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ADVANCES IN

AGRONOMY VOLUME 44

This Page Intentionally Left Blank

ADVANCES IN

AGRONOMY Prepared in Cooperation wirh the AMERICAN SOCIETYOF AGRONOMY

VOLUME 44 Edited by N. C . BRADY Science and Technology Agency for International Development Department of State Washington, D . C .

ADVISORY BOARD N. L. TAYLORH. G . HODGES

E. L. KLEPPERG . L. HORST R. J . KOHEL R. H. MILLER G . E. HAM S . MICHELSON K. H. QUESENBERRY C. W. STUBER G . H . HEICHELD. E. KISSEL

ACADEMIC PRESS, INC. Harcourt Brace Jovanovich, Publishers San Diego New York Boston London Sydney Tokyo Toronto

This book is printed on acid-free paper.

@

Copyright 0 1990 by Academic Press, Inc. All Rights Reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher.

Academic Press, Inc. San Diego, California 92 10 1 United Kingdom Edition published by Academic Press Limited 24-28 Oval Road, London NW I 7DX

50-5598

Library of Congress Catalog Card Number:

ISBN 0-12-000744-4

(alk. paper)

Printed in the United States of America 9 0 9 1 9 2 9 3 9 8 7 6 5 4

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2

1

CONTENTS CONTRIBUTORS ..........................................................................

PREPACE ..................................................................................

ix xi

VARIATION IN TIME OF SEEDLING EMERGENCE WITHIN POPULATIONS: A FEATURE THAT DETERMINES INDIVIDUAL GROWTH AND DEVELOPMENT

L. R. Benjamin I. 11. 111. 1V.

.......................................... Introduction ................................ Factors That Influence Time of Seedling Emergence.. ......................... Importance of Variation in Time of Seedling Emergence to Crop Development .............................................................................. Conclusions ............................ References .................................................................................

1 2

9 20 21

FORAGE TREE LEGUMES: THEIR MANAGEMENTAND CONTRIBUTIONTO THE NITROGEN ECONOMY OF WET AND HUMID TROPICAL ENVIRONMENTS

Graeme Blair, David Catchpoole, and Peter Horne 1. 11.

111. 1v. V. VI. VII. VIII.

Introduction.. .......................................................... Species of Useful Tree Legumes. ............................................... Agronomic Performance of Tree Legumes ........................................ Tree Legume Leaf as Animal Feed .................................................. Management of Tree Legumes........................................................ Nitrogen Yields of Material Harvested from Tree Legumes .................. Nitrogen Recycling via Leaf and Excreta.. ...................... Conclusion ................................................................................. References ........................................................................

21 28 29 34 36 45 46 49 50

STATISTICAL ANALYSES OF MULTILOCATIONTRIALS

Jose Crossa I. 11.

Introduction ................................................................................ Conventional Analysis of Variance.. ................................................ V

55

51

vi

CONTENTS

111. Joint Linear Regression................................................................. IV. Crossover Interactions.. ................................................................ V. Multivariate Analyses of Multilocation Trials .................................... VI. AMMl Analysis ........................................................................... VII. Other Methods of Analysis ............................................................ VIII. General Considerations and Conclusions .......................................... References .................................................................................

61

68 70 76 80 81 82

EVALUATION AND DOCUMENTATION OF GENETIC RESOURCES IN CEREALS

A. B. Damania I. 11. 111.

IV. V. VI. VII.

Introduction ..................... ................................................ Evaluation of Cultivated Wheat ...................................................... Evaluation of Cultivated Barley ......................................... Genetic Resources from Ethiopia.. .................................................. Evaluation of Wild and Primitive Forms of Wheat and Barley ............... Documentation of Genetic Resources .............................................. Summary and Conclusions. .................... References .................................................................................

87 90 93 95 96 I02 I05 107

MODELING CROP ROOT GROWTH AND FUNCTION

Betty Klepper and R. W.Rickman 1. 11.

111. IV. V. VI.

Introduction .............................................. Early Models .............................................................................. Desirable Model Features.. ................................................... Model Components ...................................................................... Some Existing Root Growth and Function Models ............................. Limitations to Development of Root Growth Models ..........................

...............................

I13 114 115

118 I28 130 131

GENETIC MANIPULATION OF THE COWPEA (Vigna unguiculafa [L.] Walp.) FOR ENHANCED RESISTANCE TO FUNGAL PATHOGENS AND INSECT PESTS

A. 0. Latunde-Dada 1. 11. 111.

IV.

Introduction ................................................................................ Insect Pests ................................................................................ Fungal Pathogens.. ....................................................................... Tissue Culture Technology ............................................................

133 139 141 142

vii

CONTENTS V.

Conclusions and Epilogue.. .................................................... ........ References ............................................................ ....................

.

149

I 50

NITROGEN FIXATION BY LEGUMES IN TROPICAL AND SUBTROPICAL AGRICULTURE

Mark B. Peoples and David F. Herridge

I. 11.

111. IV. V. VI .

.

Introduction.. .................................................................. ........... Methods of Assessing N2 Fixation N2 Fixation in Legume Production Systems ...................................... Contribution of Legume N to Plant and Animal Producti Strategies to Enhance N2 Fixation ................................................... Concluding Remarks .................................,............ References ............................. ..............................................

i56 158 177 190 202 216 216

DISTRIBUTION, COLLECTION, AND EVALUATION OF Gossypium

A. Edward Percival and Russell J. Kohel

.

11.

Introduction.. ........ ........ ....................... Distribution ..........,.....................................................................

Ill. IV . V.

Evaluation.. ................................................................................ Concluding Remarks ................................ ..

1.

225 228 235 245 253 253

BREEDING WHEAT FOR RESISTANCE TO Septoria nodorum AND Septoria tritici

Lloyd R. Nelson and David Marshall

I. 11. 111. IV. V. VI .

Introduction.. .............................................................................. Identification of Resistance. ....................... Pathogen Variation.. ........... ......................................................... Genetics of Resistance ............................................. Sources of Resistance ..... ....,....................... Discussion and Conclusions ...........................................................

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

257 258 268 270 272 272 214

279


CONTRIBUTORS Numbers in parentheses indicate the pages on which the authors' contributions begin.

L. R. BENJAMIN ( l ) , AFRC Institute of Horticultural Research, Wellesbourne, Wanvick CV35 9EF, England GRAEME BLAIR (27), Australian Centre for International Agricultural Research, Department of Agronomy and Soil Science, University of New England, Armidale, New South Wales 2351, Australia DAVID CATCHPOOLE* (27), Australian Centre for International Agricultural Research, Department of Agronomy and Soil Science, University of New England, Armidale, New South Wales 2351, Australia JOSE CROSSA (55), Biometrics and Statistics Unit, International Maize and Wheat Improvement Center (CIMMYT),06600 Mexico D. F., Mexico A. B. DAMANIA (87), Genetic Resources Unit, International Centerfor Agricultural Research in the Dry Areas (ICARDA),Aleppo, Syria DAVID F. HERRIDGE (155), Australian Centre for International Agricultural Research (Project 8800),New South Wales Agriculture and Fisheries, Tamworth, New South Wales 2340, Australia PETER HORNE (27), Australian Centre for International Agricultural Research, Department of Agronomy and Soil Science, university of New England, Armidale, New South Wales 2351, Australia BETTY KLEPPER ( 1 13), United States Department of Agriculture, Agricultural Research Service, Columbia Plateau Conservation Research Center, Pendleton, Oregon 97801 RUSSELL J. KOHEL (229, United States Department of Agriculture, Agricultural Research Service, Southern Crops Research Laboratory, College Station, Texas 77840 A. 0. LATUNDE-DADA (133), Department of Crop Production, College of Agricultural Sciences, Ogun State university, Ago-Iwoye, Ogun State, Nigeria DAVID MARSHALL (257), Texas A&M University Research and Extension Center at Dallas, Dallas, Texas 75252 LLOYD R. NELSON (257), Texas A&M University Agricultural Research and Extension Center at Overton, Overton, Texas 75684

*Present address: Queensland Department of Primary Industries, Ayr. Queensland 4807, Australia.

ix

X

CONTRIBUTORS

MARK B. PEOPLES ( I S ) , Australian Centre for International Agricultural Research (Project SSOO), CSIRO Division of Plant Industry, Canberra, A . C . T . 2601, Australia A. EDWARD PERCIVAL (225), United States Department of Agriculture, Agricultural Research Service, Southern Crops Research Laboratory, College Station, Texas 77840 R. W. RICKMAN ( 1 13), United States Department of Agriculture, Agricultural Research Service, Columbia Plateau Conservation Research Center, Pendleton, Oregon 97801

PREFACE In the nearly 25 years I have had the privilege of editing this serial, it has been an inspiration to witness the desire and willingness of crop and soil scientists to prepare review articles for their compatriots. Scientists throughout the world have taken literally thousands of hours of their own time and energies to prepare articles for Advances in Agronomy gaining little but the satisfaction that they were doing a favor for their fellow scientists. They have indeed furthered the cause of science by writing these reviews. The authors of the nine articles in this volume have followed the tradition of their predecessors. Located at research institutions in six different countries, they maintain the international focus of this serial. The subjects covered vary from genetic resources of cereals and cotton to timing of seedling emergence and modeling of root growth and function. Two articles focus on tropical crops and agriculture as well as agro-forestry, subjects of keen concern as low-income farmers of the tropics struggle to increase food production while maintaining the quality of their environment and especially of their soils. Efforts to increase the host resistance of wheat and cowpeas are covered in two articles. These are evidence of the increasing focus on alternatives to the use of chemical pesticides to control plant pests. Host resistance is one of the characteristics evaluated in multilocational field trials around the world. The statistical analyses of such trials are the subject of another article in this volume. Thanks are due the advisory board of the American Society of Agronomy and the directors-general of three international agricultural research centers for suggesting topics and authors for this serial. To the 15 authors of the important reviews contained herein I express my special gratitude. N. C. BRADY

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ADVANCES IN AGRONOMY, VOL. 44

VARIATION IN TIME OF SEEDLING EMERGENCE WITHIN POPULATIONS: A FEATURE THAT DETERMINES INDIVIDUAL GROWTH AND DEVELOPMENT L. R. Benjamin AFRC Institute of Horticultural Research Wellesbourne, Warwick CV35 9EF, England

Introduction Factors That Influence Time of Seedling Emergence A. Water B . Temperature C . Sowing Depth D . Seed Attributes E. Conclusions Ill. Importance of Variation in Time of Seedling Emergence to Crop Development A. Total Plant Growth B. Partitioning between Organs C . Organ Morphology and Composition D. Longevity IV. Conclusions References 1. 11.

I. INTRODUCTION The point in time when the growing point of a shoot emerges from the soil into the aerial environment is one of the most easily observed events in crop development. The range of percentage and timing of seedling emergence can be large, even in cultivated species, because emergence is the culmination of a large number of preceding events. For example, FinchSavage (1984) reported in carrots sown at eight different times between 1 1 February and 15 June in the United Kingdom that the number of days between the 10 and 90 percentile points for emergence ranged from 11 to 24. In noncultivated Umbelliferae. and in some cultivated Umbelliferae 1 Copyright Q 1990 by Academic Press. Inc. All rights of reproductionin any form reserved.

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species, there are also dormancy mechanisms that result in periodicity of emergence times (Roberts, 1979). Much attention has been directed to unraveling the complex interactions between the agronomic and genetic factors that influence seedling emergence. The salient features of these factors and their influence on variation in seedling emergence time will be reviewed here. Most plant communities are characterized by intense competition between individuals for growth resources, which leads to the development of dominance hierarchies (Watkinson, 1985; Benjamin and Hardwick, 1986; Weiner and Thomas, 1986). These hierarchies are important in crops because they contribute to variation in weight per plant, which is undesirable for a market that increasingly requires uniformly sized produce for processing and the fresh market (Anonymous, 1982), and can also contribute to loss of economic yield (Benjamin and Hardwick, 1986). The hierarchies are also important in natural communities because they contribute to size-dependent fecundity (Pacala and Slander, 1985; Watkinson et al., 1989) and to size-dependent mortality (Mithen et ul., 1984; Schmitt et ul., 1987; Thomas and Weiner, 1989). This review will examine the relevance of time of seedling emergence to the development of these hierarchies and seek mechanisms to account for any relationships.

II. FACTORS THAT INFLUENCE TIME OF SEEDLING EMERGENCE Crops have been bred and selected for genetic uniformity and elimination of seed dormancy mechanisms. Engineers have developed sophisticated equipment to produce good seedbed tilths and to sow seeds at uniform depth. So why should there be variation in times of seedling emergence? About a hundred papers are published annually on germination (Lovato, 1981) and this subject has been reviewed extensively (Koller, 1972; Heydecker, 1973; Harper, 1977; Heydecker and Coolbear, 1977; Johnston, 1979; Perry, 1982). The purpose of this review is not to make another exhaustive study but rather to examine the ideas that are implicit in most of these studies and to determine how much is already known about the causes of variation in time of seedling emergence. Although germination is a complex process, it has only three requirements: water, warmth, and a free exchange of gases. Seed dormancy is common in most species, but despite some notable exceptions, it has largely been overcome in commercial crops (Villiers,

SEEDLING EMERGENCE WITHIN POPULATIONS

3

1972; Maguire, 1983). Seeds are usually sown directly into soil, often at varying depths, and the subsequent germination is in conditions of fluctuating temperature and water supply. The effects of these factors on time of seedling emergence will be considered in the next sections. A. WATER Water influences the spread in time of seedling emergence in a number of ways. First of all, water is essential for germination, so any restriction on its supply reduces the rate and final percentage of seed germination. The supply of water to the seed is governed by the conductivity of the soil water (Collis-George and Sands, 1959; Williams and Shaykewich, 1971; Hadas and Russo, 1974a), the degree of seed-soil water contact (Sedgley, 1963; Manohar and Heydecker, 1964; Collis-George and Hector, 1966; Harper and Benton, 1966; Hadas and Russo, 1974a), and the osmotic and matric potentials (Collis-George and Sands, 1959, 1962; Manohar and Heydecker, 1964; Williams and Shaykewich, 1971; Dasberg and Mendel, 1971; El-Sharkawi and Springuel, 1979; Ross and Hegarty, 1979; Willat and Struss, 1979; Tipton, 1988). Increasing the supply of water can restrict the supply of oxygen that is necessary for germination. Oxygen is sparingly soluble and its solubility decreases with increasing temperature, whereas the metabolic demand for this gas increases with temperature. In addition, any complementary buildup of carbon dioxide has a poisoning effect on germination (Heydecker, 1958). Consequently, even slight excesses in the amount of moisture can have large inhibitory effects on germination (Heydecker et al., 1969; Dasberg and Mendel, 1971). Hanks and Thorp (1956) reported that emergence of wheat was restricted when the oxygen diffusion rate g cm-2 min-I. This corresponded to an air (ODR) fell below 75-100 x pore space of 16% in a silt clay and 25% in a fine-sandy loam. Subsequent work shows that the rate of germination is restricted by an ODR as little as 20 x lo-' g cmP2min-l (Dasberg and Mendel, 1971). Insufficient oxygen supply has been alleviated by coating seeds with calcium or zinc peroxides, or by incorporating calcium peroxide in the growing medium, but the beneficial effects varied greatly with species and occurred only when the moisture content of the growing medium was very high. Furthermore, the addition of peroxides in drier media often had a detrimental effect on germination and emergence (Brocklehurst and Dearman, 1983; Langan et af., 1986). Even if germination proceeds rapidly and uniformly, there can be a wide spread in time of seedling emergence due to a restriction of seedling growth

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L. R. BENJAMIN

by the strength of the soil, which is largely governed by its water content (Arndt, 1965; Collis-George and Williams, 1968; Royle and Hegarty, 1977; Hegarty and Royle, 1978). In addition, slow drying gives closer packing of soil particles, resulting in high soil strengths (Gerard, 1965). However, the more important restriction to seedling emergence is the creation of crusts by surface drying (Hanks and Thorp, 1956,1957; Royle and Hegarty, 1977; Nuttall, 1982). Spread in time of emergence is determined by soil strength because the emergence force that seedlings exert develops dynamically and is a linear function of volumetric soil-water content and the cross-sectional area of the seedlings (Gerard, 1980). Taylor and Broeck (1988) measured the emergence force exerted by nine vegetable species at 25°C in sand at 15% moisture content and showed that the time taken to exert maximum force ranged from 4 hr in red beet to 21 hr in snap bean. Increasing the salinity of soil water caused a reduction in the size of the emergence force exerted by seedlings and increased the time required to exert the maximum force (Sexton and Gerard, 1982). Adding nitrogen fertilizers to soils has reduced percentage emergence, presumably because of osmotic effects (Hegarty, 1976a; Page and Cleaver, 1983). Nearly all studies of the effects of fertilizers on seedling growth have examined only final percentage emergence. However, Henriksen (1978)showed that addition of 75 or 150 kg N ha-' prior to sowing onions increased the standard deviation of emergence times by about half a day as well as reduced the percentage emergence compared with addition of the nitrogen after emergence. The salts that increase the salinity of the soil water can have the opposite effect of stimulating seedling growth by supplying essential mineral nutrients, such as phosphorus (Costigan, 1984). Most studies of seedling emergence have imposed constant soil moisture conditions. In nature, however, seeds are exposed to a fluctuating supply of water. This fluctuation affects variation in mean time of seedling emergence between populations in both weed (Roberts, 1984) and cultivated species (Hegarty, 1976b; Finch-Savage, 1986), but is also liable to be a major determinant of the individual-to-individual variation in time of seedling emergence within a population. B. TEMPERATURE In some species, seeds require exposure to low temperatures to break dormancy (see Roberts, 1972 for a review). All species show a qualitative relationship between germination parameters and temperature. The usual


5

responses are an approximately linear increase in rate (reciprocal in time taken to start of or some percentage of germination) with increasing temperature from a threshold to a maximum, with or without a plateau, followed by a linear decline at superoptimal temperatures. As a consequence of this linearity, it is convenient to describe the effect of temperature on the mean time of seedling emergence in terms of temperature sums (often erroneously called heat sums) (Hegarty, 1973; Bierhuizen and Wagenvoort, 1974; Garcia-Huidobro et al., 1982a). Only a few studies have examined the effect of temperature on the variability in the time of germination, but there is evidence in carrots that the spread in time of germination decreases with increase in temperature over the range 5°C to 25°C (Gray, 1979). In nature, seeds are exposed to fluctuating temperatures and, for noncultivated species, this might be a requirement for germination (Thompson, 1974). However, for most cultivated species, fluctuations in temperature have negligible practical effects on time of germination (Wagenvoort and Bierhuizen, 1977; Garcia-Huidobro et al., 1982b). In moist seedbeds, the rate of seedling emergence has a relationship with temperature similar to that described for germination (Muendel, 1986; Finch-Savage, 1986), and temperature sums have been used to describe the effects of temperature on the timing of emergence (Khah et al., 1986; Tenhovuori, 1986). However, the timing of seedling emergence is not governed entirely by the relationship between germination and temperature, because low temperatures also increase the time taken by seedlings to exert maximum force (Gerard, 1980). An example of this interaction between temperature and soil compaction was found in calabrese by Hegarty and Royle (1978). They showed that as temperature decreased from 20°C to 6"C, percentage emergence decreased from 93% to 78% when 0.6 N cm-* pressure had been applied, but the percentage emergence decreased from 90% to 33% when 4.8 N cm-* had been applied. The interaction between temperature and soil-water matric potential was quantified by Tenhovuori (1986), who showed that the temperature sum required for 50% emergence increased linearly above a threshold value as the soil-water matric potential increased. Gummerson ( 1989) examined the influence of seedbed preparation practices on the influence of moisture content, impedance, aeration, and temperature on the emergence of sugar beet. Of all four factors, he reported that temperature was the one that consistently limited rate of seedling emergence. There appear to be no studies that have quantified the relative importance of temperature for the spread in time of seedling emergence.

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L. R. BENJAMIN

C. SOWING DEPTH The amplitude of diurnal variation in temperature lessens and the time of maximum and minimum daily temperature shifts with increasing depth (Orchard and Wurr, 1977). Hence, deep-sown seeds experience a more uniform temperature than shallow-sown seeds. Similar considerations would apply to moisture content of the soil. However, deep-sown seeds would be expected to take longer to emerge and small seeds often do not have the ability to penetrate through a deep layer of soil (Moore, 1943; Black, 1956; Stickler and Wassom, 1963; Arnott, 1969; Snyder and Filban, 1970; Bedford and MacKay, 1973; Wagenvoort and Bierhuizen, 1977; Abul-Fatih and Bazzaz, 1979; Buckley, 1982;Nuttall, 1982). This inability could be due to insufficient stored materials to generate the osmotic gradient necessary to overcome the pressure exerted by the soil (Black, 1956)or the seedling might be too weak to withstand the forces necessary to overcome the resistance of the soil, with the hypocotyl breaking as it drags the cotyledon through the soil (Rathore et al., 1981). Nuttall (1982) attributed better emergence of rape from small seeds to the requirement for less energy to push small cotyledons through the soil crusts. However, the differences in seed sizes were confounded with differences in cultivar in his experiments and the optimum sowing depths for cabbage, lettuce, carrot, and onion were 1.5-2.5 cm, despite differences between these species in seed size, presence of endosperm, and being mono- or dicotyledons (Heydecker, 1956). D. SEEDATTRIBUTES The previous sections have concentrated on the effects of the external environment on variation in time of seedling germination and emergence, but attributes of the seed also influence the rate of germination and emergence. Even in a favorable, uniform environment, seeds do not germinate synchronously but display a probability of germinating in a unit length of time (Thornley, 1977; Bould and Abrol, 1981).The effect of environmental factors such as temperature and water supply is to influence this probability of seed germination (Harper, 1977; Bould and Abrol, 1981). This stochastic nature might be an inevitable consequence of germination being a chain of many physical, biochemical, and physiological events (Thornley, 1977; Tipton 1984). For example, in carrots, germination was faster in seeds containing large embryos (from primary umbels) than in those containing small embryos (from secondary umbels) (Gray, 1979). Also the


7

standard deviation of germination time was less in seed lots with a low seed-to-seed variation in embryo length (mature seed lots) than in those containing variable embryo lengths (immature seed lots). Although dormancy is not considered to be a problem for germination in most cultivated species, it is well known in many natural species. Furthermore, there is a well-known inhibition of germination in some cultivated species by specific environmental stimuli. For example, light can inhibit germination of some cultivars of lettuce, tobacco, and tomato (Pollock, 1972). The corky capsules that surround beet seeds contain a watersoluble inhibitor to germination (but see Morris et al., 1984 for an opposing view). Carrot seeds were considered not to contain such inhibitors, but recent work on seed priming has revealed their presence (Pill and FinchSavage, 1988). Thus, these inhibitors of germination may be more ubiquitous in cultivated crops than previously suspected. Attributes of the seed also interact with environmental factors to determine the rate of germination. For example, Harper and Benton (1966) showed that the germination of all types of seeds was restricted by low matric potential when placed on sintered glass disks, but mucilaginous seeds were least sensitive, spiny reticulate seeds were the most sensitive, and smooth seeds showed a graded response to water tension. Small seeds were less sensitive to water tension than large seeds. Time of seedling emergence is controlled by genetic constitution (Eagles, 1988; Lafond and Baker (1986) and seed size (Lafond and Baker, 1986). However, some studies showed no effect of seed size on time of seedling emergence (Naylor, 1980; Stanton, 1984). These inconsistent results might be attributed to the use of different growing media in the different studies. The optimum seed-soil water contact for germination is achieved when the mean aggregate size of soil particles is one-fifth to one-tenth of the seed’s diameter (Hadas and Russo, 1974b). Adverse soil conditions might be partially overcome by using seeds that are “robust.” Some seed lots have persistently high field emergence over a wide range of soil conditions (Hegarty, 1974). Osmotic priming of seeds often improves seedling establishment, presumably by bringing all seeds to a uniformly mature state (see Bradford, 1986 for a review of this technique). It might be possible to breed for specific seed properties that favor germination, for example, small seeds and cracked testas (Whittington, 1978). However, these factors that favor germination might be detrimental to emergence of seedlings in field conditions. It is interesting to consider whether seed attributes or environmental factors dominate time of seedling emergence. Only a few studies have addressed this question directly, but indirect studies indicate an overriding importance of the environment. For example, varying soil texture has

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large effects on seedling emergence (Hammerton, 1961 ;Wurr e f al., 1982). There are even large interactions between the method of watering (by capillary action or by surface watering) and soil moisture content on the percentage of seedling emergence (Heydecker, 1961). However, attributes of the seed can influence emergence in unexpected ways. For example, oil seed rape seedlings adapt to high soil impedance by decreasing the time taken to develop their full emergence force. This response to soil impedance was enhanced or inhibited by substances that affected ethylene production or action (Clarke and Moore, 1986). When such subtle interactions occur between seed and environment, it is perhaps naive to determine their relative importance. However, the relative importance of various attributes of seeds for variation in time of seedling emergence has been estimated (Waller, 1985). Waller collected seeds from cleistogamous (self-pollinating) and chasmogamous (cross-pollinating)flowers of jewelweed (Impatiens capensis) and found that between a third and a quarter of the variation in time of seedling emergence was associated with seed weight, seed type, maternal parent, and their interaction. E. CONCLUSIONS

Variation in time of seedling emergence arises because it is the culmination of a large number of preceding processes whose rates can differ between individuals. Differences between seeds in their genetic constitution, development on the mother plant, and exposure to extraneous factors, such as fungal attack, produce variation in time of germination in uniform environments. In nature, an additional source of variation in time of germination occurs from heterogeneity of the soil. Harper et al. (1965) suggested that germination of broadcast seeds depends on available sites of warmth and moisture. This idea is a useful concept also for buried seeds. Hegarty and Royle (1978) noted that there was greater seedling emergence in a dry soil that had been compacted than in a similar soil that had not been compacted. They speculated that compaction had improved the water supply to the seeds, presumably by increased seed-water contact, which effectively increased the number of sites for germination. Dasberg and Mendel (1971) claimed that “the rate of seed-water uptake governs germination. This rate is determined in general by the energy status of the water in the germination medium, by its conductivity, and by the area of contact between seed and medium, which is a function of pore geometry and surface tension.” Seed death is another important aspect of the effects of soil conditions on seedling emergence (Harper, 1955; Hegarty, 1978). In a system as multifaceted as the seed-soil complex, it is inevitable that


9

there is a wide spread in seedling emergence times, even in a crop sown synchronously (Hegarty, 1976b). The foregoing studies indicate that manipulation of any one of a number of processes would reduce the spread in time of seedling emergence, but no one treatment would produce synchrony of emergence. Spread in time of seedling emergence can be reduced by improved seed production techniques, by laboratory techniques to bring all seeds to maturity (priming), and by improved engineering to give uniform depth and optimum seed-soil contact in the seedbed. However, the most pragmatic way of reducing the spread in time of seedling emergence is to ensure a continued supply of soil moisture at a level that is optimum for germination during the period of imbibition, radicle emergence, and eruption of the shoots through the soil surface. The purpose of the rest of this review is to examine the importance of this spread in time of seedling emergence to the subsequent development of the plant community.

111. IMPORTANCE OF VARIATION IN TIME OF SEEDLING EMERGENCE TO CROP DEVELOPMENT In the remaining part of this review, I shall examine the importance of seedling-to-seedling variation in time of emergence within populations on the subsequent development of each plant. Although much work has been done to compare the effects of treatments that influence mean time of seedling emergence in separate populations (Hegarty, 1976b; Symonides, 1978; Gummerson, 1989), this is of little value for determining the importance of time of seedling emergence on the interactions between individuals within a population. Therefore, the remainder of the review will be confined to those few studies that examined the development of individual plants. Is the time of seedling emergence truly a boundary in the course of plant development, or is it just an event of no consequence to the plant but easily observed by humans? Certainly there is a switch from carbon for growth provided by the mobilization of seed reserves to carbon provided by photosynthesis. However, presumably some mineral nutrient and water absorption occurs through the roots of a seedling whose shoots have not yet broken the soil surface. Black and Wilkinson (1963) appear to be the only workers to have experimentally distinguished between time of seedling emergence and preemergence relative growth rate. Pregerminated subterranean clover seeds were sown either synchronously or in plots containing a mixture of

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two sowing dates. In mixed sowing date plots, the plants were sown on a square grid with the early and late sowings alternating in a checkerboard design. The difference in sowing time was either 2, 4, or 8 days and the sowing positions were 1.5 cm apart. Despite sowing seeds carefully at uniform depth in boxes of compost, there was a spread in emergence time of 8 to 14 days for the early-sown plants and 5 to 10 days for the late-sown plants. Thus, there was a wide range of preemergence growth rates, which resulted in a wide overlap in the seedling emergence times from the different sowings. When the plants had a foliage height of 30 cm, the logarithm of dry weight was negatively correlated with time of seedling emergence. The novel point about this work was that the effect of time of sowing on the regression of weight per plant at harvest on seedling emergence time was examined and was found to have only a slight effect. Thus, time of seedling emergence, and not any correlation with preemergence growth rate, was responsible for the subsequent effects on plant weight. In the following sections the effect of time of seedling emergence on the growth, form, and composition of individuals in populations is examined.

A. TOTALPLANT GROWTH

At the point of seedlingemergence, plant weight is still minute compared with the potential and probable weight that the plant will attain. Plant growth at this time is nearly always exponential because there is virtually no self-shading or competition for growth resources from neighbors. Consequently, a difference of a few days in seedling emergence time can result in a manyfold difference in weight between plants. For example, Black and Wilkinson (1963)found that a delay in emergence of 5 days brought about a reduction in subterranean clover weight of about 50%, and a delay of 8 or 9 days produced a reduction in weight of at least 75%. Gray (1976) showed that, in lettuce at 26 days after sowing, seedlings that had emerged at 7 days were five to six times larger than those that had emerged at 15 days. When considering the importance of relative times of seedling emergence for the subsequent dry matter increment of individuals within a population, a number of factors have to be taken into consideration. First, the spread in time of seedling emergence in a population is important, but most studies relied on the natural spread in time of seedling emergence rather than attempting to modify it artificially. The time from seedling emergence to harvest is also relevant. As this time interval increases, there is a greater probability that individual plant growth will be influenced by some extraneous factor, for example, herbivory. Finally, the “state” of the population must be considered, such as the density of plants, or


11

whether the plants under consideration are a monoculture or part of a mixed-species population. Table I presents a summary of these factors and the percentage weight variation accounted for by spread in time of seedling emergence in a number of species. The percentage of weight variation associated with spread in time of seedling emergence was usually greatest when fewer than 20 days have elapsed between mean time of seedling emergence and harvest (Table I). (Gray, 1976; Benjamin, 1987). The paper by Benjamin (1982) (Table I) best illustrates how the percentage of weight variation associated with spread in time of seedling emergence increases as spread in time of seedling emergence increases. This trend is also seen in other work (Table I). Benjamin (1982) reduced the spread in time of carrot seedling emergence from 19 to 14 days by using a contact herbicide to kill the first seedlings to emerge. This treatment had no detectable effect on the frequency distribution of storage roots in different diameter grades, suggesting that relatively slight changes in spread of seedling emergence time have no detectable influence on variation in weight. Controlling time of seedling emergence might allow other sources of weight variability to be expressed more strongly. However, the residual sum of squares of root weight (after taking out the effect of emergence time) from plots that had small spreads in emergence times was no greater than the residual sum of squares from plots that had large spreads in emergence times (Benjamin, 1982). Therefore, there is no evidence that other sources of variation are able to express themselves to a greater extent when time of seedling emergence is controlled. The effect of density on the relationship between spread in time of seedling emergence and plant weight is difficult to interpret from Table I because the other factors were varied too. The very high percentage variation in weight associated with spread in time of seedling emergence reported by Ross and Harper (1972) is perhaps because they used extremely high densities (Table I). Benjamin (1982) showed that the increase in coefficient of variation (CV) of carrot shoot and storage root weight at wider spreads in seedling emergence time was greater at 400 than at 25 plants mP2. Ross and Harper (1972) noted that the last cocksfoot seedlings to emerge in a population growing at 30,000 plants m-’ had a weight only a little greater than that of seeds, even after 35 days of growth. The implication is that late-emerging seedlings are denied resources for growth by the earlieremerging plants and these competitive interactions are more intense at high densities. More direct evidence that relative time of seedling emergence determines the relative amount of growth resources that can be captured by an individual comes from a second experiment by Ross and Harper (1972) in

Table I Percentage Shoot Weight Variation Associated with Spread in Time of seedling Emergence

Species e

N

Dactylis glomerata Lactuca sativa

Spread in time of seedling emergence 10

Density (m-*)

Mean days from emergence to harvest

Accounted % variation

in weight

Notes

Reference

30,000

40

95

Ross and Harper

13 13 13 13 13 13 13

17 63 69 17

81 63 49 94

Gray (1976)

(1972) 9 9 9 11 11 6 5-10

Lolium perenne

-a

Impatiens capensis

23

24.48, or%

seedlings in 34 x 12cm tray 500- 1000

20

90

22 17

72 80

180

50

ca. 105

0.40. Culling of the F2 population for progression to the F3generation was made on the basis of N2 fixation (xylem relative ureides > 32%, see Fig. lo), plant type, and seed color. To establish the heritability of N2 fixation, the seed of 100 F2 lines, selected to cover all 1 1 families and range of xylem ureide levels, was sown in a replicated experiment in 1987. Levels of N2 fixation were again assessed for F3 plants by the ureide method and compared with data for the

selected for F3 generation

Mean

634 F2‘s rejected as low-fixing

s FIG.10. Ranges of relative abundance of ureide-N in xylem sap for the 1 1 F2 families and for the commercial and Korean parents. Plants were grown in high-nitrate soil in the field. The horizontal line indicates the cutoff value (32%) for selection of material for the F3generation.

210

MARK B. PEOPLES AND DAVID F. HERRIDGE

same lines the previous season. When data were divided into groups designated by a single common parent, correlations (broad-sense heritabilities) between F2 and F3 xylem ureide data were higher (range r = 0.24-0.72) relative to the pooled (Le., all parents) data ( r = 0.27). This implied that the separate populations behaved differently in the genetic control of N2 fixation. The generally significant correlations between F2 and F3 relative ureides indicated that nitrate tolerance was under quantitative genetic control with a broad-sense heritability of between 0.24 and 0.72 (Rose et al., 1989). B. RHIZOBIA, INOCULATION, AND PLANTNODULATION Legume inoculation is a long-established and successful practice. Vincent (1965) and others (e.g., Allen and Allen, 1958) have argued that it is a desirable practice in most agricultural soils throughout the world. Date (1977), however, cautioned that the need to inoculate was not universal and should be carefully determined for each individual situation before investing in inoculant production and use. There are three major groups of legumes that can be distinguished on the basis of compatibility with a range of strains of Rhizobium (Table XIX). At one extreme is a group of legumes that can form an effective symbiosis with a wide range of strains. Members of this group were nodulated by “cowpea-type” rhizobia and these Rhizobium spp. are so widespread in tropical soils that such legumes seldom respond to inoculation. Yet even within this supposedly “promiscuous” group that can be some host-strain specificity in terms of the symbiotic effectiveness of the associations formed (Gibson et al., 1982). At the other extreme are legumes with very specific rhizobial requirements. These specificities are most relevant when the legume is introduced to new areas. Response to inoculation of these legumes is usually successful provided that adequate numbers of rhizobia are applied at sowing. The third and intermediate group of legumes nodulate with many strains of Rhizobium, but effectively fix N2 with only a limited number of them. Thus inoculation and nodulation failures are more frequent because the inoculum strain is unable to compete with the ineffective but established soil populations of rhizobia. There are a number of conditions under which soils may be devoid of Rhizobium to form an effective symbiosis with a legume and which may warrant inoculation: (a) the absence of the same or a symbiotically related legume in the immediate past history; ( 6 ) poor nodulation when the same crop was grown previously; (c) when the legume follows a nonleguminous

NITROGEN FIXATION BY TROPICAL LEGUMES

21 1

Table XIX Legumes Grouped on the Basis of Nodulation and N2 Fmation with a Range of Rhizobium Speciesa

Nodulate effectively with a wide range of strains. Genera listed forming one loose group. Albizia Alysicarpus Arachis Calliandra Calopogonium Cajanus Canavalia Clitoria Croialaria Dolichos Eryihrina

Galaciia Gliricidia Indigofera Lablab Lespedeza Macropiilium Macroiyloma Mimosa Pachyrhizus Pongamia Neonotonia

Psophocarpus Pueraria Rhynchosia Siylosanihes (several subgroups) Tephrosia Teramnus Vigna Voandzeia Zornia

Nodulate with a range of strains but often ineffectively. Genera listed forming individual groups with some crossing between groups. Subgroups distinguishable. Acacia Adesmia Aeschynomene

Astragalus Centrosema ( 2 subgroups) Desmanihus Desmodium (2 subgroups)

Psoralea Sesbania(2 subgroups)

Nodulate effectively with specific strains only. Genera listed forming specific groups. Cicer Coronilla Glycine max Hedysarum Lathyrus Lens Leucaena a

Lotononis-Listia ( 3 subgroups) Lotus ( 3 subgroups) Lupinus (2 subgroups) Medicago Melilotus Onobrychis Ornithopus

Phase o1us Pisum Trifolium (many subgroups) Trigonella Vicia

After Peoples et al. (1989a).

crop in a rotation; (d)in land reclamation; and, (e) when environmental conditions are unfavorable for Rhizobium survival (e.g., very acidic or alkaline soils, under prolonged flooding, or very hot, dry conditions prior to planting). However, as a farming practice, inoculation generally remains the exception rather than the rule (Vincent, 1982). Exacting technology is essential for the production and distribution of inoculants (Date and Roughley, 1977),and the success of inoculation in the field depends on the procedure used and operator competence (Brockwell, 1980; Brockwell et al., 1988). In Australia and the United States, legume inoculation has played a funda-

212


mental role in the establishment of legume-based pasture and cropping systems, but less use has been made of inoculants elsewhere. In Latin America, only two countries use inoculants to any extent and even in Brazil, the largest producer of the seed legumes, common beans are fertilized with N rather than inoculated (Freire, 1982). Inoculation responses in tropical soils appear to be confined to crops such as soybean which have specific Rhizobium requirements (Ayanaba, 1977; Halliday, 1985). Typically responses are substantial when indigenous, infective rhizobia are absent and soil nitrate is low (Table XX). In a high-nitrate soil, nodulation of, and NZfixation by, inoculated plants can be suppressed. However, nodulation and NZfixation (but not necessarily yields) could be increased by very high rates of inoculation ( 1 0 0 0 ~normal; see Table XX; Bergersen et al., 1989). When populations of infective rhizobia exist in high numbers in soils, they present a formidable barrier to the successful exploitation of superior Table XX Effect of Inoculation on Nodulation, N2Fixation, and Productivity of Bragg Soybean Grown in Various Backgroundsof Soil Nitrate and Bradyrhizobium japonicum" ~

Treatment B. japonicum-free soil Low nitrate Uninoculated Normal inoculation High inoculation High nitrate Uninoculated Normal inoculation High inoculation

High B. japonicum soil Low nitrate Uninoculated Normal inoculation

Nodule massb (mglplant)

P'

Crop dry matte@ (tlha)

Crop Nd (kg N/ha)

Seed yield (t/ha)

66 I68 I95

I .7 3.3 3.0

0 72 334

0.11 0.61

4.9 6.8 7.0

0 4

0 0 0.17

8.9 8.0 8.5

205 I96 213

3.2 2.9 3.3

9.8 9.3

258 24 I

2.2 2.0

50

I29 146

0.44

Derived from Herridge et a!. (1987); Herridge and Brockwell(1988). Sampled either 62 or 70 days after planting. Calculated by the ureide method according to Herridge and Peoples (1990). Values represent the mean of four sap samplings between days 70 and 109. Sampled when shoot dry matter and N were at a maxima. a


213

strains of Rhizobium used as inoculants (see Table XX) (Devine, 1984). In the United States, large populations of soybean Rhizobium have become established in soil with cropping so that now less than 10% of nodules are formed on soybean by the inoculant and yield responses are rare (Berg et al., 1988; Halliday, 1985). Research programs in several laboratories (e.g., Devine, 1984; Cregan and Keyser, 1986) currently aim to produce soybean cultivars that bypass the resident rhizobia in the soil to be nodulated by better, selected inoculant strains (this assumes that fixation and N supply are limited by the effectiveness of indigenous rhizobia). A similar strategy was employed for groundnut by Nambiar et al. (1984), who exploited host X strain specificity with cultivar Robut 33-1 and strain NC 92 to obtain consistent yield responses (mean of 16% over nine experiments) in soils containing moderate to high numbers of infective rhizobia and where all uninoculated plants were well nodulated. A contrasting strategy is to develop varieties that can be effectively nodulated by the resident soil rhizobia. Nangju (1980) observed that soybean genotypes from Southeast Asia nodulated successfully with the indigenous rhizobia in Nigeria, but U .S.-bred cultivars nodulated poorly without inoculation. Hybridization of the Asian and U.S. types has resulted in high-yielding lines capable of fixing large amounts of N without inoculation (Kueneman et al., 1984). C. CROPA N D SOILMANAGEMENT

Both yield and P can be influenced by crop and soil management; we examine two important practices. 1 . Tillage

Cultivation accelerates the oxidation of organic matter in soils (Doran, 1980) and generally results in higher nitrate-N in the profile (e.g., Thomas et al., 1973; Dowdell et al., 1983). Cultivation may also decrease the rates of denitrification (Doran, 1980; Rice and Smith, 1982), immobilization (Rice and Smith, 1982), and leaching (Thomas et al., 1973) of nitrate compared to in untilled soils. Additional fertilizer N may be required by cereals under reduced tillage treatments, but for legumes, the lowered soil nitrate levels should result in enhanced N2 fixation. No-till systems can also modify and improve soil structure to create more favorable soil moisture and temperature regimes for plant growth (Lal, 1989). In cropping systems research involving soybean in a moderate rainfall

214


environment (1000 mm annually) in coastal, subtropical Australia, nodulation and N2 fixation were substantially improved under no-tillage, compared with the cultivated system (Table XXI). The increased N2 fixed resulted primarily from increased P (0.88 for no-till versus 0.73 for cultivated), since yields were essentially unaffected by tillage practice. N balances were positive for both systems, although substantially higher for no-tillage. In a drier region of subtropical Australia (650 mm annual average rainfall), the largest effect of no-tillage on Nz fixation was through yield. In 7 of the 11 crops grown over a 3-year period, plant growth and N accumulation were increased under no-tillage (Fig. 11). Soil nitrate levels were reduced under no-tillage relative to the cultivated plots. At the high-fertility (Site A, Fig. 11) and the low-fertility (Site C, Fig. 11) sites, N2 fixation by soybean was effectively suppressed in all treatments as a result of a combination of severe moisture stress restricting nodulation and crop growth (both sites) and high levels of soil nitrate (A site only). At the moderate-fertility site (Site B, Fig. 1l), soybean showed increased nodulation, crop yields, and seed production in the no-tillage treatment (Table XXII). Although P (assessed using the ureide method, see Table XXII) was also higher for the no-till plants in these experiments, the greatest effect on total N2 fixed was through increased yield (355 versus 236 kg N/ha; equivalent to a 50% increase). 2 . Cropping Intensity and Sequence

The quantity of soil nitrate available to a legume can be influenced by the recent cropping. Irrigated soybeans grown immediately after an oat crop Table XXI N Budgets for Soybean Grown with Cultivation or No-Tillage"**

Tillage

Nodule mass' (mg/plant)

Crop N (kg N/ha)

Seed N (kg N/ha)

Fixed N" (kg N/ha)

N balance'

Cultivated No-tillage

86 139

245 264

150 I52

I80 232

+ 30 +80

Values shown are means of four crops grown over 3 years of experimentation. Taken from Hughes and Herridge (1989). Sampled between 40 and 46 days after sowing. Assessed using the ureide method. Fixed N - seed N.

215


I

-20 ! 1983

1984 1985 Year FIG. 11. Relative changes in total N uptake by four crop legumes under no-tillage compared with cultivated cropping. Soybean data for 1983, 1984, and 1985 are the means of one, two, and three varieties, respectively. From D. F. Herridge and J. F. Holland (unpublished data).

fixed 244 kg Nlha compared with 143 kg N/ha fixed by soybeans growing in previously fallowed soil; the proportions of fixed N in seed were 68% and 33%, and net N balances were +39 and -44 kg N/ha, respectively (Bergersen et al., 1985). At another site, winter cereal cropping removed 130 kg N/ha and left 19 mg/kg soil (0-30 cm) of extractable mineral N at soybean planting, compared with 38 mg/kg in winter-fallowed soil. Both treatments produced similar soybean yields (3.5 and 3.3 t/ha, respectively), but P was 0.57 in the winter-cropped and only 0.09 in the winter-

Table XXll Effect of Tillage on Soil Nitrate, Nodulation, and N2Fixation and Crop Growth by FieldGrown Soybean (cv. Forrest)"

Tillage

Soil nitrateb (kg N/ha)

Nodule mass (mg/plant)

Crop N (kg N/ha)

Seed N (kg N/ha)

Relative ureide-N' (%)

Cultivated No-tillage

214 185

69 219

236 355

161 182

55 64

a

D. F. Herridge and J. F. Holland, unpublished data. At sowing, 0 to 1.2 m depth. Mean values of eight samplings.

216


fallowed soils (Bergersen et al., 1989). Thus with proper choice of rotation, cropping systems can be managed for improved N2 fixation. In a different approach, intercropping maize and rice bean was found to increase P above the levels attained by the monocropped legume due to competition with maize for soil N (Table VIII). (Rerkasem et al., 1988; Rerkasem and Rerkasem, 1988). The net result was a higher total N yield of the intercrop (maize plus legume) relative to combined weighted N yield of maize and ricebean monocrops.

VI. CONCLUDING REMARKS We have considered the amounts of N fixed by various legumes in tropical and subtropical systems, examined the benefits of the legumes and of the fixed N to productivity of those systems, and argued that reduced N2-fixing activity is associated with low plant yield and reduced P . Efficient management of legumes to maximize the benefits depends on accurate assessment of N2 fixation in the field. This knowledge not only provides an insight into the N economy of the legume, but adds to our understanding of the general N cycle. Using the information gained, strategies can be developed to solve problems involving N in agricultural and natural systems. Solutions will come in the form of cropping and tillage systems to enhance N2 fixation, improved legume genotypes, improvements in methods of inoculation, and adoption of management practices to stimulate the establishment of large populations of desirable microbes in the soil. Data from individual experiments will be used not only to solve problems and provide a base for management decisions, but also for developing principles and, eventually, functional models. Fixation could then be predicted or estimated, even by farmers, given relevant information on cropping history, climatic data, plant species, and precrop soil nutrient tests.

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ADVANCES IN AGRONOMY, VOL. 44

DISTRIBUTION, COLLECTION, AND EVALUATION OF Gossypium A. Edward Percival and RusseMJ Kohel United States Department of Agriculture Agricultural Research Service Southern Crops Research Laboratory College Station, Texas 77840

I . Introduction A. History of Domestication 11. Distribution A. Taxonomy B. Geographic Distribution C. Species D. Evolution 111. Collection A. Source of the Collection B. Collectors C. Plant Explorations IV. Evaluation A. Genetics and Cytology B. Electrophoresis C. Improvement V . Concluding Remarks References

I. INTRODUCTION Cotton is an agricultural and technological, rather than a botanical term, which has been used to describe cultivated species of the genus Gossypiurn. The first word ever defined as meaning cotton is the Sanskrit “karpasa-i.” Even today the word for cotton in modern Hindustani is “kapas.” The word “karapas” in the Bible, Esther 1:6, means cotton and may have contributed to, or derived from, the Sanskrit original (Crawford, 1948). The Spanish, Portuguese, French, and Italian words “algodon,” “algodao,” “cotone,” and “coton” are obviously derivatives of the Arabic “al” or “el-kutum,” as is the English word “cotton,” which also 225

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comes from a corruption of the Arabic word “qutum” or “kutum” (Brown, 1958). Cotton is presently grown between 47”Nand 32”s latitude with over 50% of the production above 30”N latitude (Kohel and Lewis, 1984). Over 32 million ha of cotton were grown worldwide in 1988 (Anonymous, 1988), which indicates the importance of this crop. Cotton, a natural fiber, competes with synthetic fibers in the textile industry, and though competition from synthetic fibers has reduced the relative use of this crop in the recent past, its preeminence as the fiber of choice has been reestablished during the last decade. Although cotton is primarily a fiber crop, it is also important as a food and feed crop. Cottonseed is the world’s second most important oil seed; the oil is used for culinary purposes, and the oil cake residue is a protein-rich feed for ruminant livestock (Kohel and Lewis, 1984). A. HISTORY OF DOMESTICATION Hutchinson (1954) concluded that a form of one of the Asiatic cottons, the South African perennial Gossypium herbaceum L. race africanum, is truly wild and is the modern representative of the wild ancestor of the two cultivated “Old World” diploid cottons. Humans used this wild race africanum and developed the primitive race acerifolium. Its northward spread may have followed the loss of photoperiodism, which is standard for modern cultivated cottons of all species. Botanical relationships and the geographic patterns of ancient trade routes suggested to Hutchinson (1959) that southern Arabia was the locality where domestication as a fiber crop first took place. This seems plausible as the climate there at the beginning of recent times ( 1 1,000 years ago) was more hospitable for humans than it is at present (Fryxell, 1965). From the primitive perennial G. herbaceum, which spread into India, arose the earliest form of G. arboreum L. (Rozi). Presumably cotton was first grown for uses other than textile yarn, such as for wound dressing and wadding. Cotton may have been introduced to the area where the technology for spinning and weaving of flax (Linum usitatissimum L.) already existed (Lee, 1984).Thus, the weaving of cotton followed and first occurred in India, where it developed into a fine craft. The oldest archaeological record of cotton textile dates to 2700 B.C. and was found in excavations at Mohenjo Daro in the valley of the Indus River in what is now Pakistan (Gulatti and Turner, 1928). Knowledge and use of cotton fiber spread from India and Arabia to Greece during the time of Alexander the Great, circa 350 B.C. Cotton culture was spread across North Africa and into Spain by the Moors, and the Crusaders (1096-

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1270 A . D . ) introduced Levantine and Occidental cottons to other parts of Europe. The Crusaders also disseminated a knowledge of cotton goods and initiated an industry in the Crusader states of Asia Minor and later a lively trade in cotton goods between the Italian city-states and Asia (Crawford, 1948). A parallel cotton technology developed in the New World with no known connection to that which occurred in the Old World. In the Americas, where allotetraploid cottons were used for lint, domestication occurred after the differentiation of the lint-bearing species (Fryxell, 1965). Stephens and Mosely (1974) examined fiber samples found at the archaeological site of Ancon-Chillon in central coastal Peru, dating from about 2500 to 1750 B.C. (Lee, 1984). It is the general opinion that cotton in America was first used by the peoples that inhabited the coastal areas of Peru, and from there the textile craft spread northward and westward. The pre-Inca and Inca civilizations (1200 ~.c.-1530A . D . ) used G. barbadense L. as their source of lint; though the Inca peoples lived out of the range of cotton culture, they secured it by trade and barter from the Upper Amazon and from the coasts, where it was extensively cultivated (von Hagen, 1961). The Maya civilization (2000 ~ . c . - 1 5 2 7A . D . ) of Guatemala and Yucatan, Mexico, also cultivated cotton and developed a fine textile industry, as did the Aztecs (200 ~ . c . - 1 5 1 9A . D . ) and their predecessors, the Toltecs. The Aztecs obtained most of their cotton material from subjugated tribes that grew cotton on the coastal regions of present-day Mexico. However, it was the weaving craft that spread and not the species of cotton grown, as these peoples of Central America and Mexico cultivated G. hirsutum L. (von Hagen, 1961). Indian tribes of the southwestern United States picked up the weaving craft about 2000 years ago, which reached its peak about 1400 A . D . , and grew cotton as late as 1925 (Jones, 1936). It is evident that cotton growing persisted in the area for a long period of time, as there is still seed available today of a variety of G. hisrutum (Hopi) that was once cultivated by the Indians of Arizona. This variety is adapted to a short growing period (84-100 days), grows at relatively high elevations, and is tolerant of arid conditions (Kent, 1957). The cottons grown commercially in the Americas today are direct descendants of the native varieties found at the time of “discovery” of this hemisphere by Columbus. These are G. hirsutum, native to Mexico and parts of Central America, and G. barbadense, native to South America. The early American colonists grew G. hirsutum in upland sites and called them “Upland” cotton. Types of G. barbadense were found to be adapted to the islands of the coasts of the Carolinas and Georgia and were designated “Sea Island” cottons. These names persist to this day for types of

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both species (Lewis and Richmond, 1968). Sea Island was introduced into Egypt during the last century and resulted in the development of the “Egyptian” long-staple cottons, which were reintroduced to the southwestern United States and resulted in the development of “Pima” cottons. Of the cotton grown in the United States today, 98% is G . hirsuturn and 2% is G . barbadense (Anonymous, 1988). The worldwide distribution of these two species has essentially displaced most of the G . arboreurn and G . herbaceurn previously grown in Asia and the Middle East.

II. DISTRIBUTION A. TAXONOMY The genus Gossypium was first named by Linnaeus in the mideighteenth century. Students of the subject have differed as to whether “cotton” (Gossypiurn) should be placed with the Malvaceae or the Bombacaceae family, or the Hibisceae or Gossypieae tribe (Lewis and Richmond, 1968). Edlin (1935) and Prokhanov (1953) classified them as Bombacaceae, whereas Alefeld ( 1 862) had previously divided them between the two families. Mauer (1954)and Kearney (1951)classified Gossypium spp. as Malvaceae. Fryxell (1968) disposed of any lingering taxonomic arguments of classification and removed Gossypium from the tribe Hibisceae. He points to the facts that Gossypieae are unique in possessing lysigenous glands, associated with the capacity to synthesize the sesquiterpene gossypol, and differences in embryo structure, thus establishing the classification of Gossypium as follows: Family-Malvaceae, TribeGossypieae, Genus-Gossypium. According to Fryxell (1979, 1984), a 1928 paper by G. S. Zaitzev, entitled “A Contribution to the Classification of the Genus Gossypium L. ,” is the basis for our current understanding of this genus. It was Zaitzev who first observed that the cottons of the Old World are diploid (2n = 26) and those of the New World are allotetraploid (2n = 52), and each of these could be further subdivided. Zaitzev, he further states, “paved the way for subsequent work and enabled us to advance in our taxonomic understanding of Gossypiurn.”

B. GEOGRAPHIC DISTRIBUTION The genus Gossypium presently contains 432 diverse species. Four species are cultivated and bear spinales seed fibers (lint). These are the two diploid (2n = 2x = 26), Asiatic species G . arboreurn and G . herbaceurn,

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which are confined to the “Old World,” and the other two are the amphidiploid (2n = 4x = 52) species G . hirsutum and G . barbadense. The latter two have centers of variability in Mexico-Central America and South America, but are now widely distributed in cultivation throughout the world (Hutchinson, 1959). The remaining 39 species are all considered wild and are not cultivated. The seed hairs of the wild species are very short and firmly attached to the seed. Four of the wild species are amphidiploid, one each indigenous to Mexico, the Hawaiian Islands, the Galapagos Islands, and Brazil. The other 35 wild diploid species are found in relatively arid areas of their respective tropical and subtropical regions (Anonymous, 1968). The genus Gossypium is divided into seven genome groups that are diploid and an eighth amphidiploid group that combines the A and D genomes. These groups show cytogenetic separation as well as distinctive geographic distribution: A genome-Two cultivated species from the Far East, Middle East, and Africa. B genome-Six wild species from Africa and the Cape Verde Islands. C genome-Ten wild species from Australia. D genome-Thirteen wild species from Mexico, Peru, and the Galapagos Islands. E genome-Four wild species from the Arabian Peninsula and Northeast Africa. F genome-One wild species from East Central Africa. G genome-One wild species from Australia. AD genome-Six (two cultivated and four wild) species from Mexico, South America, and Hawaiian Islands, the Galapagos Islands, and Brazil (the cultivated two having recently attained worldwide distribution through cultivation) (Fryxell, 1984).

C. SPECIES

The +43 recognized Gossypium species are listed in Table I. Beasley (1940, 1942) established a cytological classification of genomes that is closely related to taxonomic affinities and geographic distribution. However, in recent years opinions have been expressed for a reassessment of the present classifications within the genus. Vollesen (1986) has attempted to address this problem for the species native to Africa and the area of the Arabian Peninsula. However, it may be necessary to do this for the entire genus as recent explorations have uncovered new species and additional existing variabilities and relationships within species groupings.

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A. EDWARD PERCIVAL AND RUSSELL J. KOHEL Table I The Species of Gossypium'

Species

Genomic group

Distribution

1. Diploids (2n = 2 x G. herbaceum L. G. arboreum L. G. anomalum Wawr. & Peyr. G. rriphyllum (Harv. & Sand.) Hochr. G. capiris-viridis Mauer G. trifurcarum Vollesen G. bricchetrii (Ulbri.) Vollesen G. benadirense Mattei G . srurrianum J. H. Willis G. nandewarense (Derera) Fryx. G. robinsonii F. Muell. G. australe F. Muell. G. costularum Tod. G . cunninghamii Tod. G. nelsonii Fryx. G. pilosum Fryx. G. populifolium (Benth.) Tod. G. pulchellum (C. A. Gardn.) Fryx. G. rhurberi Tod. G. armourianum Kearn. G. harknessii Brandg. G. dauidsonii Kell. G. klofzschianum Anderss. G. aridum (Rose & Standl.) Skov. G. raimondii Ulbr. G. gossypioides (Ulbr.) Standl. G. lobatum Gentry G. frilobum (Moc. & Sess. ex DC.) Skov.

emend. Kearn. G. laxum Phillips G. turner; Fryx. G. schwendimanii Fryx. G. srocksii Mast. ex Hook. G. somalense (Gurke) Hutch. G. areysianum (Defl.) Hutch. G. incanum (Schwartz) Hillc. G. longicalyx Hutch. & Lee G. bickii Prokh.

Old World cultigen Old World cultigen Africa Africa Cape Verde Islands Africa Africa Africa Australia Australia Australia Australia Australia Australia Australia Australia Australia Australia Mexico, United States (Arizona) Mexico Mexico Mexico Galapagos Islands Mexico Mexico Mexico Mexico Mexico Mexico Mexico Mexico Arabia Arabia Arabia Arabia Africa Australia (continued)

23 1

DISTRIBUTION AND EVALUATION OF Gossypium Table I (Conrinued)

Species

Genomic group

2. Allotetraploids (2n G . hirsutum L. G . barbadense L. G . lomentosum Nutt. ex Seem. G . mustelinum Miers ex Watt G . darwinii Watt G . lanceolarum Tod.‘

=

Distribution

4x = 5 2 )

(AD), (AD), (AD)3 (AD), (AD), (AD)?

New World cultigen New World cultigen Hawaii Brazil Galapagos Islands Mexico

Adapted from Endrizzi e t a / . (1984). Dash indicates that genome designation has not been determined. Questions remain concerning the elevation of this variant to species level.

D. EVOLUTION 1. Origin of the Allotetraploids

Skovsted (1937) was the first to advance the hypothesis that the natural amphidiploids G. hirsutum, G. barbadense, and G . tomentosum combine on A genome from a taxon of the Asiatic diploid group and a D genome from a taxon of the American diploid group. He showed that the American amphidiploids consist of a large chromosome set homologous with the 13 chromosomes of similar size in the Asiatic (A) cottons, and 13 smaller chromosomes homologoils with the small chromosomes of the American (D) wild diploid species. Independently, Beasley (January, 1940) and Harland (March, 1940) confirmed Skovsted’s hypothesis by synthesizing amphidiploid hybrids from A and D genomic diploids. Each used G. arboreum (A2) X G . thurberi (D1)to show that the synthetic amphidiploids 2 (A2D1)were morphologically and cytogenetically compatible with the natural amphidiploids. In Beasley’s work, synthetic allotetraploids were produced by doubling the chromosome number in hybrids of G. arboreum x G . thurberi, using colchicine (C22H2506N).In the diploid hybrids between the original species, less than half of the chromosomes paired; those bivalents that were present showed bridges at anaphase, which indicated that structural differences existed between all of the chromosomes of the two species (A2 and D1). After doubling the chromosomes to 2(A2DI),Beasley found mostly pairing, but did observe some multivalents with one or more univalents. The hybrid allotetraploid was then crossed with G. hirsutum (A2D1 X AhDh) and the meiosis of this amphidiploid hybrid observed. In some cells

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all the chromosomes were paired, with one to three or more multivalent associations found. The hybrids were also self-fertile, and fertile when backcrossed to G . hirsutum. Using a similar technique as the preceding, Beasley (1942) synthesized hexaploid hybrids of G . hirsutum x G . herbaceum 2(AhDh) X A, and G . hirsutum X G . thurberi 2(AhDh) X D1. Beasley again found meiotic figures in which some of the chromosomes were in complex associations, indicating overpairing. At the same time, hybrids of G. hirsutum x G . anomalum 2(AhDh) X BI and G . hirsutum X G . sturtianum 2(AhDh) X C1 were near normal in chromosomal behavior; thus, any homologies that might exist between the B1 and CI genomes and chromosomes of the G . hirsutum set must be low. These facts left little doubt that the American 26 chromosome cottons were allotetraploids, with one parent species similar to each of an American D and an Asiatic A 13-chromosome species. Brown (1951) demonstrated that doubling of the chromosome number can occur spontaneously in F I hybrids of Gossypium spp. In addition, incompatibility of the amphidiploid with natural species satisfies the requirement of genetic isolation that would perpetuate it.

2. Genome Parentage of the Allotetraploids Having established that the,New World amphidiploids are of the general constitution that combines one Old World diploid and one New World diploid, work was directed toward pinpointing the taxa of the original parents. Hutchinson et al. (1947), citing Stephens (1942), pointed out that multivalent formation in hybrids in which each genome is represented twice is a more sensitive index of homology than is pairing in hybrids in which it occurs only once. In the former case, normal pairing between true homologues is possible, and any overpairing must indicate fairly close homology. However, in the latter case, in the absence of true homology, even very low affinities may result in pairing. a . A Genome Parent. In some species, translocations may be common and even occur in single populations; this is not the case with Gossypium. Brown and Menzel(l952) reviewed the case of Gossypium translocations known within the species. The American wild diploids (D’s) have shown none when crossed among themselves and with the American allotetraploids. With this in mind, Gerstel (1953a) concluded that translocations in Gossypium would be a useful tool in measuring homology in species hybrids. He found that in triploid hybrids of New World allotetraploids x the two Asiatic diploid species, the most frequent type of meta-

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~ 131 for G . hirsutum x G . herbaceum and 811 + phase 1’s were 911 + 2 1 + 11v + 1v1+ 131 for G. hirsutum X G . arboreum. The cytological evidence thus suggested that G . herbaceum (A,) is more closely related to the allotetraploid New World cotton than G . arboreum (A*),because G . herbaceum has one less translocated chromosome arm relative to G . hirsutum than does G . arboreum. b . D Genome Parent. Allohexaploid hybrids involving Asiatic diploids, New World diploids, and the natural allotetraploid species were synthesized and analyzed cytologically for multivalent frequencies and genetically for segregation of mutant genes located in the A and D genomes. The pairing relationships and genetic ratios observed in the analysis of the hexaploid hybrids involving the D species showed that those involving G . raimondii (DS) most closely approached autotetraploid behavior, which confirms that this species is the most closely related to the D subgene contributor of the AD allotetraploids (Gerstel, 1953b, 1956, 1963; Sarvella, 1958; Gerstel and Phillips, 1958; Phillips and Gerstel, 1959; Phillips, 1960, 1962, 1963, 1964). Thus, the New World amphidiploids (AD) have been shown to be most closely related to G . herbaceum (A,) and G . raimondii (Ds). However, the D genome group is not as closely related as is the A genome group. This fact would indicate that the chromosome structure in G. raimondii probably evolved at a more rapid pace than it has in G . hirsutum and in G . herbaceum. An alternative possibility to this thesis is that there is an extant species of the D genome that has not yet been found or that is extinct. If found, this D, species would then probably be as closely related as is the A genome species to the AD’S (Phillips, 1963). 3 . Theories of the Origin

Having concluded that A, and DS are the closest derivatives of the ancestral parents of the New World amphidiploids, the question remains as to when and how these two ancestral species were brought together so that hybridization could take place. a . Ancient Origin Theories. Harland (1939), noting the occurrence of New World cottons in widely scattered Micronesian and Polynesian islands, proposed that A and D species came together on a trans-Pacific land bridge in the late Cretaceous or Tertiary (about 60 million years ago). Stebbins (1947) proposed that the natural amphidiploids arose in America before the Eccene (about 70 million years ago) and subsequent to the

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migration of the Asiatic type from the Old to the New World via Behringia. Saunders (1961) also proposed a Tertiary origin supposing that the A and D species involved were sympatric in what is now eastern South America before the rift developed that ultimately led to the formation of the South American and African continents. b. Recent Origin Theories. Davie (1935) proposed that the allotetraploids arose by hybridization in the very recent past. Hutchinson et al. (1947) and Hutchinson (1959) suggested a scenario in which G. arboreum cotton was introduced into the New World by humans over a Pacific route. Sherwin (1970) and Johnson (1975) proposed a polyphyletic and recent origin for the allotetraploids. Though the arguments of the latter two researchers differ, their premise is that G. herbaceum was transported to America by people, or resulting from human activity, where it was cultivated and then hybridized with more than one D genome species.

c . Most Accepted Origin Theory. Reviewing the evidence, Phillips (1963) interpreted the cytogenetic data as establishing that the allotetraploids were of monophyletic origin, and that the event occurred during the Pleistocene (about 1 million years ago). Cytogenetic data showed that the A and D subgenomes of the allotetraploids, primarily the A, had diverged little during their evolution from the progenitor genomes represented in the A and D species. This is assumed to be incompatible with an ancient origin, and since the allotetraploidshave differentiatedinto several distinct species it also suggests that they are not recent in origin. Fryxell (1965, 1979) concurred with this interpretation, and in addition stressed the importance of the several pairs of sibling species and the association of endemic allotetraploids with littoral habitats. Recent data using chloroplast DNA analysis support this last hypothesis. Wendel (1989) observed only 12 mutations out of a total of 3920 restriction sites assayed among seven species of A (diploid) and AD (allotetraploid) genome cottons and indicated that the concomitant low estimate of sequence divergence suggests that the initial hybridization and polyploidization events that led to the evolution of allotetraploid cottons were within the estimates made by Phillips and Fryxell, as given earlier. Wendel also suggests “that although formal methods are lacking for the estimation of divergence time from sequence divergence values calculated from restriction site data, substitution rates have been estimated for several chloroplast genes; these are between 0.12% and 0.16% per million years. It is not clear that nucleotide substitutions accumulate linearly over time or at equivalent rates among plant lineages, nor is it known if substi-


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tution rates calculated from information on specific gene sequences are applicable to data derived from restriction enzyme analysis of entire chloroplast genomes. If, however, these potential sources of error prove to be unimportant, then the time of origin of allotetraploid cotton may be estimated. Assuming an average sequence divergence rate of 0.14 per million years, and a sequence divergence estimate of 0.20% 4 0.06% (range 0.15%-0.27%), allotetraploid Gossypium would have originated 1.43 f 0.43 million years ago, in the middle Pleistocene” (Wendel, 1989).

Ill. COLLECTION The U.S. National Cotton Germplasm Collection resides in the Southern Crops Research Laboratory, Southern Plains Area, Agricultural Research Service (ARS), United States Department of Agriculture (USDA), in cooperation with the Soil and Crop Sciences Department, Texas A&M University, College Station, Texas. Regional coordination of its activities is under the auspices of the Technical Committee of Regional Research Project S-77. The Collection is part of the National Plant Germplasm System (NPGS) and, as part of this system, all aspects of the preservation and use of the data and physical germplasm are coordinated through the Cotton Crop Advisory Committee (CCAC). The CCAC functions as an advisory group to provide expert advice to individuals and organizations such as the National Plant Genetics Resources Board (NPGRB), the National Plant Germplasm Committee (NPGC), ARS, State Agricultural Experiment Stations (SAES), and others on technical matters related to cotton germplasm, its breeding, and effective utilization. Information on accessions maintained, and the evaluation information of these, is accessible through the Germplasm Resources Information Network (GRIN) computer system, which is part of the Data Base Management System (DBMS), a part of the Plant Genetics and Germplasm Institute, Beltsville, Maryland. A. SOURCE OF THE COLLECTION The Collection presently maintains 5100 seed accessions of the Gossypium spp. This material has been accumulated through the years and represents a significant base of scientific capital from 76 countries and political jurisdictions. The material was obtained from planned explorations to various parts of the world, by donations from individual collectors,

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and by exchanges with other similar international collections, such as the Institut de Recherche du Coton et des Textiles Exotique, France; Central Institute for Cotton Research, India; Instituto Nacional de Investigaciones Agricolas, Mexico; Cotton Research Institute, Pakistan; Institute of Plant Industry, USSR; Germplasm Resources Research Division, People’s Republic of China; and others. The Collection makes available and preserves the broadest possible genetic base for cotton. It provides source material for basic studies in genetics, cytogenetics, taxonomy, and other disciplines, as well as applied studies in screening for resistance to pests, disease, and environmental stress and in plant productivity. Seeds from the Collection are available to cooperators for research studies of various kinds, within and outside of Regional Research Project S-77. However, activities that focus on maintenance and acquisition continue to be the primary objectives in order to preserve the natural variability of cotton as a resource for continued efforts to modify and improve cotton cultivars (Percival, 1987).

B. COLLECTORS Cotton collecting expeditions have been taking place since the turn of the century. The early collections were for the most part to the purported center of variability of G.hirsutum, that is, southern Mexico and Guatemala. These early expeditions were time-consuming and difficult to arrange, because at that time there were only limited travel facilities in the areas explored. As interest in cotton germplasm collecting and preservation has increased, funding for this type of activity has become available, and today these collections are more easily arranged and carried out. Added interest in obtaining and preserving Gossypium germplasm has also increased the scope, not only of the geographic areas explored, but also of the material collected. The following list includes many of the collectors, and the countries explored, who have participated in this activity since the early 1900s (Anonymous 1974; Percival, 1987).

Collectors 0. F. Cook 0. F. Cook and B. T. Jordan G. N. Collins and C. B. Doyle 0. F. Cook and J. W. Hubbard F. M. Mauer and S. M. Bukasov T. R. Richmond and C. W. Manning S. G. Stephens

Date and Country 1902-1904 Guatemala 1905-1906 Guatemala, Mexico 1906-1907 Mexico 1925 Mexico, Colombia, Ecuador 1929 Mexico, Guatemala, Colombia 1946 Mexico, Guatemala 1946-1947 Mexico, Guatemala, El Salvador

DISTRIBUTION AND EVALUATION O F Gossypiurn Collectors C. W. Manning and J. 0. Ware M. Gutierez C. M. Rick, Jr. H. S. Gentry P. A. Fryxell and W. H. Cross G. Ano and J. Schwendiman G. Ano and J. Schwendiman B. B. Simpson and J. Vreeland J. M. Stewart, L. A. Craven, and P. A. Fryxell G. Ano, J. Schwendiman, and A. E. Percival P. A. Fryxell and S. Koch P. A. Fryxell and C. L. Burandt A. E. Percival and J. M. Stewart J. Schwendiman, A. E. Percival, and J. L. Belot J. M. Stewart, L. A. Craven, and P. A. Fryxell A. E. Percival and F. D. Wilson A. E. Percival, J. M. Stewart, A. Miranda, J. Moreira, and E. Freier

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Date and Country 1948 Mexico, Guatemala 1960-1961 Argentina, Paraguay 1961 Galapagos Islands 19??Mexico 1976 Honduras, Nicaragua 1980 West Indies, French Guiana 1981 Peru 1983 Peru 1983 Australia 1983 Ecuador, including Galapagos Islands 1983 Mexico 1984 Venezuela 1984 Mexico 1985 Caribbean, South Florida

1985 Australia 1986 Galapagos Islands 1988 Brazil

C. PLANTEXPLORAT~ONS Nine of the plant explorations that have taken place during this decade are reviewed next to give the reader an idea of the scope of these operations. Funding for these expeditions was provided by the USDA, ARS, and the UN, FAO, IBPGR. The information cited was gleaned from the exploration reports of these individuals. I . Simpson and Vreeland in Northern Peru, 1983 Beryl Simpson and James Vreeland, the University of Texas, Austin, had planned a botanical collection to Peru in the summer of 1983. Because they would be in the area where G. raimondii is endemic, and because this species was rumored to have become extinct since last being collected, these scientists were contracted to either verify the rumor or collect seeds of the species. Since herbarium collections of the species had been made in 1979 and 1980, it did not seem plausible that the species was extinct. Collecting during the summer of 1983 was difficult because of the excessive and unseasonable rainfall and flooding of 1982/1983 caused by the

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climatic phenomenon known as “El Niiino.” The roads in this part of the world were severely damaged, and many roads following rivers into the Andes were impassable. Nevertheless, they were able to visit known localities of G. raimondii, plus most localities illustrated in Boza and Madoo (1941) but from which specimens had never been collected, and several apparently previously unexplored neighboring areas. The first sightings of G. raimondii were from the Pan-American Highway where it crosses the Chicama River. These plants, growing on the south bank of the river, were presumably in the same locale as reported by Phillips and Stephens in their unpublished technical report of 1966. From this highway westward along the old road to Cartavio, they found several patches of plants. The plaAt population exhibited variable age distribution. After working the lower Chicama, where they also found several populations of G . barbadense, they traveled from Casca NNW toward Santa Ana. Passing the crest separating the drainage of the Cascas and Santa Ana rivers, they encountered extensive populations of G. raimondii in a region called Pampa Larga (ca. 950 m elevation). Hundreds of plants were seen growing along the valley and continued along the rocky rubble of the Santa Ana River. Descending to 800 m they also found a large population in the Santa Ana Valley. Plants became sparse as the elevation decreased. Short excursions were also made up the Cupinsque River. Because elevations above 300 m were never reached, no evidence of G. raimondii was seen. Traveling to the Huertas River Valley, they found G . raimondii, with populations observed on both sides of the road, starting about 1 km south of Chilete and ending before the town of Huerta. A trip up the Zana River Valley proved fruitless. In the Department of Cajamarca in the province of Hualgayoc, G. raimondii had been previously collected. Nanchoc, a small village that lies along the Zana River, was reached with the aid of a helicopter provided by the Peruvian Military. No G. raimondii was found, and their report indicates that the habitat is such that it is unlikely to grow in the immediate vicinity.

2. Stewart, Craven, and Fryxell in Australia, 1983 A 1983 expedition to Western Australia, conducted by James McD. Stewart, Lyn A. Craven, and Paul A. Fryxell, was a collaborative project supported by the USDA through ARS and the National Plant Germplasm Unit, and by the Commonwealth Scientific and Industrial Research Organization (CSIRO) through the Australian National Herbarium. The timing of the trip was set to correspond to the usual period when the Gossypium species of the area have matured some capsules but the plants have not desiccated. The primary purpose of this trip was to document, as far as


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possible, the extent of variation within and among Gossypium species of the region and to obtain seeds representative of that diversity for the U.S. Germplasm Collection. Seeds of G. hirsutum, G . australe, G . cunninghamii, G . philosum, G . populifolium, and G . pulchellum were collected during this expedition. It was apparent to the participants that there is extensive diversity in the wet-dry tropics of Australia. The diversity has only begun to be measured because the remoteness of the area makes the logistics of collecting difficult. A previous trip to the area by Stewart suggested that the diversity of the cotton genus was greater in the Kimberley Region of Australia than was previously realized. Collections made on this trip confirmed that the taxonomic understanding of the Gossypium of the area is not complete. Specimens taken at 10-km intervals along the length of the Mitchell Plateau will be useful in deciphering an apparent cline that occurs there. The Gossypium collections north of the Carson River are distinctive and may represent undescribed species. However, the specimens do have similarities to know taxa and will require detailed study to determine their taxonomic position. At the very least, they represent previously unknown variation that will require accommodation in current species descriptions. The location of G . cunninghammii in the Northern Territory of Australia appears disjunct from the species of the Kimberly to which it is related. Quite likely, additional Gossypium diversity will be discovered in these areas once they are penetrated by botanists, as was the case for the Kimberley, where each new area visited yielded something different. 3 . Schwendiman, Ano, and Percival in Ecuador, 1983

Jacques Schwendiman and George Ano, of the Institut de Recherches du Coton et des Textiles Exotiques (IRCT), France, and A. Edward Percival (USDA, ARS), United States, participated in a collecting expedition to Ecuador, including the Galapagos Islands, which was supported by the UN, FAO, IBPGR. They were joined by Andres Brando of the Instituto Nacional de Investigaciones Agropecuarias (INIAP), Ecuador, for part of the collecting. The first phase was collecting in continental Ecuador and began with the intent to travel from Quito south to Puyo in Pastaza Province. This travel was not possible as the road was temporarily blocked by landslides due to the unseasonable weather mentioned earlier. The participants then headed straight south to Azuay and Loja provinces, where the first cotton was collected in Loja. From southern Loja, travel was northwest to El Oro, then north to Guayas, Los Rios, and Manabi provinces. In Loja, El Oro, and Manabi, with few exceptions, only dooryard G. barbadense was

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collected. However, in Guayas and Los Rios, large populations of endemic wild G . barbadense were found. One of the main problems encountered in all of the areas explored was that much of the cotton was not open. It was apparent that the unseasonable rains had greatly delayed boll maturity. On the Galapagos Islands, G . barbadense was found on San Cristobal. Gossypium darwinii was found on Santa Cruz, Eden off of Santa Cruz, Floreana, Espanola, Gardner off of Hood, San Cristobal, and Rabida. Gossypium klotzschianum was found on Santa Cruz and San Cristobal and, as previously reported, it was found growing intermingled with G. hrwinii in extensive populations of both species. The new accessions have added to the germplasm diversity of the collections represented, and the large number of accessions collected from the Galapagos Islands should aid in clarifying questions that have been raised concerning the elevation of G. darwinii to a species level. 4 . Fryxell and Burandt in Venezuela, 1984

Paul A. Fryxell (USDA, ARS) and Charles L. Burandt (Texas A&M University) undertook this collection from January to February, 1984. A rough itinerary of the route followed was Maracaibo, Coro, Maracay, Barquisimeto, Guanare, Merida, Caracas, and back to Barquisimeto and Maracaibo. Collections of cotton seeds were made in natural vegetation, on roadsides, and in dooryards, from sea level to as high as 1800 m elevation. Most of the samples collected were of G . hirsutum, but two dooryard G . barbadense were also found. Considerable variability was found among the collections of G . hirsutum. Many samples were collected opportunistically as they were encountered; others were specifically sought out on the basis of prior information, especially the wild cottons occurring in natural vegetation, sometimes in remote places along the northern coast. The cottons collected were found to be in all stages of development: a few in full foliage and in early stages of flowering with no mature fruits, others still flowering but with both green and open bolls, still others past flowering, and some plants that were merely dry sticks lacking any foliage but with a mature crop of open bolls. The wild cottons observed in natural vegetation formed large but locally restricted populations. There was often one or a few parent plants of apparent great age in each population. Some of the cottons exhibited characteristics (e.g., short brown fiber, small flowers, and fruit) that set them apart from the dooryard and roadside cottons. In the opinion of the collectors, these wild cottons are an indigenous part of the vegetation and not escapes from cultivation.


24 1

5 . Percival and Stewart in Southern Mexico, 1984 A 1984 cotton collection by A. E. Percival and J. McD. Stewart (USDA, ARS), during the month of September, was a collaborative project with the Secretaria de Agricultura y Recursos Hidraulicos, Instituto Nacional de Investigaciones Agricolas (SARH, INIA), Mexico, represented by Arturo Hernandez and Fernando de Leon. The rough itinerary followed was: Brownsville, Texas, south through the states of Tamaulipas and Veracruz, east to Tabasco, northeast and around the Yucatan Peninsula to Chetumal and Quintana Roo, south through Chiapas, west to the Isthmus of Tehuantepec, and back north to Texas. Seeds were collected of dooryard (one atypical) and wild strains of G. hirsutum, one G . barbadense, and one G . cf. aridum. The only truly wild G . hirsutum cottons collected were G. hirsutum var. yucatanense, from the northern coast of Yucatan. The distribution, growth habit, and morphology clearly indicated that these are wild and well adapted to the ecological niche in which they were found. Interestingly, no dooryard cottons could be classified as yucatanense. Likewise, the majority of feral cottons were associated with human settlement and were of types similar to the dooryard cottons. Just as important as the sites where cotton was found were the observations in areas where cotton was not found. This is the classic story of germplasm loss. The town of Acala, Chiapas, and the valley in which it is located were specifically visited because it was the site of collections of the original germplasm that gave rise to the outstanding Acala cultivars. They found no cotton there, nor at any locations near the road that runs along the length of the valley. One individual in Acala related that promoters from Tapachula, Chiapas, tried to establish commercial cotton production in the area. When insects became a problem, the promoters recommended that all native cotton plants be destroyed to better control the insects. The commercial venture subsequently failed and the collectors found no cotton being grown there today. 6 . Stewart, Craven, and Fryxell in Australia, 1985

As with the 1983 expedition to Australia, the participants in 1985 were James McD. Stewart and Paul A. Fryxell (USDA, ARS) from the United States and Lyn Craven from Australia (Australian National Herbarium, CSIRO). This exploration was based on funding from IBPGR, USDA, and CSIRO. This plant exploration to central, northern, and northwestern Australia collected samples of most of the 12 currently recognized taxa from Austra-

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lia and 8 additional Gossypium variants. These findings have provided new germplasm for study and exploitation, and also made plain the need for taxonomic reinterpretation of the Kimberley cottons. This exploration significantly extended our knowledge of the geographic range of the Australian wild cottons and their range of variation, as was the case with the 1983 collection. The collectors found that in the arid zone of Central Australia, G . nelsonii occurs sympatrically with three other species of Gossypium, including G . australe, with which some workers confuse it. It was established (Stewart et al., 1987) that the two species are indeed distinct in the field and that G . nelsonii occurs over a much wider geographic area than the one site previously reported. The wild Kimberley cottons had previously been allocated to five species: G . costulatum, G . populifolium, G . pilosum, G . pulchellum, and G . cunninghamii. Moreover, they previously were thought to have relatively isolated distributions within the region. It is clear from the results of this collection that this is not an adequate representation of the actual situation, and the descriptions of six new species resulting from this exploration are currently in preparation by the individuals named. In the Kimberley region, Gossypium was found to be far more widespread, abundant, and more variable than previously recognized. An exception is G . cunninghamii, which occurs on the Cobourg Peninsula, outside the Kimberley, and thus is isolated from the others. However, even this species was found to be more widespread and abundant than previously known. The climate in which these species are found is tropical with alternating wet and dry seasons, and the plants are long-lived perennials that have adapted to a fire-mediated ecology by regrowing annual stems from woody rootstocks. In the absence of fire for one or more years, the stems occasionally survive the dry season and persist, especially in the erect-growing type of plants. The variability among the many populations sampled appeared to be complex, with the morphological characters recombining in various ways. It seems clear that this group of wild cottons is in an early and active stage of speciation. Thus, this exploration provided materials to begin an analysis that will lead to a more satisfactory interpretation of the variability and the recognition of newly discovered species. 7 . Schwendiman, Percival, and Belot in the Caribbean, 1985

A 1985 exploration, financed by IBPGR, included the same IRCT and USDA, ARS personnel of the 1983 exploration to Ecuador mentioned previously. It was conducted from the last of February to the first of April


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and included the following localities listed in the order collected: Trinidad and Tobago; Curacao, Bonaire, and Aruba (Netheland Antilles); Jamaica; Grand Cayman (British West Indies); southern Florida (United States); the Dominican Republic; and Puerto Rico. The period for collecting seeds was optimal, as with few exceptions the cotton found was in the late flowering, open mature boll stage. Accessions of dooryard, feral, and wild G . hirsutum and dooryard G . barbadense were collected. The distribution, growth habit, and morphology of the wild cottons indicated that they are truly wild and adapted to the ecological niches in which they were found. Wild types were found on Curacao, Bonaire, Jamaica, southern Florida, the Dominican Republic, and Puerto Rico. The feral and dooryard types were found on all the islands and in Florida and were associated with human settlements or disturbances. With the exception of those populations that appeared to be of a truly wild nature on the islands of Curacao and Bonaire, the cottons found appeared to be plentiful and in no danger of being eliminated. However, the one wild population on Curacao and the one on Bonaire could be lost to developments in the areas where they are established. 8. Percival and Wilson in the Galapagos Islands, 1985 A 1985 exploration by A. E. Percival and F. D. Wilson (USDA, ARS) was conducted to collect the western and northern islands of the Galapagos Archipelago that had not been collected during the 1983 expedition to these islands. This collection was a collaborative project with Instituto Nacional de Investigaciones Agropecuarias (INIAP), Ecuador, which was represented on the exploration by Gelasio Basante. The following islands were collected and explored during September: Santa Cruz (Indefatigable)-Puerto Ayora, road from Las Gemelas to Baltra crossing, and Turtle Beach; Marchena (Bindloe)-Black Beach and Point Mejia; Pinta (Abingdon)-Cape Chalmers and north of Cape Chalmers; Isabela (A1bemarle)-Point Vincente Roca, Banks Bay, Black Cove, Tagus Cove, Urvina Bay, Elizabeth Bay, Iguana Cove, San Pedro Cove, and the road from Villamil to Santo Tomas; and Fernandina (Narborough)-two locations between Point Espinosa and Cape Douglas. Gossypiurn darwinii was collected from Santa Cruz, Marchena, and Isabela, and G. klotzschianum was collected from Santa Cruz and Isabela. The G . klotzschianum collected from Isabela was unique, as it had not been found on this island during previous expeditions. It was found at two locations, and in each only a few small plants were seen growing and only a few seeds

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were gathered. It was not possible to determine if there might be other larger populations of the species on this island or whether the few plants growing resulted from being recently introduced. 9 . Percival and Stewart in Brazil, 1988 A 1988 USDA, ARS exploration by A. E. Percival and J. McD. Stewart to northeast Brazil during the month of September was a collaborative project with the Centro Nacional de Recursos Geneticos, Empresa Brasileira de Pesquisa Agropecuaria (CENARGEN, EMBRAPA), Brazil. Antonio Miranda, Jose de Alencar, and Elusio Freire represented EMBRAPA. The area collected involved portions of the states of Bahia, Ceara, Pernambuco, Piaui, and Rio Grande do Norte. With the exception of a small area on the northern coast around Touros, Rio Grande do Norte, all of the area collected is a tropical semiarid region with a wet-dry season. Seeds of G. hirsutum, G. mustelinum, and G . barbadense were collected. The endemic allotetraploid wild species G. mustelinum was collected at four sites from where it had previously been reported (Pickersgill et al., 1975) and from two new sites. Except for variation in the ages of some of the plants at each site, little morphological variation was noted, and all of the sites were next to or near water drainages, indicating that the species has adapted to take maximum advantage of the limited rainfall of the area. It may have been indeed fortunate that this collection was made at this time. The area collected is an area almost exclusively devoted to the production of “Moco” cotton, with limited corporate production. Moco cotton (G. hirsutum var. marie-galante) is morphologically variable and has characteristics suggesting introgression from G. barbadense and G . mustelinum. Moco is grown as a perennial and plants are ratooned (cut back) each season. Once fields are established, planting involves only replacement of plants that may have died. Moco growers are mostly small farmers who grow the crop with limited or no technical agricultural input. Many of the fields are established on rocky hillsides, almost exclusively adaptable to a crop such as Moco cotton that can survive the dry season, where the plants can grow among the rocks and boulders. There are native insect pests, such as boll worms, that damage the crop, but not to the extent that it was not economical to grow. However, with the invasion of the area in 1985 by the boll weevil (Anthonomous grandis Boheman), production in parts has been so reduced that it is no longer economical to harvest what little crop is produced. Breeding schemes are under way by EMBRAPA personnel to reduce the impact of this insect,


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some of which involve developing early and/or resistant Moco-type cultivars. Given the environmental conditions and nature of agricultural practices of cotton production in the area, it remains to be seen whether or not this will succeed. Regardless of the outcome of the breeding efforts to produce boll weevil-resistant and adapted varieties, the germplasm base of the material presently grown will change in the not to distant future. Moco cotton will either be eradicated in parts or all of the area, or adaptable varieties will be successfully produced with introduced germplasm from other G . hirsutum types. In either case, this will permanently alter the present Moco germplasm base of the area. It is satisfying to note that this collection secured representative cotton germplasm from this area of the world. Some of this material may in future prove valuable as it appears to be variable for many lint quality and agronomic characters.

IV. EVALUATION A. GENETICS A N D CYTOLOGY

1 . Qualitative Mutants Studies dealing with the genetic mutants found in Gossypium have tended to reflect the commercial utility or importance of the particular species under scrutiny. Though there are exceptions, these studies have concentrated within the cultivated species and only involved the wild species when utilitarian characters have been found that have some degree of benefit for the improvement of the cultivated species. Within the cultivated species, the degree of interest has also been determined by the commercial importance of each of these. Thus, the progress made in identifying mutant genes has been greatest in the order G . hirsuturn, G . barbadense, and G . arboreurn. Kohel (1973) has addressed the genetic nomenclature for Gossypium and Endrizzi et al. (1984) give a current listing of the genetic mutants and linkage relationships for the genus. Endrizzi et al. (1984) list 112 mutant genes in the 26-chromosome allotetraploids, with most of these being identified in G. hirsutum. Some of these have been transferred to G . barbadense, and some have been transferred from the wild allotetraploids, diploid, and cultivated diploid species. Sixty-one mutant loci have been identified with 16 linkage groups. Eleven of these linkage groups have been identified with chromosomes, 2 have been associated with specific subgenomes, and 3 remain to be associated. In the diploid 13-chromosome Asiatic cottons, 86 currently recognized

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A. EDWARD PERCIVAL AND RUSSELL J . KOHEL

mutant loci are listed. They also point out that the last summary of linkages in the Asiatic cottons was that made by Knight (1954), who lists 17 mutant genes with 7 linkage groups. Of these 7 linkage groups, 2 are associated with 2 linkage groups in the allotetraploids. 2 . Translocations

A translocation occurs when two nonhomologous chromosomes reciprocally exchange pieces of their chromosomes. They are useful for assigning genes to specific chromosomes and for generating duplication deficiencies. They have also been used to detect incipient differentiation between the subgenomes of the A and D allotetraploid species, principally in G. hirsutum and G . barbadense (Menzel and Brown, 1952; Menzel et al., 1978, 1982; Brown, 1980). 3 . Monosomes

Plants that are deficient for one chromsome of a pair are referred to as monosomics. Unlike diploids, allopolyploids such as G. hirsutum can transmit the haplo-deficiency to subsequent generations. Thus, chromosome pairing in monosomic plants of allotetraploid cottons will normally consist of 25 bivalents and one univalent, with 26 different monosomics theoretically possible. Thus far, 15 of the 26 chromosomes of G. hirsutum have been identified. Because of the chromosome imbalance, a syndrome of morphologicalcharacters is associated with each monosomic type so far identified, which can be used to easily identify the monosomic plants from their disomic sibs. Some monosomic plants can even be identified in the seedling stage (Endrizzi and Ramsey, 1979; Endrizzi et a f . , 1984). Monosomes are used in identifying the chromosomes in translocations and have been used extensively in assigning genetic factors to specific chromosomes. They are ideal for separating duplicate linkage groups so that gene distances or linkage values for each can be determined. They are used to create chromosome substitution lines, and these lines in turn can be used to study the genetic effect of individual chromosomes on plant traits and for estimatingthe number of genes, gene interactions, and linkage relationships controlling plant characters (Endrizzi et al., 1984). 4 . Monotelodisomes and Monodisomes

Telocentric chromosomesare created by the misdivision of univalents at the first or second meiotic division and are recovered as monotelodisomic


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plants. A monotelodisomic plant has 25 bivalents, plus a heteromorphic bivalent. The heteromorphic pair consists of a telocentric chromosome plus an entire homologous chromosome. Once the association of a marker gene to a specific chromosome has been made by the monosome test, the monotelodisomic can then be used to determine the arm location of that marker gene as well as its linkage distance to the centromere. Isochromosomes are chromosomes with two homologous or identical arms, and they arise by misdivision of univalent, plus misdivision of telocentric, chromosomes. They may also be used to determine gene location on chromosome arms. However, these are not as useful as telocentrics for gene mapping studies, as they may give faulty rates of recombination frequencies because of exchanges in the trisomic arms (Endrizzi and Kohel, 1966; Endrizzi and Bray, 1980; Endrizzi et a f . , 1984).

B. ELECTROPHORESIS I . Protein and Isozyme Analysis Electrophoresis began to be employed in systematics in the early 1970s (Avis, 1975). As the reader is aware, the advent of electrophoresis (Ornstein, 1964) and its application in the struggle to measure variation in organisms bypass the problems of sterility barriers and incompatibility. Its application within the genus Gossypium was first employed by two groups, B. L. Johnson and M. M. Thein at Riverside, California, and J. P. Cherry, F. R. H. Ketterman, and J. R. Endrizzi at Tucson, Arizona. Both groups employed proteins extracted from Gossypium seeds, the premise being that proteins from dormant tissue reflect a more stable genomic state. The reserve proteins of seed form a class in which vital processes are not canalized and are buffered against environmental shock. Thus, these proteins should provide a better sample of those loci that may vary without impairment of survival ability (Cherry et al., 1970; Johnson and Thein, 1970). By using seed, populations can be sampled easily and quickly, and seed is less affected by variation in nutrition and environment during development (Dunnill and Fowden, 1965). Johnson and Thein (1970) extracted protein from seed of 25 diploid species of Gossypium for analysis and surveyed the banding patterns of these samples. In general they found that these species fell into the genomic groups to which they had been assigned on morphological and cytological evidence. However, they suggest that the evidence presented (correlation of banding patterns) should split the D genome group: one subgroup (DB) comprising the species G . ruimondii, G. lobatum, G . aridum, G . laxum, and G . gossypioides; and the other subgroup (DE) the

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species G . thurberi, G . trilobum, G . davidsonii, G . klotzschianum, G . armourianum, and G . harknessii. Their conclusion is that the DB subgenomic group evolved from B genomic group and that the DE subgenomic group evolved from the E genomic group, and that all genomic groups are derived from a common primordial population occupying Central Africa prior to continental drift. Further work by Johnson (1973, again using banding patterns obtained from crude seed proteins of allotetraploid cottons that included G . hirsutum f. palmeri, elevates “palmeri” to a species level and fits a postulated parentage of G . herbaceum (A,) and G . trilobum (Ds). Johnson (1975) also indicates that G . hirsutum originated from a combination of “ G . palmeri” and one or more other AIAIDSDstype, whereas G . barbadense is the true descendant of G . herbaceum x G . raimondii (AIAID~Ds). In addition, the cultivated varieties of G . hirsutum represent various degrees of introgression involving G . barbadense and the preceding G . hirsutum complex. Cherry et al. (1970) extracted crude proteins from seeds of 26 species and 10 varieties of the genus Gossypium. They found that the species fall into the genomic groups to which they had been previously assigned on geographical, morphological, and cytological grounds. They found the greatest variability within the D genomic group, but no pattern that would allow the splitting of it into two subgroups, as suggested by Johnson and Thein (1970). Within the groups, pairs of “sibling species” were supported by their analysis, similar to those pointed out by Fryxell(1965) to exist in all genomic groups. Further analysis by Cherry et al. (1971, 1972) used three enzyme systems (esterases, leucine aminopeptidases, and catalases). The results reported again support, in broad outline, the present classification of the genus. The major value of this early work using gel electrophoresis of plant proteins may be in having introduced the technique to the genus. Questions persist concerning the origins of Gossypium, and though there is both support for the present classification and possible evidence for some reclassification, the early application of the method is questionable. These early works employed the gel electrophoresis technique in a gross manner to measure qualitative differences, and the application of the technique in this manner may have value only in a supportive role, for the conclusions are contradictory. When contradictory conclusions are reached, using the general application of the method, judgment should be reserved until specific protein surveys can be conducted as outlined by Lewontin (1974). Only recently have improved methods using this technique been employed within the genus. The suspected close relationship of G . davidsonii and G . klotzschianum


249

was confirmed through allozyme (different enzyme forms produced by different alleles at the same locus) analysis of 33 populations for 41 loci, indicating that the allelic composition of G . klotzschianum represents a subset of G . dauidsonii, thus making the former a derivative species of the latter (Wendel and Percival, 1989). One hundred and three accessions of G . arboreurn and 3 1 of G . herbaceum were examined for allelic variation at 40 allozyme loci. Expectations, based on morphology and other chemical data, were that the two species would show a close relationship. However, the results indicated that these two species are highly differentiated, at least with respect to their allozyme composition (Wendel et al., 1989). Allozyme analysis was also performed on 153 accessions representing the spectrum of G . barbadense diversity. Materials from northwest South America contained the greatest diversity, suggesting that this region is the ancestral home of this species. The data also indicate separate diffusion pathways from the center of origin into southern, eastern, and northern (east of the Andes) South America. The Caribbean island and Central American forms appear to be derived from the northern forms. These pathways support previous historical determinations and fit the morphological evidence. The Pacific island forms have closer relationship to the accessions from eastern South America, which is opposite to their geographic proximity (Percy and Wendel, 1989). A study conducted by Saha and Stelly (1987) to develop suitable isozyme techniques for Gossypium spp. and to survey the genetic variation used profiles of five isozymes among 60 allotetraploid cultivars. Results of this study indicated that there was considerable variation between G . hirsutum and the other allotetraploid cultivars used, suggesting that interspecific genetic introgression from other allotetraploids would improve the genetic diversity of Upland cotton. Using this same technique, a further study by Saha et al. (1988) again revealed the close phylogenetic relationship between G . hirsutum and G . lanceolatum ( G .hirsutum f. palmeri) and that the relationship between G . barbadense and G . darwinii, though more distant, nevertheless was close enough to question elevating the latter to a species level. 2 . Endonuclease Restriction Analysis

Organelle DNA analysis is also valuable in phylogenetic studies associated with the evolution of Gossypium, because organelle DNA is highly conserved, making it comparable to asexual genomes without recombination (Takahata and Slatkin, 1983). Chloroplast DNA has been used in Gossypium systematics.

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Wendel (1989) has reexamined the evolution of allotetraploid cottons using variation in restriction enzyme cleavage sites in the chloroplast genome (cpDNA). The data obtained suggest that the hybridization of ancestral diploid species to form the allotetraploid species is within the estimates suggested by earlier workers and occurred “relatively recently” within the last 1-2 million years. Chloroplast DNA analysis used by Altman and Thomas (1985) indicates that the elevation of G . lanceolatum to species rank is not supported from the results; however, the elevation of G . darwinii to species rank is. Results comparing the banding patterns of the diploids G . arboreum and G . herbaceum indicated a very close relationship of these two species, which is contrary to results mentioned previously. Similar chloroplast DNA analysis of eight species (two allotetraploid and six diploid) by Wilkins and Galau (1985) indicated that their results were consistent with the current understanding of Gossypium evolution. They also found that the allotetraploids appear to have diverged earlier than their nuclear cpDNA’s, suggesting that introgressive hybridization may have occurred in their evolution. All of these studies point to the fact that continued use of the various applicationsof gel electrophoresis will greatly aid in the correct determination of the variation that exists within Gossypium and the systematics of the genus. C. IMPROVEMENT 1 . Sources of Variability

a . Wild and Diploid Germplasm. Nonfiber-producing cottons include most of the wild diploid species of Gossypium. Seeds of some of these species have hairs, but none bear usable or spinnable fiber. The seed hairs that may be present are too short and too firmly attached to the seed to be of any potential utility. Being diploids, these species are also too distantly related to cultivated allotetraploid cotton to be directly useful in conventional breeding programs. The fiber-producing cultivated Asiatic diploids also fall into this category. Nevertheless, they are potential sources of useful genes that have been, and can be, transferred to cultivated cottons using special techniques (Stewart and Hsu, 1978; Stewart, 1979). b . Wild and Allotetraploid Germplasm. The fiber-producing cottons include the two cultivated allotetraploid species G. hirsutum and G . barbadense, and may also include G . lanceolatum. The inclusion of G . lan-


25 1

ceolatum is questioned, as the elevation of this variant to species level from G . hirsutum has been questioned as needing experimental verification (Endrizzi et al., 1984). The other three allotetraploid species that are a source of potential germplasm are the wild G . tomentosum, G . darwinii, and G . mustelinum. The cultivated species have a wide range of variability in terms of cultivars, strains, feral types, and genetic mutants, followed by G . darwinii, which has less variability and is limited to its geographic distribution on each of the Galapagos islands (Fryxell, 1984). The remaining two species, G . tomentosum and G . mustelinum, have little observed variability, probably because few accessions of these have been collected, and because they have only been found in limited geographic locations. The transference of desirable characters between the allotetraploids is more straightforward, but it is also difficult. Hybrids between the allotetraploids break down in the F2 generation. The viable offspring tend to assimilate back to each of the two parent types, with the true recombinants being weak or not able to survive, thus large populations are required to transfer the desired character. c . Germplasm Modification. As stated previously, much of the cultivated cotton acreage grown throughout the world is in the temperate zone. Thus cotton, which is native to tropical and semitropical areas of the world, has had to be changed to, or selected for, photoperiodic neutrality. Since most of the wild species, and many of the primitive and/or feral forms of the cultivated species, fail to flower in a long-day regimen, it is necessary to circumvent this problem if one is to use a crossing program in plant improvement. This may be accomplished by (a) crossing in a tropical environment where day length is not a problem, (6) crossing in a greenhouse during the short-day winter months, or ( c ) introducing genes for day-neutralism into the germplasm accessions with a backcross scheme so that the genotype is disturbed as little as possible, thus making the feral cotton suitable in temperate areas. However, the ease of transference of desirable traits is related in part to the mode of inheritance of the desired trait, and in part to the closeness of the relationship of the materials involved (Fryxell, 1984). d . Germplasm Utilization. The introduction of desirable germplasm into agronomically acceptable cotton cultivars is an ongoing and dynamic enterprise in most cotton breeding programs. However, the transfer of desirable characters from exotic intraspecific and interspecific sources, though continuous, has primarily been done in state and federal breeding programs. Some examples of these have been reviewed by Fryxell(l976, 1984) and are summarized here.

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Cotton rust, Puccinia cacabata Arth. & Holw., is a disease that occurs intermittently in northern Mexico and the southwestern United States. L. M. Blank of Arizona developed an inoculation technique that permitted him to survey a wide range of cotton germplasm for resistance to this disease. He found no resistance in G. hirsutum, but found strong resistance in the wild species G. anomalum and in the cultivated G. arboreum. By creating synthetic hexaploids and allotetraploids, and backcrossing these to G. hirsutum, he created acceptable agronomic lines that were resistant to cotton rust. Bacterial blight (Xanthomonas maluacearum) resistance is conditioned by a multiplicity of genes (16 have been isolated) as the disease itself is variable and exists as differing races with varying degrees of virulence. R. L. Knight isolated blight resistance from G. hirsutum, G. barbadense, G . arboreum, G . herbaceum, and G . anomalum (Brinkerhoff, 1970). However, the most blight-resistant genes were found within the species G. hirsutum, though as many as 16 backcrosses were needed to recover the acceptable fiber properties of the recurrent parent. Fiber strength is a polygenic character, and high fiber strength comes from a variety of sources, principally by introgression from the primitive cultivar Hopi and from a hybrid made by J. 0. Beasley in the 1930s between the diploid species G. thurberi and G . arboreum. Doubling the hybrid to the allotetraploid level allowed it to be crossed and backcrossed, with relative ease, to G. hirsutum. Cotton varieties that are hairy impart resistance to insects like the jassids (Empoasca spp.), which are important pests in Africa and parts of Asia. The presence in the plant of the single major gene T I (Lee, 1985) is responsible for this desired phenotype. Conversely, the single major gene TISm controls the smoothleaf character and would be beneficial to have in varieties where dense pubescence is not desirable. Varieties with smooth leaf characteristics help control insets that require plant hairs for egg laying. Okra leaf shape is conditioned by the gene Lo, which is desirable in areas that have relatively high humid conditions as harvesting is approached. This leaf type has been found to reduce losses from boll rot organisms and effects earlier maturity because of the more open plant canopy in varieties that have this leaf characteristic (Jones, 1970). Varying degrees of pest resistance and/or plant modification have been obtained using other monogenic inherited characters such as red plant color, bract genes, nectariless genes, leaf shape genes, and dwarf genes and polygenic characters that control plant allelochemistry , fiber properties, water use efficiency, nematode resistance, and boll types (Fryxell, 1976; Niles, 1980).


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The potential for the economic development of hybrid cotton cultivars was made possible by Meyer (1973a, 1973b, 1975). She showed that the combination of the G. hirsutum nuclear genome with G. harknessii cytoplasm produces male sterility (A line); fertility could then be restored to male-sterile lines by introducing either one dominant gene or a homozygous recessive gene introgressed from G. harknessii into G . hirsutum (R line). Pure-breeding male-fertile lines, which restore male fertility to malesterile lines, can be isolated from certain stocks with G. harknessii cytoplasm. The male-sterile lines are maintained by crossing with normal, fertile G. hirsutum stocks (B lines) (Niles and Feaster, 1984).

V. CONCLUDING REMARKS Cotton is of enormous importance to the world today. It is not only important economically in international trade, but is also used to clothe a substantial portion of the world’s population. Cotton is both comfortable and utilitarian in nature. As a natural fiber and feed source, cotton is a renewable agricultural resource, which may help to keep it competitive with synthetic fibers from an environmental and ecological standpoint. Continued research with Gossypium germplasm is essential, as this is a complex genus. Though much has been accomplished in the understanding of the genus, much remains to be done. The genus contains differing ploidy levels that yield a high degree of variability, from highly improved allotetraploid species to wild diploid forms, and this variability has only begun to be tapped as a source of beneficial characteristics. In addition, much variability may yet be found. A new species has been discovered every two to three years since the late 1950s, and as old areas are explored again, because of better access, and new areas become accessible, more species are likely to be found that provide additional variability and a better understanding of the genus.

REFERENCES Alefeld, F. G . C. 1862. Osterr. Bot. Zeitschr. 12, 144-148. Altman, D. W., and Thomas, M. D. 1985. Proc. Beltwide Cotron Prod. Res. Conf., New Orleans, Louisiana, pp. 47-49. Anonymous. 1968. Southern Coop. Series Bull. no. 139. Anonymous, 1974. USDA Rep. ARS-H-2. Anonymous. 1988. “Agricultural Statistics 1988.” United States Department of Agriculture, Washington, D.C.

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Avis, J. C. 1975. Syst. 2001.23,465-481. Beasley, J. 0. 1940. Am. Nat. 74,285-286. Beasley, J. 0. 1942. Genetics 27,25-54. Boza, B., and Madoo, R. M. 1941. Ministerio de Fomento. Dir. Agric. Ganad. Bol. 22, 1-29. Brinkerhoff, L. A. 1970. Annu. Rev. Phytopathol. 8,85-110. Brown, H. B. 1958. “Cotton.” McGraw-Hill, New York. Brown, M. S. 1951. Evolution 5,25-41. Brown, M. S. 1980. J. Hered. 71,266-274. Brown, M. S., and Menzel, M. Y. 1952. Bull. Torrey Bot. Club 79, 110-125. Cherry, J. P., Katterman, F. R. H., and Endrizzi, J. E. 1970. Evolution 24(2), 431-447. Cherry, J . P., Katterman, F. R. H., and Endrizzi, J. E. 1971. Can. J. Genet. Cytol. 13, 155-158. Cherry, J. P., Katterman, F. R. H., and Endrizzi, J. E. 1972. Theor. Appl. Genet. 42, 2 18-226. Crawford, M. D. C. 1948. “The Heritage of Cotton.” Fairchild, New York. Davie, J. H. 1935. Genetica 17,487-498. Dunnill, P., and Fowden, L. 1965. Phytochemistry 4,933-944. Edlin, H. L. 1935. New Phytol. 34, 1-143. Endrizzi, J. E., and Bray, R. 1980. Genetics 94,979-988. Endrizzi, J. E., and Kohel, R. J. 1966. Genetics 54,535-550. Endrizzi, J. E., and Ramsey, G. 1979. Can. J. Genet. Cytol. 21,531-536. Endrizzi, J. E., Turcotte, E. L., and Kohel, R. J. 1984. I n “Cotton” (R. J. Kohel and C. F. Lewis, eds.), Agronomy, No. 24, pp. 81-129. American Society of Agronomy, Madison, Wisconsin. Fryxell, P. A. 1965. Adv. Front. Plant Sci. 10,31-56. Fryxell, P. A. 1968. Bot. Gaz. (Chicago) 129(4), 296-308. Fryxell, P. A. 1976. USDA Rep. ARS-S-137. Fryxell, P. A. 1979. “The Natural History of the Cotton Tribe.” Texas A & M Univ. Press, College Station, Texas. Fryxell, P. A. 1984. I n “Cotton” (R. J. Kohel and C. F. Lewis, eds.), Agronomy, No. 24, pp. 27-56. American Society of Agronomy, Madison, Wisconsin. Gerstel, D. U. 1953a. Evolution 7,234-244. Gerstel, D. U . 1953b. Genetics 38,664-665. Gerstel, D. U. 1956. Genetics 4 1 , 3 1 4 4 . Gerstel, D. U. 1963. Second Int. Wheat Genet. Symp. Hereditas Suppl. 2,481-504. Gerstel, D. U., and Phillips, L. L. 1958. Cold Spring Harbor Symp. Quant. Biol. 23,225-237. Gulatti, A. M., and Turner, A. J. 1928. Indian Central Cotton Comm., Tech. Lab. Bull. N o . 17. Harland, S. C. 1939. “The Genetics of Cotton.” Jonathan Cape, London. Harland, S. C. 1940. Trop. Agric. (Trinidad) 17,53-55. Hutchinson, J. B. 1954. Heredity 8,225-241. Hutchinson, J. B. 1959. “The Application of Genetics to Cotton Improvement.” Cambridge Univ. Press, London. Hutchinson, J. B., M o w , R. A., and Stephens, S. G. 1947. “The Evolution of Gossypium and the Differentiation of the Cultivated Cottons.” Oxford Univ. Press, London. Johnson, B. L. 1975. Bull. Torrey Bor. Club 102,340-349. Johnson, B. L., and T. M. M. 1970. A m . J. Bot. 57(9), 1081-1092. Jones, J. E. 1970. Proc. Beltwide Cotton Prod. Res. Con$ Houston, Texas, p. 5 5 . Jones, V. H . 1936. Univ.New Mexico Bull. No. 296, Anthropol. Ser. 1(5), 51-64. Kearney, K. P. 1951. A m . Midl. Nat. 46,93-131.


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Kent, K. P. 1957. Trans. A m . Philos. Soc. 47,459-732. Knight, R. L. 1954. “Abstract Bibliography of Cotton Breeding and Genetics, 1900-1950.” Commonwealth Agriculture Bureau, Farnham Royal, Cambridge, England. Kohel, R. J. 1973. J. Hered. 64,291-295. Kohel, R. J., and Lewis, C. F. 1984. In “Cotton” (R. J. Kohel and C. F . Lewis, eds.), Agronomy, No. 24, p. 12. American Society of Agronomy, Madison, Wisconsin. Lee, J. A. 1984. In “Cotton” (R. J. Kohel and C. F. Lewis, eds.), Agronomy, No. 24, pp. 1-25. American Society of Agronomy, Madison, Wisconsin. Lee, A. 1985. J . Hered, 76, 123-126. Lewis, C. F., and Richmond, T. R. 1968. In “Advances in Production and Utilization of Quality Cotton: Principles and Practice” (F. C. Elliot, M. Hoover, and W. K. Porter, eds.), pp. 1-21. Iowa State Univ. Press, Ames, Iowa. Lewontin, R. C. 1974. “The Genetic Basis of Evolutionary Change.” Columbia Univ. Press, New York and London. Mauer, F. M. 1954. “Origin and Systematics of Cotton.” Akad. Nauk Uzbek S.S.R., Tashkent. Menzel, M. Y., and Brown, M. S. 1952. Genetics 39,678-692. Menzel, M. Y., Brown, M. S., and Naqi, S. 1978. Generics 90, 133-149. Menzel, M. Y., Haskenkampf, C. A., and Stewart, J. M. 1982. Genetics 100,89-103. Meyer, V. G. 1973a. Proc. Beltwide Corron Prod. Res. Conf., Phoenix, Arizona, p. 65. Meyer, V. G. 1973b. Crop Sci. 13,778. Meyer, V. G. 1975. J. Hered. 66,23-27. Niles, G . A. 1980. In “Breeding Plants Resistant to Insects” (F. G. Maxwell and P. R. Jennings, eds.), pp. 337-369. Wiley, New York. Niles, G. A., and Feaster, C. V. 1984. In “Cotton” (R. J. Kohel and C. F. Lewis, eds.), Agronomy, No. 24, pp. 201-231. American Society of Agronomy, Madison, Wisconsin. Ornstein, L. 1964. Ann. N . Y . Acad. Sci. 121,321-349. Percival, A. E. 1987. South. Coop. Ser. June 1987, Bull. N o . 321. Percy, R. G . , and Wendel, J. F. 1989. Theor. Appl. Genet. (in press). Phillips, L. L. 1960. Genetics 46,77-83. Phillips, L. L. 1962. Am. J . Bot. 49,51-57. Phillips, L. L. 1963. Evofurion 17(4), 460-469. Phillips, L. L. 1964. Am. J . Bor. 51,324-329. Phillips, L . L., and Gerstel, D. U. 1959. J . Hered. 50, 103-108. Pickersgill, B., Barrett, S. C. H., and de Andrade-Lima, D. 1975. Biotropica 7(1). 42-54. Prokhanov, Y. I. 1953. Bot. Mat. Hebariya Bot. Inst. V . L . Kamarov, Akad. Nauk U.S.S.R. 15, 159-176. Saha, S., and Stelly, D. M. 1987. Agron. Abstr., p. 78. Saha, S., Stelly, D. M., and Percival, A. E. 1988. Proc. Beltwide Cotton Prod. Res. Conf., New Orleans, Louisiana, p. 97. Sarvella, P. 1958. Genetics 43,601-619. Saunders, J. H. 1961. “The Wild Species of Gossypium.” Oxford Univ. Press, London. Sherwin, K. H. 1970. Res. Rec. Uniu. Mus. S . Ill. Univ. Mesoamerican Stud. 6, 1-33. Skovsted, A. 1937. J. Genef.34,97-134. Stebbins, G . L 1947. Evol. Monogr. 17,213-221. Stephens, S . G. 1942. J. Genet. 44(2,3), 272-295. Stephens, S. G., and Mosely, M. E. 1974. Am. Anriq. 39, 109-122. Stewart, J. M. 1979. I n “Plant Tissue Culture: Symposium of the Southern Section of the American Society of Plant Physiology.” ( J . T. Barber, ed.), pp. 44-46. Tulane Univ., New Orleans, Louisiana.

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Stewart, J. M., and Hsu, C. L. 1978. J . Hered. 69,404-408. Stewart, J. McD., Fryxell, P. A., and Craven, L. A. 1987. Brunomia 10,215-218. Takahata, N., and Slatkin, M. 1983. Genet. Res. 42,257-265. Vollesen, K. 1986. Kew Bull. 42(2), 337-349. von Hagen, V. W. 1961. “The Ancient Sun Kingdoms of the Americas.” World, Cleveland and New York. Wendel, J. F. 1989. Proc. Narl. Acad. Sci. U . S . A . 86,4132-4136. Wendel, J. F., and Percival, A. E. 1989. Plant Syst. Euol. (in press). Wendel, J. F., Olson, P. D., and Stewart, J. MacD. 1989. Am. J . Bor. 76, 1797-1808. Wilkins, T. A., and Galau, G. A. 1985. Proc. Beltwide Cotton Prod. Res. Conf., New Orleans, Louisiana, p. 73. Zaitzev, G. S. 1928. Bull. Appl. Bot. Genet. Plant Breed. 18, 1-65.

ADVANCES IN AGRONOMY. VOL. 44

BREEDING WHEAT FOR RESISTANCE TO Septoria nodorum AND Septoria tritici Lloyd R. Nelson’ and David Marshall2

’ Texas A&M University Agricultural Research and Extension Center at Overton Overton, Texas 75684 Texas A&M University Research and Extension Center at Dallas Dallas, Texas 75252

I . Introduction 11. Identification of Resistance A. Disease and Pathogen Assessment B. Components of Resistance C. Yield Reduction 111. Pathogen Variation IV. Genetics of Resistance V. Sources of Resistance VI. Discussion and Conclusions References

I. INTRODUCTION Breeding for resistance has been the most wide.j used method of disease control for the foliar diseases of wheat (Triticum aestiuum L.). The Septoria diseases have been no exception. There are three recognized Septoria diseases of wheat, each characterized by its causal fungus. On a worldwide basis, the two most important are septoria nodorum blotch (SNB) and septoria tritici blotch (STB). The third, septoria avenae blotch, is found infrequently and is generally considered a minor disease (Cunfer, 1987), although there are exceptions (Shearer and Calpouzos, 1973; Haugen et al., 1985). SNB (aka septoria leaf and glume blotch, or glume blotch) is caused by Leptosphaeria nodorum E. Mueller (anamorph Septoria nodorum (Berk.) Berk.). Some authors (Castellani and Germano, 1977; Bisset, 1982) have described the asexual stage of the fungus as Stagnospora nodorum (Berk.) Cast. & Germ. Additionally, others (Eriksson, 1967; Hedjaroude, 1968) have argued that the sexual stage should not be Lepto257 Copyright 0 1990 by Academic Press, Inc. All rights of reproduction in any form reserved.

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LLOYD R. NELSON AND DAVID MARSHALL

sphaeria, but rather Phaeosphaeria nodorum (Mueller) Hedja. STB (aka septoria leaf blotch or speckled leaf blotch) is caused by Mycosphaerella graminicola (Fuckel) Schroeter anamorph Septoria tritici Rob. & Desm.). Many aspects of the Septoria diseases of wheat have been discussed in at least four literature reviews (Shipton et a / . , 1971; Berggren, 1981; King et al., 1983; Karjalainen, 1985) and three international workshops (Cunfer and Nelson, 1976; Scharen, 1985; Fried, 1989). Eyal et a / . , (1987) have described methodology of disease management of the septoria diseases. This review will focus explicitly on breeding for resistance to SNB and STB. We will cite research from bread wheat (Triticum aestiuum L.) and durum wheat (T. durum L.). The relative emphasis that different breeding programs place on resistance to SNB and STB typically depends on the importance of the diseases in the geographic area of interest. The need for Septoria resistance must be viewed in relation to other breeding objectives. Thus, in some breeding programs it may be sufficient to simply avoid extremely susceptible germplasm, whereas other programs may require a high level of resistance (Russell, 1981). Undoubtedly, what most breeders and pathologists want is a form of resistance that is stable over time, easy to transfer across genotypes, easy to identify in segregating progeny, effective under disease-conduciveconditions, and nondetrimental to yield potential under disease-free conditions. In this review, we will attempt to show how resistance to SNB and STB has been identified, relevant features concerning pathogen variation, what is known about the genetics of resistance, and finally a reference list containing sources of resistance to SNB and STB.

II. IDENTIFICATION OF RESISTANCE A plant interacting with a pathogen can express several forms of reaction. Besides immunity, defined as absolute resistance (Robinson, 1969), resistance, tolerance, and susceptibility are possible reactions of the host in response to the attack by the pathogen. A susceptible plant possesses all necessary qualities to be a fit host for the pathogen. Resistance is defined as the ability of the host to hinder the growth of the pathogen (Robinson, 1969). Susceptible plants do not hinder the growth of the pathogen. Furthermore, resistance can be differentiated into subclasses: complete resistance, in which the spore production is completely inhibited; and incomplete resistance, which allows for some spores to be produced (Parlevliet, 1979). Incomplete resistance, also referred to as partial resistance, results

WHEAT RESISTANCE TO Seproria DISEASES

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when the host is able to cause a reduction in spore production of the pathogen despite a relative “susceptible” reaction type. This reduction in spore production can decrease the rate of disease development and has been referred to as “slow-septoring” (Broennimann, 1982) in the case of SNB. This term is in imitation of the term “slow-rusting,’’ describing the reduced development rate of rust pathogens. Zadoks and Schein (1979) defined partial resistance simply as an intermediate level between susceptibility and resistance. Besides these terms, which evaluate the type of reaction on the basis of the visual disease development and ability to influence spore production, another form of interaction is tolerance. An infected host showing the same disease development over time, but less reduction in yield than a susceptible cultivar, is said to be tolerant of the pathogen.

A. DISEASE A N D PATHOGEN ASSESSMENT Early research in STB resistance breeding relied on identification of less severely affected germplasm in the field (Mackie, 1929). This work, as well as early work on SNB (Dantuma, 1955), showed that immunity to either pathogen could not be found, but that some varieties were more resistant than others. Renfro and Young (1956) outlined greenhouse and field methods, based on disease severity, that could be used to differentiate resistant and susceptible germplasm to STB. They found that ‘Red Chief and ‘Nabob’ had some resistance relative to ‘Westar,’ ‘Triumph,’ ‘Early Blackhull,’ and ‘Wichita,’ which were susceptible. The percentage of seedling leaves showing infection and the mean number of lesions per leaf were used by Hilu and Bever (1957) to identify the bread wheat CI 12557 as susceptible to STB and the durums ‘Kubanka’ and ‘Amautka’as intermediate and resistant, respectively. Perhaps the most common method of identifying resistance to SNB and STB has been the assessment of disease severity (percentage leaf or head area affected) in the field. Many breeding programs throughout the world have and continue to use this method to identify resistant germplasm. Also, most studies have shown good correlation between assessments made following artificial inoculation and those under natural inoculum conditions (Bayles et al., 1985). One of the earliest scales for assessing SNB severity was derived by Doling (1961), who first categorized 93 varieties as to either severe infection, moderate infection, slight infection, trace infection, or no infection, based on visual assessment of severity in the field. He further assessed the glume blotch phase of the disease and developed a glume blotch index for varieties based on weighing factors

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from either a slight, moderate, or severe visual rating. A similar scale for SNB was also used by Nelson et al. (1974) in Georgia. Cooke and Jones (1971) used similar severity scales to assess SNB and STB severity on 1 1 winter and spring wheats in the field. Rosielle (1972) used a six-category scale to score bread and durum wheats for resistance to STB. The categories accounted for lesion size and pycnidial density with both increasing as the category score increased. Rosielle noticed, however, that some varieties departed from the scale by exhibiting extensive necrotic lesions with few or no pycnidia. A positive correlation between percentage severity of SNB on flag leaves to that on the heads was identified under field conditions (Scott, 1973). Gough and Smith (1976) used visual severity estimates of STB in the field to characterize germplasm in Oklahoma. Eyal et al. (1983) developed a relation between pycnidial density on the four uppermost leaves and the ratio between height of disease divided by plant height (called septoria progress coefficient) for STB. Using this method, they categorized several wheats into four categories ranging from highly resistant to highly susceptible to STB. The majority of greenhouse/growth chamber studies have used percentage leaf area necrosis and/or pycnidial density to quantify resistance (Shaner and Finney, 1982). In most cases, seedling and adult plant reaction to SNB and STB are positively correlated, with some exceptions (Mullaney et al., 1983; Scharen and Eyal, 1983). In greenhouse tests, Rillo and Caldwell (1966) differentiated six severity classes to STB in both seedling and adult plants, where 0 represented immunity and 5 was fully susceptible. Using this method, they identified 'Bulgaria 88' as a promising source of resistance. Later, Rillo et al. (1970) distinguished just three classes of host reaction, where resistant reactions had small lesions with pycnidia absent or few; intermediate was medium to large lesions, commonly containing pycnidia; and susceptible was large lesions with abundant pycnidia. Eyal et al. (1973) utilized pycnidial density classes of wide ranges to evaluate bread and durum wheat seedlings for resistance to a number of S . tritici isolates. Lesion size was used by Krupinsky et al. (1977) to screen 6161 wheat genotypes of T. aestivum and other Triticum spp. with mixed inoculum of SNB and STB. In five experiments, only 4 bread wheats and 16 other wheats, primarily T. timopheevi and T. dicoccum, averaged 10%or less necrosis. Scharen and Krupinsky (1978) assessed segregating generations of seedlings for percentages of plants with either no symptoms, typical lesions, chlorosis without lesions, and general necrosis to derive a damage index for SNB. Eyal and Brown (1976) digitized photographic transparencies on leaves representing a range of pycnidial densities to determine more precisely the pycnidial density on leaves. Later, Eyal and Scharen


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(1977) devised a quantitative technique for evaluating germplasm for SNB resistance and found that the resistant variety ‘Manitou’ required about 2.1 times more pycnidiospores to produce a single lesion than the number required for the susceptible variety ‘Fortuna.’ However, Shearer (1978) estimated that it took nearly lo4 more pycnidiospores of STB to produce a lesion on the susceptible variety ‘Kondut’ compared to the susceptible ‘Federation.’ Mullaney et al. (1982) used photographs of seedling leaves to assess total leaf area, necrotic leaf area, and number of lesions per leaf. Baker (1970) used excised leaves on benzimidazole-supplemented agar and assessed the percentage of lesion-bearing tissue for SNB and STB. She used this technique to compare varieties to ‘Cappelle-Desprez,’ then classified as highly susceptible to SNB and tolerant to STB. Detached seedling leaves were also used by Benedikz et al. (1981) to assess lesion length for determination of resistance to SNB. Griffiths et al. (1985) used detached wheat leaves infected with S. nodorum to correlate ergosterol content with lesion severity. Resistance to SNB can also depend on the growth stage of the host. Mullaney et al. (1983) found seedlings of the spring durum wheat cultivar ‘Giorgio 396’ to be resistant whereas the mature plants showed the same disease development and yield reduction as a susceptible cultivar. On the contrary, Kajalainen (1985) found high correlation between seedling and field resistance ( r = 3 2 , p < .001). In a second experiment involving detached seedling leaves on benzimidazole agar, the correlation also was high (r = .62, p < .001). Similar results were reported by Rufty et al. (1981a), who found a high correlation (r = .64,p < .01) for the percentage of leaf necrosis between seedlings and mature plants. However, both authors reported deviations from this pattern, indicating the existence of resistance genes, which are effective only in the seedling or later growth stages. Roettges (1986) reported a high correlation (r = .93, p < .001) between the resistance index (sum of ranks over all recorded parameters) of six cultivars and their field resistance measured as reaction to natural infections of SNB over several years. Various methods have been used to assess the level of seedborne infection of SNB (S. tritici is not known to be seedborne). Cunfer (1978) determined the incidence of seedborne SNB by germinating suspected seed for 7 days, then freezing the seedlings and subsequently observing for lesions. Mathur and Lee (1978) developed the near ultraviolet (NUV) light fluorescence method on oxgall agar to detect incidence of seedborne SNB. Cunfer and Johnson (1981) used the oxgall agar-NUV fluorescence method to conclude that visual assessment of SNB on glumes in the field was not correlated to actual seed infection by S. nodorum.

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B. COMPONENTS OF RESISTANCE

It is our view that “components of resistance” and “components of partial resistance” are equivalent for the septoria diseases of wheat. Because no immunity exists, any restriction or delay in pathogen development is a form of resistance. Following Vanderplank’s (1963) epidemiological interpretation of disease progress, some investigators began researching the components of resistance to SNB and STB. Shaner et al. (1975) identified a reduced rate of STB development in several winter wheat varieties. To do this, they evaluated STB severity on the four top leaves of mature plants in the field and rated pycnidial density on an A-to-E scale, where A represented the absence of pycnidia and E was equivalent to about 12 pycnidia per square millimeter. Brokenshire (1976) evaluated seedling and adult plants in the greenhouse and field for STB resistance based on incubation period (time from inoculation to symptom expression), latent period (time from inoculation to appearance of pycnidia), sporulation (area occupied by pycnidia), and disease severity. Good agreement was found between seedling reactions in the greenhouse and adult-plant reactions in the field. Gough (1978) found that pycnidia produced on the susceptible varieties ‘TAM W-101,’ ‘Improved Triumph,’ and ‘Triumph 64’ yielded over two times the number of pycnidiospores than those produced on the resistant variety ‘Oasis.’ Parlevliet (1979) stated that partial resistance resulted in delayed progress of disease epidemics by reduction of the infection rate r, the measure for the multiplication rate of the pathogen. He divided the rate-reducing resistances into four components that collectively influenced the disease development by the pathogen: 1. Infection frequency (measured as number of sporulating lesions per amount of spores applied) can be used to assess resistance to the initial infection and also to colonization of the pathogen. 2. Latent period (time between inoculation and first appearance of mature pycnidia) is an additional assessment factor to characterize resistance to colonization. 3. Spore production (number of spores produced per unit leaf area or fruiting body) can be used to measure resistance to fungal reproduction. 4. Infectious period (time during which pycnidia are sporulating) is an additional assessment character of fungal reproduction.

Parlevliet referred to R. R. Nelson’s statement that many resistances that reduced the infection rate had polygenic inheritance. He also pointed out ample evidence for mono- or oligogenic inheritance, which he demonstrated by several examples for small grains, tomato, and maize.

WHEAT RESISTANCE TO Septoria DISEASES

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Jeger (1980) and Jeger et al. (1983) studied 11 different components of resistance to SNB in seedlings of 41 wheat cultivars and related Triticum species. Besides infection frequency, latent period, and spore production, they also recorded incubation period (time between inoculation and first appearance of symptoms), lesion size, lesion cover (percentage of leaf area covered by lesions), and percentage of necrotic leaf tissue. In addition, the three latter components and spore production were assessed again when the infected leaf had turned completely yellow. Factor analysis revealed that four independent factors conditioned resistance. Necrosis and reduced spore production were two of these factors. They were interpreted as resistance to the action of the toxin and to fungal reproduction, respectively. Lesion size, lesion cover, and latent period together accounted for the third factor (resistance to the growth of the pathogen). The fourth factor was due to combined effects of infection frequency, incubation period, and lesion cover, which is associated with resistance to colonization by the pathogen. Analysis of principal components resulted in four classes that were dominated by a different combination of components. The first principal component was influenced by latent period, lesion size, and lesion cover. The second principal component was dominated by unit spore production and necrosis. Incubation period, lesion size, infection frequency, and necrosis accounted for the third principal component. All components characterized the fourth principal component, which could not reasonably be interpreted. From the results of the two analyses, the authors suggested the presence of four independent components corresponding to Parlevliet’s (1979) classification of resistance to establishment, growth, and reproduction of the fungus and one additional component for pathogen-induced necrosis. A study of 14 components on 10 cultivars by Lancashire and Jones (1985) agreed with the findings of Jeger et al. (1983). The principal components analysis of their data resulted in four components, of which the first (characterized by resistance to growth within the host) was most predominant, accounting for 49% of the variation. The second component conditioned resistance to infection and decrease of sporulation. Lesion length was responsible for the third character, which was suggested to be related to resistance to the toxin. The fourth component was influenced mainly by lesion width, which accounted for resistance to mycelium growth. A cluster analysis of the 10 cultivars allowed for classification of three groups on the basis of their components of resistance. In one case, related cultivars were classified into one group; however, another pair of related cultivars was classified into different groups. Lancashire and Jones (1985) developed an “r-index” for comparing the relative ability of variet-

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ies to slow the rate of SNB development. Contrary to Jeger et al. (19811, Griffiths and Jones (1987) found that incubation period did not correlate with field assessments of SNB. They did find that sporulation was a good indicator of field-assessed disease ratings. Roettges (1986) studied nine components of resistance in the seedling stage of seven winter wheat cultivars and two advanced breeding lines. He found cultivar differences for every component (incubation and latent period, necrosis, infection frequency, lesion area, percentage of lesions with pycnidia, and spore production perpycnidium, cm2leafarea, and cm2 lesion area). Most of the correlations between components were large and significant, ranging from r = .63 to .90. Only small negative correlations were found between latent period and necrosis (r = -.50,p > .05) and between latent period and spore production per unit leaf area ( r = -.58,p > .05). No correlation was found between lesion area and number of spores or pycnidia per square centimeter. A ranking of cultivars within each component indicated different ranks for other components. This should not be accepted as proof of different degrees of resistance for particular components, however, because the ranking was not based on the significant differences. Variation within the ranking occurred only within two groups roughly classified as “resistant” and “susceptible.” Only ‘Kanzler’ had a susceptible reaction concerning components of the vegetative stage, and a more resistant reaction to the reproductive stage of the fungus. Similar results were obtained by Nelson and Bruno (1985) who showed significant differences in 21 winter wheat cultivars for some of the measured components of resistance. Besides variation due to environmental effects, significant cultivar differences for incubation period, latent period, necrosis, and spore production were observed. Trottet and Benacef (1989) reported that there are several mechanisms of resistance whose expression depends on growth stage, and that great differences can be found between leaves and heads for disease development. Nelson and Crowder (1989) compared winter wheats at different growth stages for components of resistance. They reported that adult plants were more susceptible than seedling plants and that lower leaves were likewise more susceptible than upper or flag leaves. For percentage necrosis, they found that ‘Oasis’ had resistance in the adult stage that was not expressed in the seedling stage. Wilkinson and Murphy (1986) investigated the combining ability of winter wheat for four components of resistance using a diallel analysis. They found significant general combining ability (GCA) for incubation period, infection frequency, and latent period. No significant GCA was observed for spore production. Specific combining ability (SCA) affected only incubation period. Reciprocal crosses did not show significant differences for


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any of the components. Except for some observed degree of dominance for susceptibility in the resistant x susceptible crosses, primarily additive effects were observed. In a similar study involving a diallel cross, Stooksbury et al. (1987) reported highly significant results for both GCA and SCA effects for incubation and latent period. Bruno and Nelson (1990) conducted a diallel analysis to investigate gene effects for six components of resistance of wheat to SNB. The components were incubation period, latent period, percentage of diseased leaf tissue, initial spore production at the end of the latent period, total spore production at 100% necrosis, and maturation period. Maturation period was defined as the time between the first visual disease symptoms and the appearance of mature pycnidia. Significance was observed for incubation period, latent period, maturation period, and total spore production; however, percentage necrosis and initial spore production were not significantly different. Cunfer et al. (1988) rated seven winter wheat varieties for incubation period, latent period, lesion development, and sporulation of SNB and found good correlation among the resistance components. After studying the effects that resistance components have in slowing SNB development, Leonard (1988) suggested that a longer latent period was more effective than a reduction in spore production on susceptible varieties, but that the opposite was true for more resistant varieties. Rapilly (1988) used a model of SNB development to conclude that the rate of necrosis on leaves was more important than incubation period, which in turn was more important than latent period in reducing disease spread. Baker and Smith (1979) investigated the number and size of lesions on adult plants caused by SNB in three winter wheats with different degrees of resistance. Only the intermediate and susceptible varieties were noted for a sharp increase in number and size of lesions at the end of the season. The susceptible genotype began to develop a larger number of lesions about 5 weeks earlier than the intermediate. They differed from each other more in lesion number than in lesion size. The authors noted a more uniform and more dense canopy of the susceptible variety, which might have influenced the microclimate (higher humidity) promoting fungal development. The effects of postinoculation wet periods on the number of lesions and necrosis on seedlings of eight wheat varieties were investigated by Eyal et al. (1977). The data showed that an increase in the postinoculation wet period increased symptom development (more lesions and higher percentage of necrosis). Winter wheats were less affected than spring wheats, but varietal differences were observed for both groups. The infection frequency also has been studied in relation to inoculum concentration and postinoculation wet and dry periods (Jeger et al., 1984).

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Seedlings of two spring wheat varieties ('Kolibri' and 'Maris Butler') showed an increasing number of lesions on the leaves with an increase of the spore concentration of the inoculum, independent of subsequent wet and dry periods. The minimum concentration for symptom development was lo3 spores per milliliter, which is in agreement with other reports (Broennimann, 1968a; Roettges, 1986). Increasing the dry period resulted in a curvilinear decrease in the number of lesions at two temperatures (15°C and 20°C). In most cases, increasing the wet period caused a linear increase in the number of lesions, except for Kolibri. For this variety, the number of lesions leveled off after about 10 hr of wetness at 15°C. The latent period was studied by Shearer and Zadoks (1972,1974) under controlled and field conditions on seedlings of a susceptible winter wheat. Under controlled conditions, the effects of eight temperature treatments (5"-25"C),three moisture treatments, and two spore concentrations of the inoculum were studied. The shortest latent period of 6 days was observed on plants continuously kept in saturated air at 23°C. If these moisture conditions were interrupted for 12 hr with exposure to 85-90% relative humidity (r.h.), the formation of mature pycnidia was delayed by 5.6 days. Leaves continuously exposed to air with 85-90% r.h. became infected but did not produce spores at all, unless they were exposed for a short period (24 hr) to saturated air. The lower spore concentration, 5 X lo4spores ml', delayed spore production on the average by 2.4 days. The response for different temperature regimes was a parabolic curve for all moisture and inoculum levels, with the shortest latent period between 20°C and 23°C. The results from field conditions were in accordance with the controlled conditions. The latent period was reduced by an increase in temperature and/or duration of leaf wetness. A multiple regression analysis showed significant effects of both parameters as well as their interaction. In an attempt to predict the latent period from the recorded data, the duration of leaf wetness and minimum temperature were most useful. When measuring latent period in our research, we normally place plants in an incubation chamber overnight to stimulate formation of pycnidia. Aust and Hau (1981) studied the compensative effects of temperature, postinoculation wetness, and inoculum density on the latent period of the spring wheat Kolibri. The temperature conditions ranged from 12°C to 25"C, the postinoculation wetting periods from 15 to 72 hr, the postinfection wet period from 2 to 8 hr, and the spore density from lo4 to lo7 spores ml-', The shortest latent period was 7.7 days for a postinoculation wetting period of 72 hr, postinoculation period of 8 hr, spore concentration of lo7 spores ml-', and temperature of 20°C. Longer wetting periods and/or higher spore concentrations were shown to compensate for suboptimal temperatures.


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C. YIELDREDUCTION Another method used to identify resistance to SNB and STB has been by measuring the amount of yield loss, from either small plots or plant components. Some researchers (Broennimann, 1968b; Ziv and Eyal, 1976; Ziv et al., 1981) have used this type of assessment to measure disease tolerance. It is our opinion that tolerance should be used to describe the phenomenon whereby plants exhibit no significant yield reduction under the same disease severity and rate of disease development compared to susceptible plants. Thus, germplasm labeled as tolerant may actually yield better than a susceptible type by inducing some sort of restriction in pathogen development, rather than by being truly tolerant. Broennimann (1968a) was among the first to show that thousand-kernel weight (TKW) was strongly affected by SNB and that TKW could be used to assess for resistance. Doling (1961) and Cooke and Jones (1970) found an association between SNB severity and the degree of grain shriveling. Cooke and Jones (1971) subsequently found a good correlation between SNB and STB severity assessments with mean yield per head, TKW, and a sieving index. Variable results were found by Sharp et al. (1972) when they compared the SNB field rating of 30 spring wheats to their respective losses in grain yield per head, TKW, and kernels per head. They noticed that SNB had little effect on the TKW of cultivars ‘MT 6903’ and ‘Centana,’ but that disease did reduce the varieties’ kernels per head. Scott (1973) found a strong positive correlation between leaf and head infection by SNB and yield loss. Eyal and Ziv (1974) used STB progress curves from field trials to relate with losses in plot yield and TKW. In the STB-resistant varieties ‘Elite Lepeuple,’ ‘Maris Dove,’ ‘Maris Ensign,’ ‘Chalk,’ and ‘Tommy,’ a good correlation was found between incubation period, latent period, disease severity, and sporulation with TKW (Brokenshire, 1976). Across many winter wheat cultivars, field ratings for leaf and head severity of SNB were negatively correlated with plot yield, TKW, and test weight (Nelson et al., 1976). Gough and Merkle (1977) suggested that the effects of STB may be more highly manifested as root mass reductions rather than reduction in grain yield, and thereby may be a better indicator of resistance. Results from studies conducted by Scott and Benedikz (1977) indicated that yield loss was positively correlated with SNB severity but that disease was more easily measured and with less variability than yield loss. Rosielle and Brown (1980) used results from SNB-inoculated and uninoculated plots of segregating wheat populations to suggest that selection for yield or seed weight in inoculated plots would aid in the identification of resistant plants more so than selection for seed weight percentage. Nass

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and Johnston (1985) found that resistance to SNB could be identified in the field by comparing the yields of fungicide-treatedto untreated plots. They indicated that SNB severity, plot yield, and TKW were good selection criteria for SNB resistance. Zilberstein et al. (1985) suggested that postanthesis chemical desiccation of field plots could be used as a screening method to identify germplasm that is able to endure severe STB infection. Kelaniyangoda (1987) identified SNB-resistant varieties by using the correlation between field severity rating and yield loss.

111. PATHOGEN VARIATION Significant variability for pathogenicity and related fitness factors in the S . nodorum and S.tritici populations can influence how to best breed for resistance to these two pathogens. Much of the early work on Septoria variability centered on determining which plant species the fungi could infect (Beach, 1919; Weber, 1922). Broennimann (1968a) found that individual isolates of S . nodorum varied in regard to spore production, but that small differences were evident in terms of their pathogenicity. Krupinsky et al. (1973) found that S. nodorum isolates varied in pathogenicity (aggressiveness) as measured by changes in the plants’ photosynthetic rate. Krupinsky et al. (1989) studied 27 isolates from 1 1 different species of grass. The isolates differed in their ability to cause SNB symptoms on wheat and this difference was interpreted to be due to aggressiveness. Scharen and Krupinsky (1970) showed the wide range of variability present in the pycnidiospores from a single pycnidium. However, Griffiths and Ao (1980) found that even though S . nodorum isolates were highly variable for several cultural characteristics, variation for pathogenicity was narrower. Septoria nodorum isolates in Florida were found to be quite variable in terms of pathogenicity on eight wheat varieties (Allingham and Jackson, 1981). Several studies have examined the effects of cross-inoculationreisolation experiments to determine host range and to detect physiological specialization. Shearer and Zadoks (1972) suggested that S.nodorum could become more specialized on a host following repeated passages. Similarly, Ao and Griffith (1976) found that virulence of S.nodorum and S . tritici may change after a single passage through an alternate host and that direction and magnitude of change are similar for both fungi. An S . nodorum isolate from barley was found to gain pathogenicity toward wheat and lose pathogenicity to barley after several passages through wheat (Fitzgerald and Cooke, 1982). However, Cunfer (1984) suggested that the S.


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nodorum found on barley in the southeastern United States was largely restricted to barley. Osbourn et al. (1986) found some changes in S. nodorum isolates with passages through barley and wheat, but concluded that the changes may have resulted from cross-contamination with subsequent selection. Eyal et al. (1973) used pycnidial density classes and percentage leaf area covered by pycnidia to suggest that true physiological specialization existed in STB isolates in Israel. Research in Argentina (Perello et al., 1989) had similar results, and they indicated that pycnidial coverage was a better parameter than necrotic lesion area to differentiate between isolates. Although some minor statistically significant differences were found between isolates and varieties, much greater interactions were evident between isolates from bread and durum wheats. Rufty et al. (1981b) assessed lesion percentage on seedling leaves and identified significant SNB isolate X wheat variety interactions, but indicated that the magnitude of the differences was small and therefore classification of the isolates into physiological races was inappropriate. A similar level of pathogenic variation in S. nodorum was found by Scharen and Eyal (1983). Specialization in S. nodorum isolates was evident among several wild species of Triticum (Yechilevich-Auster et al., 1983). Eyal et al. (1985) tested 97 isolates of S. tritici on varieties of bread wheat, durum wheat, and triticale and found significant isolate X variety interactions. They also suggested that seedlings exhibiting necrotic leaf area of below 16.6% could be considered resistant, whereas those with greater amounts of necrosis were susceptible. Similar results of Eyal and Levy (1987) suggested geographic distribution of specific virulences in S. tritici. Likewise, Scharen et al. (1985) found significant S. nodorum isolate X variety interactions with bread wheats, durum wheats, and triticales. Using percentage necrosis on seedlings, they suggested that 17.9%necrosis was the separation point between susceptibility and resistance to S. nodorum. Marshall (1985) assessed S. tritici severity in the field over 13 locations in the United States in addition to greenhouse assessments of leaf severity and pycnidial density and found wide variation for aggressiveness but no significant isolate X variety interactions. Saadaoui (1987) used bread and durum wheat cultivars and found physiological specialization in S. tritici when 20% necrotic leaf area with few pycnidia was used as the separation point between susceptibility and resistance. Van Ginkel and Scharen (1988) suggested that S. tritici isolates were specifically adapted to either bread or durum wheat (species specificity), but that cultivar specificity was not significant. Silfhout et al. (1989) reported that certain S. tritici isolates were able to overcome the resistance of cultivars, and that these isolates. must have one or more genes for specific virulence that do not occur in

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other isolates. Cordo et al. (1989) reported that isolates of STB obtained from wheat leaves have the characteristics of being heterogeneous in virulence. They can originate from pycnidia that are homogeneously virulent, avirulent, or show a mixed virulence. It is clear that genus and species (Triticum) specificity exists in both S. nodorum and S. tritici. This may be regarded as genome specificity. Specificity at the varietal level is less clear, particularly because “where you draw the line” between resistance and susceptibility greatly influences isolate by cultivar interactions. However, there is wide variability in both pathogens for pathogenic aggressiveness, which can vary with geographic location. Therefore, it seems reasonable that breeding programs should determine the locations within their geographic area of interest where the most aggressive isolates are indigenous. Single-spore cultures from the most pathogenic isolates should be used in greenhouse/growth chamber studies. Because resistance to Septoriu diseases is relative and not absolute (immunity), perhaps the most effective method to identify resistance would be to use a single, highly pathogenic isolate of S. nodorum or S. tritici (Parlevliet, 1983).

IV. GENETICS OF RESISTANCE Mackie (1929) was the first to report that S. tritici resistance could be bred into wheat and that resistance was simply inherited and recessive. Narvaez and Caldwell(l957) crossed the S. tritic&resistant‘Nabob’ with the susceptibles ‘Knox’ and ‘Vermillion’ and found that resistance was controlled by two independent, partially dominant genes with additive effect. They also found that in the ‘Lerma 52’ and ‘P14’ X ‘Lee’ and ‘Mayo 54’ crosses, resistance was controlled by a single dominant gene. Efforts to find resistance to STB were accelerated in the late 1960s and early 1970s by the generalized susceptibility of high-yielding spring wheats coupled with conducive environmental conditions that resulted in severe STB epidemics (Saari and Wilcoxson, 1974; Marshall, 1989). Rillo and Caldwell(l966) identified ‘Bulgaria 88’ as a source of resistance to S. tritici and suggested that a single, dominant gene conditioned resistance. The resistance in ‘Bulgaria 88’ was transferred to the winter wheat variety ‘Oasis’ (Patterson el al., 1975).STB resistance in an Agropyron-wheat derivative was found to originate on a singleAgropyron chromosome that was transmitted 25% of the time through the male and female gametes (Rillo et al., 1970). Rosielle and Brown (1979) used ‘Gamenya’ as the susceptible parent in crosses with the STB-resistant wheats ‘Seabreeze,’ ‘Veranopolois,’ and


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‘IAS-20.’ They found that the resistance in ‘Seabreeze’ was conditioned by at least three recessive genes, whereas a single gene probably conferred resistance in ‘Veranopolis’ and ‘IAS-20.’ Wilson (1979) reported that ‘Israel 493’ and ‘Veranopolis’ each contained a single gene for resistance to STB and that they were independent of each other. Danon et al. (1982) concluded that resistance to STB in ‘Bezostaya 1,’ ‘Colotana,’ ‘Fortaleza1,’ ‘Polk/Waldron,’ ‘Sheridan,’ and ‘Oasis’ was conferred by only one or a few genes. Lee and Gough (1984) crossed the STB-resistant ‘Carifen 12’ with the susceptible wheats ‘TAM W-101’ and ‘Triumph 64’ and found that a single, dominant gene conferred resistance. Both additive and dominance gene effects for resistance to STB were significant in several durum wheat crosses (Van Ginkel and Scharen, 1987). Broennimann (1975) found that resistance to SNB was inherited mainly additively and polygenically. Kleijer et al. (1977) crossed the monosomic set of ‘Chinese Spring’ with the SNB-resistant variety ‘Atlas 66’ and found that a single, dominant gene for resistance was located on chromosome 1B. Nelson (1980) identified ‘Oasis’ and ‘Blueboy 11’ as good sources of resistance to SNB because of the varieties’ significant general combining ability and specific combining ability. Nelson and Gates (1982) further indicated that SNB resistance in ‘Oasis’ and ‘Blueboy 11’ was additive and inherited in a very complex manner. Mullaney et al. (1982)used generation mean analysis to suggest that SNB resistance in ‘Frondoso’ and ‘Fronthatch’ was pol ygenically controlled and explained principally by additive gene effects. Because additive gene action may be quite prevalent in sources for resistance to SNB, Karjalainen (1985)proposed that transgression breeding may be a useful method for improving resistance. Resistance to SNB on leaves appeared to be independent of resistance on the heads (Fried and Meister, 1987), and overall heritability or resistance was quite low. Rapilly et al. (1988) suggested that resistance to S. nodorum as measured by incubation time and rate of spread of leaf necrosis was polygenically inherited and possibly located on chromosomes 3A, 2B, and 5B. Similarly, Ecker et al. (1989) found that resistance to SNB as assessed by infection efficiency, disease severity, lesion size, and latent period was controlled by three to four quantitative genes, with mainly additive resistance. Frecha (1973) analyzed the resistance of ‘Atlas 66’ to SNB and reported it to be inherited by a single dominant gene for resistance. However, Kleijer et al. (1977) could not reproduce the data using chromosome substitutions to locate the gene. Although only 1 substitution line (1B substitution) differed significantly from the other 20 lines, they were not able to obtain a clear 3 : 1 (resistant : susceptible) segregation, since too few plants showed a resistant reaction. On the basis of these results, they suggested the

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presence of one or more modifier genes in ‘Chinese Spring’ (the monosomic, susceptible parent) or the same chromosome. Several studies have indicated that resistance to Septoriu diseases tends to be found in wheat lines that were tall and/or late maturing. Tavella (1978) found positive correlations between low S. tritici field ratings and tall, late varieties. Rosielle and Brown (1979) suggested that even though there appeared to be a correlation between tall, late plants and resistance to STB, it should not be a major obstacle to selection. A low correlation between plant height and S. tritici severity suggested that there is probably no linkage or pleiotropy between shortness and susceptibility (Danon et ul., 1982). Scott et al. (1982) suggested that breeding S.nodorum-resistant germplasm of any height should be possible because they found genes conferring resistance that were independent of plant height and heading day. The presence of genes for tolerance that were independent from tallness was reported by Broennimann and Fossati (1977). Using induced mutation, the authors were able to recover a tolerant mutant from a short, susceptible genotype that was only slightly taller than the original genotype. In addition, they were able to induce short, tolerant mutants in tolerant but tall lines. Unfortunately, in both cases the mutants had low yields and could only be used in breeding programs.

V. SOURCES OF RESISTANCE In Table I, we have attempted to list those publications in which authors have identified sources of resistance to S. nodorum and/or S. tritici. Even though we have attempted to be thorough, we apologize in advance if any sources have been inadvertently omitted.

VI. DISCUSSION AND CONCLUSIONS Compared to other wheat diseases, such as leaf or stem rust, little progress in host plant resistance has been accomplished with the septoria diseases. Genes for immunity or complete resistance to either SNB or STB have not be discovered or reported in the literature. The complexity of the disease organism and the inheritance of resistance to SNB and STB have not been and are not clearly understood. Most of the resistant genotypes were developed in plant breeding programs located in environments that


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Table I Published Sources of Resistance to Septoria nodorum and S. fritici as listed in the Literature Septoria Baker (1970) Benedikz et a / . (1981) Bruno and Nelson (1990) Cooke and Jones (197 I ) Doling (1961) Eyal et a/. (1987) Jeger e f a/ (1983) Krupinsky et a / . (1977) Nass and Johnson (1985)

nodorum Nelson (1979) Nelson (1980) Nelson and Crowder (1989) Rufty e f al. (1981b) Scharen and Eyal(1980) Scharen et a / . (1985) Scott (1973) Sharp et a / . (1972) Wilkinson et a / . (1990)

Septoria tritici Baker (1970) Eyal et a / . (1987) Krupinsky et a / . (1977) Bayles et a!. (1985) Brokenshire (1976) Narvaez and Caldwell(1957) Renfro and Young (1956) Cooke and Jones (1971) Rosielle (1 972) Danon e t a / . (1982) Eyal et a / . (1983) Shaner and Finney (1982) Eyal et a / . (1985) Shaner et a / . (1975)

were conducive to disease epidemics, and therefore susceptible germplasm was discarded annually during normal selection procedures in the breeding program. Advances in the selection of resistant germplasm were very slow because of escapes caused by weather patterns that limited the septoria disease epidemic. Tall or late-maturing genotypes often were rated incorrectly as resistant. Other diseases such as rusts or powdery mildew often were of greater importance, and therefore the more septoriaresistant germplasm was discarded. Indentification of genes for resistance was difficult at best, because resistance was often inherited in an additive manner. During the past 10 years much has been learned about these diseases. We now use several new techniques to screen germplasm both as seedlings and as adult plants. We also know that exact environmental conditions must be maintained to conduct any genetic studies. Comprehension of components of partial resistance has begun to simplify the inheritance of resistance in some ways. At least we have begun to understand why and how some cultivars are resistant. On the other hand, utilizing or manipulating certain types of components, such as latent period, in plant breeding programs is very difficult, is time-consuming, and limits the germplasm that can be screened.

274


The future remains clouded. Many sources of resistance are available for wheat breeding programs; however, the indentification of segregating germplasm for one component or several components of resistance will be necessary to achieve high levels of resistance. This may not be practical or cost-effective in many wheat breeding programs. There is likely much more variation in both the S . nodorum and S . tritici organisms than has been reported in the literature. If this is the case, the septoria organisms may be able to adapt to and/or attack at least some components of resistance. This is certainly not as likely as with major genes for resistance on other wheat diseases. The use of multiple isolates of either S . nodorum or S . tritici may be useful in identifying components of partial resistance that are resistant to all isolates. This may not be the case, however, if some genes are resistant to only some isolates. In this case, progress for selection of these components would be difficult or perhaps useless. Great advances have been made in the production of inoculum that can be used in either the field or laboratory. Therefore it is relatively easy to produce epidemics in our breeding programs that create selection pressures that are useful in selecting superior genotypes. The use of biotechnology may offer even greater potential. Since septoria diseases produce toxins, selection at the cellular level of resistant types could be worthwhile and new and improved resistance may be found or developed. The use of RFLP (restriction fragment length polymorphism) technology also offers advances. particularly to determine if pathogenic differences between isolates of S . nodorum and/or S . tritici exist. If pathogenic differences in isolates do exist, and they can be fingerprinted, then the movement of an isolate in the field can be followed and the epidemiology of the organism will be better understood.

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INDEX A

Absorption nitrogen fixation by legumes and, 174 root growth models and, 118-120, 126, 127 Acacia, forage tree legumes and, 29, 30, 36 Acetylene reduction assay, nitrogen fixation by legumes and, 174, 175, 177, 187 Adaptation cowpea and, 145 genetic resources in cereals and, 94,97, 100, 104, 106, 107 Gossypium and, 241,243-245 multilocation trials and, 72, 74-76 nitrogen fixation by legumes and, 182, 190 time of seedling emergence and, 17, 18 wheat resistance to Septoria and, 269 Additive genes, wheat resistance to Septoria and, 271 Additive Main effect and Multiplicative Interaction, 59,71, 72,76-82 Aegilops, genetic resources in cereals and, 97-99, 101 Aeration root growth models and, 124, 129, 130 time of seedling emergence and, 5 Age cowpea and, 140 forage tree legumes and, 41,44 Gossypium and, 238,240,244 nitrogen fixation by legumes and, 172, 175

root growth models and, 130 components, 118, 120, 124, 125 features, 117 time of seedling emergence and, I6 Agricultural Research Service, Gossypium and, 235,237-244 Agropyron genetic resources in cereals and, 97,98 wheat resistance to Septoria and, 270

Alleles genetic resources in cereals and, 101 Gossypium and, 249 Allotetraploids, Gossypium and, 227, 244, 253 distribution, 231-235 evaluation, 245, 246,248-252 Allozymes, Gossypium and, 249 Aluminum, root growth models and, 129 Amides, nitrogen fixation by legumes and, 168, 169 Amino acids, nitrogen fixation by legumes and, 169, 170 Ammonia, nitrogen fixation by legumes and, 167-169, 174 Amphidiploidy, Gossypium and, 229, 231-233 Aphids, cowpea and, 139, 140, 149 Aphis craccivora, cowpea and, 139, 140 Aridity, Gossypium and, 227, 229,242

B

Backcross cowpea and, 143 genetic resources in cereals and, 106 Gossypium and, 232,251,252 Bacteria cowpea and, 134, 136, 138, 148, 149 Gossypium and, 252 Barley genetic resources in cereals and, 87, 89, 91-98, 100-103, 105 multilocation trials and, 63 wheat resistance to Septoria and, 268 Bean, nitrogen fixation by legumes and, 204,206,207,212 Beet, time of seedling emergence and, 4,5,7 Biochemistry cowpea and, 142 nitrogen fixation by legumes and, 207

279

280

INDEX

time of seedling emergence and, I5 Biology cowpea and, 141, 145 forage tree legumes and, 47 multilocation trials and, 56,62-66, 81,82 nitrogen fixation by legumes and, 156 root growth models and, 114 Blight cowpea and, 144, 146 Gossypium and, 252 Boll weevil, Gossypium and, 244,245 Bradyrhizobium japonicum, nitrogen fixation by legumes and, 202,204,212 Branching rate, root growth models and, 124, 125 Breeding cowpea and, 139, 141, 143, 150 genetic resources in cereals and, 87, 88, 90,93,96-107 Gossypium and, 244,251, 253 multilocation trials and, 5 5 , 56, 81 AMMI analysis, 77 joint linear regression, 61,64, 67,68 multivariate analyses, 74 variance, 60 nitrogen fixation by legumes and, 205-207,209 wheat resistance to Septoria and, see Wheat resistance to Septoria Buckwheat, time of seedling emergence and, 17, 18,21 Bulk density, root growth models and, 124, I29

C

Calcium cowpea and, 146 forage tree legumes and, 41 root growth models and, 123, 129 Calliandra, forage tree legumes and, 29 Calliandra calothyrsus, forage tree legumes and management, 38-40,42 nitrogen recycling, 47 nitrogen yields, 45 performance, 30 Callus, cowpea and, 142, 143

Calories, nitrogen fixation by legumes and, 177, 178 Canopy cowpea and, 138 forage tree legumes and, 32-34,43,44 Gossypium and, 252 root growth models and, 117 time of seedling emergence and, 17 Carbohydrate forage tree legumes and, 36 nitrogen fixation by legumes and, 206 root growth models and, 113, 117, 122, 127-129 time of seedling emergence and, 18 Carbon forage tree legumes and, 47 nitrogen fixation by legumes and, 162 root growth models and, 128 time of seedling emergence and, 9 Carrot genetic manipulation and, 143 multilocation trials and, 72 time of seedling emergence and, 1, 5.6, 11, 14, 15 Cellular selection, cowpea and, 143, 145 Cereal genetic resources in, 87-89, 105-107 barley, 93-95 documentation, 102-105 Ethiopia, 95, 96 primitive forms, 96-102 wheat, 89-93 nitrogen fixation by legumes and assessment, 176 contribution to production, 191, 194, 196- I99 enhancement, 213, 215 production systems, 177, 178, 192-184 root growth models and, 118, 120, 130 Characterization, genetic resources in cereals and, 88,89, 100, 104 Chenopodium, time of seedling emergence and, 14, 15 Chimaeras, cowpea and, 147, 148 Chlorophyll genetic resources in cereals and, 91 time of seedling emergence and, 18 Chloroplasts cowpea and, 146, 147 Gossypium and, 234,235, 249, 250

28 1

INDEX Chromatography, nitrogen fixation by legumes and, 174 Chromosomes cowpea and, 145 genetic resources in cereals and, 93 Gossypium and, 231-235, 245-247 wheat resistance to Septoria and, 270-272 Climate forage tree legumes and, 39.49 genetic resources in cereals and, 94,95, 101 Gossypium and, 238 multilocation trials and, 80 nitrogen fixation by legumes and, 182 time of seedling emergence and, 19 Clinal pattern, genetic resources in cereals and, 90,96 Cluster analysis, multilocation trials and, 71,74-76,81 Cocksfoot, time of seedling emergence and, 11, 15 Codariocalyx gyroides, forage tree legumes and, 38,39 Coevolution, genetic resources in cereals and, 89 Collection, Gossypiurn and, 235-245 Commonwealth Scientific and Industrial Research Organization, Gossypium and, 238, 241 Compaction, root growth models and, 124 Compensation nitrogen fixation by legumes and, 156 wheat resistance to Seproria and, 266 Competition forage tree legumes and, 33,42,44 multilocation trials and, 57 nitrogen fixation by legumes and, 174, 182,216 time of seedling emergence and, 2, 10, 1 1 . 14-21 Composite cross, genetic resources in cereals and, 105 Conservation, genetic resources in cereals and, 88, 105, 106 Core collections, genetic resources in cereals and, 104 Cotton, see Gossypium Cover crops, nitrogen fixation by legumes and, 200

Cowpea genetic manipulation of, 133-139, 149, 150 embryo culture, 145, 146 fungal pathogens, 141, 142 insects, 139-141 somaclonal variation, 144, 145 somatic hybridization, 146-148 tissue culture technology, 142-144 transformation, 148, 149 nitrogen fixation by legumes and contribution to production, 195-197 enhancement, 210, 215 production systems, 178, 181-183 Crop root growth models, see Root growth models Cross-pollination, cowpea and, 145 Crossover interactions, multilocation trials and, 68-10 Cutting, forage tree legumes and, 38-41, 43,44 Cytogenetics, Gossypium and, 231,236 Cytology, Gossypium and, 229, 233,247, 248 Cytoplasm cowpea and, 145-147 Gossypium and, 253

D

Decay forage tree legumes and, 47,48 nitrogen fixation by legumes and, 191 root growth models and, 113, 114, 117, 118 Decomposition, nitrogen fixation by legumes and, 191, 192, 197-199 Deforestation, genetic resources in cereals and, 96 Degree days, root growth models and, 128, I30 Denitrification, fixation by legumes and, 213 Density forage tree legumes and, 41-44,46 multilocation trials and, 55 time of seedling emergence and, 10-17, 19,20

282

INDEX

Detrended correspondence analysis, multilocation trials and, 80 Dicotyledon cowpea and, 148 root growth models and, 120 time of seedling emergence and, 6 Diffusion Gossypium and, 249 root growth models and, 114, 125, 126 Digitalis purpurea, time of seedling emergence and, 14, 16 Diploidy, Gossypium and, 226, 253 distribution, 229, 231-234 evaluation, 245,247, 250 Discriminant analysis, multilocation trials and, 71 Disease cowpea and, 137-142, 149 forage tree legumes and, 28 genetic resources in cereals and, 88.91, 94,95,97,99, 102-104 Cossypium and, 236,252 nitrogen fixation by legumes and, 187, I97 wheat resistance to Septoria and, see Wheat resistance to Septoria Distribution, Gossypium and, 228-235 DNA genetic resources in cereals and, 93, 106 Gossypium and, 234,235,249,250 Documentation, genetic resources in cereals and, 102-106 Domestication genetic resources in cereals and, 96 Gossypium and, 226-228 Dominance multilocation trials and, 63, 64 time of seedling emergence and, 2, 17 wheat resistance to Seproria and, 265, 270,271 Dormancy, time of seedling emergence and, 2, 7, 14 Drought forage tree legumes and, 34 genetic resources in cereals and, 91,97, 100, 103 E

Ecology cowpea and, 139

genetic resources in cereals and, 89, 104 Gossypium and, 241-243,253 multilocation trials and, 80 Economics cowpea and, 140 forage tree legumes and, 49 genetic resources in cereals and, 91,95, 100, 104, 107 Gossypium and, 244, 253 nitrogen fixation by legumes and, 176, 178, 186, 187 time of seedling emergence and, 2 Electrophoresis genetic resources in cereals and, 100, 101,106 Ethiopia, 96 wheat, 92,93 Gossypium and, 247-250 Embryo cowpea and, 143-146 Gossypium and, 228 time of seedling emergence and, 6 , 7 Endonuclease restriction, Gossypium and, 249,250 Environment cowpea and, 143, 149 forage tree legumes and, 36,49 genetic resources in cereals and, 88, 92-94,97,98, 100-102, 104-107 Gossypium and, 236, 245,247, 251, 253 multilocation trials and, 5 5 , 56, 80-82 AMMI analysis, 76-90 crossover interactions, 68-70 joint linear regression, 61-68 multivariate analyses, 70-76 variance, 57-60 nitrogen fixation by legumes and, 156 assessment, 158, 172 contribution to production, 199 enhancement, 204,206,211,214 production systems, 182, 190 root growth models and, 124, 127, 130, 131 time of seedling emergence and, 6-8, 19 wheat resistance to Seproria and, 264, 270,272, 273 Enzymes genetic resources in cereals and, 94 Gossypium and, 235,248,250 nitrogen fixation by legumes and, 174

283

INDEX Epidemics, wheat resistance to Septoriu and, 273,274 Erosion forage tree legumes and, 33 nitrogen fixation by legumes and, 184, 187 Ethiopia, genetic resources in cereals and, 90,91,94-96 Evolution cowpea and, 145, 149 genetic resources in cereals and, 89,97, I02 Gossypium and, 231-235.248-250 nitrogen fixation by legumes and, 174, 206 Expected mean squares, multilocation trials and, 60 F

Factor analysis, multilocation trials and, 71.75 Fecundity cowpea and, 146 time of seedling emergence and, 2, 12, 13, 15 Feedback root growth models and, 127 time of seedling emergence and, 17 Fertility genetic resources in cereals and, 90 Gossypium and, 232, 253 mu1tilocation.trials and, 57 nitrogen fixation by legumes and, 214 root growth models and, 116, 123, 124 Fertilization, cowpea and, 145, 146 Fertilizer forage tree legumes and management, 41 nitrogen recycling, 48, 49 nitrogen yields, 46 performance, 34,35 species, 28 multilocation trials and, 55 nitrogen fixation by legumes and, 156, 157 assessment, 175, 176 contribution to production, 193, 196, 200,201 enhancement, 202,203,206,212, 213

production systems, 180, 181, 183 root growth models and, 117 time of seedling emergence and, 4 Fitness, wheat resistance to Septoriu and, 268 Fixation, nitrogen, see Nitrogen fixation Flooding Gossypium and, 237 nitrogen fixation by legumes and, 187 root growth models and, 130 Flowering cowpea and, 136, 137, 145 genetic resources in cereals and, 94 Gossypium and, 240,243 nitrogen fixation by legumes and, 208 Fluorescence, wheat resistance to Septoriu and, 261 Food legumes, nitrogen fixation and, 177- 184 Forage, nitrogen fixation by legumes and, 156 assessment, 170, 171 contribution to production, 190, 200-202 production systems, 184, 185, 188, 189 Forage tree legumes, 27, 28,49, 50 animal feed, 34-36 management, 36-38 cutting, 38-41 density, 41-44 nitrogen recycling, 46-49 nitrogen yields, 45,46 performance, 29-34 species, 28, 29 Fungus cowpea and, 136, 138, 139, 141, 142, 145, 149 time of seedling emergence and, 8 wheat resistance to Septoriu and, 257, 262-265,268 Fusion, cowpea and, 146, 147

G

Gene pool, genetic resources in cereals and, 101, 103, 107 General combining activity, wheat resistance to Septoriu and, 264, 265, 27 1 Genetic diversity cowpea and, 138, 139

284

INDEX

genetic resources in cereals and, 92-94, loo, 102,106 Gossypium and, 249 Genetic erosion, genetic resources in cereals and, 96, 105 Genetics cereals and, see Cereals, genetic resources in cowpea and, see Cowpea, genetic manipulation of Gossypium and collection, 236 distribution, 232, 233 evaluation, 245-247, 249,25 1,253 multilocation trials and, 60-62, 79 nitrogen fixation by legumes and, 210 root growth models and, 131 time of seedling emergence and, 2 , 7 , 8 wheat resistance to Septoria and, 269-273 Genomes cowpea and, 145, 147 genetic resources in cereals and, 92,98 Gossypium and distribution, 229-235 evaluation, 247-250,253 Genotype cowpea and, 142, 143, 145 genetic resources in cereals and, 91,92, 101,104

Gossypium and, 251 multilocation trials and, 55, 56,80-82 AMMI analysis, 76-80 crossover interactions, 68-70 joint linear regression, 61-68 multivariate analyses, 70-76 variance, 57-60 nitrogen fixation by legumes and, 158, 190,205,206,208,216 stability, multilocation trials and, 61 wheat resistance to Septoria and, 258, 260,272-274 Geography genetic resources in cereals and, 89,90, 92,94,95, 102, 105 Gossypium and, 226 collection, 236, 242 distribution, 228, 229 evaluation, 248,249,251 multilocation trials and, 82

wheat resistance to Septoria and, 258, 269 Germination root growth models and, 123 time of seedling emergence and, 2-9 GermpIa sm cowpea and, 141 genetic resources in cereals and, 88-91, 93,95-98, 103-107 Gossypium and, 253 collection, 239-242, 245 distribution, 236 evaluation, 250-252 wheat resistance to Septoria and, 258-261,267,268,272-274 Gliadin, genetic resources in cereals and, 96,98 Gliricidia, forage tree legumes and, 30, 35,47 Gliricidia sepium, forage tree legumes and, 28-30, Glutamate synthase, nitrogen fixation by legumes and, 167, 169 Glutamine, nitrogen fixation by legumes and, 167, 168 Glutamine synthetase, nitrogen fixation by legumes and, 167, 169 Gluten, genetic resources in cereals and, 92 Glutenins, genetic resources in cereals and, 101 Gossypium, 225, 226, 253 collection, 235 plant explorations, 237-245 source, 235, 236 distribution evolution, 231-235 geography, 228,229 species, 229-231 taxonomy, 228 evaluation electrophoresis, 247-250 genetics, 245-247 improvement, 250-253 history of domestication, 226-228 root growth models and, 114, 115 Grass forage tree legumes and management, 42 nitrogen recycling, 47

285

INDEX nitrogen yields, 46 performance, 31,33,34 nitrogen fixation by legumes and, 188, 189, 191,201,202 root growth models and, 128, 129 time of seedling emergence and, 15, 21 Grazing forage tree legumes and, 27,28 animal feed, 36 management, 36 nitrogen recycling, 47 nitrogen yields, 46 performance, 33,34 nitrogen fixation by legumes and, 174, 177,200 Green grams nitrogen fixation by legumes and, 182, 195, 196 time of seedling emergence and, 17, 18,21 Green manure forage tree legumes and, 49 nitrogen fixation by legumes and, 176, 177, 184, 186-200

H

Habitat cowpea and, 149 genetic resources in cereals and, 92,96, 103, 104 Gossypium and, 234,238 Harvest cowpea and, 138, 140 forage tree legumes and, 29, 36, 37,40, 41,43,45-47 Gossypium and, 244,252 nitrogen fixation by legumes and, 56 assessment, 172 contribution to production, 191 193, 197,200 time of seedling emergence and, I 114, 15, 17 Harvest index, nitrogen fixation by legumes and, 191, 193, 198 Hierarchy multilocation trials and, 75,76 time of seedling emergence and, 2, 14, 15

Homology genetic resources in cereals and, 98 Gossypium and, 23 I, 232, 247 Hordeum, time of seedling emergence and, 14, I5 Hordeum murinum, genetic resources in cereals and, 100 Hordeum spontaneum, genetic resources in cereals and, 93, 100, 101 Hordeum uulgare, genetic resources in cereals and, 92,96 Humidity cowpea and, 133, 135, 141 forage tree legumes and, 28 genetic resources in cereals and, 91 Gossypium and, 252 nitrogen fixation by legumes and, 156, I86 time of seedling emergence and, 16 Hybrids cowpea and, 143-148, 150 genetic resources in cereals and, 90, 96,98 Gossypium and, 231-234,250-253 multilocation trials and, 77 nitrogen fixation by legumes and, 206, 213 Hydrogen, nitrogen fixation by legumes and, 175, 206 Hysteresis, root growth models and, 130 I

ICARDA, genetic resources in cereals and, 91,94, 102, 103 Immobilization, nitrogen fixation by legumes and, 191, 213 Immunity, wheat resistance to Septoria and, 259,260, 262 Impedance root growth models and, 129 time of seedling emergence and, 5 , 8 Incompatibility, Gossypium and, 247 Incubation, wheat resistance to Septoria and, 262-267,271 Inhibition forage tree legumes and, 42 nitrogen fixation by legumes and, 174, 202,206

286

INDEX

time of seedling emergence and, 3 , 7 , 8 wheat resistance to Septoria and, 258 Inoculation Gossypium and, 252 nitrogen fixation by legumes and, 202, 203,210-213,216 wheat resistance to Septoria and, 259, 260,263,265-268,274 Insects cowpea and, 136-143, 148-150 forage tree legumes and, 28, 50 Gossypium and, 236,241,244,252 nitrogen fixation by legumes and, 197 International Board for Plant Genetic Resources genetic resources in cereals and, 88, 103 Gossypium and, 231, 239,241, 242 International Institute of Tropical Agriculture, cowpea and, 137-142, 149 International Wheat and Maize Improvement Center, genetic resources in cereals and, 93, 94 Irradiance, forage tree legumes and, 32,44 Irrigation, nitrogen fixation by legumes and, 182,214 Isoenzymes, nitrogen fixation by legumes and, 207 Isolation, cowpea and, 146, 147 Isotopes, nitrogen fixation by legumes and, 158-165 Isozymes, genetic resources in cereals and, 88 J

Joint linear regression, multilocation trials and, 61-68 L

Landraces, genetic resources in cereals and, 89-94,98, 102, 106, 107 Latency, wheat resistance to Septoria and, 263,265-267,271,273 Leaf Area Index, forage tree legumes and, 43 Legumes forage tree, see Forage tree legumes nitrogen fixation by, see Nitrogen fixation by legumes

Lesions, wheat resistance to Septoria and genetics, 271 identification, 259-266 pathogen variation, 269 Lettuce, time of seedling emergence and, 6,7,9 Leucaena leucocephala, forage tree legumes and, 49 animal feed, 34, 35 management, 38-40,42 nitrogen recycling, 47,48 nitrogen yields, 45 performance, 29,30 Light forage tree legumes and, 30,32,33, 42,44 time of seedling emergence and, 7, 16, 17, 19 Linear regression, multilocation trials and, 61-68,81 Linkage genetic resources in cereals and, 94 Gossypium and, 246 Livestock, nitrogen fixation by legumes and, 184,200-202 Longevity, time of seedling emergence and, 19,20 Lysine, genetic resources in cereals and, 92,99, 102 M

Maize forage tree legumes and, 49 genetic manipulation and, 135, 144, 145 multilocation trials and, 73, 75, 79 nitrogen fixation by legumes and contribution to production, 196, 197, 199 enhancement, 216 production systems, 182, 184 Maruca testulalis, genetic manipulation and, 139-141, 149 Megalurothrips sjostedti, genetic manipulation and, 139, 140 Meiosis, Gossypium and, 231,232,246 Mildew cowpea and, 144 genetic resources in cereals and, 90,94, 96, 100 wheat resistance to Sepioria and, 273

287

INDEX Millet genetic manipulation and, 135 multilocation trials and, 67 nitrogen fixation by legumes and, 182 Mimosine toxicity, forage tree legumes and, 35,36 Mineralization, nitrogen fixation by legumes and, 162, 191, 192, 197, 198 Mitochondria, cowpea and, 146, 147 Mitosis, cowpea and, 144, 145, 147 Models, root growth, see Root growth models Moisture cowpea and, 136 forage tree legumes and, 30,42 genetic resources in cereals and, 97 nitrogen fixation by legumes and, 182, 197 root growth models and, 130 time of seedling emergence and, 3-6, 8,9 wheat resistance to Septoria and, 266 Moisture stress forage tree legumes and, 36 nitrogen fixation by legumes and, 214 Monocotyledons cowpea and, 148 time of seedling emergence and, 6 Monosomes Gossypium and, 246,247 wheat resistance to Septoria and, 271 Monotelodisomes, Gossypium and, 246, 247 Morphology cowpea and, 145 genetic resources in cereals and, 88.91, 92,94-96,98-100, 104 Gossypium and, 231,241-244,246-249 multilocation trials and, 75 nitrogen fixation by legumes and, 166 root growth models and, 120, 130 time of seedling emergence and, 17-19 Mortality root growth models and, 128 time of seedling emergence and, 2, 20 Multilocation trials, 55, 56, 80-82 AMMI analysis, 76-80 crossover interactions, 68-70 genetic resources in cereals and, I 0 4 joint linear regression limitation, 61-65

risk, 67,68 yield stability, 65, 66 multivariate analyses, 70, 71 cluster analysis, 75,76 factor analysis, 75 principal components, 71-74 principal coordinates, 74,75 variance, 57 components, 59-61 limitations, 58, 59 Multiple linear regression model, multilocation trials and, 80 Multivariate analysis genetic resources in cereals and, 91 multilocation trials and, 70-76 Mutagenesis, nitrogen fixation by legumes and, 206 Mutation cowpea and, 145 Gossypium and, 233,245, 246 nitrogen fixation by legumes and, 207 wheat resistance to Septoria and, 272

N

Natural selection, genetic resources in cereals and, 100 Necrosis, wheat resistance to Septoria and genetics, 271 identification, 260, 261, 263-265 pathogen variation, 269 New squares, multilocation trials and, 60 Nitrate, fixation by legumes and assessment, 168-171, 175, 176 enhancement, 202,204,212-215 Nitrate reductase, fixation by legumes and, 207 Nitrate reduction, fixation by legumes and, 168, 169 Nitrate tolerance, fixation by legumes and, 206-210 Nitrogen cowpea and, 134, 135 forage tree legumes and, 41,42,50 animal feed, 34, 35 management, 43 nitrogen recycling, 46-49 nitrogen yields, 45,46 species, 28, 29 multilocation trials and, 72, 73

288

INDEX

root growth models and, 124, 128-130 time of seedling emergence and, 4, 18 Nitrogen fixation cowpea and, 133, 135 forage tree legumes and, 28,29,34,42, 46,48 by legumes, 156-158,216 acetylene reduction assay, 174, 175 balance, 174 crops, 191-200 direct transfer, 190, 191 enhancement, 202-2 16 fertilizer, 175, 176 isotopic techniques, 158-165 livestock, 200-202 N-difference method, 165, 166 nodules, 176, 177 production, 177-190 ureide method, 167-173 Nitrogenase, fixation by legumes and, 174, 175 Nodulation cowpea and, 134 nitrogen fixation by legumes and, 156, 157 assessment, 165, 167-170, 173, 175-1 77 contribution to production, 191-193 enhancement, 202,204-208,211-214 Nopaline synthase promoter, cowpea and, 148 Nucleotides genetic resources in cereals and, 93 Gossypium and, 234 Nucleus cowpea and, 146, 147 Gossypium and, 253 Nutrient uptake, root growth models and, 113, 117, 126, 127 Nutrition forage tree legumes and, 28, 30.41 Gossypium and, 247 nitrogen fixation by legumes and, 156, 172, 177, 184, 204 root growth models and, 128 0

Onion, time of seedling emergence and, 4 , 6

Ootheca mutabilis, genetic manipulation and, 139-141 Osmotic effects, time of seedling emergence and, 4 , 6 , 7 Oxygen nitrogen fixation by legumes and, 175 root growth models and, 129 time of seedling emergence and, 3 Oxygen diffusion rate root growth models and, 123 time of seedling emergence and, 3

P Panicurn maximum, forage tree legumes and, 33, 35,42 Partitioning nitrogen fixation by legumes and, 173, 191,206 root growth models and, 122, 123, 128, 129 time of seedling emergence and, 16 Pathogens cowpea and, 141, 142, 149 root growth models and, 114 wheat resistance to Septoria and, 274 identification, 258,259,262, 263,267 variation, 268-270 Pennisetum, forage tree legumes and, 32, 33,42 Peroxide, time of seedling emergence and, 3

PH cowpea and, 146 forage tree legumes and, 30 root growth models and, 123 Phaseolae, cowpea and, 134, 141 Phaseolastrae, cowpea and, 135, 144 Phaseolinae, cowpea and, 135, 144, 146 Phaseolus, genetic manipulation and, 148 Phaseolus vulgaris, genetic manipulation and, 146 Phenotype genetic resources in cereals and, 90,95, 96, 104 Gossypium and, 252 nitrogen fixation by legumes and, 206 Phosphorus forage tree legumes and, 41 root growth models and, 124

289

INDEX time of seedling emergence and, 4 Photosynthate, root growth models and, 127, 128 Photosynthesis root growth models and, 117, 125 time of seedling emergence and, 9, 16, 17,28 wheat resistance to Septoria and, 268 Physiology cowpea and, 142 genetic resources in cereals and, 91, 98, 100

multilocation trials and, 80, 82 nitrogen fixation by legumes and, 172 root growth models and, 113, 114, 118, I19 time of seedling emergence and, 15 wheat resistance to Septoria and, 268, 269 Phytoalexins, cowpea and, 142 Planlago, time of seedling emergence and, 16, 19 Plasmogamy, cowpea and, 146, 147 Ploidy cowpea and, 145 genetic resources in cereals and, 92.93, 95,96,99, 100 Gossypium and, 253 Point mutation, cowpea and, 145 Polyacrylamide gel electrophoresis, genetic resources in cereals and, 92.98 Polymorphism, genetic resources in cereals and, 89,95 Population cowpea and, 142, 144, 145, 147 forage tree legumes and, 46 Gossypium and, 232,238,240,242, 243, 247-249,253 multilocation trials and, 65, 72 nitrogen fixation by legumes and, 156, 202,209,210,213,216 time of seedling emergence and, see Seedling emergence, time of Potassium, root growth models and, 126 Potato genetic manipulation and, 144, 145, 149, 150 root growth models and, 128 Predictive criteria, multilocation trials and, 56,77-80,82

Primary evaluation, genetic resources in cereals and, 88.89 Principal components analysis, multilocation trials and, 71-74, 76, 80-82 Principal components axes, multilocation trials and, 73,77-80 Principal coordinates analysis, multilocation trials and, 71, 74, 75 Protein cowpea and, 135, 138 forage tree legumes and, 28,35,36, 41,46 genetic resources in cereals and, 88, 92, 93,96,97,99-102 Gossypium and, 226, 247 nitrogen fixation by legumes and, 156, 177, 178, 184,202 Protoplast, cowpea and, 142-144, 146-148 Pycnidia, wheat resistance to Septoria and identification, 260, 262, 264-266 pathogen variation, 268-270

Q Qualitative interactions, multilocation trials and, 68 Quantitative interactions, multilocation trials and, 68 Quantitative traits, genetic resources in cereals and, 92

R Rain Forest Belt, cowpea and, 135, 138, 139, 141, 145, 149 Rainfall cowpea and, 135, 137 Gossypium and, 237,244 nitrogen fixation by legumes and, 213 root growth models and, 114 Reciprocal average, multilocation trials and, 80 Reciprocal crosses, wheat resistance to Septoria and, 264 Recombination cowpea and, 145, 147 genetic resources in cereals and, 98 Gossypium and, 242, 247, 249,251

290

INDEX

Recycling, forage tree legumes and, 46 Regrowth, forage tree legumes and, 40, 42-44 Relative efficiency, nitrogen fixation by legumes and, 206 Relative growth rate, time of seedling emergence and, 14, I5 Replicates genetic resources in cereals and, 89, 91,97 multilocation trials and, 56, 57, 76,77 Resistance cowpea and, 139, 141, 144, 148-150 genetic resources in cereals and, 88.94, 97-99 Gossypium and, 236,245,252 of wheat to Septoria, see Wheat resistance to Septoria Respiration root growth models and, 122, 123, 127- I29 time of seedling emergence and, 16, 18 Restricted maximum likelihood, multilocation trials and, 60, 61 Restriction fragment length polymorphism genetic resources in cereals and, I 0 6 wheat resistance to Seproria and, 214 Rhizobia, nitrogen fixation by legumes and, 202-205,207,210,212, 213 Rhizobium cowpea and, 134 nitrogen fixation by legumes and, 172, 175,206,210-213 Rhizosphere, root growth models and, 113, 126, 127 Rhizotron, root growth models and, 115, 116, 123 Rice genetic manipulation and, 144 genetic resources in cereals and, 87 nitrogen fixation by legumes and, 163, 182, 187, 198, 199 Risk, multilocation trials and, 67 Root cowpea and, 142 elongation rate, root growth models and, 124, 125 forage tree legumes and, 36,47 genetic resources in cereals and, 107 length density, 114, 116-1 18, 122, 123

nitrogen fixation by legumes and assessment, 160, 166, 167, 175, 176 contribution to production, 191-193, 197 enhancement, 204,207 production systems, 187 sink, 114, 126 time of seedling emergence and, I 1 Root growth models, 113, 114 components classification, 118-121 parameters, 120, 122, 123 soil, 123-125 uptake functions, 125-127 early models, 114, 115 existing models, 128-130 features, 115-1 18 limitations, 130, 131 Rotation forage tree legumes and, 34 nitrogen fixation by legumes and, 193, 197,21I , 216 Rust genetic resources in cereals and, 94, 98,99 Gossypium and, 252 wheat resistance to Septoria and, 259, 272,213 5

Salinity, genetic resources in cereals and, 91.97 Sand, root growth models and, 129 SDS-PAGE, genetic resources in cereals and, 101 Seed cowpea and, 134, 138, 139 genetic resources in cereals and, 88,90 Gossypium and, 227,228 collection, 235, 237,239, 243 evaluation, 248, 250 nitrogen fixation by legumes and, 156, 157 contribution to production, 191, 193-195, 197, 198 enhancement, 204,208,209,212,214, 215 wheat resistance to Septoria and, 261, 264

INDEX Seedling emergence, time of, 1 , 2, 20, 21 factors, 2,3, 8, 9 seed attributes, 6-8 sowing depth, 6 temperature, 4 , 5 water, 3 , 4 importance of variation, 9, 10 longevity, 19, 20 organ composition, 17-19 partitioning, 16, 17 total plant growth, 10-15 Selection cowpea and, 143, 145 nitrogen fixation by legumes and, 205, 206,209 wheat resistance to Septoria and, 268, 269, 272-274 Septoria nodorum, wheat resistance to, 257,268-270,272-274 Septoria nodorum blotch, wheat resistance to, 257,258,272 genetics, 271 identification, 259-264,267, 268 pathogen variation, 268, 269 Septoria tritici genetic resources in cereals and, 91 wheat resistance to, 258, 272-274 genetics, 270, 272 identification, 260, 263 pathogen variation, 269, 270 Septoria tritici blotch, wheat resistance to, 257,258,272 genetics, 270-272 identification, 259-262, 267, 268 pathogen variation, 269, 270 Sesbania, forage tree legumes and, 29 Sesbania cannabina, forage tree legumes and, 45 Sesbania formosa, forage tree legumes and, 30 Sesbania grandifiora, forage tree legumes and, 35, 38,40,45,47 Sesbania sesban, forage tree legumes and, 30, 38,41,45 Seteria, forage tree legumes and, 32, 35 Sexual incompatibility, cowpea and, 145, 146 Shading multilocation trials and, 57 nitrogen fixation by legumes and, 184

29 1

Soil cowpea and, 134-136 forage tree legumes and, 47,49 animal feed, 36 management, 41-43 nitrogen yields, 46 performance, 30 genetic resources in cereals and, 91 nitrogen fixation by legumes and, 156, 157,216 assessment, 158-166, 174-177 contribution to production, 191, 193, 197, 198,200,201 enhancement, 202,204,208-210, 212-21 6 production systems, 182, 187, 190 root growth models and, 113-1 15, 128-1 30 components, 118, 120, 122-127 features, 116, 117 time of seedling emergence and, 3.4, 6-9 Soil moisture forage tree legumes and, 30 nitrogen fixation by legumes and, 213 Somaclonal variation, cowpea and, 143-145, 147 Somatic crossover, cowpea and, 145 Somatic hybridization, cowpea and, 143-148 Sorghum genetic manipulation and, 135, 144 nitrogen fixation by legumes and, 182 Sowing cowpea and, 137 forage tree legumes and, 38 nitrogen fixation by legumes and, 200, 204,209,210 time of seedling emergence and, 4,6,9, 10, 14, 17, 20 Soybean multilocation trials and, 72-74,77-79 nitrogen fixation by legumes and, 156, 157 assessment, 163, 165, 170, 171, 173 contribution to production, 193, 194, 196, 197 enhancement, 202,204,207,208, 212-215 production systems, 176, 178-182, 184

292

INDEX

root growth models and, 117 Specific combining ability, wheat resistance to Septoria and, 264, 265, 27 1 Spore production, wheat resistance to Septoria and, 258,259,262-268 Statistical analysis of multilocation trials, see Multilocation trials Sterility, Gossypium and, 247,253 Stress genetic resources in cereals and, 88,91, 96, 100, 106 Gossypium and, 236 multilocation trials and, 80 nitrogen fixation by legumes and, 175 root growth models and, 128, 130 Subterranean clover, time of seedling emergence and, 9, 10 Subtropical agriculture, nitrogen fixation by legumes and, see Nitrogen fixation by legumes Sugar cane, genetic manipulation and, 144, 145, 150 Sum of squared difference, multilocation trials and, 77,78 Suppression, time of seedling emergence and, 17, 18 Survival Gossypium and, 247 time of seedling emergence and, 19, 20 Susceptibility, wheat resistance to Septoria and, 273 genetics, 270-272 identification, 258-262, 264,265 pathogen variation, 269,270 Symbiosis cowpea and, 134 forage tree legumes and, 46,48, 50 nitrogen fixation by legumes and, 156, 157

assessment, 158, 161, 165, 169, 173, 175, 176 enhancement, 206-21 1 production systems, 179 Synchrony cowpea and, 138 time of seedling emergence and, 6 , 9 , 2 0 Systematic evaluation, genetic resources in cereals and, 89

T

Taxonomy cowpea and, 135, 136 genetic resources in cereals and, 97 Gossypium and, 229,236,239,242 Telocentrics, Gossypium and, 246, 247 Temperature forage tree legumes and, 48 genetic resources in cereals and, 97, 103 nitrogen fixation by legumes and, 197, 213 root growth models and, 123-125, 128- 130 time of seedling emergence and, 3-6, 16 wheat resistance to Septoria and, 266 Thrips, cowpea and, 139, 140, 149 Tillage, nitrogen fixation by legumes and, 177,213-216 Tissue culture technology, cowpea and, 142-149 Tobacco cowpea and, 146, 147 time of seedling emergence and, 7 Tolerance genetic resources in cereals and, 96 Gossypium and, 227 nitrogen fixation by legumes and, 208 wheat resistance to Septoria and, 258, 259,261,267,272 Totipotency, cowpea and, 142, 143 Toxicity, cowpea and, 135, 145 Transformation cowpea and, 143-145, 148, 149 nitrogen fixation by legumes and, 197 Transgression, wheat resistance to Septoria and, 271 Translocation, Gossypium and, 232,233, 246 Transpiration forage tree legumes and, 42 nitrogen fixation by legumes and, 170 root growth models and, I18 Tree legumes, forage, see Forage tree legumes Triticum genetic resources in cereals and, 98-101 wheat resistance to Septoria and, 260, 261,263,269,270

293

INDEX Triticum aestivum genetic resources in cereals and, 91,92 wheat resistance to Septoria and, 257, 260 Triticum dicoccoides, genetic resources in cereals and, 97-99, 101 Tropical agriculture, nitrogen fixation by legumes and, see Nitrogen fixation by legumes Tropical environments forage tree legumes and, see Forage tree legumes Gossypium and, 244 multilocation trials and, 79 Turgor pressure, root growth models and, 123, 124, 129 U

United States Department of Agriculture genetic resources in cereals and, 90, 92-94, 105 Gossypium and, 235,237-241,243,244 Ureide method, nitrogen fixation by legumes and assessment, 167-173, 177 enhancement, 202,209,210,215 V

Variability cowpea and, 144, 147 genetic resources in cereals and, 88,89, 91-101, 104-106 Vigna unguiculata, see Cowpea Virulence Gossypium and, 252 wheat resistance to Septoria and, 268-270 Virus, cowpea and, 136, 138, 148 W

Water forage Cree legumes and, 46 nitrogen fixation by legumes and, 165, 182.204

root growth models and, 113-115, 128-130 classification, 118, 119 soil, 124, 125 time of seedling emergence and, 2-4, 7-9 Weeds cowpea and, 136 genetic resources in cereals and, 96 nitrogen fixation by legumes and, 184, 186, 187 time of seedling emergence and, 14, 15 Weighted average, multilocation trials and, 80 Wheat genetic manipulation and, 144, 149 genetic resources in cereals and, 87, 89-93,95-101, 103 multilocation trials and, 75 nitrogen fixation by legumes and, 182 resistance to Septoria and, 257,258, 272-274 assessment, 259-261 components, 262-266 genetics, 270-272 identification, 258,259 pathogen variation, 268-270 sources, 272 yield reduction, 267,268 root growth models and, 120, 121, 125, 128 time of seedling emergence and, 3 X

Xylem nitrogen fixation by legumes and assessment, 167-173 enhancement, 202,208-210 root growth models and, 130 Y

Yield cowpea and, 138, 140, 141, 143, 149 forage tree legumes and, 31,33,34, 37-50

294 genetic resources in cereals and, 87, 90,97 multilocation trials and, 55, 56, 81 AMMI analysis, 76, 77 joint linear regression, 61,63-68 multivariate analyses, 75

INDEX variance, 58,60 nitrogen fixation by legumes and, 166, 176, 182, 198,200,208,213-215 time of seedling emergence and, 14 wheat resistance to Septoria and, 261, 267,268,270

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