 52 – 3 nitrification 50 nitrification inhibitors 70, 100– 1 nitrogen abiotic transformations 52 – 3 acid rain 95 – 6 15

313 ammonia volatilization 53 – 63, 67 – 9, 76 – 9, 83 – 6, 102– 4 ammonium fixation 52 animal excreta deposition 43– 4, 54 biological fixation 40 – 2, 54 biotic transformations 48 – 52 denitrification 52, 60, 63 – 7, 69 –76, 79 – 82, 102– 4 effluent irrigation 45 – 8, 54 fertilizers cereal lodging 242– 3 denitrification 65 environmental effects 94– 5, 97 – 8 grazed pasture inputs 41 – 3, 54 variable charge soils 201 gaseous emission from grazed pastures 37 – 104 ammonia volatilization 53 – 63, 67 – 9, 76 – 9, 83 – 6, 102– 4 climatic factors 68 – 9, 75 – 6 control management practices 98 – 102 denitrification 52, 60, 63 – 7, 69 – 76, 79 – 82, 102– 4 dynamics in pasture soils 48 – 53 environmental implications 94 – 8 factors affecting emission 67 – 76 future research 102–4 input sources of nitrogen 40 – 8, 54 measuring 76 – 82 modeling 83 – 94 nitrous oxide emission 57 – 9, 66 – 7, 71, 82, 86 – 94, 96 – 8 soil factors 67 – 75 transformation reactions 48 – 53 geo-medical issues 23, 27 global food production 39 global warming 94, 96 – 8 immobilization 51 inputs in grazed pasture 40 –8, 54 lodging 242– 4 manure application 45 – 8, 54, 65 – 6, 97 – 8, 100 mineralization 48 – 50, 60 nitrate leaching 52 – 3 nitrification 50

314

INDEX

ozone depletion 96 – 8 nitrogen factor 51 nitrosamine 20 nitrous oxide emissions 57 – 9, 66 – 7, 71, 82, 86 – 94, 96 – 8 Normalized Difference Vegetation Index (NDVI) 93 no-till systems 101– 2 novel fatty acids 281– 3, 296– 7 NOx emissions 95 NuSun sunflower 284– 92 identity preservation 289 industry progress 288 –9 inheritance 284– 6 production methods 287– 8 saturated fatty acid reduction 289– 90 tocopherol role 291– 2 nutrition see also mineral nutrients animal 10 – 11 lodging 242– 4 malnutrition 26 –7 under-nutrition 26 – 7 NZ-DNDC see New Zealand Denitrification and Decompostion model

O

oesophageal cancer 19 – 20 oil seed crops Brassica 292– 7 fatty acid composition 273–300 peanut 297– 300 soybean 274– 83 sunflower 283– 92 oleic acid Brassica 295– 7 peanut oil 297– 300 soybean oil 278– 9 sunflower oil 283– 9 oleoyl-phosphatidylcholine desaturase 300 olive oil 284 opaline silica 166 organic carbon, variable charge soils 194– 5 organic farming 101

organic matter denitrification rate 72 – 4 variable charge soils management 198– 9 Otomac tribe 6 Oxisols see variable charge soils oxyanions 172 oxygen availability and denitrification 69 – 70 consumption rate (respiration) 60, 69 – 70 ozone depletion 96 – 8

P

palmitic acid NuSun sunflower oil 290 soybean oil 279– 82 parasitic infections 6 –7 partial pressure 68 particle interaction effects 182–90 pastures gaseous nitrogen emission 37– 104 world productivity 39 peanut (Arachis hypogaea) 297– 300 breeding objectives 297– 8 oleic acid 297– 300 permanently charged clays 198– 202 Pervenets varieties 285– 6 PGRs see plant growth regulators pH charged surfaces interaction effects 183– 4 rain, foliar cadmium uptake 135 soil ammonia volatilization 67 – 8 cadmium uptake 127 decline in variable charge soils 194 denitrification rate 72, 75 variable charge soils management 195, 197 phloem, cadmium transport 143 phosphate cadmium accumulation in soils 13 fertilizers 13 geo-medical issues 21 – 2, 27

INDEX variable charge soils management 198– 202 phosphorus geo-medical issues 21 – 2 lodging 244 photosynthesis 226 phylloplane 123, 128 phyllosilicates dual charge sorbents 168– 70 iron oxide interactions 185– 90 volcanic ash soils 164 piggery effluents 46 – 7 pith 232– 3 plant growth regulators (PGRs) 219, 245– 54, 262– 3 plants see also height breeding and lodging 254–7, 262 cadmium accumulation mechanisms 136– 9 cadmium uptake and accumulation models 121– 47 density and lodging 240– 1 lodging 217– 63 mineral elements uptake 8 podoconidosis 7 point of zero charge (PZC) 185 point of zero net charge (PZNC) 167 point of zero net proton charge (PZNPC) 167 Poisson– Boltzmann equation 182 pollution agricultural 94 geo-medical issues 3 –4, 27– 8 pores 134– 5 potassium geo-medical issues 22, 27 lodging 244 potential determining ions 172– 4 poultry manure 45 –6 process-based models 89 proximal regulators 60, 69 pytochelatines 136– 8 PZC see point of zero charge PZNC see point of zero net charge PZNPC see point of zero net proton charge

315 Q

quality effects, lodging 226– 8 Quantitative Trait Loci (QTL), lodging 257 R

radon 5 – 6 rainfall cadmium deposition on leaves 128– 9, 135– 6 lodging 223 rain pH, foliar cadmium uptake 135 rapeseed see Brassica REA see relaxed eddy-accumulation reduced height alleles 254–5 relaxed eddy-accumulation (REA) technique 78 respiration 60, 69 – 70 rhizosheath 234 rhizosphere 123, 140 Rht alleles 254– 5 rolling 238–9, 260– 1 roots cadmium uptake empirical models 124– 8 exudates 134 mechanistic models 129– 32 parameters affecting 139– 40 processes and phenomena 133– 4 failure 220– 2, 233– 4 growth equations 139– 40 lodging 220– 2, 233–4 radius 140 rhizosphere 123, 140 ruminants 10 – 11 ryegrass 127 S

salt adsorption 174– 5, 188– 9 saturated fatty acids Brassica 294, 296– 7 NuSun sunflower 289–90 soybean oil 279– 81

316

INDEX

seeds, cadmium accumulation 143–4 selenium 24 – 5 self-weight moment 228 semi-dwarf varieties 218– 19 sewage sludge 123, 128– 9, 135 shear strength 234– 7 sheep excreta deposition 43 – 4 shoot leverage 228 shoot lodging 217– 63 short-distance cadmium transport 142– 3 SIDS see sudden infant death syndrome silicate 198– 202 silicon 244 slurry applications 54, 65 – 6 sodium 24 soil acidification 95– 6 acidity 72, 75 aeration 69 – 70 ammonia volatilization 67 – 8 compaction 65, 70 denitrification 69 – 75 erosion 5, 19 – 20 fertility 8– 9 infant mortality/moisture content correlation 9 –10 moisture content denitrification 69 – 71, 76 infant mortality 9 – 10 soil strength 235 organic carbon 194– 5 particle surface charge 168– 72 pH ammonia volatilization 67 – 8 cadmium uptake 127 denitrification rate 72, 75 variable charge soils 194– 5, 197 pollution 3 – 4, 27 – 8 shear strength 234– 7 splash 135– 6, 145 strength 234– 9, 263 temperature ammonia volatilization 68 – 9 cadmium accumulation in plants 138 denitrification rate 75 – 6 texture 70

types ammonia volatilization 55 – 6 cadmium deposition on leaves 135– 6 denitrification rate 70 – 1, 73 – 4 nitrous oxide emission 57– 9 variable charge soils 159– 202 water content 9– 10, 69 – 71, 76, 235 water thresholds 70, 71 soil organic matter (SOM) 193, 198– 9 soil-related geo-medical issues see geo-medical issues soil-to-man mineral nutrient supply chain 6 –9 solar ultraviolet radiation 96 solid-like/unlike potential determining ions 172– 4 solid phase chemistry, variable charge soils 168 solid – aqueous interfaces 176– 93 SOM see soil organic matter sorbents dual-charge 168– 70 variable charge 170– 2 sorghum sickness 51 sorption, variable charge soils 172– 6 sowing, date, rate and depth 239– 42 SOx emissions 95 soybean (Glycine max) 274–83 cadmium uptake 127 genetic engineering 281– 3 linolenic acid 274– 8 novel fatty acids 281– 3 oleic acid 278– 9 saturated fatty acids 279– 81 unsaturated fatty acids 274– 9 spatial patterns 223–5 Spodsols see variable charge soils stearic acid NuSun sunflower oil 290 soybean oil 279– 81 stele system 142 stem base strengthening 246– 7, 250– 1, 256 curvature 232 failure 232– 3

INDEX failure moment 232, 256 lodging types 220– 1 stock camps 44 stock reduction 99 stubble sickness 51 subsistence communities 5 sudden infant death syndrome (SIDS) 10 sunflower (Helianthus annuus) 283–92 NuSun sunflower oil 284– 92 superphosphate 202 surface charge 182– 90 surface effective charge 190– 3 surface potential 177– 8 surface sites, background electrolyte ion competition 175– 6 surface waters 46 symbiotic fungi 141– 2 T

temperature soil ammonia volatilization 68 – 9 cadmium accumulation in plants 138 denitrification rate 75 – 6 unsaturated fatty acid synthesis 279 temporal fluctuations 75 – 6 temporal patterns 222– 3 terrestrial thermal radiation 96 texture, soil 70 thermal radiation 96 tillage 101– 2 tocopherol 291– 2 tolerance, cadmium in plants 136– 7 tomato spotted wilt tospovirus 299 trace elements animal nutrition 10 – 11 lodging 244 tramlines 223, 225 trans fatty acids 283 Transkei, South Africa 19 – 20 transport, cadmium 142– 4 treading by animals 65, 70 triple layer model 179– 80 two-pond farm effluent treatment system 46 – 7

317 U

Ultisols see variable charge soils ultraviolet radiation, solar 96 under-nutrition 26– 7 unsaturated fatty acids 274– 9 uptake, modeling cadmium uptake by plants 121–47 urban pollution 4 urea fertilizers 54, 75, 97 hydrolysis 61 – 2 urine 43 – 4, 54, 98

V

variable charge soils (VCS) 159– 202 aqueous phase chemistry 167– 8 chemical degradation 194– 5 chemical reactions at solid-aqueous interfaces 176– 93 chemistry 167– 93 direct probing of electrical double layer 176– 7 dual-charge sorbents 168– 70 highly weathered soils 163– 4, 193 management 193– 202 mineralogy 161– 7 modeling the interfaces 177– 93 soil particles and their surface charge 168– 72 solid phase chemistry 168 sorption 172– 6 variable charge sorbents 170– 2 volcanic ash soils 164– 7 world distribution 160– 1 variable charge sorbents 170– 2 VAS see volcanic ash soils vegetable oils see also Brassica; peanut; soybean; sunflower world consumption 273 vitamin C 20 volatilization, ammonia 53 –63, 67– 9, 76 – 9, 83 – 6, 102– 4 volcanic ash soils (VAS) 164– 7 volcanic glass 165

318

INDEX W

water content see moisture content water-filled porosity (WFP) 70, 71 water thresholds of soil 70, 71 weathering factors determining rate 165 highly weathered soils 163– 4, 193 isoelectric 168 volcanic deposits 164– 5 wet soils, infant mortality 9 – 10 WFP see water-filled porosity wheel-ways (tramlines) 223, 225 wind ammonia volatilization 68, 78 – 9 bending moments 228– 32 crop management 253– 4 failure wind speed 236– 7 gusts 238 -induced base bending moment 228– 32, 261 lodging 223, 228– 32, 236– 8, 253– 4 speed 68 tunnels 78 – 9, 231

X

X-ray standing wave (XSW) 177 X-ray techniques, electrical double layer structure 177 xylem 143

Y

yield base bending moment 260 chlormequat effect 247– 8, 251– 2 ethephon effect 249, 252– 3 lodging 218– 19, 225–6, 247– 9, 251– 3 plant growth regulators 247– 9, 251– 3

Z

zero charge 167, 185 zinc 25 – 7 ZINST height 77 – 8

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