Water Properties in Food, Health, Pharmaceutical and Biological Systems: ISOPOW 10

WATER PROPERTIES IN FOOD, HEALTH, PHARMACEUTICAL AND BIOLOGICAL SYSTEMS: ISOPOW 10 Edited by DAVID S. REID TANABOON SA...

Author: David S. Reid | Tanaboon Sajjaanantakul | Peter J. Lillford | Sanguansri Charoenrein

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WATER PROPERTIES IN FOOD, HEALTH, PHARMACEUTICAL AND BIOLOGICAL SYSTEMS: ISOPOW 10

Edited by DAVID S. REID TANABOON SAJJAANANTAKUL PETER J. LILLFORD SANGUANSRI CHAROENREIN

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P A John Wiley & Sons, Inc., Publication

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Edited by DAVID S. REID TANABOON SAJJAANANTAKUL PETER J. LILLFORD SANGUANSRI CHAROENREIN

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Edition first published 2010 © 2010 Blackwell Publishing Chapter 18 and 28 copyrights held by Anne-Marie Hermansson. Blackwell Publishing was acquired by John Wiley & Sons in February 2007. Blackwell’s publishing program has been merged with Wiley’s global Scientific, Technical, and Medical business to form Wiley-Blackwell. Editorial Office 2121 State Avenue, Ames, Iowa 50014-8300, USA For details of our global editorial offices, for customer services, and for information about how to apply for permission to reuse the copyright material in this book, please see our website at www.wiley.com/ wiley-blackwell. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by Blackwell Publishing, provided that the base fee is paid directly to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For those organizations that have been granted a photocopy license by CCC, a separate system of payments has been arranged. The fee codes for users of the Transactional Reporting Service are ISBN-13: 978-0-8138-1273-1/2010. Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought. Library of Congress Cataloguing-in-Publication Data International Symposium on the Properties of Water (10th : 2007 : Bangkok, Thailand) Water properties in food, health, pharmaceutical and biological systems : ISOPOW 10 / edited by David Reid, Tanaboon Sajjaanantakul, et al. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-8138-1273-1 (alk. paper) ISBN-10: 0-8138-1273-9 (alk. paper) 1. Food–Water activity–Congresses. 2. Food–Moisture–Congresses. 3. Pharmaceutical chemistry– Congresses. I. Reid, David. II. Sajjaanantakul, Tanaboon. III. Title. TX553.W3I57 2007 664–dc22 2008054012 A catalog record for this book is available from the U.S. Library of Congress. Set in 10/12 pt Times by Toppan Best-set Premedia Limited Printed in Singapore Disclaimer The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation warranties of fitness for a particular purpose. No warranty may be created or extended by sales or promotional materials. The advice and strategies contained herein may not be suitable for every situation. This work is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional services. If professional assistance is required, the services of a competent professional person should be sought. Neither the publisher nor the author shall be liable for damages arising herefrom. The fact that an organization or Website is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Website may provide or recommendations it may make. Further, readers should be aware that Internet Websites listed in this work may have changed or disappeared between when this work was written and when it is read. 1

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Table of Contents

Preface Editorial Note Acknowledgments Contributors PART 1 Session 1:

Invited Speakers and Oral Presentations Water Mobility/Dynamics and Its Application in Food and Pharmaceutical Systems

xiii xv xvii xix 3

5

Invited Speakers 1. Complementary Aspects of Thermodynamics, Nonequilibrium Criteria, and Water Dynamics in the Development of Foods and Ingredients M. P. Buera 2. Water Mobility in Solid Pharmaceuticals as Determined by Nuclear Magnetic Resonance, Isothermal Sorption, and Dielectric Relaxation Measurements S. Yoshioka and Y. Aso

9

25

Oral Presentations 3. The Effect of Water and Fat Contents on the Enthalpy of Dissolution of Model Food Powders: A Thermodynamic Insight A. Marabi, A. Raemy, A. Burbidge, R. Wallach, and I. S. Saguy

41

4. “Solvent Water” Concept Simplifies Mathematical Modeling in Fermenting Dough, a Multiphase Semisolid Food S. M. Loveday and R. J. Winger

49

5. Microdomain Distribution in Food Matrices: Glass Transition Temperature, Water Mobility, and Reaction Kinetics Evidence in Model Dough Systems Y. Kou

59

v

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Table of Contents

Session 2: Water Essence and the Stability of Food and Biological Systems

67

Invited Speakers 6. Effect of Combined Physical Stresses on Cells: The Role of Water J.-M. Perrier-Cornet, M. Moussa, H. Simonin, L. Beney, and P. Gervais 7. Soft Condensed Matter: A Perspective on the Physics of Food States and Stability T. P. Labuza, T. J. Labuza, K. M. Labuza, and P. S. Labuza 8. Antiplasticization of Food Polymer Systems by Low Molecular Mass Diluents C. C. Seow

71

87

115

Oral Presentations 9. Freeze Drying of Lactobacillus coryniformis Si3: Focus on Water Å. Schoug, J. Schnürer, and S. Håkansson

141

10. Water-Sorption Properties and Stability of Inclusion Complexes of Thymol and Cinnamaldehyde with β-Cyclodextrins P. A. Ponce, M. P. Buera, and B. E. Elizalde

149

11. Beyond Water: Waterlike Functions of Other Biological Compounds in a Waterless System B. R. Bhandari

157

12. Water Sorption and Transport in Dry, Crispy Bread Crust M. B. J. Meinders, N. H. van Nieuwenhuijzen, R. H. Tromp, R. J. Hamer, and T. van Vliet

165

13. Water State and Distribution During Storage of Soy Bread with and without Almond A. Lodi and Y. Vodovotz

175

14. Phase Separation of Ice Crystals in Starch-Based Systems During Freezing and Effects on Moisture Content and Starch Glass Transition T. Tran, K. Piyachomkwan, and K. Sriroth

185

15. Carrot Fiber as a Carrier in Spray Drying of Fructose K. Cheuyglintase and K. R. Morison

191

Session 3:

199

Microstructured and Nanostructured Changes in Food

Invited Speakers 16. Taking the Measure of Water D. S. Reid

203

Table of Contents

17. Rehydration Modeling of Food Particulates by Using Principles of Water Transport in Porous Media I. S. Saguy, O. Troygot, A. Marabi, and R. Wallach 18. Protein Hydration in Structure Creation P. J. Lillford and A.-M. Hermansson

vii

219 237

19. Water Partitioning in Colloidal Systems as Determined by Nuclear Magnetic Resonance P. Chinachoti and P. Chatakanonda

251

20. Physical Changes in Confectionery Products Caused by the Availability of Water, with a Special Focus on Lactitol Crystallization M. H. Lim, B. Lampen, L. F. Siow, and T. Rades

271

Oral Presentations 21. Entrapment of Probiotic Bacteria in Frozen Cryoprotectants and Viability in Freeze Drying Y. H. Roos and K. S. Pehkonen

285

22. Fracture Behavior of Biopolymer Films Prepared from Aqueous Solutions 291 I. Yakimets, S. S. Paes, N. Wellner, and J. R. Mitchell Session 4:

Biomaterial Sciences: Water in Stability and Delivery of Active Biomolecules

297

Invited Speakers 23. The Plasticization-Antiplasticization Threshold of Water in Microcrystalline Cellulose: A Perspective Based on Bulk Free Volume S. P. Chamarthy, F. X. Diringer, and R. Pinal 24. Understanding the Role of Water in Nonaqueous Pharmaceutical Systems B. D. Anderson, S. S. Rane, and T.-X. Xiang

301 315

25. Crystallization, Collapse, and Glass Transition in Low-Water Food Systems Y. H. Roos

335

26. Carbohydrates in Amorphous States: Molecular Packing, Nanostructure, and Interaction with Water J. Ubbink

353

27. Ice Crystallization in Gels and Foods Manipulated by the Polymer Network N. Murase, S. Yamada, and N. Ijima

373

28. Marine-Inspired Water-Structured Biomaterials A.-M. Hermansson, P. Olofsson, S. Ekstedt, M. Pihl, and P. Gatenholm

385

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Table of Contents

PART 2 Poster Presentations

397

Session 5: Role of Water Mobility/Dynamics in Food and Pharmaceutical Systems

399

29. Another Unusual Property of Water: It Increases the Glass Transition Temperature of a Glassy Polymer S. P. Chamarthy and R. Pinal

401

30. Molecular Mobility Interpretation of Water-Sorption Isotherms of Food Materials by Means of Gravimetric Nuclear Magnetic Resonance W. P. Weglarz, M. Witek, C. Inoue, H. Van As, and J. van Duynhoven

411

31. Kinetics of Enthalpy Relaxation in Corn Syrup–Sucrose Mixtures B. R. Bhandari and R. W. Hartel 32. Development of a Novel Phase Transition Measurement Device for Solid Food Materials: Thermal Mechanical Compression Test (TMCT) Y. Liu, P. Intipunya, T. T. Truong, W. Zhou, and B. R. Bhandari

419

429

33. Proton Nuclear Magnetic Resonance Studies of Molecular Mobility in Potato Systems in Relation to Nonenzymatic Browning N. C. Acevedo, C. Schebor, and M. P. Buera

437

34. Nonenzymatic Browning Reaction and Enthalpy Relaxation of Glassy Foods K. Tsuji, K. Kawai, M. Watanabe, and T. Suzuki

445

35. Film-Forming Ability of Duck Egg White and Its Water-Vapor Barrier Property W. Garnjanagoonchorn, A. Yimjaroenpornsakul, N. Poovarodom, and S. Praditdoung 36. Water-Vapor Permeability of Chitosan and Methoxy Poly(ethylene glycol)-b-poly(ε-caprolactone) Blend Homogeneous Films N. Niamsa, N. Morakot, and Y. Baimark 37. Ice Formation in Concentrated Aqueous Glucose Solutions P. Thanatuksorn, K. Kajiwara, N. Murase, and F. Franks

453

459 465

38. Effects of Sodium and Potassium Ions on the Viscosities in the Sodium/Potassium-Glucose-Water Ternary System M. Soga, K. Kurosaki, and K. Kajiwara

473

39. Comparison of Water Sorption and Crystallization Behaviors of Freeze-Dried Lactose, Lactitol, Maltose, and Maltitol K. Jouppila, M. Lähdesmäki, P. Laine, M. Savolainen, and R. A. Talja

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40. Sorption Behavior of Extruded Rice Starch in the Presence of Glycerol J. Enrione, S. Hill, J. R. Mitchell, and F. Pedreschi 41. Water State and Mobility Affect the Mechanical Properties of Coffee Beans P. Pittia, G. Sacchetti, P. Rocculi, L. Venturi, M. Cremonini, and M. Dalla Rosa

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483

491

42. Effect of Water Activity on the Release Characteristics of Encapsulated Flavor A. Soottitantawat, H. Yoshii, and T. Furuta

499

43. Water and Protein Modifier Effects on the Phase Transitions and Microstructure of Mung-Bean Starch Granules P. Hongsprabhas and K. Israkarn

507

44. Evaluation of the Disintegration and Diffusion of Pharmaceutical Solid Matrices by Image Processing and Nonlinear Dynamics D. I. Téllez-Medina, A. Ortíz-Moreno, J. J. Chanona-Pérez, L. Alamilla-Beltrán, and G. F. Gutiérrez-López

Session 6:

Properties and Stability of Food and Biological Systems

515

523

45. Effect of Water Content on Physical Properties of Potato Chips F. Pedreschi and P. Moyano

525

46. Predicting Water Migration in Starchy Food During Cooking S. Thammathongchat, M. Fukuoka, T. Hagiwara, T. Sakiyama, and H. Watanabe

533

47. Nonenzymatic Browning May Be Inhibited or Accelerated by Magnesium Chloride According to the Level of Water Availability and Saccharide-Specific Interactions P. R. Santagapita, S. B. Matiacevich, and M. P. Buera

539

48. Combined Effect of Cinnamon Essential Oil and Water Activity on Growth Inhibition of Rhizopus stolonifer and Aspergillus flavus and Possible Application in Extending the Shelf Life of Bread S. Nanasombat, N. Piumnoppakun, D. Atikanbodee, and M. Rattanasuwan

545

49. From Water to Ice: Investigation of the Effect of Ice Crystal Reduction on the Stability of Frozen Large Unilamellar Vesicles L. F. Siow, T. Rades, and M. H. Lim

551

50. Does Microencapsulation Improve Storage Stability of Cloudberry (Rubus chamaemorus) Ellagitannins? P. Laine, P. Kylli, M. Heinonen, and K. Jouppila

563

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51. Nonenzymatic Browning Reaction of Glassy Foods: Characterization of Local Reactions Independent of the Glassy Matrix K. Kawai, T. Suzuki, and K. Kajiwara

571

52. Physical Properties of Protein-Carbohydrate Sheets Produced by a Twin-Screw Extruder R. A. Talja, K. S. Pehkonen, K. Jouppila, and Y. H. Roos

577

53. Thermal Transitions, Mechanical Properties, and Molecular Mobility in Cornflakes as Affected by Water Content A. Farroni, S. B. Matiacevich, S. Guerrero, S. Alzamora, and M. P. Buera 54. Texture of Glassy Tapioca-Flour–Based Baked Products as a Function of Moisture Content R. Kulchan, P. Suppakul, and W. Boonsupthip 55. Effects of Excipients on the Storage Stability of Freeze-Dried Xanthine Oxidase P. Srirangsan, K. Kawai, N. Hamada-Sato, M. Watanabe, and T. Suzuki 56. Water Properties in Bread Produced with an Innovative Mixer E. Curti, E. Vittadini, A. Di Pasquale, L. Riviera, F. Antoniazzi, and A. Storci 57. Evaluation of Deformation and Shrinking of Potato Slabs During Convective Drying R. Campos-Mendiola, C. Gumeta-Chávez, J. J. Chanona-Pérez, L. Alamilla-Beltrán, A. Jiménez-Aparicio, and G. F. Gutiérrez-López 58. Effects of Different Cut-Induced Microstructural and Macrostructural Arrays on Convective Drying of Agave atrovirens Karw C. Gumeta-Chávez, J. J. Chanona-Pérez, L. Alamilla-Beltrán, G. Calderón-Domínguez, A. Vega, P. Ligero, J. A. Mendoza-Pérez, and G. F. Gutiérrez-López 59. Study of White-Bread Structural Evolution by Means of Image Analysis and Associated Thermal History and Water-Loss Kinetics A. Pérez-Nieto, J. J. Chanona-Pérez, G. Calderón-Domínguez, R. Farrera-Rebollo, L. Alamilla-Beltrán, and G. F. Gutiérrez-López

583

591

599

605

613

619

627

60. Effect of Hydrothermal Treatment on the Rheological Properties of High-Amylose Rice Starch P. Khunae, T. Tran, and P. Sirivongpisal

635

61. Influence of Glass Transition on Oxygen Permeability of Starch-Based Edible Films D. Thirathumthavorn, S. Charoenrein, and J. M. Krochta

641

Table of Contents

62. Molecular Mobility and Seed Longevity in Chenopodium quinoa M. Castellión, S. Maldonado, and M. P. Buera 63. Analyzing the Effect of Freeze-Thaw Cycle on the Off-Aroma of Pineapple by Using an Electronic Nose Technique S. Charoenrein and T. Kaewtathip 64. Water Uptake and Solid Loss During Soaking of Milled Rice Grains P. Chatakanonda and K. Sriroth 65. Microstructural, Physical, and Rehydration Properties of Maltodextrin Powders Obtained by Spray Drying A. L. Muñoz-Herrera, V. Tejeda-Hernández, A. Jiménez-Aparicio, J. Welti-Chanes, J. J. Chanona-Pérez, L. Alamilla-Beltrán, and G. F. Gutiérrez-López 66. Nanostructures and Minimum Integral Entropy as Related to Food Stability L. A. Pascual-Pineda, E. Flores-Andrade, C. I. B. Guevara, L. Alamilla-Beltrán, J. J. Chanona-Pérez, E. Azuara-Nieto, and G. F. Gutiérrez-López Index

xi

647

657 663

673

681

689

Preface

Water plays an important role in the structure, functionality, and stability of food and biomaterials. The ubiquitous water molecules are small and simple, yet they possess unusual properties and develop complex interactions with surrounding molecules and compounds. An increasing understanding of water properties and their significance in interacting and regulating chemical and biological systems has led to in-depth research to better understand water ’s role in food structure and stability. Water-sorption isotherms of foods were first published in 1943, and the concept of water activity as a major control variable in food spoilage was introduced in 1953. ISOPOW—the International Symposium on the Properties of Water—was first organized in Glasgow, Scotland, in 1974 (see the Editorial Note for details) to promote the exchange of knowledge between scientists in the field of food science and scientists whose interests in water derived from different disciplines. Since then, ISOPOW has become an important focal point for scientific presentations and discussion on water properties, such as water activity, aqueous glass transitions, and water mobility as related to food, pharmaceutical, biological, and biomaterial systems. This volume is based on lectures, oral presentations, and posters presented at the 10th ISOPOW in Bangkok, Thailand, on 2–7 September 2007. The title Water Properties in Food, Health, Pharmaceutical and Biological Systems: ISOPOW 10 emphasizes the context of research findings presented at the symposium. Part 1 of the book is from full manuscripts of invited lectures and oral presentations and is divided into four sessions. Session 1 deals with water dynamics and its application in food and pharmaceutical systems, with some examples in food powders and dough systems. Session 2 involves water and its influence on food and biological systems. Soft condensed matter, antiplasticization of food polymers, and physical stress on cells are among the topics presented. Session 3 examines the microstructured and nanostructured changes in food, including the measurement of water properties, rehydration modeling of food particulates, water in colloids, and examples of water ’s effects in confectionary products. Session 4 discusses biomaterial science aspects of water, such as its properties considered by bulk free volume concepts and its role in nonaqueous pharmaceutical systems. The behavior of water in phase transition, molecular packing, and nanostructure in food systems, along with water in structured biomaterials (as elucidated by marine jellyfish), is discussed in the session. Part 2 of the book has been compiled from research posters presented at the symposium in two sessions. The role of water mobility/dynamics in various food products xiii

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Preface

and systems is presented in Session 5. Session 6 represents different aspects of current research on the understanding of chemical and physical changes in food and food stability control as affected by water. These two sessions reflect the vast array of investigations and applications of water worldwide. It is hoped that these proceedings will provide a useful reference on water, its properties, and applications to the scientific community according to the spirit of ISOPOW.

Editorial Note

ISOPOW (International Symposium on the Properties of Water) is a nonprofit scientific organization and a standing committee under the International Union of Food Science and Technology (IUFoST). The first ISOPOW was organized in Glasgow, Scotland, in 1974 through the initiative of Dr. Ron B. Duckworth and Dr. Louis Rockland. Their goals were to present the state of knowledge on water and its application in food science and related disciplines, to organize meetings and stimulate discussions between academic and industrial scientists, to bring together participants under conditions conducive to the greatest interactions, and to publish symposium proceedings of high scientific quality. In addition to food scientists, biological and pharmaceutical scientists have recognized that water plays an important role influencing structure, functionality, and stability of biomaterials. ISOPOW symposia always include delegates from other fields for cross-understanding and multidisciplinary approaches to the study of water. Each symposium provides multiple opportunities for speakers and participants to share perspectives, address challenges, and develop collaborations to advance understanding in the field of water properties. ISOPOW meetings, held in various locations, reflect the worldwide dimension of ISOPOW and the interdisciplinary characteristics of the subject. Most of the meetings have resulted in the publication of books of the proceedings. Previous ISOPOWs were ISOPOW 1 Glasgow, UK, 1974 ISOPOW 2 Osaka, Japan, 1978 ISOPOW 3 Beaune, France, 1983 ISOPOW 4 Banff, Canada, 1987 ISOPOW Practicum I Penang, Malaysia, 1987 ISOPOW 5 Peniscola, Spain, 1992 ISOPOW Practicum II Puebla, Mexico, 1994 ISOPOW 6 Santa Rosa, USA, 1996 ISOPOW 7 Helsinki, Finland, 1998 ISOPOW 8 Zichron Yaakov, Israel, 2000 ISOPOW 9 Mar del Plata, Argentina, 2004 The 10th ISOPOW’s success was based on strong support from the ISOPOW Central Committee. Members of the central committee at the time were: xv

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Editorial Note

Dr. David S. Reid, University of California, USA, President Dr. María del Pilar Buera, Universidad de Buenos Aires, Argentina, President-Elect Dr. Louis B. Rockland, FoodTech Research and Development, USA, Honorary President Dr. Imad A. Farhat, Firmenich, Switzerland Dr. Patrick Gervais, Université de Bourgogne, France Dr. Miang Hoong Lim, University of Otago, New Zealand Dr. David Lechuga-Ballesteros, Nektar Therapeutics, USA Dr. Jim Leslie, Consultant, UK Dr. Peter J. Lillford, University of York, UK Dr. Norio Murase, Tokyo Denki University, Japan Dr. Yrjö H. Roos, University College Cork, Ireland Dr. Tanaboon Sajjaanantakul, Kasetsart University, Thailand Dr. Denise Simatos, Université de Bourgogne, France Dr. Jorge Welti-Chanes, Universidad de las Américas, Mexico With suggestions and support from the Central Committee, the scientific program was formulated. The 10th ISOPOW in Bangkok, Thailand included 22 invited lectures from renowned food scientists, pharmacists, and physical chemists from academic and research institutions and related industries. From the abstracts submitted, 18 oral presentations were selected and 58 poster presentations were displayed for discussion. The symposium attracted 120 participants from 25 different countries worldwide. The participation of young scientists is one of the key successes in expanding the knowledge and enhancing the spirit of the ISOPOW meeting. For the 10th ISOPOW, the Central Committee has granted five travel bursaries to assist young scientists in presenting their findings at the symposium. The proceedings of the 10th ISOPOW are the product of the symposium, and all author contributions are thankfully acknowledged. The symposium was made possible by cosponsorship by the Thailand Commission on Higher Education, Kasetsart University, the ISOPOW Central Committee, the National Science and Technology Development Agency (Thailand), the Thailand Convention and Exhibition Bureau, Nestlé (Thai) Ltd., and several international and Thai food industry allies, detailed in the 10th ISOPOW book of abstracts published by the Department of Food Science and Technology, Kasetsart University, at the time of the symposium. David S. Reid Tanaboon Sajjaanantakul Peter J. Lillford Sanguansri Charoenrein

Acknowledgments

It is our pleasure to acknowledge the ISOPOW Central Committee, all session chairpersons, and the local scientific committee for their efforts in reviewing the scientific program and the proceedings. Special thanks are due to Dr. Denise Simatos, Dr. Pilar Buera, Dr. David Reid, and Dr. Peter Lillford for valuable suggestions early in the preparation for ISOPOW 10. Appreciation also goes to all local organizing committees, particularly faculty members and staff of the Department of Food Science and Technology, Kasetsart University, for their due diligence in activities required for the success of the symposium. Kasetsart Food Science’s undergraduate and graduate students provided symposium attendees with a warm welcome and outstanding hospitality. The students’ liveliness and eagerness contributed to a pleasant atmosphere that promoted interaction among the symposium participants. We express our gratitude to Dr. Sanguansri Charoenrein, Dr. Utai Klinkesorn, Dr. Parichat Hongsprabhas, Miss Wasaporn Chanput, and Miss Kunwadee Kaewka of the Department of Food Science and Technology, Kasetsart University, for their assistance in preparation of manuscripts for this volume. Finally, the Central Committee congratulates the local organizers, lead by Dr. Tanaboon Sajjaanantakul, for a delightful, stimulating meeting.

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Contributors

Acevedo, Nuria Cristina Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Alamilla-Beltrán, Liliana Departamento de Ingeniería, Bioquímica y Graduados en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politénico Nacional, México City, México Alzamora, Stella Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Anderson, Bradley D. Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, Kentucky, USA Antoniazzi, F. Food Science and Technology, Department of Industrial Engineering, University of Parma, Parma, Italy Aso, Yukio National Institute of Health Sciences, Tokyo, Japan

Atikanbodee, Dusita Department of Applied Biology, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand Azuara-Nieto, Ebner Instituto de Ciencias básicas, Universidad Veracruzana, Xalapa, Vercruz, México Baimark, Yodthong Department of Chemistry, Faculty of Science, Mahasarakham University, Mahasarakham, Thailand Beney, Laurent Laboratoire de Génie des procédés Alimentaires et Biotechnologiques, ENSBANA, Université de Bourgogne, Dijon, France Bhandari, Bhesh R. School of Land, Crop, and Food Sciences, University of Queensland, Brisbane, Australia Boonsupthip, Waraporn Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand xix

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Contributors

Buera, María del Pilar Departamentos de Industrias y de Química Orgánica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Burbidge, A. Nestlé Research Center, Nestec Ltd., Lausanne, Switzerland Calderón-Domínguez, Georgina Departamento de Ingeniería, Bioquímica y Graduados en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politénico Nacional, México City, México Campos-Mendiola, R. Escuela Nacional de Ciencias Biológicas, Instituto Politénico Nacional, México City, México Castellión, Martina Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Chamarthy, Sai Prasanth Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, Indiana, USA; and Respiratory Product Development, Schering-Plough Research Institute, Summit, New Jersey, USA Chanona-Pérez, Jose Jorge Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politénico Nacional, México City, México

Charoenrein, Sanguansri Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand Chatakanonda, Pathama Kasetsart Agricultural and AgroIndustrial Product Improvement Institute, Kasetsart University, Bangkok, Thailand Cheuyglintase, Kloyjai Rajamongala University of Technology Tunyaburi, Pathumtani, Thailand; and Department of Chemical and Process Engineering, University of Canterbury, Christchurch, New Zealand Chinachoti, Pavinee Faculty of Agro-Industry, Prince of Songkla University, Songkla, Thailand Cremonini, Mauro Department of Food Science, Alma Mater Studiorum, University of Bologna, Campus of Food Science, Cesena, Italy Curti, Elena Food Science and Technology, Department of Industrial Engineering, University of Parma, Parma, Italy Dalla Rosa, Marco Department of Food Science, Alma Mater Studiorum, University of Bologna, Campus of Food Science, Cesena, Italy

Contributors

Di Pasquale, A. Food Science and Technology, Department of Industrial Engineering, University of Parma, Parma, Italy

Flores-Andrade, Enrique Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México

Diringer, F. X. Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, Indiana, USA; and Faculté de Pharmacie, Université Louis Pasteur de Strasbourg, Srasbourg, France

Franks, Felix BioUpdate Foundation, London, UK

Ekstedt, S. SIK/Swedish Institute for Food and Biotechnology, Gothenburg, Sweden Elizalde, Beatriz E. Departamento de Industias, Facultad Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Enrione, Javier Departamento de Ciencia y Tecnologías de los Alimentos, Facultad Tecnológica, Universidad de Santiago de Chile, Santiago, Chile

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Fukuoka, Mika Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Furuta, Takeshi Department of Biotechnology, Tottori University, Tottori, Japan Garnjanagoonchorn, Wunwiboon Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand Gatenholm, Paul Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden

Farrera-Rebollo, R. Departamento de Ingeniería, Bioquímica y Graduados en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politénico Nacional, México City, México

Gervais, Patrick Laboratoire de Génie des procédés Alimentaires et Biotechnologiques, ENSBANA, Université de Bourgogne, Dijon, France

Farroni, Abel Instituto Nacional de Tecnología Agropecuaria, Pergamino, Pcia de Buenos Aires, Buenos Aires, Argentina

Guerrero, Sandra Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina

xxii

Contributors

Guevara, César Ignacio Beristain Instituto de Ciencias básicas, Universidad Veracruzana, Xalapa, Vercruz, México Gumeta-Chávez, Carolina Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Gutiérrez-López, Gustavo F. Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Hagiwara, Tomoaki Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Håkansson, Sebastian Department of Microbiology, Swedish University of Agricultural Sciences, Uppsala, Sweden

Heinonen, Marina Department of Applied Chemistry and Microbiology, University of Helsinki, Helsinki, Finland Hermansson, Anne-Marie SIK/Swedish Institute for Food and Biotechnology, Gothenburg, Sweden; and Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden Hill, Sandra Division of Food Sciences, School of Biosciences, University of Nottingham–Sutton Bonington Campus, Leicester, UK Hongsprabhas, Parichat Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand

Hamada-Sato, Naoko Course of Safety management in Food Supply Chain, Tokyo University of Marine Science and Technology, Tokyo, Japan

Ijima, Noriyuki Division of Life Science and Engineering, School of Science and Engineering, Tokyo Denki University, Saitama, Japan

Hamer, R. J. T.I. Food and Nutrition, Wageningen, The Netherlands; and TNO Quality of Life, Zeist, The Netherlands

Inoue, Chiharu Unilever Food and Health Research Institute, Vlaardingen, The Netherlands

Hartel, Richard W. Department of Food Science, University of Wisconsin, Madison, Wisconsin, USA

Intipunya, Pilairuk School of Land, Crop and Food Sciences, University of Queensland, Brisbane, Australia

Contributors

Israkarn, Kamolwan Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand Jiménez-Aparicio, Antonio Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Jouppila, Kirsi Department of Food Technology, University of Helsinki, Helsinki, Finland Kaewtathip, Thipthida Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand Kajiwara, Kazuhito School of Bionics, Tokyo University of Technology, Tokyo, Japan Kawai, Kiyoshi Department of Biofunctional Science and Technology, Graduate School of Biosphere Science, Hiroshima University, Hiroshima, Japan Khunae, Parida Department of Food Technology, Faculty of Agro-Industry, Prince of Songkla University, Songkhla, Thailand

xxiii

Kou, Yang General Mills, Inc., Riverside Technical Center, Minneapolis, Minnesota, USA Krochta, John M. Department of Food Science and Technology, University of California, Davis, California, USA Kulchan, Ratchaneewan Department of Packaging Technology, Faculty of Agro-Industry, Kasetsart University, Bangkok, Thailand Kurosaki, Kousuke School of Bionics, Tokyo University of Technology–Hachioji, Tokyo, Japan Kylli, Petri Department of Applied Chemistry and Microbiology, University of Helsinki, Helsinki, Finland Labuza, Katherine M. St. Paul Academy, St. Paul, Minnesota, USA Labuza, Peter S. St. Paul Academy, St. Paul, Minnesota, USA Labuza, Ted P. St. Paul Academy, St. Paul, Minnesota, USA Labuza, Theodore J. Department of Food Science and Nutrition, University of Minnesota, St. Paul, Minnesota, USA

xxiv

Contributors

Lähdesmäki, Maarit Department of Food Technology, University of Helsinki, Helsinki, Finland Laine, Pia Department of Food Technology, University of Helsinki, Helsinki, Finland Lampen, Ben Department of Food Science, University of Otago, Dunedin, New Zealand Ligero, Pablo Universidad de la Coruña, A Coruña, Spain Lillford, Peter J. Centre for Formulation Engineering, Chemical Engineering, University of Birmingham, Birmingham, UK Lim, Miang Hoong Department of Food Science, University of Otago, Dunedin, New Zealand Liu, Yeting Food Science & Technology Programme, National University of Singapore, Singapore Lodi, A. Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA

Loveday, Simon M. Riddet Institute, Massey University, Palmerston North, New Zealand Maldonado, Sara Departamento de Biodiversidad y Biología Experimental, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Marabi, Alejandro Nestlé Research Center, Nestec Ltd., Lausanne, Switzerland; and Institute of Biochemistry, Food Science and Nutrition, Faculty of Agricultural, Food and Environmental Quality Sciences, The Hebrew University of Jerusalem, Rehovot, Israel Matiacevich, Silvia Beatriz Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Meinders, Marcel B. J. T.I. Food and Nutrition, Wageningen, The Netherlands; and Wageningen University and Research Centre, Wageningen, The Netherlands Mendoza-Pérez, Jorge A. Secretaría de Marina México, México City, México Mitchell, John R. Division of Food Sciences, School of Biosciences, University of Nottingham–Sutton Bonington Campus, Leicester, UK

Contributors

xxv

Morakot, Nongnit Department of Chemistry, Faculty of Science, Mahasarakham University, Mahasarakham, Thailand

Olofsson, P. SIK/Swedish Institute for Food and Biotechnology, Gothenburg, Sweden

Morison, K. R. Department of Chemical and Process Engineering, University of Canterbury, Christchurch, New Zealand

Ortíz-Moreno, A. Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México

Moussa, Marwen Laboratoire de Génie des procédés Alimentaires et Biotechnologiques, ENSBANA, Université de Bourgogne, Dijon, France

Paes, Sabrina S. Division of Food Sciences, School of Biosciences, University of Nottingham–Sutton Bonington Campus, Leicester, UK

Moyano, Pedro Departamento de Ingeniería Química Universidad de Santiago de Chile, Santiago, Chile Muñoz-Herrera, Ana Laura Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Murase, Norio Division of Life Science and Engineering, School of Science and Engineering, Tokyo Denki University, Saitama, Japan Nanasombat, Suree Department of Applied Biology, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand Niamsa, Noi Department of Chemistry, Faculty of Science, Mahasarakham University, Mahasarakham, Thailand

Pascual-Pineda, Luz A. Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Pedreschi, Franco Pontificia Universidad Católica de Chile, Departmento de Ingeniería Química y Bioprocesos, Santiago, Chile Pehkonen, Kati S. Department of Food and Nutritional Sciences, University College Cork, Cork, Ireland Pérez-Nieto, A. Universidad de Guanajuato–Unidad de Estudios Superiores de Salvatierra, Salvatierra, México Perrier-Cornet, Jean-Marie Laboratoire de Génie des procédés Alimentaires et Biotechnologiques, ENSBANA, Université de Bourgogne, Dijon, France

xxvi

Contributors

Pihl, M. Department of Chemical and Biological Engineering, Chalmers University of Technology, Gothenburg, Sweden Pinal, Rodolfo Department of Industrial and Physical Pharmacy, Purdue University, West Lafayette, Indiana, USA Pittia, Paola Department of Food Science, University of Teramo, Teramo, Italy

Rades, Thomas School of Pharmacy, University of Otago, Dunedin, New Zealand Raemy, A. Nestlé Research Center, Nestec Ltd., Lausanne, Switzerland Rane, Sagar S. Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, Kentucky, USA

Piumnoppakun, Nattaya Department of Applied Biology, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

Rattanasuwan, Metavee Department of Applied Biology, Faculty of Science, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand

Piyachomkwan, Kuakoon Cassava and Starch Technology Research Unit, National Center for Genetic Engineering and Biotechnology, Kasetsart University, Bangkok, Thailand

Reid, David S. Department of Food Science and Technology, University of California, Davis, California, USA

Ponce, Peggy A. Departamento de Industias, Facultad Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Poovarodom, Ngamtip Department of Packaging Technology, Faculty of Agro-Industry, Kasetsart University, Bangkok, Thailand Praditdoung, Saisanom Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand

Riviera, Luca Storci Spa, Lemignano di Collecchio (PR), Italy Rocculi, Pietro Department of Food Science, Alma Mater Studiorum, University of Bologna, Campus of Food Science, Cesena, Italy Roos, Yrjö H. School of Food and Nutritional Sciences, University College Cork, Cork, Ireland Sacchetti, Giampiero Department of Food Science, University of Teramo, Teramo, Italy

Contributors

Saguy, I. Sam Institute of Biochemistry, Food Science and Nutrition, The Robert H. Smith Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel Sakiyama, Takaharu Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Santagapita, Patricio Román Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Savolainen, Marja Division of Pharmaceutical Technology, Faculty of Pharmacy, University of Helsinki, Helsinki, Finland Schebor, Carolina Departamento de Industrias, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina Schnürer, Johan Department of Microbiology, Swedish University of Agricultural Sciences, Uppsala, Sweden Schoug, Åsa Department of Microbiology, Swedish University of Agricultural Sciences, Uppsala, Sweden Seow, Chee Choon FoodTech Consultancy, Penang, Malaysia

xxvii

Simonin, Hélène Laboratoire de Génie des procédés Alimentaires et Biotechnologiques ENSBANA, Université de Bourgogne, Dijon, France Siow, Lee Fong Department of Food Science, University of Otago, Dunedin, New Zealand Sirivongpisal, Piyarat Department of Food Technology, Faculty of Agro-Industry, Prince of Songkla University, Songkhla, Thailand Soga, Makoto School of Bionics, Tokyo University of Technology–Hachioji, Tokyo, Japan Soottitantawat, Apinan Center of Excellence in Particle Technology, Department of Chemical Engineering, Chulalongkorn University, Bangkok, Thailand Srirangsan, Paveena Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Sriroth, Klanarong Cassava and Starch Technology Research Unit, National Center for Genetic Engineering and Biotechnology, Kasetsart University, Bangkok, Thailand; Kasetsart Agricultural and Agro-Industrial Product Improvement Institute, Kasetsart University, Bangkok, Thailand; and Department of Biotechnology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand

xxviii

Contributors

Storci, Alfio Storci Spa, Lemignano di Collecchio (PR), Italy Suppakul, Panuwat Department of Packaging Technology, Faculty of Agro-Industry, Kasetsart University, Bangkok, Thailand Suzuki, Toru Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Talja, Riku A. Department of Food Technology, University of Helsinki, Helsinki, Finland Tejeda-Hernández, Violeta Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Téllez-Medina, D. I. Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Thammathongchat, Savitree Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Thanatuksorn, Pariya School of Bionics, Tokyo University of Technology–Hachioji, Tokyo, Japan

Thirathumthavorn, Doungjai Department of Food Technology, Silpakorn University, Nakhon Pathom, Thailand Tran, Thierry Cassava and Starch Technology Research Unit, National Center for Genetic Engineering and Biotechnology, Kasetsart University, Bangkok, Thailand Tromp, R. Hans T.I. Food and Nutrition, Wageningen, The Netherlands; and NIZO Food Research, Ede, The Netherlands Troygot, Oranit Institute of Biochemistry, Food Science and Nutrition, The Robert H. Smith Faculty of Agricultural, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel Truong, Tuyen Thuc School of Land, Crop and Food Sciences, University of Queensland, Brisbane, Australia Tsuji, Kaori Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Ubbink, Job Nestlé Research Center, Lausanne, Switzerland Van As, Henk Wageningen University and NMR Centre, Wageningen, The Netherlands

Contributors

van Duynhoven, John Unilever Food and Health Research Institute, Vlaardingen, The Netherlands Van Nieuwenhuijzen, Neleke H. T.I. Food and Nutrition, Wageningen, The Netherlands; and Wageningen University and Research Centre, Wageningen, The Netherlands Van Vliet, Ton T.I. Food and Nutrition, Wageningen, The Netherlands; and Wageningen University and Research Centre, Wageningen, The Netherlands Vega, Alberto Universidad de la Coruña, A Coruña, Spain Venturi, Luca Department of Food Science, Alma Mater Studiorum, University of Bologna, Campus of Food Science, Cesena, Italy Vittadini, Elena Food Science and Technology, Department of Industrial Engineering, University of Parma, Parma, Italy Vodovotz, Yael Department of Food Science and Technology, Ohio State University, Columbus, Ohio, USA Wallach, Rony Department of Soil and Water Sciences, The Robert H. Smith Faculty of Agricultural, Food and Environment, The Hebrew University of Jerusalem, Rehovot, Israel

xxix

Watanabe, Hisahiko Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Watanabe, Manabu Department of Food Science and Technology, Tokyo University of Marine Science and Technology, Tokyo, Japan Weglarz, Wladyslaw P. Unilever Food and Health Research Institute, Vlaardingen, The Netherlands; and Department of Magnetic Resonance Imaging, Institute of Nuclear Physics, Polish Academy of Sciences, Kraków, Poland Wellner, Nikolaus Institute of Food Research, Norwich Research Park, Norwich, UK Welti-Chanes, Jorge Departamento de Graduados e Investigación en Alimentos, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional, México City, México Winger, Ray J. Institute of Food, Nutrition and Human Health, Massey University, Palmerston North, New Zealand Witek, Magdalena Wageningen University and NMR Centre, Wageningen, The Netherlands

xxx

Contributors

Xiang, Tian-xiang Department of Pharmaceutical Sciences, College of Pharmacy, University of Kentucky, Lexington, Kentucky, USA Yakimets, Iryna Division of Food Sciences, School of Biosciences, University of Nottingham–Sutton Bonington Campus, Leicester, UK Yamada, Shunsuke Division of Life Science and Engineering, School of Science and Engineering, Tokyo Denki University, Saitama, Japan Yimjaroenpornsakul, Achana Department of Food Science and Technology, Faculty of AgroIndustry, Kasetsart University, Bangkok, Thailand

Yoshii, Hidefumi Department of Biotechnology, Tottori University, Tottori, Japan Yoshioka, Sumie National Institute of Health Sciences, Tokyo, Japan Zhou, Weibiao Food Science and Technology Programme, National University of Singapore, Singapore


PART 1 Invited Speakers and Oral Presentations

Session 1 Water Mobility/Dynamics and Its Application in Food and Pharmaceutical Systems

Invited Speakers

1 Complementary Aspects of Thermodynamics, Nonequilibrium Criteria, and Water Dynamics in the Development of Foods and Ingredients M. P. Buera

Abstract Temperature and water content of the systems have been the variables most widely employed to define and predict the kinetic coefficients of desirable and undesirable changes in foods. Supplemented temperature vs composition phase diagrams have been demonstrated to be helpful in determining the feasibility of occurrence of phase or state transitions. These diagrams include the glass transition temperature (Tg) curve and the equilibrium liquidus curves. The inclusion of the nonequilibrium curves enables relationships with the time coordinate and, thus, with the dynamic behavior of the systems to be established and helps to predict whether the systems are under thermodynamic or kinetic control for given composition vs temperature conditions, provided that the thermal history of the samples is known. The present work analyzed how complementary aspects of thermodynamics and nonequilibrium criteria and water dynamics can be assembled in order to demonstrate the formulation and processing strategies to optimize the stability of food products and ingredients, especially in dry systems. A wide variety of kinetic data from several chemical reactions (in vegetable and animal tissues, dairy products, ingredients, and pharmaceutical formulations or model systems) from the published literature on the results from specifically designed experiments were distributed in supplemented phase diagrams. The results indicated that both solid-water interactions and structural characteristics of the systems governed the dependence of reaction rates on relative humidity. In addition to the supplemented phase diagrams, structural aspects of the matrices where the reaction takes place, water-sorption properties, and water mobility itself were key aspects for a complete interpretation to describe the dynamics of the chemical reactions.

Introduction The kinetic control of desirable and undesirable aspects of chemical reactions represents a challenge in basic and applied areas of chemistry and food sciences. Therefore, the impact of the variables and mechanisms that determine reaction rates has been given much attention. Temperature and water content of the systems have been the variables most widely employed to define and predict the kinetic coefficients. The significance of state and phase transitions in the stability of amorphous food materials 9

10

PART 1: Invited Speakers and Oral Presentations

and also their impact on chemical and enzymatic reactions have been evaluated since the 1980s (Slade and others 1989; Roos and Karel 1991; Karmas and others 1992; Levine and Slade 1992; Bell and Hageman 1994; Bell 1995; Buera and Karel 1995; Lievonen and others 1998; Bell and White 2000; Kouasi and Roos 2000). Since an equilibrium state does not exist in these systems, the conservation of desirable properties in foods and ingredients is governed by conditions of metastability, often based on the maintenance of the systems in an amorphous state (Levine and Slade 1992): although the system components are not thermodynamically stable, they are kinetically stabilized. Supplemented temperature composition phase diagrams have proven helpful in determining the potential of phase or state transitions (Slade and others 1989; Levine and Slade 1992). These diagrams include the nonequilibrium glass transition temperature (Tg) curve and the equilibrium liquidus curves. The inclusion of the nonequilibrium curves enables the relationships with the time coordinate and, thus, with the dynamic behavior of the systems to be established and helps to predict whether the systems are under thermodynamic or kinetic control for given temperature/composition conditions, providing that the thermal history of the samples is known. Structural aspects of the matrices where the reactions occur, sorption, and water mobility itself were also detected as key aspects in describing the dynamic of this reaction. The present work analyzed how complementary aspects of thermodynamics and nonequilibrium criteria and water dynamics can be assembled in order to point out formulations or processing strategies to optimize the stability of food products and ingredients, especially in dry systems.

Reactions, Materials, and Methods The stability of selected dehydrated systems toward the Maillard reaction, the loss of enzymatic activity, or carotene degradation was analyzed. Data obtained in freezedried vegetable tissues, dairy products, ingredients, and pharmaceutical formulations or model systems as the result of specifically designed experiments (Mazzobre and others 2001; Longinotti and others 2002; Prado and others 2006; Acevedo and others 2006, 2008b; Sutter and others 2007) were plotted in supplemented phase diagrams. Additional information on water dynamics and water-sorption properties was obtained. Differential scanning calorimetry (DSC) was helpful in analyzing thermal transitions and generating temperature- vs composition-supplemented state diagrams. Timeresolved proton nuclear magnetic resonance (1H-NMR) was used to complement DSC with the aim of obtaining a better understanding of the mobility of water and food solids in the systems (Schmidt and Lai 1991; Kou and others 2000; Tang and others 2000; Chatakanonda and others 2003). X-ray diffraction and microscopy provided information on molecular and microscopic structural changes.

Maillard Reaction The Maillard reaction may have a positive or a negative contribution to the quality of food products, and its complexity necessitates a deep kinetic analysis of reaction

Water Dynamics in the Development of Foods and Ingredients

11

media and the variables involved to direct the reaction with the desirable outcome. In dehydrated foods, the reaction is the cause of off-flavors, off-colors, and loss of nutritional value. The kinetics of the Maillard reaction must be controlled also as a requirement of new food technologies: in the development of natural flavors, pigments, emulsifiers, antimicrobials, and antioxidants; in the formulation of protective media for biological systems and ingredients; and for controlled modification of biomolecular functionality or structure. The reaction rate is strongly dependent on the concentration, ratio, and chemical nature of reactants, temperature, water content, pH, and water activity (aw) (Labuza and Baisier 1992), but it is also influenced by the physical properties of the media. In liquid systems, the Maillard reaction rate diminishes continuously as relative humidity (RH) increases, mainly because water is a product of the reaction (Hodge 1953; Eichner and Karel 1972; Labuza and Saltmarch 1981). However, in solid or quasi-solid systems, in which reactants are constrained by mobility restrictions, a maximum rate of nonenzymatic browning (NEB) is observed at a given intermediate RH value. Thus, the presence of a maximum in the plot of rate versus water content (or aw) is a consequence of the low reaction rates due to mobility limitations of the reactants (at low water content) and inhibition by the product (at high water content) (Buera and Karel 1995; Van Boekel 2001). Systems with different structural characteristics were analyzed to elucidate the relationship among browning rate, water-solid interaction, and water mobility and the incidence of structural changes accompanying phase or state transitions: highly collapsible polymeric (polyvinylpyrrolidone [PVP40]) matrices, crystallizing lactose and milk systems, and vegetable tissues exhibiting an intermediate degree of collapse because of the presence of water-insoluble polymers capable of providing residual structure. The shaded areas in Figures 1.1 and 1.2 represent the temperature vs composition conditions at which the Maillard reaction was analyzed, and the circled regions show the conditions at which the maximum rates were observed. The corresponding Tg curves are shown in Figures 1.1 and 1.2 also as a function of water content. Since sugars are the main soluble components determining Tg values in vegetable and dairy systems, solubility curves for the main sugars present were included as a reference. In PVP systems (Figure 1.1) at a given temperature, the Maillard reaction rate increased as water content increased, and the maximum rate occurred at a water content at which Tg was close to the storage temperature. Above this point, the samples presented a fully collapsed fluid aspect, and the Maillard rate decreased when water content increased (behavior similar to that of liquid systems). In the crystallizable lactose- or trehalose-containing systems (Figure 1.1), the maximum rate occurred at conditions in which a considerable degree of sugar crystallization had occurred, but when the samples were totally crystalline the rate decreased. Figure 1.3 shows the rate of the Maillard reaction as a function of water content for lactose systems compared with the rates with milk and lactose-starch. It should be noted that, in milk or lactose-starch systems, the presence of proteins or biopolymers retarded lactose crystallization. Consequently, the maximum rate of

Figure 1.1. State diagrams showing the glass transition temperatures (Tg) as a function of the mass fraction of water (w) for (a) polymeric (PVP), (b) lactose, and (c) trehalose matrices in which the Maillard reaction was developed. Shaded areas represent the regions in which the experiments were performed. The conditions at which fast-collapse or crystallization phenomena were observed are indicated by dotted lines. Circled regions indicate the conditions at which the maximum browning rate was observed.

12

Figure 1.2. State diagrams showing the glass transition temperatures (Tg) as a function of the mass fraction of water (w) for (a) apple, (b) cabbage, and (c) potato in which the Maillard reaction was developed. Shaded areas represent the regions in which the experiments were performed. The solubility curves (S) for the sugars fructose (fru), glucose (glu), and sucrose (suc) are indicated as a reference. Circled regions indicate the conditions at which the maximum browning rate was observed.

13

14


150 Crystallization zone

0.3

k lactose

50

Tg

k milk

0.2 0

k lactose-starch

-50 -100

K

Tg (°C)

100

0.1 0

10

20

30

40

50

W Figure 1.3. State diagrams showing the lactose glass transition temperature (Tg) as a function of the mass fraction of water (W). Browning rate constants (k) for the lactose, milk, and lactose-starch systems are also shown as a function of W.

browning occurred with a higher water content, and the maximum rate was maintained in higher water contents than in the sugar-only matrices (complete crystallization occurred at higher water content values in those samples). In vegetable tissues containing structure-maintaining water-insoluble biopolymers and presenting an intermediate degree of collapse, the maximum rate of NEB occurred at RHs in a range of 50%–80% when the samples were well above Tg at the storage temperature (Figure 1.2). In all cases analyzed, the Maillard reaction occurred below the Tg and required a minimum of water content (w in Figure 1.2) to mobilize the reactants, but the reaction was immediately inhibited by water in excess of this requirement. The minimum water content was directly related neither to the monolayer Guggenheim-Anderson-de Boer (GAB) value nor to the Tg value of the systems. The browning rate of the vegetables and food models analyzed was very low in the glassy state, but at temperatures above the Tg, in addition to the decreasing viscosity and increasing rate, other changes such as crystallization and collapse affected the browning rate. As already discussed, the maximum reaction rates were reached either close to or well above the Tg, depending on the system structure. The observation of the maximum rate as a function of water content indicated that the reaction rate decreased at a point at which the matrix was unable to adsorb water either because of crystallization (as in the case of lactose-containing systems), saturation of the most active sites of the water-adsorbing matrix, or capillary condensation. I thus analyzed the location of the beginning of the third water-sorption stage, the transverse spin-spin 1H-NMR relaxation times by spin echo after the Hahn sequence pulse, and the detection of frozen water by DSC. The location of the beginning of the third sorption stage was analyzed by the inverse plot of the GAB model, as proposed by Timmermann and Chirife (1991). The analysis of proton spin-spin relaxation times by the Hahn spin-echo pulse sequence in the samples at different water contents showed two T2 components. A fast-decaying component, with T2-Hahn-1 values on the order of 30–40 ms was present


15

at all the RHs analyzed and corresponds to both protons of solids and protons of water molecules that are strongly influenced by their proximity to the solid components. (It could also be detected by free-induction decay [FID] measured after a single 90° pulse.) Above a given water content (in the proximity of aw = 0.22), a slow-relaxing component (T2-Hahn-2) in the range of 400–950 ms was also observed, the value of which increased linearly up to the beginning of the third sorption stage, as previously defined, and then became constant. The inhibitory water concentration was associated with the second inflection point of the water-sorption isotherm up to the appearance of freezable water as determined by DSC and up to the saturation of the second sorption stage as determined by proton spin-spin transverse relaxation times (T2) analyzed by 1HNMR with the Hahn pulse sequence (Acevedo and others 2008b). Upon the appearance of freezable water and highly mobile water (determined by the T2-Hahn-2 value), the NEB rate decreased as the water molecules inhibited the reaction and/or diluted the reactants. As the scheme in Figure 1.4 shows, the water content at a maximum Maillard reaction rate results from the compromise between water plasticization and its inhibitory effect. These conditions can be predicted on the basis of sorption and structural properties and of thermal transitions of the matrices where the reaction takes place and through the analysis of water mobility.

Matrix crystallization (lactose)

Matrix collapse (PVP)

3rd sorption stage (T2-2 ~ 1 ms) (vegetables)

Tem

per

atur

e

kb

Figure 1.4. Schematic tridimensional plot showing the browning rate (kb, in arbitrary units) as a function of the temperature and mass fraction of water (w). The conditions for the decreasing rate constant after the maximum were different for each type of system and are indicated by the arrows. PVP, polymeric matrix.

16


Enzyme Stability Due to chemical and physical changes, most proteins lose their activity when stored for extended periods in aqueous solution, and they are generally freeze-dried to achieve a stable product. The dry state slows chemical degradation and alleviates physical problems, such as protein unfolding and aggregation. However, protein stability in the solid state can be worse than that in liquid state if adequate components are not present during the process to form suitable matrices (Crowe and others 1998). Sugars, and particularly trehalose, have been found to be optimal in protecting enzymes during drying and later storage (Leslie and others 1995; Suzuki and others 1997; Crowe and others 1998). Much knowledge about protein stability is derived from understanding how organisms survive thermal and hydric stresses (Sun and Leopold 1997). Vitrification of protective sugars is possibly the main strategy in nature to avoid the crystallization of these sugars in anhydrobiotic organisms. Mazzobre and others (2003, 2008) analyzed the stability of freeze-dried enzymes (β-galactosidase, invertase, honey amylase, soy urease, and soy transaminase) over a wide range of temperature and water-content conditions. Materials capable of forming amorphous matrices, but with different physicochemical characteristics, were chosen to compare their efficiency in protecting the enzymes. In the polymeric glassy matrices, the enzyme stability was diminished either by increasing water content at a certain temperature or by increasing the storage temperature at fixed water content. The good glass–former polymers maltodextrin and PVP were not effective in protecting the enzyme during heat treatment, the enzyme stability being affected mainly by effects of temperature. Crowe and others (1998) reported that although vitrification of the structure is necessary for improved enzyme stability, it is not the only condition required for the protection of molecules, since specific hydrogen-bond interactions between the matrix and the protein are also needed. According to this, sugars, and especially trehalose, were more effective protectants despite their lower Tg values, even at relatively high temperatures. The enzymes retained quite good activity in the trehalose supercooled region, but their activity decreased drastically when the sugar crystallized at a mass fraction of water greater than 0.1. Starch protected the enzymes adequately at high water content and low temperature where stability was completely lost in other systems. Enzyme interactions with the surface of starch granules and the high Tg value of this matrix may have played a role in enzyme stability. When sugar crystallizes, the protein is excluded from the sugar crystals, and is exposed to a matrix where, besides lacking the stabilizing effect of hydroxyl groups, the changes in pH, concentration of reactive groups, and ionic strength may also negatively affect its stability. However, it has been observed that, for many enzymes, if sugar crystallization is inhibited or conveniently delayed, the protective action of sugars may be extended to the supercooled-liquid state (Suzuki and others 1997; Buera and others 2005; Mazzobre and others 2008). The addition of polymers, other sugars, or salts extended the protective effect of sugars to the supercooled region by delaying crystallization (Mazzobre and others 1997; Gabarra and Hartel 1998). In dairy systems, compared with pure-lactose systems


17

Figure 1.5. Supplemented phase diagram showing the sucrose glass transition temperature (Tg) as a function of the mass fraction of water (W): Ts, sucrose solubility curve; and Tm, water-melting curve. The effect of magnesium chloride on the sucrose curves is indicated by arrows. The dotted lines indicate the freezing-point depression for increasing sugar/salt proportions (R), from R1 to R3: w ′g, the mass fraction of water for the maximum cryoconcentrated matrix; and Tg′, the glass transition temperature of the maximally concentrated matrix. Adapted from Mazzobre and others (2001).

(Jouppila and Roos 1994), the presence of proteins delayed lactose crystallization. Gelatin inhibited crystallization of raffinose and, in the presence of bovine serum albumin, of sucrose, and raffinose crystallization was inhibited even at high RH (84%) (Espinosa and others 2006). Additives like polymers that raise the overall Tg of pure sugars reduced molecular mobility and inhibited crystallization, although delayed crystallization in many studies was related to the modification of the molecular environment of the crystallizing sugar in those mixtures, affecting thermodynamic and geometric factors that control nucleation without changing Tg significantly (Mazzobre and others 2001; Longinotti and others 2002). A special set of studies was dedicated to the analysis of the effect of salts on the phase diagram of sugars (Mazzobre and others 2001, 2008; Longinotti and others 2002), which are presented in Figure 1.5. Water sorption and water or sugar crystallization behavior indicated that the effect of salts on the sugar phase diagram was directly related to the charge/mass ratio of the cations present (Mg > Ca > Na > K). Measurements of electrical conductivity in concentrated sugar-salt-water systems revealed a high population of local inhomogeneities, which were induced by preferential solvation of the ions as a consequence of the larger ion-water interactions as compared with the ion-disaccharide interactions. Therefore, whereas the ion mobility is enhanced by a low-viscosity local environment, sugar molecular mobility should

18


be depressed by a high local viscosity. Ediger (2000) described spatially heterogeneous dynamics in supercooled liquids, as resulted from analysis by different techniques. The dynamics in regions separated by a few nanometers could be different by several orders of magnitude. The short-range dynamics of sugar-water systems could change dramatically without modifying the Tg of the system, which is a result of suprastructural relaxation. Thus, the presence of salts could retard the sugar crystallization even when Tg remains unchanged. This effect should be more pronounced for ions with stronger interactions with water. In frozen systems, on the other hand, the salts have a colligative effect (Figure 1.5) and promote an increase of the water associated with the maximally concentrated nonfrozen phase (w in Figure 1.5). Consequently, the Tg of this phase decreases. Decreased enzyme activity was observed in these saltcontaining systems. Mazzobre and others (2008) observed that the effect of salts, with regard to sugar crystallization kinetics and enzyme inactivation, seems also to be associated with the magnitude of their effect on disrupting the tetrahedral hydrogen-bond network of water. Water structure-maker ions (citrate > acetate; Mg+2) enhance the tetrahedral coordinated hydrogen-bond structure of water, and water structure-breaker ions (K+) disrupt the tetrahedral coordination of water. Some ions, such as Na+ or Cl−, are considered neutral (Calligaris and Nicoli 2006). Trehalose acts as a structure breaker but provides enzyme stabilization by strong hydrogen-bonding interactions (Patist and Zoerb 2005). In restricted water environments, such as the dehydrated (or frozen) systems analyzed in the present work, the amount of water determines the kinetics of phase changes and enzyme inactivation. Thus, the type of water-ion interactions are manifested in those dynamic changes, and the use of the so-called Hofmeister series could offer great help in their description. To optimize the efficiency of biomolecular dehydroprotectant agents, the development of state diagrams is a good starting point for the analysis of the dynamics of quality changes, but the diagrams must be complemented by knowledge of the intermolecular interactions that may occur. Besides supramolecular aspects, like Tg and crystallinity, the density of the molecular packing of the matrices, reducing power, and hydrogen-bonding capacity determined the effectiveness of agents as biomolecular protectants. Electrolytes commonly present in biological media or food and pharmaceutical formulations modified metastable systems, affecting the kinetics of water and sugar crystallization and enzyme inactivation, by both molecular and supramolecular interactions.

Degradation of Carotenes Stability and retention of labile biomolecules during drying and later storage often depend on encapsulation of the biomolecules in the amorphous matrix formed during dehydration processes (Constantino and others 1998; Pyne and others 2003). The high degree of unsaturation in the structure of carotenes renders them extremely susceptible to oxidation. Amorphous sugars are effective encapsulating agents. However, sugar crystallization as a consequence of storage above the Tg promotes not only the loss of the stabilizing effect on biomolecules such as enzymes, as previously discussed, but


19

also the release of encapsulated lipids (Shimada and others 1991; Labrousse and others 1992). The changes in the physical structure of the matrix may also lead to increased permeability and diffusivity of gases (water and oxygen) that affect reaction rates and decrease stability of encapsulated active materials (Karel 1991; Karel and Saguy 1991). Figure 1.6 presents the phase diagram of PVP (a) and crystallizable trehalose (b) matrices. The shaded area indicates the magnitude of the kinetic constants of carotene degradation.

Figure 1.6. State diagram showing the glass transition temperatures (Tg) as a function of the mass fraction of water (w) for (a) polymeric (PVP) and (b) trehalose matrices in which β-carotene was encapsulated. The conditions at which fast-collapse or crystallization phenomena were observed are indicated by dotted lines. Shaded areas represent the regions in which the experiments were performed; within those areas, the darker regions indicate a high β-carotene loss rate. Arrows show the direction of the kinetic constant increase for β-carotene loss.

20


Elizalde and others (2002) showed that the rate of encapsulated β-carotene loss in a trehalose matrix was affected mainly by the moisture in excess of that necessary for trehalose dihydrate crystallization. In fact, when water content was low but higher than 10%, the available water crystallized with trehalose, forming the dihydrate, and less water was free to liberate the encapsulated β-carotene. Once crystallization was completed, the kinetics of β-carotene loss were strongly accelerated (Figure 1.6a). Prado and others (2006) demonstrated that β-carotene loss in a freeze-dried polymeric (PVP-40) matrix was observed mainly in the glassy state (below Tg), where the highporosity matrix allowed oxygen diffusion and then fast degradation of β-carotene. To the contrary, the lower degradation rate constants were observed under conditions in which the structural collapse caused the disappearance or dramatic decrease of matrix micropores (Figure 1.6b). Although maltodextrins improved the shelf life of β-carotene in spray-dried carrot juice (Desobry and others 1998), and the release of encapsulated material has been qualitatively related to structural collapse or shrinkage caused by storage above the matrix Tg (Omatete and King 1978; Levi and Karel 1995; Selim and others 2000; Serris and Biliaderis 2001), in the case of oxidizable compounds the sample porosity in freeze-dried amorphous systems may negatively affect the stability of encapsulated compounds. Mannitol is a popular excipient used in freeze-dried formulations to stabilize biomolecules (proteins, enzymes, hormones, and vitamins). Obtaining amorphous pure mannitol is difficult because of the great tendency of this polyol to crystallize. Various solutes that remain amorphous in frozen solutions and during freeze drying (sodium chloride, dipotassium hydrogen phosphate [K2HPO3], and glycine) were reported to inhibit mannitol crystallization (Pikal and others 1991; Constantino and others 1998; Pyne and others 2003; Yoshinari and others 2003). As in the case of sugars, discussed previously with regard to enzyme stability, the effect of salts on carotene encapsulation was studied in mannitol systems (Sutter and others 2007). Phosphate salts significantly delayed mannitol crystallization during freeze drying, and consequently the degree of β-carotene encapsulation increased (Sutter and others 2007). This effect was maintained for quite a long time during storage of the freeze-dried samples at 25°C. The divalent cations showed a synergistic effect and also modified β-carotene degradation kinetics during storage, increasing carotene’s stability. The mechanism of crystallization inhibition likely includes a change in the hydrogen-bond network and/or a change in molecular mobility in the presence of divalent cations and phosphate anions. The degradation rate of β-carotene in a mannitol–potassium dihydrogen phosphate matrix increased as the %RH increased until reaching a value at which the samples collapsed (75% RH) and then the degradation rate decreased.

Structural Effects In systems with very low water content, water released during the Maillard reaction or sugar crystallization accelerated enzyme inactivation and browning (Kim and others 1981; Burin and others 2000), and the magnitude of the effect depended on the degree of collapse or porosity, which affected the retention of water in the systems (Buera


21

and Karel 1995; Burin and others 2004). The water-content increase resulting from the Maillard reaction was also reflected in a Tg depression (Roos and others 1996; Burin and others 2004). Acevedo and others (2008a) showed that the different structure generated during drying of apple discs, depending on the type of drying method used (air convection or the use of different freezing rates before freeze drying) affected sorption properties of the dried material and, consequently, the rate of browning development, which in turn were also different from those of dried-apple powdered samples. An inverse correlation was observed between degradation rate constants for βcarotene and degree of collapse. Thus, matrix collapse under controlled conditions during product processing may improve the stability of encapsulated biomolecules. These observations demonstrated that factors such as microstructure and matrix porosity may be important modifiers of reaction kinetics, and the sample structure is another variable that has to be considered when the kinetics of deteriorative reactions are analyzed.

Concluding Remarks The rates of three different chemical reactions were analyzed from the perspective of phase diagrams of the matrices where the reactions occurred. Both solid-water interactions and structural characteristics of the systems governed the dependence of reaction rates on RH. In addition to affecting chemical reactions via aw and by plasticizing amorphous systems, water mobility itself was demonstrated to have a direct impact on chemical reactivity in low-moisture and intermediate-moisture systems. In this way, besides the valuable information provided by localizing the plausible system conditions (compositions and temperatures) on supplemented phase diagrams, structural aspects of the matrices where the reaction occurs, water-sorption properties, and water mobility itself were detected also as key aspects that must be considered for a complete interpretation in describing the dynamics of the chemical reactions. Product formulation, process, and storage may be managed through knowledge of reaction kinetics, solid and water dynamic properties, transition temperatures, and process variables (mainly water content and temperature). Potential topics for further research include the study of macroscopic and molecular properties of the materials, such as the effect of sub-Tg relaxations on the kinetics of chemical reactions, or local heterogeneities in water distribution at microscopic scales. Also, the quantification of structural effects such as collapse and compression would be valuable in the complete interpretation of deteriorative reaction kinetics.

Acknowledgments The author acknowledges financial support from the University of Buenos Aires (EX226), the Argentine National Agency of Scientific and Technological Promotion (Agencia Nacional de Promoción Científica y Tecnológica [PICT 20545 and 3066]), and the Argentine National Scientific and Technical Research Council (Consejo

22


Nacional de Investigaciones Científicas y Técnicas [CONICET]). The findings in this work are part of the technical report of the International Union of Pure and Applied Chemistry (IUPAC) Project (2003-036-2-100).

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Karel M. 1991. Physical structure and quality of dehydrated foods. In: Mujumdar AS, Filkova I, editors. Drying ’91. Amsterdam: Elsevier. p 26–35. Karel M, Saguy I. 1991. Effects of water on diffusion in food systems. In: Levine H, Slade L, editors. Water relationships of foods. New York: Plenum. p 157–73. Karmas R, Buera MP, Karel M. 1992. Effect of glass transition on rates of non-enzymatic browning in food systems. J Agric Food Chem 40:873–9. Kim M, Saltmarch M, Labuza TP. 1981. Non-enzymatic browning of hygroscopic whey powders in open versus sealed pouches. J Food Proc Preserv 5:49–57. Kou Y, Dickinson LC, Chinachoti P. 2000. Mobility characterization of waxy corn starch using wide-line 1 H nuclear magnetic resonance. J Agric Food Chem 48:5489–95. Kouasi K, Roos YH. 2000. Glass transition and water effects on sucrose inversion by invertase in a lactosesucrose system. J Agric Food Chem 48:2461–6. Labrousse S, Roos Y, Karel M. 1992. Collapse and crystallization in amorphous matrices with encapsulated compounds. Sci Aliments 12:575–769. Labuza T, Baisier WM. 1992. The kinetics of nonenzymatic browning. In: Schwartzberg H, Hartel R, editors. Physical chemistry of foods. New York: Marcel Dekker. p 595–649. Labuza T, Saltmarch M. 1981. Kinetics of browning and protein quality loss in whey powders during steady state and nonsteady state storage conditions. J Food Sci 41:92–6. Leslie SB, Israeli E, Lighthart B, Crowe JH, Crowe LM. 1995. Trehalose and sucrose protect both membranes and proteins in intact bacteria during drying. Appl Environ Microbiol 61:3592–7. Levi G, Karel M. 1995. The effect of phase transitions on release of n-propanol entrapped in carbohydrate glasses. J Food Eng 24:1–13. Levine H, Slade L. 1992. Glass transitions in foods. In: Schwartzberg H, Hartel R, editors. Physical chemistry of foods. New York: Marcel Dekker. p 83–221. Lievonen SM, Laaksonen TJ, Roos YH. 1998. Glass transition and reaction rates: nonenzymatic browning in glassy and liquid systems. J Agric Food Chem 46:2778–84. Longinotti MP, Mazzobre MF, Buera MP, Corti HR. 2002. Effect of salts on the properties of aqueous sugar systems in relation to biomaterial stabilization. 2. Sugar crystallization rate and electrical conductivity behaviour. Phys Chem Chem Phys 4:533–40. Mazzobre MF, Buera MP, Chirife J. 1997. Protective role of trehalose on thermal stability of lactase in relation to its glass and crystal forming properties and effect of delaying crystallization. Lebensm Wiss Technol 30:324–9. Mazzobre MF, Hough G, Buera MP. 2003. Phase transitions and functionality of enzymes and yeasts in dehydrated matrices. Food Sci Technol Int 9:163–72. Mazzobre MF, Longinotti MP, Buera MP, Corti HR. 2001. Effect of salts on the properties of aqueous sugar systems in relation to biomaterial stabilization. 1. Water sorption behavior and ice crystallization/ melting. Cryobiology 43:199–210. Mazzobre MF, Santagapita PR, Gutiérrez N, Buera MP. 2008. Consequences of matrix structural changes on functional stability of enzymes as affected by electrolytes. In: Gutiérrez-López GF, Barbosa-Cánovas GV, Welti-Chanes J, Parada-Arias E, editors. Food engineering: integrated approaches. New York: Springer. p 73–87. Omatete OO, Judson King C. 1978. Volatiles retention during rehumidification of freeze-dried food models. J Food Technol 13:265–80. Patist A, Zoerb H. 2005. Preservation mechanisms of trehalose in foods and biosystems. Colloids Surf [B] 40:107–13. Pikal MJ, Dellerman KM, Roy MI, Riggin RM. 1991. The effects of formulation variables on the stability of freeze-dried human growth hormone. Pharm Res 8:427–36. Prado SM, Buera MP, Elizalde BE. 2006. Structural collapse prevents β-carotene loss in a super-cooled polymeric matrix. J Agric Food Chem 54:79–85. Pyne A, Koustov CH, Suryanarayanan R. 2003. Solute crystallization in mannitol-glycine systems: implications on protein stabilization in freeze-dried formulations. J Pharm Sci 92:2272–83. Roos Y, Jouppila K, Zielasko B. 1996. Non-enzymatic browning-induced water plastification: glass transition temperature depression and reaction kinetics determination using DSC. J Thermal Anal 47:1437–50.

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Roos YH, Karel M. 1991. Plasticizing effect of water on thermal behavior and crystallization of amorphous food models. J Food Sci 56:38–43. Schmidt SJ, Lai H. 1991. Use of NMR and MRI to study water relations in foods. In: Levine H, Slade L, editors. Water relationships in foods. New York: Plenum. p 405–52. Selim K, Tsimidou M, Biliaderis CG. 2000. Kinetic studies of saffron carotenoids encapsulated in amorphous polymer matrices. Food Chem 71:199–206. Serris GS, Biliaderis CG. 2001. Degradation of beetroot pigment encapsulated in polymeric matrices. J Sci Food Agric 81:691–700. Shimada Y, Roos Y, Karel M. 1991. Oxidation of methyl linoleate encapsulated in amorphous lactose-based food model. J Agric Food Chem 39:637–41. Slade L, Levine H, Finlay JW. 1989. In: Phillips R, Findlay LAW, editors. Protein quality and the effects of processing. Amsterdam: Elsevier Science. p 9–124. Sun WQ, Leopold AC. 1997. Cytoplasmatic vitrification and survival of anhydrobiotic organisms. Plant Physiol 89:767–72. Sutter SC, Buera MP, Elizalde BE. 2007. β-Carotene encapsulation in a mannitol matrix as affected by divalent cations and phosphate anion. Int J Pharm 332:45–54. Suzuki T, Imamura K, Yamamoto K, Satoh T, Okazaki M. 1997. Thermal stabilization of freeze-dried enzymes by sugars. J Chem Eng Jpn 30:609–13. Tang HR, Godward J, Hills B. 2000. The distribution of water in native starch granules: a multinuclear NMR study. Carbohydr Polym 43:375–87. Timmermann EO, Chirife J. 1991. The physical state of water sorbed at high activities in starch in terms of the GAB sorption equation. J Food Eng 13:171–9. Van Boekel MA. 2001. Kinetic aspects of the Maillard reaction: a critical review. Nahrung/Food 45:150–9. Yoshinari T, Forbes RT, York P, Karawahisma Y. 2003. Crystallization of amorphous mannitol is retarded using boric acid. Int J Pharm 258:109–20.

2 Water Mobility in Solid Pharmaceuticals as Determined by Nuclear Magnetic Resonance, Isothermal Sorption, and Dielectric Relaxation Measurements S. Yoshioka and Y. Aso

Abstract Nuclear magnetic resonance, dielectric relaxation spectroscopy, differential scanning calorimetry, and water-sorption isotherm data are presented to demonstrate a wide range of molecular mobilities observed for water molecules present in solid active pharmaceutical ingredients and water molecules coexisting with pharmaceutical excipients.

Introduction It is widely recognized that the presence of water molecules in solid pharmaceuticals can affect the chemical and physical stability of these solids. For example, water can act as a reactant or medium for chemical degradation, or as a plasticizer, which enhances chemical and physical degradation, in amorphous pharmaceuticals (Shalaev and Zografi 1996). In contrast, small amounts of water can stabilize solid peptide and protein drugs. Because the significance of these effects is often related to the mobility of water molecules, an understanding of water mobility in solid pharmaceuticals should be of great value in the development of stable solid-dosage forms. This chapter presents the experimental data on the mobility of water molecules present in solid active pharmaceutical ingredients (APIs) and water molecules coexisting with various pharmaceutical excipients, which demonstrate a wide range of water mobilities in the solids. Nuclear magnetic resonance (NMR), dielectric relaxation spectroscopy (DRS), differential scanning calorimetry (DSC), and water-sorption isotherm analysis were used to determine the molecular mobility of water. This chapter includes the interpretation of NMR data partially modified according to the comments of Prof. Peter Lillford at the Tenth International Symposium on the Properties of Water (ISOPOW 10).

Apparent Correlations Between the Stability of Solid APIs and the Molecular Mobility of Water Correlations between stability and water mobility are suggested for various APIs in the solid state. For example, the hydrolysis rate of cephalothin in freeze-dried formulations containing one of several excipients such as starch and methylcellulose appears 25

26


0.02

kapp (h-1)

0.015 MC

0.01

SSTA STA

0.005

0

MCC

5

10

15

20

25

T1 (ms)

Figure 2.1. Correlation between the T1 of deuterium (2H2O) and the hydrolysis rate of cephalothin in freeze-dried formulations. MC, methyl cellulose; SSTA, water-soluble starch; STA, starch; and MCC, microcrystalline cellulose.

to be correlated with the molecular mobility of water as determined by the spin-lattice relaxation time (T1) of deuterium in the water molecule, as shown in Figure 2.1 (Aso and others 1997). The hydrolysis rate of flomoxef in gelatin gel containing kanamycin also exhibited an apparent correlation with the molecular mobility of water as determined by the T1 of 17O in the molecule (Yoshioka and others 1992). Not only chemical stability but also physical stability, such as crystallization of solid APIs during storage, appear to be correlated with the molecular mobility of water. The crystallization rate of amorphous nifedipine in solid dispersion formulations exhibited an apparent correlation with the T1 of deuterium in the water molecule, as shown in Figure 2.2. Similar correlations are observed for the stability of lyophilized protein formulations.

Molecular Mobility of Water in API Hydrates Water molecules in API hydrates exhibit a variety of physical states, suggesting a wide range of molecular mobilities. Because water of hydration plays important roles in determining the physical characteristics—such as solubility and flowability—of the API hydrate, an understanding of the molecular mobility of hydration water is critical in the formulation of API hydrates. Molecular Mobility of Hydration Water as Determined by NMR NMR has been used to determine the molecular mobility of water in the solid state and to examine the various mechanisms by which solids interact with water. However, there have been few studies in which the molecular mobility of water in API hydrates was determined using NMR. This may be because proton nuclear magnetic resonance (1H-NMR), even high-resolution 1H-NMR, cannot separate the peaks of the water

Water Mobility in Solid Pharmaceuticals

27

1.0

1/t 50 (h-1)

0.8

0.6

STA MCC

0.4

MC PVA

0.2 0.0

7

9

11

13

15

17

T1 (ms)

Figure 2.2. Correlation between the T1 of deuterium (2H2O) and the crystallization rate of amorphous nifedipine in solid dispersion formulations. STA, starch; MCC, microcrystalline cellulose; MC, methyl cellulose; and PVA, polyvinyl alcohol.

protons from those of the protons in other components, which prevents specific determination of water mobility. Although the preparation of API hydrate samples by using 17 O-labeled water enables the molecular mobility of the water molecules to be specifically determined by 17O-NMR, unaffected by the other components this approach is expensive and labor intensive. Thus, determination of the molecular mobility of hydration water in API hydrates by using NMR presents some challenges. However, the molecular mobility of hydration water in API hydrates can be determined by spin-spin relaxation measurement, providing the spin-spin relaxation time (T2) of the water protons is significantly different from that of the API protons. Furthermore, the T1 of the water protons may be a useful indicator of water mobility if the ratio of water protons to API protons is sufficiently large or if the water protons have a correlation time (τc) corresponding to the T1 minimum, such that the T1 of the water proton is sensitively reflected in the measured T1 value without being affected by spin diffusion between the water and the API protons. For example, in Na2HPO4 · 12H2O and Na2HPO4 · 2H2O, water protons are predominant (24/25 and 4/5, respectively). Na2HPO4 · 12H2O exhibited slower spin-spin relaxation (larger T2), as shown in Figure 2.3, and faster spin-lattice relaxation (smaller T1) (Figure 2.4), compared with Na2HPO4 · 2H2O, which indicates that either T1 or T2 can be used as an indicator for approximate comparison of the molecular mobility of hydration water (Yoshioka and others 2008). Moreover, even if the ratio of water protons to API protons is not particularly large, and even if the water proton does not have a τc corresponding to the T1 minimum, it may be possible to compare the molecular mobility of hydration water in API hydrates

28


1400 1200

Intensity

1000 800 600

12H2O

400 200 0

2H2O 0

20

40

60

Time (μs)

Figure 2.3. Free-induction decay for Na2HPO4 · 12H2O and Na2HPO4 · 2H2O. 1.5 12H2O

1.0

Intensity

0.5

2H2O

0.0 -0.5 -1.0 -1.5

0

50

100

150

200

Pulse interval (s)

Figure 2.4. Spin-lattice relaxation for Na2HPO4 · 12H2O and Na2HPO4 · 2H2O.

based on measured T1 values if both the T1 of the API proton and the ratio of water protons to API protons are similar for all of the API hydrates compared. We measured spin-spin and spin-lattice relaxation for the 11 API hydrates listed in the Japanese Pharmacopoeia by using pulsed 1H-NMR to examine the possibility of determining the molecular mobility of hydration water in API hydrates by NMR relaxation measurement (Yoshioka and others 2008). Of the four antibiotic hydrates


Intensity

1500

29

ceftazidime

1000

500

0

0

20

40

60

80

100

80

100

Time (μs)

Intensity

1500

cefazolin sodium

1000

500

0

0

20

40

60

Time (μs)

Figure 2.5. Free-induction decay for ceftazidime and cefazolin sodium hydrates.

(cefazolin sodium, ceftazidime, amoxicillin, and ampicillin), all exhibited both Gaussian-type decay and Lorentzian decay, as exemplified by ceftazidime and cefazolin sodium hydrates (Figure 2.5). The other seven API hydrates exhibited only Gaussian-type decay, as exemplified by quinidine sulfate and scopolamine hydrobromide hydrates (Figure 2.6). The time courses of spin-spin relaxation observed for the four antibiotic hydrates were well fitted to Equation 2.1 by using the proportion of water protons calculated from the water content measured by the Karl Fischer method, as shown by the regression curve in Figure 2.5. I ( t ) = I 0 ( PG exp ( − (1 2 ) (t T2(G) ) ) + PL exp ( − t T2(L ) )) 2

(2.1)

30


1500

Intensity

quinidine sulfate 1000

500

0

0

20

40

60

80

100

Time (μs)

1500

Intensity

scopolamine hydrobromide 1000

500

0

0

20

40

60

80

100

Time (μs)

Figure 2.6. Free-induction decay for quinidine sulfate and scopolamine hydrobromide hydrates.

where I(t) and I0 are signal intensity at time t and time 0, respectively. T2(G) and T2(L) are T2 for Gaussian decay and Lorentzian decay, respectively, and PG and PL are the proportion of protons that show Gaussian decay and Lorentzian decay, respectively. Therefore, all of the water protons in the molecule are considered to show Lorentzian decay, and the Gaussian decay is attributed to the drug protons. The other seven API hydrates did not exhibit Lorentzian decay, indicating that all water protons and drug protons in the molecule showed Gaussian decay. The T2 value of the water protons was calculated according to Equation 2.2, assuming that the T2 of the water protons is similar to that of the drug protons. I ( t ) = I 0 exp ( − (1 2 )( t T2 )

2

)

(2.2)


31

Ease of Evaporation for Hydration Water as Determined by DSC and Water-Sorption Isotherm Measurements The four antibiotic hydrates, which exhibited Lorentzian decay upon spin-spin relaxation, showed a single endothermic peak due to water evaporation, as shown in Figure 2.7a. The onset temperature was determined as a parameter for approximate comparison of ease of evaporation among the API hydrates, along with ease of evaporation under isothermal conditions as determined by water-vapor-sorption analysis (Figure 2.8). Onset temperature is known to depend on various factors, such as the heating rate, the shapes of the pan and lid, the surface area of the sample, and the flow rate of nitrogen gas. In this study, controllable factors such as the heating rate and the flow rate of nitrogen gas were kept constant, and a pan without a lid was used. The ease of evaporation for the four antibiotic hydrates as determined based on the observed onset temperature was in this order: ampicillin < amoxicillin < ceftazidime < cefazolin sodium. Berberine chloride, quinine hydrochloride, scopolamine hydrobromide, and saccharin sodium hydrates, which did not exhibit Lorentzian decay, showed two endothermic peaks, indicating the presence of two water populations: molecules that evaporate at high temperature and others that evaporate at lower temperature (Figure 2.7b). Pipemidic acid, sulpyrine, and quinidine sulfate hydrate, which did not exhibit Lorentzian decay, showed a single endothermic peak at a relatively high temperature (Figure 2.7c). The water-sorption isotherms observed for cefazolin sodium hydrates, which showed Lorentzian decay upon spin-spin relaxation, indicate that, during the desorption process, the water content decreased with decreasing humidity in the range of 90% relative humidity (RH) to 0% RH, with a significant slope in the plot of the water content versus humidity (Figure 2.8a). Pipemidic acid hydrate gave a water desorption isotherm in which the water content was constant over a wide range of humidity, as shown in Figure 2.8b. The water desorption isotherm observed for scopolamine hydrobromide showed flat lines at two levels of water content (Figure 2.8c). Correlation of Water Mobility as Determined by NMR with That as Determined by DSC and Water-Sorption Isotherm Measurements The T2 values determined based on the Lorentzian decay observed for hydration water in the four antibiotic hydrates increased as the onset temperature of the endothermic peak due to water evaporation decreased, as shown in Figure 2.9. This indicates that hydration water, which evaporates at lower temperatures, has greater molecular mobility as determined by T2, suggesting that ease of evaporation under nonisothermal conditions is correlated with T2. As exemplified by ceftazidime hydrate shown in Figure 2.10, T2 increased significantly with increasing temperature, indicating that T2 reflects the increases in molecular mobility associated with increases in temperature. Thus, molecular mobility can be considered to correlate with T2. As shown in Figure 2.11, antibiotic hydrates with

Figure 2.7. Differential scanning calorimetric (DSC) thermograms for active pharmaceutical ingredient (API) hydrates. W/g, watt per gram of sample.

32

(a)

Number of water molecules per hydrate molecule

6 5 4

cefazoline sodium

3 2 1 0

0

20 40 60 80 Relative humidity (%RH)

100

(b)


6 5 pipemidic acid

4 3 2 1 0

0


100

(c)


6

4 3 2 1 0

Figure 2.8. hydrates.

scopolamine hydrobromide

5

0


100

Water-sorption isotherms for active pharmaceutical ingredient (API)

33

34


1.10

1.80

1.05

1.75

1.00

1.70

0.95

1.65

0.90 3.1

3.2

3.3

3.4

3.5

log T2 (μs)

log T2 (μs)

Figure 2.9. Correlation between onset temperature and T2 for four antibiotic hydrates. DSC, differential scanning calorimetry.

1.60 3.6

1000/T

Figure 2.10. Temperature dependence of T2 for ceftazidime hydrates (circles) and pipemidic acid (triangles) hydrates.

smaller T2 values showed a smaller change in T2 with temperature change. This finding suggests that lower values of T2 reflect a smaller scale of molecular motion of water, with lower activation energies. The values of T2 for the Gaussian decay observed for hydration water in the API hydrates other than the antibiotic hydrates did not vary significantly. Furthermore, the onset temperatures of the single endothermic peaks due to water evaporation for quinidine sulfate, pipemidic acid, and sulpyrine hydrates (Figure 2.7c), as well as


35

Figure 2.11. Correlation between T2 and temperature dependence of T2 for four antibiotic hydrates.

each of the two peaks due to water evaporation observed for quinine hydrochloride, scopolamine hydrobromide, saccharin sodium, and berberine chloride hydrates (Figure 2.7b), were not correlated with T2. These findings suggest that the molecular mobility of hydration water that shows Gaussian decay is too low to be reflected in T2. The endothermic peaks shown in Figure 2.7c seem to be due to hydration water with low molecular mobility, as suggested by the finding that their onset temperatures were not correlated with T2. Changes in T2 associated with changes in temperature were much smaller than those observed for the antibiotic hydrates that exhibited Lorentzian decay, as exemplified by pipemidic acid in Figure 2.10. This finding also indicates that the molecular mobility of hydration water is too low to be reflected in T2; thus, Gaussian decay rather than Lorentzian decay is observed, in contrast to the antibiotic hydrates. The water content versus humidity plot for pipemidic acid showed a flat line at three water molecules per hydrate molecule, and evaporation of these water molecules was observed under only very low humidity conditions (Figure 2.8b). This also supports the conclusion that the hydration water molecules show low molecular mobility. For the double endothermic peaks presented in Figure 2.7b, the peak at a higher temperature may be attributable to hydration water with low mobility, as observed for pipemidic acid hydrate, whereas the one observed at a lower temperature may be attributable to hydration water with higher mobility. The water content versus humidity plot for scopolamine hydrobromide showed flat lines at two levels of water content (Figure 2.8c), suggesting the presence of two water populations: molecules that evaporate at high humidity, and others that evaporate at lower humidity. This seems to be consistent with the observation of two endothermic peaks in DSC. The onset temperatures of evaporation for water molecules that easily evaporate at low humidity were lower than those observed for water molecules that exhibited Lorentzian decay, such as those of ceftazidime hydrate, indicating greater ease of evaporation. Such ease of

36


evaporation may explain why Lorentzian decay was not observed in NMR relaxation measurements. Although the T1 of protons in the four antibiotic hydrates was determined, correlation between T1 and T2 was not observed. This finding indicates that for API hydrates containing a significant amount of drug protons, such as these antibiotic hydrates, the molecular mobility of hydration waters is not reflected in T1. Usefulness and Limitation of Determination of Water Mobility by NMR It was found that T2 is a useful parameter that can indicate the molecular mobility of water of hydration, which has relatively high mobility and shows Lorentzian decay upon spin-spin relaxation. For these water molecules, molecular mobility as determined by T2 is correlated with ease of evaporation under both nonisothermal and isothermal conditions, such that water molecules with greater ease of evaporation have higher T2 values. In contrast, for hydration water that has low mobility and shows Gaussian decay, T2 was found not to correlate with ease of evaporation under nonisothermal conditions, suggesting that molecular motion that determines the ease of evaporation is not reflected in T2; in this case, T2 cannot be used as a parameter to indicate molecular mobility. The water molecules in the API hydrates were found to have wide-ranging molecular mobilities, from low molecular mobility that could not be evaluated by NMR relaxation times, such as the water molecules in pipemidic acid hydrate, to high molecular mobility that could be evaluated by NMR relaxation times, such as the water molecules in ceftazidime hydrate.

Molecular Mobility of Water Coexisting with Various Pharmaceutical Excipients Pharmaceutical excipients exhibit a variety of water-sorption behaviors, as shown in Figure 2.12, which compares water contents at 60% RH and 10% RH determined for widely used pharmaceutical excipients (Yoshioka and others 2007). Alpha-cornstarch and alpha-potato starch absorb a similar amount of water as povidone (PVP) at 10% RH but much less at 60% RH than PVP. Thus, this figure indicates a variety of watervapor-sorption behaviors among excipients. The molecular mobility of water absorbed in dextran, methylcellulose, and PVP was compared by DRS (Yoshioka and others 1999). For each of the water-excipient mixtures, the water content of which was adjusted to be approximately the same, two relaxation processes were observed at frequencies of 108–109 Hz and 109–1010 Hz, indicating the presence of two water populations, one with high mobility and one with lower mobility. As shown in Table 2.1, the ratio of high-mobility water to lowermobility water calculated by curve-fitting of spectra was the smallest for dextran and the largest for PVP. These data indicate that pharmaceutical excipients contain water molecules with widely ranging ratios of high and low mobilities, even at a similar water content.

PVP cros-PVP CMC-Na CMS-Na cros-CMC-Na CMC-Ca Potato starch Cornstarch Pullulan alpha-Cornstarch 60% RH 10% RH

alpha-Potato starch L-HPC Dextrin CMC PVP/VA Dextrin MC Powdered cellulose MCC HPC HPMC 50

0

100

150

200

250

Water sorbed (mg/g)

Figure 2.12. Water contents of various pharmaceutical excipients at 10% RH and 60% RH. cros, cross-linked; Na, sodium; Ca, calcium; CMC, carboxymethyl cellulose (carmellose); CMS, carboxymethyl starch; HPC, hydroxypropyl cellulose; HPMC, hydroxypropylmethyl cellulose; L-HPC, low-density hydroxypropyl cellulose; MC, methyl cellulose; MCC, microcrystalline cellulose; PVP, povidone; and PVP/VA, copovidone. Table 2.1. The ratio of high-mobility water to low-mobility water in water-excipient mixtures Water content (g/g)

% RH

[H2O]h/[H2O]l

Dextran

0.29

86

0.93

MC

0.23

86

1.7

MC

0.38

98

3.3

PVP

0.34

75

4.4

MC, methylcellulose; and PVP, povidone.

37

38


Concluding Remarks Water molecules present in solid APIs and those coexisting with pharmaceutical excipients have widely ranging molecular mobilities, as determined by NMR, DRS, DSC, and water-sorption isotherm measurements. Therefore, it is very important to gain insight into the molecular mobility of water in the formulation of solid APIs.

References Aso Y, Sufang T, Yoshioka S, Kojima S. 1997. Amount of mobile water estimated from 2H spin-lattice relaxation time, and its effects on the stability of cephalothin in mixtures with pharmaceutical excipients. Drug Stability 1:237–42. Shalaev EY, Zografi G. 1996. How does residual water affect the solid-state degradation of drugs in the amorphous state? J Pharm Sci 85:1137–41. Yoshioka S, Aso Y, Kawanishi T. 2007. Water sorption isotherms of pharmaceutical excipients listed in Japanese Pharmacopoeia. Pharm Regul Sci 38:228–34. Yoshioka S, Aso Y, Kojima S. 1999. The effect of excipients on the molecular mobility of lyophilized formulations, as measured by glass transition temperature and NMR relaxation-based critical mobility temperature. Pharm Res 16:135–40. Yoshioka S, Aso Y, Osako T, Kawanishi T. 2008. Wide-ranging molecular mobilities of water in active pharmaceutical ingredient (API) hydrates as determined by NMR relaxation times. J Pharm Sci 97:4258–68. Yoshioka S, Aso Y, Terao T. 1992. Effect of water mobility on dug hydrolysis rates in gelatin gels. Pharm Res 9:607–12.

Oral Presentations

3 The Effect of Water and Fat Contents on the Enthalpy of Dissolution of Model Food Powders: A Thermodynamic Insight A. Marabi, A. Raemy, A. Burbidge, R. Wallach, and I. S. Saguy Abstract The dissolution process of food powders is a topic of vast practical and commercial importance. However, the physical and chemical processes involved are far from being fully understood. Calorimetric determination of dissolution enthalpies (ΔHdiss) of food powders enables the extent of solute-solvent interactions to be assessed in terms of thermodynamic parameters. In this context, this work studied the effect of water and fat content representing typical food powders on the enthalpy of dissolution measured by isothermal calorimetry. The model food powders were obtained by freeze-drying a mixture of skim-milk powder, maltodextrin, and variable amounts of butter fat. The moisture content (MC) was determined gravimetrically, and the enthalpy of dissolution was measured by isothermal calorimetry at 30°C. The powders were studied in the dry state and after equilibration at different water activity (aw) values. Near-infrared spectroscopy and X-ray powder diffraction data indicated that the powders were in an amorphous state after freeze-drying. Crystallization of lactose was observed after exposure of the powders to the higher aw investigated. The enthalpy of dissolution decreased (less exothermic) with increasing fat content in the dry samples (MC = ∼1% dry basis [db]), ranging from −62 to −34 J/g for powders containing 0.7 and 45% fat (wet basis [wb]), respectively. The MC also had a significant effect on the enthalpy of dissolution. The exothermic enthalpy decreased from −62 to −5 J/g for powders containing 0.7% fat (wb) in the dry state (MC = 1.7% db) and after equilibration at 0.54 aw (MC = 11.4% db), respectively. A similar trend was observed for all other samples, for which the exothermic ΔHdiss of the equilibrated samples decreased with an increase in the MC.

Introduction The study of the dissolution process of powders started more than a century ago, possibly with the classic work of Noyes and Whitney (1897). The dissolution kinetics of powders are of critical importance in many applications, including food and pharmaceutical products. In the food industry, in particular, it is one of the significant factors that defines the quality of the product (Marabi and others 2007b). Frequently, the aim is to obtain a powder with good dissolution and reconstitution properties. The thermodynamic aspects of the dissolution of powders can be addressed by isothermal solution calorimetry, in which the heat of solution is measured. The output 41

42


is a composite of wetting responses, liquid penetration, dissolution phenomena, and any other interaction process that might occur (Buckton 1995; Gao and Rytting 2006). The significantly different dissolution behavior of crystalline and amorphous saccharides has also been studied (Miller and others 1997; Miller and de Pablo 2000; Salvetti and others 2007). All of the crystalline samples examined presented endothermic enthalpies of dissolution. Conversely, the same samples in the amorphous state showed an exothermic response. The effect of the moisture content (MC) on the thermodynamic response of dissolving powders was studied, and significantly less exothermic values were reported for amorphous lactose samples stored at increasing humidity (Hogan and Buckton 2000). As composition and especially moisture and fat contents are expected to affect the enthalpy of dissolution, the objective of the present study was to quantify the effects of increasing moisture and fat contents on the thermodynamic response measured during the dissolution process of a model food powder. It should be noted that the term dissolution is used in the present work, but other possible terms for this process have been suggested and discussed during this symposium. It was argued that dissolution applies to the process in which a crystalline material is put into solution and does not apply for amorphous materials because they can be defined as a solid solution. Some of the suggested terms included liquefying, rehydration, dilution of the glass, and redissolution or redispersion. However, there was no clear agreement, so we retained the term dissolution for this work. Clearly, this issue should be discussed, including questions regarding, for example, what would be the term to use for a powder containing crystalline and amorphous domains.

Experimental Methods Five samples containing different amounts of fat were produced by freeze drying (FD). The materials used included maltodextrin DE 21 (MD), skim-milk powder (SMP), and butter fat. The composition of the wet and dry mixes is listed in Table 3.1. The materials were mixed in water at 50°C and then homogenized in two steps at 50 and 250 bar, respectively. The samples were frozen at −55°C, FD at 10−6 bar for 48 h with

Table 3.1. Characterization of the model food powders Sample

A

B

C

D

E

Wet mix before freeze drying Butter fat (% wt/wt) Maltodextrin (% wt/wt) Skim-milk powder (% wt/wt) Water (% wt/wt)

0

5

10

15

20

14

14

14

14

14

7

7

7

7

7

79

74

69

64

59

14.3

29.3

35.7

45.0

Freeze-dried powder Fat (% wt/wt)

0.7

Water activity

0.06

0.05

0.05

0.05

0.05

Water content (g/100 g dry solids)

1.71

0.96

0.70

0.64

0.58

Effect of Water and Fat on Enthalpy of Dissolution

43

a stepwise temperature increase from −50° to 25°C and ground in a mill yielding a powder passing 30 mesh. All the samples were transferred to hermetically sealed aluminum pouches to avoid moisture uptake, and stored for at least 1 week prior to the calorimetric studies for internal equilibration of water within the matrix. The FD samples were then exposed to different saturated salt solutions (water activity [aw] values: 0.11, 0.22, 0.33, 0.43, and 0.54) in desiccators at 20° ± 1°C until no significant weight change was observed (∼4 weeks). The fat content of the different samples of the model powder was determined by the Mojonnier method (AOAC 2006). The MC was determined by exposing the samples at 102°C in vacuum to phosphorus pentoxide. The enthalpy of dissolution was quantified isothermally (30°C) in a Calvet calorimeter (Marabi and others 2007a, 2007b). The results are expressed in J/g of total sample weight (i.e., including the MC). The calorimetric curves obtained are integrated, yielding the heat (J/g) adsorbed or released during the complete dissolution of the solid sample. A negative value for the enthalpy of dissolution indicates the release of heat (exothermic process), and positive values indicate an absorption of heat (endothermic process).

Results and Discussion The freeze-dried particles presented a typical flakelike shape resembling broken glass, and increasing amounts of fat were observed at the surface of the particles (i.e., by scanning electron microscopy; data not shown). The X-ray powder diffraction (XRPD) patterns of the powders confirmed that all the samples were in the amorphous state after FD, as observed by the broad and diffuse halo with no sharp peaks (data not shown). The dissolution of all the powders at all the conditions tested produced exothermic responses. The effect of increasing the amount of fat in the samples is clearly related to a decrease in the amount of heat released during the dissolution process (Figure 3.1). The decrease in the enthalpy of dissolution (i.e., a less exothermic process) ranged from about −62 to −34 J/g for samples with 0.7% and 45% fat, respectively. The enthalpy of dissolution of pure butter fat was also measured, and a slight endothermic response was observed (1.7 J/g). This small value is expected because, when two immiscible compounds are mixed, only a very small calorimetric response representing the heat of immersion is measured. Therefore, the immersion of this ingredient is responsible for lowering the enthalpy of dissolution of the powders. To elucidate the effect of the fat content further, the enthalpy of dissolution measured for all aw was normalized by the amount of nonfat solids in the samples. Figure 3.2 clearly shows that the enthalpy of dissolution is independent of the amount of fat in the powders, because a single curve was obtained for all the conditions tested. Consequently, the exothermic response can be assumed to arise from the dissolution of the MD and the SMP ingredients. We have also shown the effects of the physical state of MD and SMP on the enthalpy of dissolution (Marabi and others 2007b). For FD amorphous samples, large exothermic responses were observed, whereas both

Figure 3.1. Typical dissolution calorimetry curves of the freeze-dried samples (aw ≤ 0.06) containing different amounts of fat. EXO, exothermic responses.

Figure 3.2. Enthalpy of dissolution of all the samples tested as a function of the water activity. Note that the enthalpy of dissolution (ΔHdiss) is normalized by the amount of nonfat content. Exo, exothermic responses.

44


45

Figure 3.3. Typical dissolution calorimetry curves of samples containing 14.3% fat equilibrated at various water activities. EXO, exothermic responses.

increased MC and recrystallized lactose in the SMP resulted in decreased exothermic responses. The different behavior of crystalline and amorphous powders is attributed to the higher entropy and internal free energy of the metastable amorphous state, leading to an enhanced dissolution rate and chemical reactivity, relative to the thermodynamically more favorable and stable crystalline state (Hancock and Zografi 1997; Hancock and Parks 2000; Hancock 2002; Wong and others 2006). When the enthalpy of dissolution was measured for the powders equilibrated at increasing aw, a decrease in the exothermic response was also observed (Figure 3.3). The ΔHdiss for the samples with 0.7% fat decreased from about −62 for the sample with an MC of 1.7% (FD) to −5 J/g for the sample with an MC of 11.2% (aw 0.54). Similar trends were observed for all other fat contents (Figure 3.4). The highly exothermic ΔHdiss values for the FD samples are possibly due to the hydration of hydrophilic groups in the powders. This effect was explained in terms of the exothermic nature of the wetting process, resulting in a less exothermic response for samples with higher MC as compared to a completely dry sample. It is often argued that the sorption of water by a dry powder is the first stage of wetting and that the first few molecules adsorbed on the surface are responsible for the greatest part of the overall exothermic wetting response (Buckton 1995; Hancock and Shamblin 1998; Hancock and Dalton 1999; Hogan and Buckton 2000). Increasing the fat concentration on the particles’ surface and the amount of adsorbed water leads to a reduced number of hydrogen-bonding sites available for additional sorption of water molecules during the dissolution process. Consequently, less

46


Figure 3.4. Enthalpy of dissolution (ΔHdiss) of all the samples tested as a function of their water and fat contents. db, dry basis; and EXO, exothermic responses.

exothermic values of ΔHdiss were observed for samples equilibrated at higher aw. Furthermore, the recrystallization of lactose at aw values higher than 0.43 (as observed by near-infrared spectroscopy and XRPD; data not shown) also contributes to a less exothermic overall response. In another publication (Marabi and others 2007b), we have shown that less exothermic responses are related to slower dissolution rates. Apart from the common wettability problems arising from the presence of fat on the surface of the powders, the current results indicate that the thermodynamics of the process might play a key role and could therefore be used to better characterize and predict the dissolution of food powders.

Conclusions The usefulness of the enthalpy of dissolution for studying the thermodynamic behavior of soluble food powders was demonstrated. Valuable information previously unavailable was obtained, providing a new insight into the dissolution process of food powders. These data complement those obtained with in situ kinetic measurements, providing the basis for better understanding the coupling between heat and mass transfer during the dissolution process. The effects of the fat and MC on the enthalpy of dissolution were elucidated. Higher water and fat contents led to less exothermic responses. This behavior is due to the negligible endothermic enthalpy of the fat, and the decrease in exothermic enthalpy measured as fewer hydrogen bonds are formed


47

during the dissolution in powders with higher MC. In addition, the recrystallization of lactose in the samples contributes to an endothermic response, thus lowering the overall exothermic value measured. The present data highlight that the dissolution is a complex phenomenon in which local heat transfer can play an important role.

References AOAC (Association of Official Analytical Chemists) 2006. Official methods of analysis, 16th ed. Washington, DC: Association of Official Analytical Chemists. Buckton G. 1995. Applications of isothermal microcalorimetry in the pharmaceutical sciences. Thermochim Acta 248:117–29. Gao D, Rytting JH. 2006. Use of solution calorimetry to determine the extent of crystallinity of drugs and excipients. Int J Pharm 151:183–92. Hancock BC. 2002. Disordered drug delivery: destiny, dynamics and the Deborah number. J Pharm Pharmacol 54:737–46. Hancock BC, Dalton CR. 1999. The effect of temperature on water vapor sorption by some amorphous pharmaceutical sugars. Pharm Dev Technol 4:125–31. Hancock BC, Parks M. 2000. What is the true solubility advantage for amorphous pharmaceuticals? Pharm Res 17:397–404. Hancock BC, Shamblin SL. 1998. Water vapour sorption by pharmaceutical sugars. Pharm Sci Technol Today 1:345–51. Hancock BC, Zografi G. 1997. Characteristics and significance of the amorphous state in pharmaceutical systems. J Pharm Sci 86:1–12. Hogan SE, Buckton G. 2000. The quantification of small degrees of disorder in lactose using solution calorimetry. Int J Pharm 207:57–64. Marabi A, Mayor G, Burbidge A, Wallach R, Saguy IS. 2007a. Assessing dissolution kinetics of powders by a single particle approach. Chem Eng J 139:118–27. Marabi A, Mayor G, Raemy A, Bauwens I, Claude J, Burbidge A, Wallach R, Saguy IS. 2007b. Solution calorimetry: a novel perspective into the dissolution process of food powders. Food Res Int 40:1286–98. Miller DP, de Pablo JJ. 2000. Calorimetric solution properties of simple saccharides and their significance for the stabilization of biological structure and function. J Phys Chem [B] 104:8876–83. Miller DP, de Pablo JJ, Corti H. 1997. Thermophysical properties of trehalose and its concentrated aqueous solutions. Pharm Res 14:578–90. Noyes A, Whitney WR. 1897. The rate of solution of solid substances in their own solutions. J Am Chem Soc 19:930–4. Salvetti G, Tognoni E, Tombari E, Johari GP. 2007. Excess energy of polymorphic states or glass over the crystal state by heat of solution measurement. Thermochim Acta 285:243–52. Wong SM, Kellaway IW, Murdan S. 2006. Enhancement of the dissolution rate and oral absorption of a poorly water soluble drug by formation of surfactant-containing microparticles. Int J Pharm 317:61–8.

4 “Solvent Water” Concept Simplifies Mathematical Modeling in Fermenting Dough, a Multiphase Semisolid Food S. M. Loveday and R. J. Winger

Abstract The shelf life of frozen dough depends on retention of yeast activity through frozen storage. It is difficult to study yeast cells in situ within the dough because they are embedded in a fine semisolid network structure. Mathematical modeling can simulate the environment around yeast cells and provide information about their interaction with that environment. This mathematical model predicts sugar consumption in fermenting dough, based on a mechanistic model of yeast cell fermentation in liquid broth. Adapting the liquid model to dough required knowledge of the water distribution and availability in dough. The solvent-water concept assumes that water in the presence of biopolymers and solutes can be divided into (a) solvent water, which has physical properties equivalent to pure liquid water; and (b) nonsolvent water, which has altered physical properties because of its interactions with solids and solutes. This assumption facilitated construction of an accurate model for sugar consumption in fermenting dough.

Introduction The yeast-leavened frozen-dough segment of the bakery industry supplies foodservice, commercial, and domestic consumers with products that require only thawing, proofing, and baking. In the proofing (AKA proving) stage, the dough is held under warm, humid conditions and expands due to the production of carbon dioxide by yeast cells fermenting sugars. The shelf life of frozen dough is limited by the decline of post-thaw proofing power. This is primarily because of a loss of yeast activity and carbon dioxide production. Inadequate proofing power means a frozen dough takes too long to proof or will not proof to adequate volume in the required time. If doughs are fermented (deliberately or accidentally) before freezing, the loss in proofing power is much faster and shelf life is dramatically shortened. The mechanistic basis for this effect is poorly understood, partly because of the colloidal-scale complexity, semisolid texture, and dynamic nature of dough. In most baking research, sugar concentrations in dough are expressed as weight percentages, which give no indication of concentration in different phases or locations within a dough piece. Comparisons with industrial fermentation literature would be easier if concentrations could be expressed as molarities. 49

50


Detailed mechanistic knowledge of dough fermentation requires an understanding of the physicochemical environment around yeast cells. Here we have sought to understand that environment via knowledge of the distribution and state of water in dough. We have mathematically modeled yeast substrate flux in fermenting dough in a way that facilitates comparisons with kinetic studies in other liquid and semisolid systems.

Dough Structure Dough constitutes a hierarchy of dispersed gaseous, liquid, and solid phases (Schiraldi and Fessas 2003). On the macroscopic scale, it is a foam of gas cells dispersed in a continuous semisolid viscoelastic phase. The semisolid phase is further phaseseparated on the colloidal scale into a bicontinuous network of hydrated gluten proteins and an aqueous phase containing water-soluble proteins and oligosaccharides, low molecular weight solutes, starch granules, and yeast cells (Eliasson and Larsson 1993). The colloidal phase separation is driven by hydrophobic association of gluten proteins and the immiscibility of gluten proteins with polysaccharides, soluble proteins, and starch (Tolstoguzov 1997). Water is the continuous medium of both phases, and its partitioning between phases is affected by dissolved solutes such as salts and sugars.

Solvent-Water Concept In the middle of the 20th century, the term nonsolvent water emerged from the realization that “the concentration of a solute in an aqueous solution is increased by the immersion of a solid [because] a certain amount of water, preferentially sorbed by the solid, has not become available as solvent” (Lindenberg and others 1963). This formed the basis of a widespread method for measuring water sorption by a solid material (Lindenberg and others 1963; Gary-Bobo 1967). The effective concentration of a probe solute in a solid-solute-water system was determined via accurate measurement of a colligative property such as vapor pressure. Since the amount of solute and its effective concentration were known, the amount of water in the solutewater part of the tertiary system could be calculated. This approach relied on the working assumption that total water could be cleanly delineated into solvent and nonsolvent fractions. That assumption was recognized as an oversimplification (Gary-Bobo 1967), but was useful in the absence of detailed knowledge about how and where water interacted with polymers or solutes. It is now thought that water interacts with solids and solutes via hydrogen bonding, dipole-dipole and ion-dipole forces, van der Waals interactions, and hydrophobic hydration (Franks 2000). The multiplicity of interaction types, strengths, time scales, and orientations create an extremely complex picture on the molecular scale. Most foods contain water, hydrophilic or amphiphilic biopolymers, and low molecular weight solutes. In intermediate-moisture and high-moisture foods, a proportion of total water behaves identically to pure water; this fraction is often termed bulk water

“Solvent Water” Concept Simplifies Mathematical Modeling

51

(Garti and others 2001). The remaining water exhibits different physical properties than pure water (e.g., fugacity, heat capacity, and freezing point) by virtue of its interactions with solutes or polymers. Moreover, it is not homogeneous, as previously thought. The water fraction that does not behave like pure water has attracted names such as unfreezable and bound. These are ill-defined and misleading terms (Franks 1991), but nonetheless have gained widespread use. Although the term bulk water has attracted relatively little criticism, it gives the impression of excluding water that cannot be readily separated from a sample by physical means; for example, water in capillaries. Solvent water is a less ambiguous alternative. For the purposes of mathematical modeling, dividing water into two fractions based on similarity to pure water, although not strictly representative of the real situation, reduces the degree of complexity required in model equations.

Solvent Water in Dough Studies of water in dough have found several populations of water molecules with different physical properties. Solvent water appears only above a certain looselydefined water-content threshold. Below 20–25 g H2O per 100 g dry matter (g H2O · [100 g DM]−1) or water activity (aw) of ∼0.8, the latent heat of water sorption by flour is greater than the latent heat of condensation (Bushuk and Winkler 1957; Rückold and others 2003), indicating that water interacts with polymers in flour (proteins, starch, pentosans). The latent heat of adsorption approaches the latent heat of condensation at 20–30 g H2O · (100 g DM)−1, indicating capillary condensation of solvent water (Bushuk and Winkler 1957; Ruckold and others 2003). Moisture-sorption isotherms curve sharply upward in this region (Bushuk and Winkler 1957; Roman-Gutierrez and others 2002a). Recent nuclear magnetic resonance studies have fitted proton-relaxation data from dough with continuous spectra featuring three distinct peaks (Ruan and Chen 1998; Ruan and others 1999; Kou and others 2002; Esselink and others 2003). Only two proton populations with low and intermediate mobility are observed below 23 g H2O · (100 g DM)−1 (Ruan and others 1999). Increasing moisture content to 35 g H2O · (100 g DM)−1 leads to (a) the disappearance of the low-mobility proton population; (b) enlargement of the intermediate-mobility population, which shifts to slightly lower mobility; and (c) the appearance of one or more high-mobility populations (Ruan and Chen 1998; Ruan and others 1999). The high-mobility population fits the description of solvent water. Differential thermal analysis (DTA) (Davies and Webb 1969; Bushuk and Mehrotra 1977) and differential scanning calorimetry (DSC) experiments (Roman-Gutierrez and others 2002b) have reported the appearance of water freezable at −50°C only where the water content of dough is more than 30–33 g H2O · (100 g DM)−1. These findings should be interpreted cautiously in light of objections raised by Hatley and others (1991) to such methodologies. Davies and Webb (1969) concluded that all water

52


above 33 g H2O · (100 g DM)−1 was freezable at −50°C, in agreement with the magnetic resonance study by Toledo and others (1968). These results from independent research groups using different methodologies are in quite good agreement that solvent water, as described here, is not present until the water content of dough exceeds 0.3 g of water per gram of flour DM. In this study, it was assumed that all water above 0.3 g per g DM was solvent water.

Materials and Methods Dough Manufacture Full details of dough manufacture and sugar extraction are provided by Loveday and Winger (2007). Each 1-kg batch of dough contained 600 g high-grade white wheat flour (11.5% protein, 12.0% moisture), 330 g water, 20 g compressed yeast (67.3% water), 20 g canola oil, 10 g iodized salt, and 20 g glucose, fructose, or sucrose. Ingredients were mixed for 18 min in a domestic breadmaker. Doughs were divided by hand into 50-g pieces that were shaped into slabs, sealed in plastic bags, and fermented at 30°C in a temperature-controlled room for 0–180 min. Sugar Extraction and Analysis Approximately 30 g of dough was quench-frozen in liquid nitrogen and shattered to a powder in a precooled laboratory Waring blender. A 2.5-g sample of frozen dough powder was added to 25 mL of water at room temperature and homogenized for 30 s. An aliquot of homogenate was filtered through a 0.8-μm filter into a 1.5-mL plastic tube. Extracts were held at 85°C in a water bath for 1 h to inactivate enzymes, cooled on ice for 10 min, and centrifuged. The supernatant was analyzed for glucose, fructose, and sucrose content by enzymatic assays (BioAnalysis kits; Roche Diagnostics, Mannheim, Germany). Results were expressed as millimoles (mmol) per 100 g dough (fresh weight). Duplicate analyses were performed on three independent doughs. Sugar uptake rates were expressed as differential equations and solved numerically with Matlab version 6.5 release 13 (Mathworks, Natick, MA, USA).

Results and Discussion The aqueous phase of dough is analogous to the liquid medium in broth culture; that is, a solution of sugars and other nutrients in which yeast cells are suspended. Glucose uptake was described with a hyperbolic equation (Equation 4.1) derived from a mechanistic description of sugar-carrier proteins traversing the cell membrane (CornishBowden 1995). VG = Vmax G ⋅ X ⋅

G G + KG

(4.1)

VG is the rate of glucose uptake (mmol · L−1 · h−1), Vmax G is the maximum specific rate of glucose uptake (mmol · g biomass−1 · h−1), X is yeast biomass concentration


53

(g biomass · L−1), G is the concentration of glucose (mmol · L−1), and KG is the affinity constant (mmol · L−1). Saccharomyces cerevisiae cells consume glucose in preference to fructose when both are available (Serrano and De la Fuente 1974). In broth cultures fed with a mixture of glucose and fructose, the influence of glucose on fructose uptake is well fitted by Equation 4.2 (Barford and others 1992), which is derived from mechanistic enzyme competitive inhibition equations commonly seen in enzymology textbooks (e.g., Cornish-Bowden 1995). VF = Vmax F ⋅ X ⋅

F G ⎞ ⎛ F + KF ⎜ 1 + ⎟ ⎝ K GF ⎠

(4.2)

KGF is a constant describing competitive inhibition of fructose uptake by glucose (mmol · L−1), while F, VF, Vmax F, and KF are analogous to G, VG, Vmax G, and KG in Equation 4.1. The total moisture present in doughs, calculated from the moisture content of ingredients, was 41.55 g · (100 g dough)−1. Doughs contained 60 g flour per 100 g dough, and flour contained 12.0% moisture. According to the literature, nonsolvent water comprised 0.3 g per 100 g flour solids; that is, 0.3 × 60 (1 − 0.12) = 15.84 g · (100 g dough)−1. Solvent water was therefore 41.55 − 15.84 = 25.71 g · (100 g dough)−1. It was assumed that all the solvent water was in the aqueous phase and that the density of solvent water was 103 g · L−1. The latter assumption enabled conversion from molalities to molarities so that kinetic constants were in the same units as those in the fermentation literature. Glucose and fructose contents expressed in mmol · (100 g dough)−1 were converted to molarities in the aqueous phase by dividing by 25.71 × 10−3 L · (100 g dough)−1. It was assumed that the solids in compressed yeast (32.7% solids) comprised biomass only. Biomass concentration in the solvent water (X) was calculated from the amount of compressed yeast and the volume of solvent water in dough. Cell numbers were assumed to remain constant, in agreement with the low biomass yield from anaerobic fermentation (Chen and Chiger 1985). In yeasted doughs made with 2% added glucose or fructose only, sugar was consumed at a constant rate during fermentation at 30°C. Vmax G and Vmax F were calculated from the rate of decline of each sugar during 90 min of fermentation at 30°C. Sucrose was almost completely hydrolyzed during mixing (Loveday and Winger 2007). Initial values of G and F (designated Gi and Fi) were calculated from glucose and fructose concentrations immediately after mixing in doughs made with 2% added sucrose. Experimental parameters are summarized in Table 4.1. KG, KF, and KGF were initially set at the values reported by Barford and others (1992) and then modified to improve fit to experimental results. Equations 4.1 and 4.2 fitted glucose and fructose consumption well (Figure 4.1). KG was two orders of magnitude higher than the value used by Barford and others (1992) but of similar magnitude to inhibition coefficients

Figure 4.1. Concentration of glucose (top) and fructose (bottom) in dough made with 2% yeast and 2% added sucrose fermenting at 30°C. Points are experimental data (mean ± SE of six assay results) and lines are fits from Equations 4.1 and 4.2. Sugar concentrations are expressed as mmol · L−1 in the solvent water (left, y-axis) or as a weight percentage of dough on a wet basis (right, x-axis). KG, affinity constant; and KGF, a constant describing competitive inhibition of fructose uptake by glucose.

54


55

Table 4.1. Summary of mathematical model parameters Symbol

Description

Unit

Value

Gi

Initial glucose concentration

mmol · L−1

250

Fi

Initial fructose concentration

mmol · L−1

389

X

Biomass concentration

(g biomass) · L−1

Vmax G

Maximal glucose uptake rate

mmol · (g biomass)−1 · h−1

6.53

Vmax F

Maximal fructose uptake rate

mmol · (g biomass)−1 · h−1

6.26

25.4

Table 4.2. Affinity constants for glucose uptake by Saccharomyces cerevisiae reported in various studies Reference

KG (mmol · L−1)

Glucose concentration (mmol · L−1)

Maier and others 2002 (HXT1)

129

111

Serrano and De la Fuente 1974

100

100

Elbing and others 2004

76

111

This work

50

250

Reifenberger and others 1997

46

100

Maier and others 2002 (HXT3)

34.2

111

Barford and others 1992

0.5

55.6

KG, affinity constant; HXT1 and HXT3, acronyms for specific glucose transporter proteins in S. cerevisiae.

in other reports (Table 4.2) (Serrano and De la Fuente 1974; Bisson and Fraenkel 1983; Reifenberger and others 1997; Maier and others 2002; Elbing and others 2004). At 0.35 mmol · L−1, KFG was similar to other reports of 0.27 (Herwig and others 2001) and 1.0 (Barford and others 1992).

Conclusions Dividing water in semisolid foods into solvent and nonsolvent is a simplification, but a useful one. There is quite good consensus among researchers that in dough, ∼0.3 g water per gram of dry matter has the characteristics of nonsolvent water. The assumption that the remainder was solvent water simplified mathematical modeling and facilitated the use of liquid system models to predict sugar-fermentation rates in dough.

References Barford JP, Phillips PJ, Orlowski JH. 1992. A new model of uptake of multiple sugars by S. cerevisiae (part 1). Bioproc Eng 7:297–302. Bisson L, Fraenkel DG. 1983. Involvement of kinases in glucose and fructose uptake by Saccharomyces cerevisiae. Proc Natl Acad Sci USA 80:1730–4. Bushuk W, Mehrotra VK. 1977. Studies of water binding by differential thermal analysis. II. Dough studies using the melting mode. Cereal Chem 54:320–5.

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Bushuk W, Winkler CA. 1957. Sorption of water vapor on wheat flour, starch, and gluten. Cereal Chem 34:73–86. Chen SL, Chiger M. 1985. Production of baker ’s yeast. In: Moo-Young M, editor. Comprehensive biotechnology: the principles, applications, and regulations of biotechnology in industry, agriculture, and medicine. Oxford: Pergamon. p 429–62. Cornish-Bowden A. 1995. Fundamentals of enzyme kinetics. London: Portland. Davies RJ, Webb T. 1969. Calorimetric determination of freezable water in dough. Chem Ind (London) 1969:1138–9. Elbing K, Larsson C, Bill RM, Albers E, Snoep JL, Boles E, Hohmann S, Gustafsson L. 2004. Role of hexose transport in control of glycolytic flux in Saccharomyces cerevisiae. Appl Environ Microbiol 70:5323–30. Eliasson AC, Larsson K. 1993. Cereals in breadmaking: a molecular colloidal approach. New York: Marcel Dekker. Esselink EFJ, Van Aalst H, Maliepaard M, Van Duynhoven JPM. 2003. Long-term storage effect in frozen dough by spectroscopy and microscopy. Cereal Chem 80:396–403. Franks F. 1991. Hydration phenomena: an update and implications for the food processing industry. In: Levine H, Slade L, editors. Water relationships in foods: advances in the 1980s and trends for the 1990s. New York: Plenum. p 1–19. Franks F. 2000. Water: a matrix of life. 2nd ed. Cambridge: Royal Society of Chemistry. Garti N, Asering A, Fanun M, Leser ME, Ezrahi S. 2001. Sub-zero temperature behavior of water in W/O microemulsions. In: Berk Z, Leslie RB, Lillford PJ, Mizrahi S, editors. Water science for food, health, agriculture and environment. International Symposium on the Properties of Water in Foods 8. Lancaster, PA: Technomic. p 97–124. Gary-Bobo CM. 1967. Nonsolvent water in human erythrocytes and hemoglobin solutions. J Gen Physiol 50:2547–64. Hatley RHM, Van den Berg C, Franks F. 1991. The unfrozen water content of maximally freezeconcentrated carbohydrate solutions: validity of the methods used for its determination. Cryo Lett 12:113–24. Herwig C, Doerries C, Marison I, von Stockar U. 2001. Quantitative analysis of the regulation scheme of invertase expression in Saccharomyces cerevisiae. Biotechnol Bioeng 76:247–58. Kou Y, Ross EW, Taub IA. 2002. Microstructural domains in foods: effect of constituents on the dynamics of water in dough, as studied by magnetic resonance spectroscopy. In: Levine H, editor. Amorphous food and pharmaceutical systems. Cambridge: Royal Society of Chemistry. p 48–58. Lindenberg AB, Dang-Vu-Bien, Castan-Rechencq E. 1963. Constancy of extrapolated amount of nonsolvent water in cellulose, immersed in different salt solutions of varying concentration. Nature 200:358–9. Loveday SM, Winger RJ. 2007. Mathematical model of sugar uptake in fermenting yeasted dough. J Agric Food Chem 55:6325–9. Maier A, Volker B, Boles E, Fuhrmann GF. 2002. Characterisation of glucose transport in Saccharomyces cerevisiae with plasma membrane vesicles (countertransport) and intact cells (initial uptake) with single Hxt1, Hxt2, Hxt3, Hxt4, Hxt6, Hxt7 or Gal2 transporters. FEMS Yeast Res 2:539–50. Reifenberger E, Boles E, Ciriacy M. 1997. Kinetic characterization of individual hexose transporters of Saccharomyces cerevisiae and their relation to the triggering mechanisms of glucose repression. Eur J Biochem 245:324–33. Roman-Gutierrez AD, Guilbert S, Cuq B. 2002a. Distribution of water between wheat flour components: a dynamic water vapour adsorption study. J Cereal Sci 36:347–55. Roman-Gutierrez AD, Guilbert S, Cuq B. 2002b. Frozen and unfrozen water contents of wheat flours and their components. Cereal Chem 79:471–5. Ruan RR, Chen PL. 1998. Water in foods and biological materials: a nuclear magnetic resonance approach. Lancaster, PA: Technomic. Ruan RR, Wang XA, Chen PL, Fulcher RG, Pesheck P, Chakrabarti S. 1999. Study of water in dough using nuclear magnetic resonance. Cereal Chem 72:231–5.


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Rückold S, Isengard H-D, Hanss J, Grobecker KH. 2003. The energy of interaction between water and surfaces of biological reference materials. Food Chem 82:51–9. Schiraldi A, Fessas D. 2003. The role of water in dough formation and bread quality. In: Cauvain SP, editor. Breadmaking: improving quality. Cambridge, UK: Woodhead. p 306–20. Serrano R, De la Fuente G. 1974. Regulatory properties of the constitutive hexose transport in Saccharomyces cerevisiae. Mol Cell Biochem 5:161–71. Toledo R, Steinberg MP, Nelson AI. 1968. Quantitative determination of bound water by NMR. J Food Sci 33:315–7. Tolstoguzov V. 1997. Thermodynamic aspects of dough formation and functionality. Food Hydrocolloids 11:181–93.

5 Microdomain Distribution in Food Matrices: Glass Transition Temperature, Water Mobility, and Reaction Kinetics Evidence in Model Dough Systems Y. Kou

Abstract The concept of distribution of microstructural domains within an amorphous food matrix provides a basis for explaining the dispersion of its physical properties. These spatially separated domains correspond to differing molecular arrangements within and about the proteinaceous and aqueous phases of flour-based and meat-based food matrices. The volume averaging of these localized properties determines the global values of such properties as glass transition temperature (Tg), water mobility as reflected in proton spin-spin relaxation time (T2), and reaction rate constants (k). The changes in Tg, T2, and k (for a reduction reaction) as moisture content and temperature were changed were measured using primarily electron spin resonance and timedomain nuclear magnetic resonance (NMR) techniques. These measured values were then correlated where appropriate, and distribution functions for the microdomains were obtained from the Tg, T2, and k values.

Introduction Unlike many synthetic polymers, most food materials are complex in chemical composition, heterogeneous in structure, and reactive. The stability of a food matrix depends strongly on its microstructure, local viscosity, and associated molecular mobility (Slade and Levine 1991; Fennema 1996). Moisture content, concentration of constituents, and temperature are key factors that determine the structure and distribution of microstructural domains in an amorphous food matrix, and control local viscosity and molecular mobility. Microstructural domains are defined as regions of differing local viscosity and molecular mobility, which are randomly distributed. The concept of a distribution of microstructural domains within an amorphous food matrix provides a basis for explaining the dispersion in its physical properties (Lillford and others 1980; Kou and others 2002; Kou 2006). These spatially separated domains correspond to differing molecular arrangements within and about the proteinaceous and aqueous phases of flour-based and meat-based food matrices. Such arrangements influence local viscosity and molecular mobility. Consequently, the volume averaging of these localized properties in turn determines the global values of such properties as glass transition temperature (Tg), water mobility as reflected in proton spin-spin relaxation time (T2), and reaction rate constant (k). 59

60


To understand the nature of these microdomains, their distributions were either discerned or inferred from measurements made on dough matrices of different moisture contents and at different temperatures. The changes in Tg, T2, and k (for a reduction reaction) as moisture content and temperature are changed were measured using primarily electron spin resonance (ESR) and time-domain nuclear magnetic resonance (NMR) techniques. These measured values were then correlated where appropriate, and distribution functions for the microdomains were obtained from the Tg, T2, and k values. The main implication in the microdomains concept is that such localized differences in structure and properties need to be quantitatively considered to ensure that the physically, chemically, or microbiologically least-stable part of the matrix does not compromise quality or safety.

Materials and Methods Sample Preparation Wheat flour (12% protein, 11% moisture, 0.49% ash; Manildra Milling, Shawnee Mission, KS, USA) was used to make dough (flour + water) samples of varying water content (28%, 30%, 33%, and 35%, total weight basis). In the NMR experiment, samples were prepared prior to use, and ∼10 g of sample was weighed and placed into a glass test tube. In the kinetic study using ESR spectroscopy, erythorbic acid (Aldrich Chemical, Milwaukee, WI, USA), and TEMPO (tetramethylpiperidine nitroxide; Aldrich Chemical) were added to separate dough samples that were then mixed together by kneading equal volumes just prior to use. To ensure that the kneading uniformly distributed the reactants, aliquots of dough containing either TEMPO or erythorbic acid in judiciously chosen concentrations were kneaded together in 1 : 1, 1 : 2, 1 : 4, and 1 : 9 proportions, respectively; no differences in the results were found. NMR Experiments A 20-MHz PCT 20/20 NMR analyzer (Process Control Technology, Ft. Collins, CO, USA) was used in all NMR experiments. A 90° pulse sequence and a Carr-PurcellMeiboom-Gill (CPMG) pulse sequence were combined and used for acquisition of free-induction decay (FID) data for T2. Experimental parameters were set appropriately to maximize signal-to-noise ratio and to cover the entire relaxation range as completely as possible. ESR Experiments An ESR spectrometer equipped with a VT-2000 temperature controller (model EMX; Bruker Instruments, Billerica, MA, USA) was used to study the spectral pattern and chemical reduction of TEMPO. All samples were placed in a special plastic holder that fit into the resonator, the temperature of which was controlled by cold nitrogen gas. Temperature accuracy is ±0.1 K. The equilibrium time, even for the largest change in temperature, was less than 2 min. Microwave power was set to 0.63 mW. Scan

Microdomain Distribution in Food Matrices

61

range, scan rate, time constant, and field modulation amplitude were adjusted so that distortion of the spectra was avoided. Mathematical Model The dispersive model (Kou and others 2002; Kou 2006) describes a mathematical procedure for analyzing data obtained from experiments on the time-dependent behavior of dough samples subjected to various moisture and temperature conditions. The data consisted of either proton NMR or ESR signal arising from the reduction of TEMPO with erythorbic acid in the dough. The dough is viewed as an assemblage of many randomly distributed domains, each with specific physical properties. In each domain, a first-order or a pseudo–first-order reaction is assumed to take place, and the change in the NMR or ESR signal is taken as the sum of all changes associated with these reactions. The spatially distinct reactions are assumed to occur at different, random rates and to be affected by moisture and temperature, whose levels may be constant or variable over time. As described in the dispersive model, the mathematical procedure can be generalized for cases where more than one reaction or process of this sort is occurring simultaneously. Similar extensions can be made when two or more reactions are thought to take place. However, the parameter estimates become less reliable as the number of parameters increases, so there is a limit (essentially governed by the noise level of the data) beyond which applying this model is not useful.

Results and Discussion Glass Transition Temperature Representation of a system using an average value will be inadequate if the system is not sufficiently homogeneous in terms of physical structure and chemical composition (Ruan and others 1999). In fact, many food systems are heterogeneous, and such heterogeneity may be caused by ingredients’ incompatibility, poor mixing, or their redistribution during processing and storage. Therefore, there will be a nonuniform distribution of physical structure and moisture content within such a food matrix, and a variable spatial distribution of Tg values is expected. The NMR method for determination of Tg is based on the fact that polymers, when undergoing glass transition, experience a dramatic change in segmental mobility that can be measured by the spin-lattice and spin-spin reaction time constants from NMR experiments. The Tg can vary at the local or microscopic level and should be described in terms of an average and a dispersion. Ruan and others (1999) demonstrated this by measuring the Tg of a piece of bread (25 mm) while using magnetic resonance imaging with the spin-lattice (T1) mapping technique to achieve a resolution of 200 μm. The results indicate that microscopic distribution of Tg exists in bread matrix. The average Tg value is −10°C, with a standard deviation of 11°C. As in similar measurements on maltodextrin samples (Ruan and others 1999), the spread in Tg implies that microdomains exist, because most foods matrices are complex in chemical composition, heterogeneous in microstructure, and nonuniform in reaction reactivity.

62


Water Mobility (Proton Spin-Spin Relaxation Time, T2) Since spin-spin relaxation is an entropy relaxation process, it is directly linked to the environment of water molecules and can be used to measure their rotational mobility. Higher T2 values of protons on water imply an increased water mobility and, in turn, less viscous locality. Accordingly, measurements of T2 in dough matrices show that mobility decreases as moisture content and temperature decrease. It is widely believed that water molecules in foods are in some way associated with different sites on constituents or are exchanged with such site-associated water (socalled bound water) and relax faster than the molecules in bulk water and thus have much lower T2 than does bulk water (Ablett and others 1991). Therefore, use of a single relaxation time constant to describe complex and heterogeneous food systems may be an oversimplification. In a heterogeneous system, spins exist in a large variety of environments, giving rise to a wide range of relaxation time constants. Thus, it is reasonable to assume that a continuous relaxation time constant would arise from a continuum of different environments and exchange rates (Ablett and others 1991; Ruan and others 1999; Kou and others 2002). In the present experiment, a 90° or CPMG pulse sequence set the proton magnetization signals at their maximum values, which began to decay immediately after the pulse was removed. The resulting decay curve is usually termed free-induction decay (FID), representing both the fast (rigid proton signals) and slow (mobile proton signals) relaxation processes in samples, and can be described by a single-exponential or multiple-exponential equation that can yield a single T2 or several discrete T2 values. Rigid proton signals (i.e., in a microsecond range) originated from solid molecules (i.e., gluten or starch in this case) or from water molecules tightly associated with solids, whereas mobile proton signals (i.e., in a millisecond range) originated from water molecules with relatively high mobility (Kou and others 2000). The experimental data were fitted to our mathematical model in order to obtain predicted values and the probability density function for T2. There was good agreement between the predicted and experimental values in both the microsecond and millisecond ranges. Figure 5.1 shows the distribution of values of the probability density function for T2, in the microsecond range (i.e., rigid proton signals), for 30% moisture dough samples at different temperatures (258–298 K). Model fitting resulted in one T2 peak with a different dispersion for each dough sample. As expected, because of the lower overall average viscosity, the average T2 increases with increasing temperature. Also, peak dispersion increases with decreasing temperature, which indicates that the degree of homogeneity in sample decreases with decreasing temperature. Figure 5.2 shows the distribution of values of the probability density function for T2, in the millisecond range (i.e., mobile proton signals), for 30% moisture dough samples at differing temperatures (258–298 K). Model fitting resulted in two T2 peaks with a different dispersion for each dough sample. The appearance of a second peak in the mobile proton signal suggested that new physical or chemical environments were formed within the system. Average T2 values ranged from about 2–9 ms, which suggested that the signals detected were from water molecules with relatively high mobility.


63

3.5

2.5

Wt (1/T2)

Temperature (K)

298

3.0

288

2.0

278

1.5 1.0

268

0.5 0.0 0.00

258 0.02

0.04

0.06

1/T2

0.08

0.10

0.12

(μs-1)

Figure 5.1. The distribution of values of probability density function for T2, in the microsecond range (i.e., rigid proton signals), for 30% moisture dough at different temperatures (258–298 K).

Wt (1/T2 )

0.3

0.2

0.1

0.0 0.0

Temperature (K) 298

0.4

288

0.3

278 268 258

Wt (1/T2)

0.4

0.2 0.1 0.0 0.0

0.1

0.2

0.3

1/T2 (ms-1)

0.5

1.0

1/T2

1.5

(ms-1)

Figure 5.2. The distribution of values of probability density function for T2, in the millisecond range (i.e., mobile proton signals), for 30% moisture dough at different temperatures (258–298 K).

A comparison of these averaged T2 values with values obtained from an exponential model showed good agreement between the two approaches. However, the “continuum” approach used here is more consistent with the “continuum” nature of water mobility in food systems (Lillford and others 1980; Slade and Levine 1991). Furthermore, additional information may be obtained from a continuum model. For

64


example, a spectrum with a larger number of peaks or with broader peaks would be expected for heterogeneous samples rather than for relatively homogeneous samples. In other words, the number of peaks and their breadth could be used as a measure of the homogeneity of a sample under analysis. Reaction Kinetics To investigate further the microscopic distribution of local viscosity and the inhomogeneous reaction kinetics in a dough matrix, the spin probe (TEMPO) was dissolved in the dough matrix and then monitored with ESR spectroscopy. In the kinetic study, an excess of erythorbic acid was used as the reductant. Dough samples were prepared right before an experiment by mixing two equal-weight portions, one containing TEMPO and the other the reductant. Both the shape of the ESR spectral patterns for TEMPO and the changes in signal intensity for TEMPO, upon reduction to its spin-inactive form through reaction with erythorbic acid, were monitored at several combinations of temperature and moisture content. Although the ESR spectral pattern for TEMPO was, in all cases, affected by temperature and moisture content, under appropriate conditions there was only a slight change in the spectral pattern because the ESR signal for TEMPO was reduced by reacting with the erythorbic acid. This finding suggested that the decreases in fast-line intensity could be used to monitor the reaction. Since localized differences in matrix viscosity can affect the rates of reaction between two diffusing molecules, the reduction in spin-active TEMPO by erythorbic acid was monitored in dough matrices at different moisture contents and temperatures. Such reduction converts TEMPO to a spin-inactive state, so the spectral intensity decreases as the reaction proceeds. To simplify the kinetics, excess erythorbic acid was used, so a pseudo–first-order process should have been observed. However, a semilogarithmic plot of normalized signal intensity, It/Io, against time was curved rather than straight. This result indicated that the reduction of TEMPO by erythorbic acid did not conform to homogeneous kinetics. The ever-decreasing rate of reaction with increasing time was characteristic of dispersive kinetics, which could be modeled by taking into account the distribution of microstructural domains. In other words, the data could be analyzed on the basis of a microscopic distribution of local domains, each with characteristic local viscosity and associated rate constant. Experimental data for the ESR signal intensity of TEMPO as a function of reaction time were obtained at combinations of six temperatures (273–298 K) and four moisture contents (28%–35%). As expected, the higher the temperature, the faster was the reduction of TEMPO because of the lower overall average viscosity. The same trend was observed for the effect of moisture content (i.e., higher moisture content resulted in faster reduction). The distribution of values for the reaction rate constant as a function of temperature for 35% moisture dough samples is presented in Figure 5.3. The average reaction rate constant, kave, increased with increasing temperature because of lower overall average viscosity, while the dispersion about the peak also increased with increasing temperature, which indicates that the degree of sample inhomogeneity increased with increas-


65

Probability density function, Wt (k)

20 35% moisture

273K 15 278K 10

283K 288K

5

293K

0 0.0

0.2

298K

0.4

0.6

Reaction rate constant (k,

0.8

min-1)

Figure 5.3. Distribution of the reaction rate constant, k, as a function of temperature for 35% moisture dough.

Probability density function, Wt (k)

8 35%

288K

33%

6

30% 4

28%

2

0

0.0

0.1

0.2

0.3

0.4

0.5

Reaction rate constant (k, min-1)

Figure 5.4. Distribution of the reaction rate constant, k, as a function of moisture content in dough at 288 K.

ing temperature. Figure 5.4 shows the distribution of values of the probability density function, Wt(k), for reaction rate constant as a function of moisture content in dough samples at 288 K. The results indicate that the average reaction rate constant, kave, increased with increasing moisture content because of lower overall average viscosity. It was also observed that the dispersion about the peak decreased with increasing moisture content, which indicates that the degree of sample inhomogeneity decreased with increasing moisture content.

66


When the resulting kave values obtained from these analyses were plotted semilogarithmically against reciprocal temperature, the observed reduction reaction apparently followed the Arrhenius relationship, and the activation energies corresponded to ∼12 kcal/mol. This finding suggests that there are barriers to both diffusion and electron transfer (following encounter and complex formation). Overall, the kinetic results were consistent with other rheological and relaxational phenomena, all of which reflect dispersion in the data associated with spatial inhomogeneities in microstructure.

Conclusions The concept of a distribution of microdomains within a complex and heterogeneous food matrix provides a basis for explaining the observed dispersion in its volumeaveraged properties. Glass transition temperature, molecular mobility, local viscosity, and reactivity are properties that can vary at the local or microscopic level. They are best described in terms of an average and dispersion. Since physical, chemical, and microbiological changes can occur in regions of low viscosity or high reactivity, the distribution of microstructural domains should be considered in assessing food safety, quality, and stability.

References Ablett S, Darke AH, Lillford PJ. 1991. The effect of mechanical deformation on the movement of water in foods. In: Levine H, Slade L, editors. Water relationships in foods. New York: Plenum. p 453–63. Fennema R. 1996. Food chemistry. 3rd ed. New York: Marcel Dekker. Kou Y. 2006. Microdomain distributions in food matrices: kinetic evidence from the reduction of spinactive TEMPO in model dough systems. Paper presented at the Amorph 2006 Conference, University of Cambridge. Kou Y, Dickinson LC, Chinachoti P. 2000. Mobility characterization of waxy corn starch using wide-line 1 H nuclear magnetic resonance. J Agric Food Chem 48:5489–95. Kou Y, Ross EW, Taub IA. 2002. Microstructural domains in foods: effect of constituents on the dynamics of water in dough, as studied by magnetic resonance spectroscopy. In: Levine H, editor. Amorphous food and pharmaceutical systems. London: Royal Society of Chemistry. p 48–58. Lillford PJ, Clark AH, Jones DV. 1980. Distribution of water in heterogeneous food and model systems. In: Comstock MJ, editor. Water in polymers. American Chemical Society Symposium Series 127. Washington, DC: American Chemical Society. p 177–95. Ruan R, Long Z, Chang K, Chen PL, Taub I. 1999. Glass transition temperature mapping using magnetic resonance imaging. Trans ASAE 42:1055–9. Slade L, Levine H. 1991. Beyond water activity: recent advances based on an alternative approach to the assessment of food quality and safety. Crit Rev Food Sci Nutr 30:115–360.

Session 2 Water Essence and the Stability of Food and Biological Systems

Invited Speakers

6 Effect of Combined Physical Stresses on Cells: The Role of Water J.-M. Perrier-Cornet, M. Moussa, H. Simonin, L. Beney, and P. Gervais

Abstract The role of water in microorganism viability was envisaged through the application of combined physical perturbations. The combination of different physical parameters could enable one to balance the property variations (especially water related) resulting from the increase of one parameter alone. The first example shows that the combination of osmotic level and temperature can enable yeast cell survival to be optimized when following membrane fluidity variations. This analysis has enabled a better comprehension of cell inactivation during rehydration and dehydration. The second example deals with the combination effect of high hydrostatic pressure, low temperature, and medium water activity (aw) on Escherichia coli resistance. The synergetic effect of high pressure and low temperature was observed only at a pressure level lower than 300 MPa and with high water content. Otherwise, low temperature, as well as low aw, protect the microorganisms from inactivation even at an extreme pressure level (P > 600 MPa).

Introduction The change in physical environment (e.g., hydrostatic pressure and temperature) or physicochemical environment (e.g., water activity [aw] and pH) induces significant stress on eukaryotic and prokaryotic cells. Depending on how the level of perturbation and the kinetics of conditions change, this stress could lead to the inactivation of relevant cells. When high-level and rapid perturbations are used in a poor medium, cells have only few active systems for adaptation, and their response is, in this case, essentially passive. Under these conditions, cell resistance can be attributed to the cell’s constitution (e.g., a robust cell wall, adaptability of the cell membrane, its cytoskeleton) and the repair systems that the cell can use after its return to more favorable conditions. A combination of physical treatments can modulate the effect of each stress and provide interesting information about the mechanisms implicated. The biological basis of these interactions is not yet clearly understood. Numerous experiments have shown the role of cell osmotic balance and of cell membrane passive and active permeability. Membrane structure and fluidity seem to play an important role during dehydration, rehydration, and generally in all stress conditions. 71

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The effects of these intense perturbations on cell survival are highly important when food processes like drying, freezing, sterilization, and pasteurization are considered. In these processes, very drastic perturbations are applied to food products and their microorganisms. These perturbations were intended to inactivate pathogens (for food preservation) or preserve food and/or cells (by drying or freezing). These industrial processes generally combine different drastic physical modifications including temperature, osmotic pressure, and/or hydrostatic pressure. Combinations of physical perturbations have been experimented with in a model medium to understand the mechanisms leading to microbial inactivation. A better perception of such mechanisms would enable not only these food processes to be optimized but also would have other applications, like the conservation of human cells at ambient temperature or in a frozen state. We approach this research theme through two examples of physical perturbation combinations. The first example deals with the effect of hyperosmotic stress and the possibility of combining it with temperature. The second is centered on the effect of high hydrostatic pressure on cells and the effect of a combination of low temperature and/or low aw.

Example 1: Effects of Combined Hyperosmotic and Temperature Perturbation Sequence of Hyperosmotic Perturbation of Yeast Cells During the first part of dehydration, sudden exposure to a hyperosmotic stress causes rapid equilibration of the osmotic pressures of the cytoplasm and the external medium. During the transitional step of the passive osmotic response, water flows out of the cells, leading to cell shrinkage, and permeant solutes, such as glycerol, penetrate into the cells. This exchange is rapid (Berner and Gervais 1994) and ends in a stationary step when osmotic pressures are equilibrated. As shown in Figure 6.1, cell volume decreased exponentially between an aw of 0.99 and 0.8, before reaching a constant volume corresponding to 40% of the initial volume, generally called nonosmotic volume. Cell volume was evaluated from light-microscopic images, and thus the total envelope of the yeast was taken into account; that is, cell wall and membrane. In contrast to plant cells and bacteria, in which the plasma membrane shrinks away from the cell wall, in yeast the entire cell volume shrinks when cells are placed in hypertonic solutions (Morris and others 1986). Considering the poor compressibility of biological membranes, this strong cell shrinkage must be associated with wrinkling of the membrane. According to Adya and others (2006), the cell shape became irregular. In decreasing aw to below 0.55, the cells became more permeable as indicated by the ratio of propidium iodide (PI)-stained cells in Figure 6.2. Therefore, this osmotic pressure interval appears to be critical for membrane permeability during dehydration. Phase transitions of phospholipids have been proposed as the main cause of the increase in membrane permeability in both phospholipid vesicles (Yamazaki and others 1989) and yeasts (Laroche and others 2001) under osmotic stress. Water loss from phospholipid head groups may lead to phase transition in some lipids, resulting

Figure 6.1. Variations in average cell volume (open circles) and cell viability (open squares) of Saccharomyces cerevisiae after an osmotic shock from a culture medium (water activity = 0.99) to a binary medium (water + glycerol) at different water activity levels. Volume data were obtained by the analysis of confocal images and viability was determined by the colony-forming unit method.

% of stained cells (or viability)

100

80

60

40

20

0 0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Water activity

Figure 6.2. Viability and membrane permeability of Saccharomyces cerevisiae versus water activity by use of two probes: Lucifer yellow (LY) and propidium iodide (PI). Shown are cells with increased permeability (solid circles), which are doubled marked; cells with endocytosis (open circles), which are marked with LY; and intact cells after rehydration (open squares).

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in a lateral phase separation (Lehtonen and Kinnunen 1995) that allows the leakage of intracellular content (Crowe and others 1992). A phase transition in yeast membrane lipids from aw 0.64 to 0.38 in glycerol solution at an average temperature of 22°C (Laroche and others 2001) could explain the permeabilization observed. During hyperosmotic treatments, the number of Lucifer yellow (LY) stained cells also increased with increasing osmotic pressures (Figure 6.2). LY is a membraneimpermeant anionic dye. This polar tracer is usually loaded by microinjection, pinocytosis, or scrape loading. It has been used to characterize endocytosis in plant cells (Roszak and Rambour 1997) and yeasts (Wiederkehr and others 2001) in which the presence of a cell wall prevents the access of high molecular weight molecules to the plasma membrane. In PI/LY double-stained cells, LY probably penetrated the cells because the plasma membranes were made permeable. In cells stained only with LY, plasma membrane endocytic vesiculation under hyperosmotic conditions seems possible. Endovesicles have already observed by Mille and others (2002) with E. coli. Slaninova and others (2000) reported deep plasma membrane invaginations filled from the periplasmic side with an amorphous cell wall material when Saccharomyces cerevisiae cells were transferred to hyperosmotic growth medium. Such invaginations, when associated with lipid phase separation induced by dehydration, could lead to the formation of endocytic vesicles. In fact, Liu and others (2006) showed that the scission of membrane invaginations could be promoted by lipid phase separation to form endovesicles. The percentage of increased permeability (PI stained) cells was constant below an aw of 0.86 during rehydration and increased strongly at the upper levels of rehydration, showing that most of the cells that had reached a critical aw (0.35) could not recover their permeability. Therefore, the aw interval between 0.86 and 0.99 appears to be critical for membrane permeability during rehydration. The existence of this critical step could be related to membrane events that occur during dehydration. Indeed, cells labeled with LY may have suffered from a reduction in surface area associated with the formation of endovesicles, as has already been proposed by Shalaev and Steponkus (1999) and is supported by our observations. Therefore, exposing these cells to rehydration levels that impose significant increases in volume (cf. Figure 6.1) may cause their lysis during volume expansion. Okada and Rechsteiner (1982) reported that endovesicles that form under hyperosmotic conditions swell and burst upon rehydration of the cytosol. In fact, we show that, for an aw lower than 0.6, the removal of a portion of water from the cells may lead to changes in the cell permeability resulting from the phase separation of phospholipids. In fact, lipid phase transition affects the resistance of membranes to shear forces (Sparr and Wennerstrom 2001), and volume contraction may thus be critical when this occurs. Plasma membrane changes are strongly implicated in the mechanism leading to cell death during osmotic dehydration and rehydration. In particular, permeabilization resulting from lipid phase transitions and severe volume contractions could explain the observed sequence of events. Moreover, the changes that occur during the dehydration step and the rehydration step are interdependent.

Effect of Combined Physical Stresses on Cells: The Role of Water

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Figure 6.3. Isoviability (N/N0) diagram of Saccharomyces cerevisiae versus temperature (4–40°C) and water activity. The viability data were obtained after 1 h at the physical conditions indicated and rehydration to optimum conditions.

Effect of Combined Osmotic and Thermal Stress To show the link between yeast survival following combined osmotic and thermal treatments and membrane-fluidity variations induced by the treatments, a cell-viability diagram (aw and temperature) and a membrane-fluidity diagram (aw and temperature) are presented in Figures 6.3 and 6.4. According to these figures, we see that, without a phase change during dehydration, we can expect to have a higher survival percentage. Thus, the fluidity diagram appears to be a potential tool for controlling membrane fluidity during cell dehydration and rehydration by simultaneously and independently managing aw and temperature over time. The fact that cell death provoked by osmotic shocks depends on temperature is well established. Dried-yeast recovery is optimal if rehydration is performed at 38°– 40° or 50°C (Poirier and others 1999). Furthermore, the temperature at which dehydration shock occurs in liquid medium has been shown to affect cell viability greatly (Laroche and Gervais 2003). The results presented in Figure 6.4 show that the yeast

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Figure 6.4. Isoanisotropy of Saccharomyces cerevisiae membrane versus temperature and water activity. Anisotropy was measured by using diphenylhexatriene fluorescence polarization.

has an enhanced resistance to osmotic shock at temperatures lower than 10°C and higher than 22°C. However, resistance to osmotic shock based on temperature is strain dependent, and each strain may have a specific behavior. A strain-dependent response to glycerol osmotic stresses has also been reported by Blomberg (1997). Laroche and Gervais (2003) proposed that mortality following rapid dehydration or rehydration was related to water flow through an unstable membrane. Guyot and others (2006) confirmed this assumption and hypothesized that change in the fluidity of the plasma membrane was the critical event leading to cell death and that water flow was not necessarily involved in the cell-death mechanism. Our present work confirms this latest assumption. However, here, if water outflow is insufficient to provoke cell death, fluidity variation in the case of thermal stress alone in the range of 4°–40°C—that is, without osmotic stress—did not provoke cell death. Thus, change in membrane fluidity is the critical event, but must be accompanied by osmotic stress and certainly subsequent volume contraction. In the case of hyperosmotic shock, not


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only are the membranes in phase transition, but also the cells are contracted. It is well known that cells shrink in response to osmotic stress. Adya and others (2006) have associated the surface topology of S. cerevisiae (irregular shape, surface roughness) and volume loss to the cell’s resistance to both thermal and osmotic stress. Slaninova and others (2000) reported deep invaginations in the plasma membrane and bulges in osmotically stressed yeasts. Such conditions of shrinkage associated with lipid phase separation occurring before and/or during the dehydration-rehydration steps (Δr2 provoked by the osmotic stress) probably leads to plasma membrane permeabilization and leakage of cellular components. Our hypotheses regarding the mechanism leading to cell death during dehydration and rehydration are developed in two recent investigations (Simonin and others 2007a, 2007b). Conclusions Based on the First Example: Combination of Osmosis and Temperature Membrane state and survival of osmotic stresses are linked. Particularly, changes in membrane fluidity before and/or during osmotic treatment influence yeast survival, and lipid phase transition in membranes is disadvantageous for cells submitted to osmotic shock. The use of the membrane-fluidity diagram enabled control of the membrane fluidity of cells during dehydration and rehydration. To understand the plasma membrane changes occurring during dehydration and rehydration, complementary techniques of membrane study should be used. Actually, it must be taken into account that membranes are complex organelles composed of a variety of lipids structured in membrane domains, and a global coefficient related to membrane fluidity is insufficient to appreciate all the changes occurring in them. In fact, complex lipid phase behavior is known to occur when water content is low (Milhaud 2004). Particularly, nonlamellar phases are suspected to arise at low water concentrations, as observed in model biomembranes (Shalaev and Steponkus 2001). We show that such a diagram should be a useful tool for improving yeast survival in dehydration-rehydration processes. Such processes are involved not only when drying food or fermenting, but also in freezing. In fact, a freezing process at a moderate temperature (Δt < 1000°C/min) consists essentially for microorganisms in a hyperosmotic perturbation at low temperature (near 0°C, during water crystallization). Cell inactivation in this process might mainly be attributed to the combination of osmotic and temperature perturbation (Dumont and others 2006).

Example 2: Effects of Combined High Hydrostatic Pressure, Low Temperature, and Hyperosmotic Perturbations Combination of High Hydrostatic Pressure and Low Temperature on Escherichia coli Survival Numerous studies have demonstrated that the antimicrobial effects of high pressure depend on temperature (Sonoike and others 1992). Moreover, the efficiency of highpressure treatments is controlled by other process parameters such as the pressure applied and the kinetics of pressurization (Palou and others 1998), as well as by the

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physicochemical properties of the medium being treated, such as pH (Alpas and others 2000) and aw (Van Opstal and others 2003). These parameters must be controlled precisely to ensure efficient treatment. With appropriate combinations of these parameters, a synergistic effect might be achieved, reducing the pressures and treatment times required. The combined effects of high pressure and low or subzero temperatures on microbial inactivation have been studied. A synergistic effect between these parameters has generally been reported in the inactivation of vegetative microorganisms (Hashizume and others 1995; Perrier-Cornet and others 2005). In some cases, the initial microbial populations were completely inactivated with a combined treatment of high pressure and low or subzero temperature, whereas only a slight microbial inactivation was achieved under the same pressure conditions at room temperature (Perrier-Cornet and others 2005). The magnitude of this synergistic effect depends strongly on the type of microorganism (Takahashi 1992). The interaction of high pressure and subzero temperature in microbial inactivation is complex, and possible phase-transition phenomena must be taken into account. Some authors have demonstrated that freezing under hyperbaric conditions is effective in reducing microbial contamination (Luscher and others 2004). In addition to the antimicrobial effects of combining high-pressure and subzero-temperature treatments, the combination offers various processing advantages, such as rapid freezing and thawing and cold storage of foods under liquid conditions (Cheftel and others 2002). Figure 6.5 shows the effect of a 10-min treatment at different pressure and temperature levels on the logarithmic inactivation of E. coli K12TG1. At −20°C, in the supercooled region, the pressure sensitivity was greater than at 25°C for pressure lower than 350 MPa. This synergism between high pressure and subzero temperature made it possible to reduce the pressure and/or improve pressure-mediated inactivation. Irrespective of the inactivation rate, our findings corroborate the observations reported by Takahashi (1992), who examined the inactivation of E. coli after pressure treatment (200 MPa, 20 min) at −20°C and at room temperature. More recently, we reported that, at a fixed pressure of 150 MPa, an initial population of S. cerevisiae was completely inactivated at −20°C (>8 log cycles under liquid conditions), whereas it was only slightly inactivated at 25°C ( 400 MPa), water behavior becomes more regular. To confirm this relation with water thermodynamic comportment at low temperature, the aw of the medium has been modulated. Effect of Low Temperature and Hyperosmotic Perturbation on Escherichia coli Baroresistance As shown in Figure 6.6, the pressure sensitivity of E. coli K12TG1 was highly dependent on the aw of the system. When the bacterium was suspended in a water-glycerol solution with an aw of 0.85, it was more pressure resistant than at an aw of 0.99. This finding underscores the baroprotective effect of solutes, previously described for E. coli (Satomi and others 1995; Van Opstal and others 2003), Rhodotorula rubra (Oxen and Knorr 1993), and Zygosaccharomyces bailii (Palou and others 1997). The combination of subzero temperature and high pressure at an aw of 0.85 caused a cumulative

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Figure 6.6. Isoinactivation (log N0/N) of Escherichia coli versus pressure and temperature in a binary medium (water + glycerol) at a water activity of 0.85. The sample was maintained for 10 min at the conditions indicated before being grown under optimum conditions.

protective effect of solute and subzero temperature against pressure-induced inactivation. Only the protective effect of low temperature appears in Figure 6.6 in a medium with an aw of 0.85. The protection by the solute led to the higher pressure level necessary to inactivate E. coli, and then inactivation occurs only in the pressure-temperature domain where the antagonistic effect was dominant. When pressurized in distilled water (aw = ∼1), E. coli K12TG1 showed a much higher pressure sensitivity than at lower aw, especially at −20°C (Figure 6.7). In this case, only the synergistic effect of low temperature is observed, probably because the entire microbial population is inactivated at a pressure lower than 400 MPa. Parallel Changes with Pressure and Temperature of Protein Behavior, Microbial Inactivation, and Water Structure Several studies have highlighted the crucial role of water in the pressure-induced denaturation of biological systems. Oliveira and others (1994) reported that protein denaturation decreased linearly with a decrease in water concentration. Similarly,


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Figure 6.7. Isoinactivation (log N0/N) of Escherichia coli versus pressure and temperature in distilled water. The sample was maintained for 10 min at the conditions indicated before being grown under optimum conditions.

Kinsho and others (2002) observed that the removal of water by the addition of polyols or small cationic ions had an efficient protective effect against enzyme inactivation at high pressures and subzero temperatures. The latter authors also reported that coldinactivation mechanisms were pressure dependent and differed at pressures below 200 MPa from those at pressures above 200 MPa. Moreover, a maximum stability temperature was evidenced for different proteins, and a bell-shaped dependence of protein stability on temperature was observed (Smeller 2002). A parallel has been proposed between the structure of water and the thermal denaturation of proteins (Klotz 1999). In fact, among other similarities, the graph of liquid water density follows a bell-shaped curve at atmospheric pressure, with a maximum at 4°C. Some authors have emphasized the effect of pressure on water density as a key for understanding cold denaturation of proteins at high pressure (Marques and others 2003). The properties of water under pressure vary and are largely a function of the pressure range (Cavaille and others 1996). Indeed, the effect of increasing pressure on the behavior of cold water is to push the temperature of maximum density systematically to lower and lower temperatures. The so-called atypical properties are observed for

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pressures below 200 MPa. However, above 400 MPa pressure, water loses its particular characteristics and behaves like a classic hydrogen-bonded liquid. The addition of solutes causes the formation of hydration shells, leading to a new organization of water molecules. This phenomenon is strongly enhanced when the pressure is increased and, accordingly, it cancels out the particular properties of pure water in the pressure range of 0.1–200 MPa (Kanno and Angell 1979). The variation in water properties with pressure, temperature, and the presence of solutes reflects changes in the arrangement of water molecules. From a biological perspective, this could explain the baroprotective effects of solutes on proteins and microorganisms under denaturing conditions. The mechanisms of pressure-induced microbial inactivation may involve denaturation of some critical life processes such as enzyme reactions, as suggested by some authors (Hashizume and others 1995; Perrier-Cornet and others 2005). Also, a parallel between water properties and microbial inactivation can be identified. For a known set of hydration conditions, a synergistic effect was observed at pressures up to a critical level (250 MPa for an aw of 0.992), whereas antagonism occurred at pressures higher than this critical level. The consequence of increasing the hydration rate at a fixed pressure was to enhance the synergism and increase the pressure threshold that marked the crossover between synergism and antagonism. Below this threshold, pressure and temperature affect microbial viability in a similar manner and, in the same way, water behaves as a singular liquid. Above this threshold, pressure and temperature have roughly opposite effects on microbial viability and, at the same time, water behaves as a classic hydrogen-bonded liquid. Conclusions Based on the Second Example: Combination of High Pressure, Temperature, and Osmosis This work shows that combined high-pressure and subzero-temperature treatment is a promising way to optimize high-hydrostatic-pressure processes, since the combination made it possible to reduce the pressure magnitude and/or improve the pressuremediated inactivation. Nevertheless, the interaction between high pressure and subzero temperature appears to be complex. Indeed, it was pointed out that, depending on pressure level and aw of the medium being treated, subzero temperature counteracted the inactivation caused by high pressure. This unexpected phenomenon leads to the necessity to take into account the process parameters to ensure efficient treatment. Considering the structure of water in relation to the stability of proteins and to microbial inactivation led to the suspicion of a crucial role of water in this phenomenon. Further work should be undertaken with a view to better elucidate this phenomenon.

Conclusions These two examples show the critical role of thermodynamic properties of water in the survival of microorganisms. Maintenance of living structures by water is effective only if water retains its specific properties. Modifying thermodynamic properties


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by pressure, temperature, or osmotic solutes changes cell equilibrium. This change in thermodynamic conditions is also accompanied by mechanical constraints (water efflux with hyperosmotic stress or hydrostatic compression with pressure) that contribute to the destabilization of the cell and especially the cell membrane. In minimizing such perturbations and using correct thermodynamic properties, the viability of live cells can be maintained even under drastic conditions. The osmotic dehydration at a controlled temperature can enable viable dehydrated cells to be obtained even for sensitive organisms. High-pressure processing at low temperature can also enable cell viability to be maintained at very high pressure. This process would be useful in maintaining cells at low temperature and high pressure in liquid water. Thus, understanding the role of water in the maintenance of cell viability would enable specific promising processes combining different thermodynamic parameters to be developed to preserve or inactivate organisms and microorganisms

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Takahashi K. 1992. Sterilization of microorganisms by hydrostatic pressure at low temperature. In: Balny C, Hayashi R, Heremans K, Masson P, editors. High pressure and biotechnology. London: John Libbey Eurotext. p 303–7. Van Opstal I, Vanmuysen SCM, Michiels CW. 2003. High sucrose concentration protects E. coli against high pressure inactivation but not against high pressure sensitization to the lactoperoxidase system. Int J Food Microbiol 88:1–9. Wiederkehr A, Meier KD, Riezman H. 2001. Identification and characterization of Saccharomyces cerevisiae mutants defective in fluid-phase endocytosis. Yeast 18:759–73. Yamazaki M, Ohnishi S, Ito T. 1989. Osmoelastic coupling in biological structures: decrease in membrane fluidity and osmophobic association of phospholipid vesicles in response to osmotic stress. Biochemistry 28:3710–5.

7 Soft Condensed Matter: A Perspective on the Physics of Food States and Stability T. P. Labuza, T. J. Labuza, K. M. Labuza, and P. S. Labuza

Abstract Several foods are complex examples of soft condensed matter (SCM) that can undergo phase transition from an amorphous glass to an amorphous rubber state and vice versa. The concept of SCM in terms of the state diagram is presented for an understanding of physical state changes in foods. Transformation of a food matrix from its glassy to rubbery state enables gravity-induced collapse, flow, and possible recrystallization of a food component producing drastic changes in food textural property and affecting its quality as perceived by consumers. Discussion is focused on cotton candy, hard-ball candy, and crisp snacks in terms of the effect of water content and temperature on their state behavior. The sensory crispness paradigm of hard cookies and crisp snacks can be predicted from changes in SCM states from brittle material into truly soft SCM.

Introduction In 1991, Roos and Karel (1991a, 1991b, 1991c) introduced the concept of applying the glass transition temperature (Tg) curve for sugar on top of the phase diagram of the sugar-water mixture. Although an extremely useful tool that can combine water activity (aw) and Tg in one graph, it has had limited applicability, likely because of misunderstanding of the basic physics, thermodynamics, and kinetics of food systems by many researchers. In 2005, a group of Nestle/University of Fribourg (Switzerland) physicists stirred up the pot of understanding of food physics by publishing a paper on “soft condensed matter” (Mezzenga and others 2005, p 729), in which they noted, Foods make up some of the most complex examples of soft condensed matter (SCM) with which we interact daily. Their complexity arises from several factors: the intricacy of components, the different aggregation states in which foods are encountered, and the multitude of relevant characteristic time and length scales. Because foodstuffs are governed by the rules of SCM physics but with all the complications related to real systems, the experimental and theoretical approaches of SCM physics have deepened our comprehension of their nature and behaviour, but many questions remain. … With their complexity, heterogeneity and multitude of states, foods provide SCM physics with a challenge of remarkable importance. 87

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What they said is very relevant to what has occurred in the field of watermanagement science and the physical state of foods; that is, material science concepts applied to SCM. We will present this concept of SCM in terms of the state diagram of Karel and Roos for understanding physical state changes in foods, which they did not cover in much depth because the study of glass transition was in its infancy. The work in this chapter was initiated by my children because I wanted to clarify a base understanding so that it could be used to educate our undergraduates and graduate students in food science. The focus will be on cotton candy, hard-ball candy, and crisp snacks in terms of the effect of water content and temperature on the change in physical state; that is, an amorphous glass either to/from an amorphous rubber state or to a crystalline state. For example, crystalline sucrose when melted and spun forms a dry amorphous glass (cotton candy) that upon humidification above the glass transition line enters the rubbery state, another form of SCM. The higher the humidity, the faster the amorphous glass transforms into an amorphous rubber, which allows for gravityinduced collapse, flow, and recrystallization. With a hard-ball candy (mostly sucrose with maltodextrins), which is a more dense glass, both temperature and humidity induce surface stickiness above the Tg line. At high enough temperature (55°–65°C) at all humidities, the hard ball begins to flow (collapse) under gravity and, if confined in a can, re-forms into a hockey-puck shape when cooled. Hard cookies and crisp snacks also show changes in SCM states, starting out as brittle material that transforms into truly soft SCM in the rubbery state for which we can project a sensory crispness paradigm. Why this occurs is a lesson in the physics of foods. With hard cookies, the transition from a glass to a rubber causes a loss of crispness, which can be tied to the brittle-ductile line. Understanding this will show why food science is as fascinating as E = mc2 and Feynman string theory. (We won’t get into pasta texture at this time even though good spaghetti simulates a string.) The Background When water interacts with a dissolved solute or with amorphous or crystalline materials, the thermodynamics of the system change such that the free energy of the water is decreased. This is manifested by decreased vapor pressure in the gas phase, a reduced freezing-point curve as the amount of interacting dissolved solute increases, and an increase in boiling and melting points of the solutes. These three curves represent the thermodynamic equilibrium conditions and, at any one point of water/ temperature, the water has a specific free energy that can be represented as the water activity through the first law of thermodynamics (Glasstone 1946; Barbosa-Cánovas and others 2007).

μ = μo + RT Ln ( aw )

(7.1)

In Equation 7.1, μ is the free energy of water in a given state, μ0 is the free energy of pure water at the system temperature T, R is the gas constant, and aw is the measured water activity of the system at those conditions. This concept of water activity (aw) or equilibrium relative humidity (ERH) (i.e., ERH = 100 × aw = 100 × [p/p0]),

Soft Condensed Matter: A Perspective on the Physics of Food States and Stability

Texture

Lipid oxidation

Mobility point

Enzyme activity

Vitamins

Mold

Moisture 0.1

ISOPOW IX 2004

0.2

0.3

0.4

Moisture content

Relative reaction rate

NEB

0.0

89

0.5 0.6 0.7 Water activity

Yeast 0.8

0.9

Bacteria 1.0

Figure 7.1. Water activity (aw) stability diagram of relative reaction rate vs aw. ISOPOW, International Symposium on the Properties of Water; and NEB, nonenzymatic browning.

where p is pressure, was brought to the forefront of food science by Scott (1957) and the early leaders who formed ISOPOW (the International Symposium on the Properties of Water). This led to an understanding of water management in foods in terms of molecular mobility and its relationship to microbial and chemical reactions that cause deterioration, as well as physical state changes, the focus of this review (Labuza and others 1970; Duckworth 1975). What resulted is the aw stability map (Figure 7.1), first presented in 1970 (Labuza and others 1970), and the formation of the ISOPOW group that had its first meeting on water in foods in Glasgow in 1971. The research that followed led to an important list of aw criteria for chemical, physical, and microbiological guide points in assessing the stability of dry, semimoist, and high-moisture foods (Labuza 1975). In practice, this also led to the development of several instruments for reliable aw measurement and the incorporation of aw into government regulations related to food safety. An example is the US Food and Drug Administration’s regulation, 21 CFR 113, which requires that foods with an aw of ≥0.85 coupled with a pH of ≥0.46 that are heated to sterility in sealed hermetic containers, so they are stable at room temperature and pose no pathogenic risk, must have a heat process that delivers a ≥12 log-cycle reduction in the number of Clostridium botulinum spores present. The research by hundreds of researchers in the food science field has led to a series of general rules with respect to the measured aw and food stability, which are listed here: aw ∼ 0.2–0.3: Brunauer-Emmett-Teller (BET) monolayer. At and below this value, reactions requiring a water phase do not occur. aw ∼ 0.2–0.3: Below this, the rate of lipid oxidation increases.

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aw ∼ 0.35–0.4: Onset of stickiness. aw ∼ 0.4–0.5: Onset of a loss of crispness on gain of moisture by dry foods. aw ∼ 0.5: Onset of hardening (e.g., raisins) on loss of moisture. aw ∼ 0.6: Onset of microbial growth. aw ∼ 0.65–0.85: Maximum reaction rate in amorphous systems as a function of aw (e.g., enzymes, nonenzymatic browning [NEB], lipid oxidation). aw ∼ 0.85: Onset of growth of bacterial pathogens and the limit of aw in thermal processing as already noted. Also of importance is that the difference in the chemical potential of water (μ), and thus the aw difference between two systems, results in moisture exchange (Hyman and Labuza 1998), a critical problem in multidomain systems (e.g., a cheese-and-cracker sandwich). Slade and Levine (1989, 1990) after almost 30 years of the food industry’s practical use of aw as a guiding principle stirred the pot by noting that foods generally are never at true equilibrium and thus a polymer science approach based on Tg phenomena was a better way to understand stability. This Tg was a function of moisture content and represented a moisture vs T line that separated dry and intermediate moisture foods (IMFs) into two states: an amorphous glassy state and an amorphous rubbery state. Thus, we can represent states of matter as in the chart in Figure 7.2, which we will return to. Slade and Levine (1989, 1990) and Levine and Slade (1993), early on when Tg was being introduced to food scientists, suggested that there was no need to invoke any concept of aw at all. The proven use of its principles, however, vis-à-vis the whole IMF revolution in the 1970s; the rapid development of reliable aw-measuring devices by Rotronics, Nova-Sina, and Decagon; and its measured value lending itself to predict potential stability problems, allowed that one should not throw out the baby with the Solid System States Solid Food Matrix State High-moisture elastic gel, colloidal dispersion, dough or cell trapped

Moisture removal or freezing

Amorphous (unstructured)

Concentration or freezing

Crystallization of ice and sugars structured mininum free energy

Moisture loss or T decrease below Tg

Glassy or brittle dry

Hold below Tm but above Tg

Rubbery or ductile semimoist

Moisture gain or T above Tg

Hardening in storage

Figure 7.2. Hypothetical states of matter of foods, drugs, and biologics. T, absolute temperature; Tg, glass transition temperature; and Tm, melting temperature.


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bathwater; that is, perhaps the two concepts were compatible. It should be noted that, in a 1948 chemical engineering textbook on polymer science and technology, Schmidt and Marles suggested that glass transition could probably explain the physical states of confectionaries, but this was overlooked until 1987 even though the senior author of this chapter used that very textbook in 1959 for a polymer science course in chemical engineering while an undergraduate at MIT. Of course, only one paragraph was devoted to Tg in that book, so this oversight can be forgiven. Given this and the better understanding of physical states, a consolidating approach first presented by Roos and Karel (1991b, 1991c) and reviewed by Rahman (2006) 15 years later is the theoretical development of a state diagram, as shown in Figure 7.3, that combines equilibrium curves with the Tg line as a hypothetical way to understand food states. The state diagram, which combines equilibrium freezing-point, melting-point, and boiling-point curves on the same graph with the glass transition curve (i.e., Tg vs % solids), supplements the aforementioned aw stability map to better explain physical state changes in processing and storage of foods, drugs, and biologics. This is particularly useful when considering frozen foods, and also foods that exist in the dry glassy state either at or slightly above room temperature, occupying a small region on the right side close to the vertical center of the diagram (the small triangular area in Figure 7.3), as well as semimoist foods such as soft candies and meat and fish jerkys. Raising temperature and humidity moves a dry product from the glassy state into the rubbery state (i.e., above the Tg line), thereby allowing for increases in mobility of both water and other molecules and a local, reduced storage modulus related to texture. The consequence of this is that if temperature or moisture content are increased for products in the glassy state, like rigid or brittle dry foods (e.g., crackers), such that they cross the Tg line into the rubbery state, crisps become soft, losing crispness; sugary foods, such as hard candies and infant formula, can crystallize with stickiness and caking that occur; and soft cookies become hard. In addition, reactions requiring an aqueous phase increase in rate exponentially with an increase in the ERH or aw (Labuza and others 2004). The position in either the glassy or the rubbery region thus becomes very important to shelf-life control and is a tool along with the aforementioned aw paradigms for both the understanding and the management of moisture in foods. This can be further illustrated by a simple depiction of the changes in the physical state of a food undergoing processing and storage, as is shown in Figure 7.2. In essence, we begin at the top with a high-moisture system with an aw close to 1 and remove water by some means; for example, through evaporation (boiling), drying, or freezing. On the right side, water can be converted to ice by lowering the temperature or it can be removed by boiling or evaporation as is used in the process to crystallize out solutes such as sugar or salt. The change in state on the drying side on the left brings us into the amorphous state, which can be either a rubbery (semimoist) or glassy (dry) state. For systems high in sugars, such as a pre-candy mix or a cookie dough (state 1 [solid circle] in Figure 7.4 at room temperature), the system during processing by partial evaporation (boiling or baking) can end up in a rubbery state once cooled to room temperature (state 2 [solid square] in Figure 7.4) (e.g., a gummy candy, a soft cookie,

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or a caramel). By further water removal in baking or boiling, the system will end up as hard and glassy, as designated by the small triangular area in Figure 7.3 (Dry-food region), which is the final place at room temperature for state 3 (solid triangle) in Figure 7.4 (e.g., crispy cracker, hard-ball candy, or peanut brittle). Thus, the state diagram can be used to follow the physical state changes as a function of moisture content (or plasticizer)

Vapor Solution crystal-melt line

Boiling-point line 0 °C

Dry Tm

Freezing-point line

Dry Tg Tamb

Te

Rubber

Ice and super sat solution

Dry-food region

Tg′

Glass

–135 °C 0

100%

% solids

Figure 7.3. A hypothetical state diagram. sat, saturated; Tamb, ambient temperature; Te, eutectic temperature; Tg, glass transition temperature; Tg′ , solute-specific glass transition temperature; and Tm, melting temperature.

Vapor Boiling line

Solution crystal-melt line

Freezing line

0 °C

Tm Tg

23 °C

Rubbery state

Te

Ice and super sat solution

dry

Glassy state

–140 °C

Tg′ 0

100% % solids

Figure 7.4. Hypothetical state diagram showing equilibrium and amorphous regions: state 1 (solid circle), initial nonequilibrium sugar mix or cereal dough; state 2 (solid square), final rubbery state (e.g., for soft cookie or caramel); and state 3 (solid triangle), final glassy state for hard-ball candy, cotton candy, or crisp cookie. Te, eutectic temperature; Tg, glass transition temperature; Tg′, solute-specific glass transition temperature; Tm, melting temperature; and sat, saturated.


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in relationship to the theoretical equilibrium-state functions during any water-removal process such as drying, baking, extrusion, or evaporation, as well to explain changes occurring in storage.

Physical State Changes in Foods in Storage Glass transition theory from the study of polymer science also helps in understanding textural properties of food systems and explains changes that occur during food storage, such as stickiness, caking, collapse under the force of gravity, softening, and hardening (Stearne and Ward 1969; Levine and Slade 1989; Slade and Levine 1989; Roos and Karel 1991a, 1991b, 1991c; Sperling 1992). Figure 7.5 shows a glass-rubber transition diagram, the line representing the glass temperature, Tg. The glass transition point is the temperature (Tg) at a given moisture content where a transition from a glassy stable amorphous solid state to a rubbery amorphous solid state can begin (Sperling 1992). As seen in Figure 7.5, this can take place by either the temperature being increased or the plasticizer amount (e.g., water or polyols in foods) being increased or both. In the amorphous state of a solid the molecules are randomly distributed and mobile, whereas in a crystal the molecules are in a distinct arrangement with little mobility. This results in a distinct X-ray fingerprint pattern (Suryanarayanan 1995). The glassy state, which is below the Tg line, has brittlelike properties similar to stiff, hard plastics, glass wool, or a crisp cracker. In the rubbery state above the Tg line at constant temperature and thus increasing RH, the material can pick up water and collapse (flow) under the force of gravity. If the amorphous material is composed of small molecules like sugars, the sugars become mobile as they absorb water and then can recrystallize, becoming very hard and losing weight as moisture is lost (Roos and Karel 1991a, 1991b; Chuy and Labuza 1994). This is explained by there being a dramatic increase in the local mobility of both monomers like sugars and polymer chains just above the glass transition temperature

RUBBERY

C

¥ stickiness ¥ caking ¥ collapse

Temperature

B

A

Tg curve GLASSY

% solids

Figure 7.5. Influence of temperature and moisture increase on state change. Tg, glass transition temperature.

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over the whole moisture range. As a system moves from the glassy into the rubbery state when the temperature or moisture content is increased (relative to the external RH), the local viscosity (or storage modulus G′) drops dramatically at the molecular level from approximately 1012 down to 109 Pa · s just above the glass transition temperature (Sperling 1992). The reduced local viscosity allows for greater polymer chain and reactant mobility. The amount of free volume, defined as the amount of system-associated space that is not taken up by polymer chains themselves, also changes between the glassy and rubbery states. The free volume available within a glassy system has been estimated to be between 2% and 11.3% of the total volume and is believed to result from an increase in the thermal expansion coefficient (Ferry 1980). This increase in free volume should allow for faster diffusion of reactants. Based on the free volume required for diffusion, the size of a diffusing molecule may also be an important factor affecting diffusion rates. Diffusion is a function of the probability of creating a matrix hole that is sufficiently large enough for a molecule to occupy. When a molecule is large compared to the available free-volume pore or voids, the probability of creating such a hole is low. However, in addition to translational mobility, short-range mobility may also be important for reactions such as crystallization. The diffusivity of water is obviously greater in the rubbery than in the glassy state, but one must be careful in stating this since, in the glassy phase, diffusion of both water and oxygen most likely occurs in the vapor phase, with a diffusivity about 10,000 times greater than in the liquid state (2.5 × 10−5 m2/s in the gas phase vs 2 × 10−9 m2/s for the liquid state). Thus, crystallization and reactions could occur, although more slowly below Tg, such as nucleation and crystallization in the microregions. Using electron spin resonance, Roozen and coworkers (1990, 1991) found a significant increase in the rotational mobility of spin probes within sucrose-water, glycerol-water, and maltodextrin-water mixtures at a temperature that corresponded to the glass transition temperature. The mobility of protons, as measured by nuclear magnetic resonance (NMR), has also been found to be higher in the rubbery state compared to the glassy state (Kalichevsky and others 1992). Sherwin and others (2002) and Sherwin and Labuza (2003) used cross-polarization magic-angle spinning NMR to show similar effects in the Maillard reaction at limited aw. In a multidomain food (e.g., with a soft moist center and crisp outer layer), where domain states 2 and 3 (Figure 7.3) are in contact, they will exchange moisture if their water activities (and most likely moisture contents) are different (Hyman and Labuza 1998). Given this, products at state 2 will lose moisture and become more leathery (move to the right), whereas those in state 3 will gain moisture (moving to the left) and become softer, creating another storage problem.

Examples of Use of the State Diagram and Glass Transition Curve To illustrate the use of the state diagram and state changes, three food systems will be discussed: (1) crystallization of cotton candy, (2) stickiness of hard candy, and (3) softening of crisp foods.


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1. Sugar Recrystallization in Storage of Foods: Sucrose and Cotton Candy The physical structure of a food, important from both functional and sensory standpoints, is often altered by changes in aw due to moisture gain resulting in a transition from the glassy to the rubbery state. Moisture pickup also causes crisp hard baked, fried puffed, or extruded (glassy) foods to become soft due to the plasticization of carbohydrate polymers into the rubber zone (Katz and Labuza 1981). When powders are made by spray drying or freeze drying, the sugars after drying are generally in the amorphous glassy state since they are dried quickly to low moisture so as to prevent recrystallization during drying (Roos and Karel 1991a, 1991b, 1991c). Thus, they end up in the small triangular zone at room temperature shown in Figure 7.2. Since amorphous sugars are very hygroscopic, if they are exposed to high humidity they will cross over into the rubbery zone as a function of the temperature and humidity, and caking, collapse, and crystallization will occur, resulting in state changes forming either a sticky texture or a hard, coarse, or grainy texture (Saltmarch and Labuza 1980; Downton and others 1982). Both loss of crispness and caking generally begin to happen when the aw is raised to above 0.3–0.4 at room temperature via moisture pickup through the package or moisture redistribution from other microdomains. Caking interferes with the powder ’s ability to dissolve or be free flowing, and phase transitions can lead to volatile loss or oxidation of encapsulated lipids. Cotton candy made from pure sucrose is one of the most simple forms of food; in this case, a carbohydrate confection. It has been made for over a century, but little has been studied about its stability during distribution and storage (Labuza and Labuza 2004). Cotton candy is made by a spin-melt-cool and air-drying process that uses crystalline sucrose, possibly with minor additional ingredients (flavoring and coloring). This process has not changed much in the 169 years since the product’s introduction to the American public at the 1830 World’s Fair (Hetzler 2001). There are earlier reports of it, termed angel floss, in 16th-century Europe, but no details could be found. It was commercially introduced sometime in the late 1890s when it was produced by the Nashville candy makers William Morrison and John C. Wharton (Bishop 1998; Davis 2001). They later designed the world’s first electric machine that allowed crystallized sugar to be poured onto a heated spinning plate and then be pushed by centrifugal force through a series of tiny holes. The product was first sold as fairy floss at the 1904 St. Louis World’s Fair. Though the Nashville maker ’s first production is well documented, many believe that cotton candy was invented earlier in the 1900s by a vendor at Ringling Brothers and Barnum & Bailey Circus. Makower and Dye (1956) performed the first experiments on state changes of pure amorphous sucrose by using a freeze-dried frozen saturated sucrose solution rather than a spin-melt-cool process as in the making of cotton candy. They determined the moisture uptake for sucrose at 25°C at different relative humidities (%RHs). At 180°C, which is then rapidly cooled in a mold without crystallizing. At room temperature and low humidity, the hard ball exists as a hard glasslike amorphous solid of the SCM state noted earlier. This is a much more compact solid amorphous state (∼1200 g/L) then found for cotton candy (50–100 g/L) discussed previously. Sucrose crystals have a density of 1587 g/L; thus, the glass density is less, but depends on the method used to make it. An observation made by Katherine Labuza when she inadvertently left a commercial hard-ball product (Altoids) in the family car in the direct summer sun in the central valley of California was that the product became unattractive by virtue of being completely stuck together. This suggested that the physical state of hard-ball candy may depend on both temperature and RH at least on the surface. A composite T vs % sucrose transition line formed from the data of Roe and Labuza (2005) and Sun and Zografi (1996) is presented in Figure 7.12. Figure 7.12 represents the amorphous states of a sucrose-based hard candy that would be glassy below the line and rubbery above the line. In addition, the data of Labuza and Labuza (2004), noted previously, used this plot to show that cotton candy entered the sticky state and collapsed (i.e., flow of the material under the force of gravity) if held at or above the Tg line at ≥33% (i.e., higher moisture and lower % sucrose). This is very close to the moisture content that gives a Tg of 23°C. Based on this work, one could speculate that if a hard candy is abused at high temperatures or increased humidity or both, the candy could become sticky and clump together, causing consumer complaints. Hard candy may be exposed to very warm temperatures. For example, McLaren and others (2005) demonstrated that the interior of a car,

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Experimental Tg

Glass transition temperture

80

Gordon Taylor

60 40 20 0 –20 –40 –60 –80

60

70

80 % Sucrose

90

100

Figure 7.12. Glass transition line for sucrose. Composite of data by Sun and Zografi (1996) and Roe and Labuza (2005). Tg, glass transition temperature.

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Vehicle Temperature Rise Over Time

Vehicle temperature (°F)

140 130 120 110

Ambient temperature 71 74 77 78 84 88 93

100 90 80 70

0

5

15

10

20

25 30 35 40 Elapsed time (min)

45

50

55

60

Glass transition temperature (°C)

Figure 7.13. Car interior temperature rise over time (McLaren and others 2005). 50.0 Tg onset Tg end Tg half

40.0 30.0 20.0 10.0 0.0 –10.0 –20.0 –30.0

0

20

40 RH (%)

60

80

Figure 7.14. Glass transition temperature as a function of % relative humidity (RH) for hard-ball candy (surface material).

a typical place where candy might be stored, left in the sun can reach temperatures over 60°C (140°F) (Figure 7.13). To determine why this occurs, the hard-ball candy was held at 5 different %RHs for 3 weeks and then the outer surface was shaved off and a DSC scan was run on the scrapings. This resulted in obtaining both the Tg and crystal melt of the sucrose since, during the run at 10 K/min, the candy crystallized first from the amorphous rubbery state, as temperature increased, and then melted. Figures 7.14 and 7.15 show these results as a function of %RH. As noted, the T at room temperature is at about 30% RH, similar to the prior studies already noted. Using this as the basis for state changes, the Altoids were then humidified to 4 humidities over saturated salt solutions for 3 weeks. Surface material was scrapped


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Melting temperature (°C)

140

120

100

80

60

10

0

20

30

40

50

60

70

80

RH (%)

Figure 7.15. Onset temperature for crystallization of amorphous-state hard-ball candy as a function of % relative humidity (RH).

Glass transition temperature (°C)

70 60 50

5

5

4

4

30 20

5

4

5

3.5

3.5

1

1.5

3.5

4.5

1

1

3.5

3.5

2.5

40

5

4.5

10 0 –10

Tg end

–20

Tg start

–30

0

20

40

60

80

RH (%)

Figure 7.16. States of hard-ball candies stored at different abuse conditions as compared to storage condition at or above Tg. A PerkinElmer (PE) Model 7 differential scanning calorimeter was used with a scanning rate of 10°C/min. 1, free flowing and separate; 2, stuck pieces break apart with gentle shaking; 3, very sticky pieces that pull apart by hand; 4, pieces stuck in one mass; and 5, pieces all flow into one mass in shape of hockey puck. RH, relative humidity.

off samples from each humidity and then subjected to DSC to obtain the onset and end-point Tg values shown in Figure 7.16. The cover was put on, and then the product was subjected to 12-h storage at 25°, 35°, 45°, 55°, and 65°C, cooled, and then evaluated for obvious physical state changes on a five-point scale as shown in Figure 7.16.

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Figure 7.17. Visualization of hard-ball candy states after humidification at 33% relative humidity and then temperature abused.

These results show that if stored at about 7°–10°C above the Tg line, the candy begins to become sticky, whereas at or below Tg it remains free flowing after cooling to room temperature. This follows the pattern shown for powders containing amorphous-phase sugars mentioned earlier. Once the storage condition is >10°C above Tg, the candies stick together such that they do not fall out of an open can when it is turned upside down. At >55°C storage temperature, the force of gravity overcomes the internal hydrogen-bonding force within the hard ball such that the mass flows, completely disrupting the original structure reacting in the material becoming a hockey-puck shape, as in the bottom right of Figure 7.17. Note that at 65°C at all humidities tested, the product is below the melting point of sugar (Figure 7.15), so the flow is not a crystalline melt. It is obvious from this study that increasing either the temperature or the moisture content in the region above Tg increases molecular mobility, allowing the product to become sticky and then flow. Mazzobre and others (1997) found that raising the Tg of trehalose in a mixture inhibited the rate of crystallization of lactose by decreasing mobility; that is, resulted in a smaller T − Tg. Review of these results produced the following observations: (1) Hard-ball candy (e.g., Altoids) is an amorphous glassy material, which initially shows a physical state in which the candy is free flowing and can be easily picked out of a can. (2) Such candies are subject to stickiness when exposed to abusive temperatures or stored at higher humidities, if they enter the rubbery zone above Tg. This can occur when stored in a closed car directly exposed to the sun, where the inside air temperature can increase to 60°C. (3) The glass transition curve (Tg vs %RH) can be used to define the dividing line for optimal storage conditions where below this line the


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candies are separate and nonsticky, whereas above the line the hard candies go through various sticky and flow states. (4) Closed cans with or without the original seal provide some protection against %RH increases at temperatures below 45°C; that is, the candies may become a little sticky, but shaking the can separates the individual hard candies. However, unopened cans with or without a seal demonstrate that a temperature increase to 55° or 65°C has a greater detrimental effect than an increase in %RH to 75%. (5) At all %RHs, temperatures of 55° and 65°C cause serious physical state changes, including complete flow and collapse to form a hockey-puck-shaped structure (solid mass), well below the melt temperature at ≤58% RH; thus the caution on the product package to “store in a cool dry place.” 3. Loss of Crispness or Hardness Texture is an important sensory attribute for many cereal-based foods, and the loss of desired texture leads to a loss in product quality and a reduction in shelf life (AC Nielsen Company 1979). Recently, the First International Symposium Crispy Cracks: Creating and Retaining the Crispiness of Food was held at the University of Wageningen in the Netherlands (Crispy Cracks 2008). The texture of dry crisp foods was first studied as a function of aw by Katz and Labuza (1981), although work 5 years earlier at Cornell University by Vickers and Bourne (1976) indicated that the perception of the crispness of dry cereal snacks was the result of sounds generated when chewed, which diminished as the aw was increased. Note that this work on crispness occurred about 10 years before an understanding of the application of glass transition to food. Vickers and Bourne concluded that the perception of crispiness was due to the sound generated in the mouth, moving through the jaw bone to the ear. Katz and Labuza (1981) determined that saltine crackers (baked), popcorn (hot-oil puffed), extruded corn curls, and deep-fat-fried potato chips lost crispness if the aw exceeded the range of 0.35–0.50. The crispness was attributed to intermolecular hydrogen bonding of starch forming small crystalline-like regions when little water was present. These regions require force to break apart, which gives the food a crisp texture as fractures perpetrate through the structure during chewing. Above a certain aw, the water was presumed to disrupt these bonds, allowing the starch molecules to slip past one another when chewed. Hsieh and others (1990) also observed that puffed-rice cakes lost crispness at an aw just above 0.44. Sauvageot and Blond (1991) suggested that some type of physicochemical change other than lubrication by water was occurring in the cereal systems because the crispness intensity decreased sharply instead of gradually as aw increased. They were on the right track, but both they and Roudaut and others (1998) conducted only cursory sensory studies that did not show a direct relationship with thermomechanical properties. Glass transition provides a clearer approach to understanding the physical and texture changes of crisp cereals or snacks as water content increases. If an amorphous material exists in the glassy state, it is hard and brittle; for cereal-based snack foods, it would represent a crisp or hard product because the elastic modulus, which is related to flow, extendibility, and bending, is approximately 103 times higher in the glassy state than it is in the rubbery state (Sperling 1992). In the rubbery state, the material is soft and elastic; for

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a fried snack or cereal, this would be an undesirable soggy state. The desirable crispiness of crackers and dry snack products such as hard cookies, crackers, potato chips, and breakfast cereals is lost if the moisture gained is enough to exceed the moisture content of a matrix that is just at the glass temperature for that material. In Figure 7.4, state 3 represents the crisp glass product, so it could lose crispness by gaining moisture at a constant temperature (i.e., moving toward state 2) or by being stored at a temperature above the Tg for the given moisture content. If textural changes in a cereal system can be correlated with a glass transition, and the state diagram for the cereal food is known, then the processing and environmental conditions can be controlled such that the desired state for the food is achieved and retained during distribution and storage. Unfortunately, measurement of the Tg of composite complex foods like crackers or cookies is not easy. DSC is problematic because the sample size (10–20 mg) is too small. Nikoladis and Labuza (1996) were among the first to use dynamic mechanical thermal analysis (DMTA) on cookies and crackers. They noted the main difficulties were in mounting the sample, the loss of moisture during the temperature scan, and the fact that the recorded temperature was not exactly the product temperature. About the same time, both Roudaut and others (1998), in France, and Roos and others (1998), in Finland, suggested that crispness was related to Tg, they but offered no exact sensory proof as to where the sensory loss of crispness occurs in terms of a moisture-temperature curve like the Tg vs moisture curve. An easy alternative to the measure of glass transition is brittle ductile transition (Vincent 1960; Young and Lovell 1991; ASTM 1997; Folk and others 1998; Dobraszczyk and Vincent 1999; Payne and Labuza 2004a). The brittle fracture is distinguished by the capability of an object broken into pieces to be returned to its original size and dimensions. As temperature or moisture increases, the food system begins to yield before fracture occurs. When the temperature of the object is raised, the object yields to the stress being applied; that is, it begins to deform and change shape. When the sample becomes ductile, there is no clean break. Upon fracture, the sample cannot be put back together in its original dimensions. A brittle material breaks cleanly and can be put back together in its same initial shape, whereas a ductile material deforms during stress, does not break cleanly and, if put back together, has a different shape. Brittle fracture and yielding (deformation or ductile behavior) are separate processes and have a different dependence on temperature (Vincent 1960; Stearne and Ward 1969; Young and Lovell 1991; Ward and Hadley 1993). In general, the maximum stress before breaking or deformation changes little as a function of either temperature at constant plasticizer content, or change in plasticizer amount at constant temperature. After a certain point, the property measured decreases dramatically. The point where the two lines cross corresponds to the brittle-ductile transition temperature (Tb) (Vincent 1960; Stearne and Ward 1969; Young and Lovell 1991; Ward and Hadley 1993). The brittle-ductile transition in food systems has been shown to be comparable to the glass transition (Dobraszczyk and Vincent 1999) and to the decrease in the sensory textural attribute, crispness (Nicholls and others 1995; Le Meste and others 1996). In


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most of these studies, the brittle-ductile transition has generally been determined over a range of moisture contents at only one temperature. Another way to determine the brittle-ductile transition is by keeping the amount of plasticizer constant and testing the material as a function of temperature (Folk and others 1998). Nicholls and others (1995) suggested that the change in crispness in snack-food systems correlates better with the Tb than the Tg but, again, did not offer quantitative proof. The fracture response (brittle-ductile transition) of a food material is commonly determined by a three-point bend method (Dobraszczyk and Vincent 1999). At a predetermined cross-head speed, a probe is used to apply force in the center of a sample that is supported on each side. From this, the peak force and the apparent Young’s modulus (stress divided by deformation at that distance) can be measured. Very simply, to determine Tb, product is stored at 23°C at five or six different water activities. After equilibration, some of this product is transferred, after being wrapped tightly with foil, to several temperature cabinets to equilibrate. The cookies are then tested on a texture analyzer for the stress-strain relationship. Following this procedure, one can the get the brittle-ductile transition as the intersection point between the two regions. Labuza (2002) in some preliminary studies applied this to brittle, chocolateflavored (not chocolate-coated) sugar snap cookies in a series of tests at both constant T with variable moisture and constant moisture with variable T based on the aforementioned principles. As shown in Figure 7.18, a clear break point is seen in each case. What is useful about this procedure is that the actual measurement of Tb takes less than 30 min after equilibration of the sample, and additional samples can be used for sensory evaluation. Based on this preliminary work, Payne and Labuza (2004a) conducted a more extensive study with 5 moistures and 8–10 temperatures. Figure 7.19a shows an example stress-strain plot for the same sugar snap wafer cookie stored at 0.05% RH and 23°C. The stress rises steeply and then, at the peak, falls to zero as the cookie breaks. In Figure 7.19b, the same cookie was stored at 23°C and 75% RH. At 75% RH in Figure 7.19b, there is no clean break, with an extended deformation to 5 mm vs the break at 0.5-mm deformation. In addition, the peak force went from about 23 Newtons for the dry wafer down to 1 Newton, a factor of 25-fold. These data were then used to determine a Tb vs moisture-content line. Payne and Labuza (2004a) showed that the Tb curve closely followed the Tg curve measured by dynamic mechanical analysis (DMA) or DMTA for a brittle sugar snap cookie. It was about 10° to 30°C lower than the Tg line. Payne and Labuza (2004b) then took this work further and used 10 trained panelists to determine sensory crispness intensity at 8–10 temperatures for each of five different moisture contents. In addition to sensory analysis, they also measured the elastic properties of the sugar snap cookie by DMTA, DMA, and the brittle-ductile test, as noted earlier. Figure 7.20 shows the actual measured values determined by an individual tester in triplicate at nine different temperatures. As shown, at a certain temperature, crisp-

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(a) 30.00

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Figure 7.18. (a) Brittle-ductile transition temperature (Tb) plot as a function of moisture (i.e., % equilibrium relative humidity) at constant temperature (25°C) for a sugar snap cookie (Labuza 2002). (b) Tb plot as a function of temperature for a sugar snap cookie at constant moisture (∼6%) content (Labuza 2002).

ness intensity decreases dramatically. The Tci (crispness intensity temperature) for that moisture was determined from the data by applying the Fermi equation using the procedure of Peleg (1992, 1994). The end result of the comparison is presented in Figure 7.21. As shown, the sensory line falls about 7°C above the brittle-ductile line as a function of moisture content and at about the same distance below the elastic storage modulus (G′) as measured by DMTA. This remarkable correlation suggests that, indeed, sensory crispness is related to the ability of water to plasticize the polymer structure. It also suggests that measuring the Tb, which is a lot simpler, would be a useful tool for bakeries in terms of optimizing moisture loss during baking. It

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Figure 7.19. (a) Stress/strain plot for a wafer cookie at ∼0.05% relative humidity (RH) and 23°C (Payne and Labuza 2004a). (b) Stress/strain plot for a wafer cookie at ∼75% RH and 23°C (Payne and Labuza 2004a). N, Newton.

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120

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Figure 7.20. Sensory crispness intensity (solid circles) as a function of temperature for a wafer cookie at ∼5% moisture content. The intersection point represents the critical point for onset of crispness loss.

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Figure 7.21. Transition temperatures of chocolate wafers as a function of moisture content: sensory crispness (open circles); brittle-ductile method (X); G′ onset, Tg by dynamic mechanical thermal analysis (DMTA) (solid diamonds); and G′ midpoint, Tg by DMTA (open triangles). G′, elastic storage modulus; and Tg, glass transition temperature.

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further suggests that loss of sensory crispness is very close to the Tg for any moisture content.

Conclusions This chapter has reviewed the influence of moisture and temperature on physical state properties and food changes related to the crystalline, glassy, and rubbery states; that is, the properties of soft condensed matter. The results point out the need for a state diagram that includes the glass transition line. Data for cotton candy and hard-ball candy show that caking and crystallization occur in real time at or near the Tg value. Projection of time to crystallization from higher-temperature data can be modeled with either the WLF equation or the Arrhenius equation, but one must be careful not to combine data at different moisture contents. We also showed that loss of sensory brittleness of foods is related to the plasticizing nature of water and seems to follow the brittle-ductile temperature transition curve (Tb) as a function of moisture content. Finally, on July 29, 2008, the day this chapter was submitted, the article “The Nature of Glass Remains Anything But Clear” appeared in the New York Times. In it was the following statement by Philip W. Anderson, a Nobel Prize–winning physicist at Princeton University, who wrote in 1995, “The deepest and most interesting unsolved problem in solid state theory is probably the theory of the nature of glass and the glass transition.” The entire article concerned physicists around the world working on this sticky problem but mentioned nothing about food science and Tg. It seems to me we are somewhat ahead in this area of SCM and have proven its use in solving many problems.

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8 Antiplasticization of Food Polymer Systems by Low Molecular Mass Diluents C. C. Seow

Abstract Low molecular mass (LMM) compounds or diluents, acting as external plasticizers, are generally used to enhance the workability, flexibility, ductility, and/or distensibility of synthetic glassy polymers. However, at low concentrations, the presence of many of such diluents may instead cause a polymer-diluent blend to become stiffer or more brittle than the neat polymer—a phenomenon termed antiplasticization—even though the glass transition temperature (Tg) is depressed. Such a phenomenon appears not to be confined to synthetic polymers. Most food and other biomaterials may be regarded as partially amorphous, partially crystalline metastable polymeric systems, that display remarkable fundamental and generic similarities to synthetic polymers. Thus, LMM diluents (notably water, sugars, and polyols), which normally act as plasticizers, may exert effects on the mechanical properties of reduced-moisture food systems similarly in ways that reflect antiplasticization rather than plasticization. LMM diluents are therefore neither intrinsically plasticizers nor antiplasticizers. Besides alterations in properties of the polymer-diluent blend, abrupt changes in properties of the diluent itself may be indirect reflections of mechanical antiplasticization of the polymer. Although the physical manifestation of antiplasticization by LMM diluents is undisputed, the actual mechanisms involved remain unresolved. This review presents an overview of this important fundamental phenomenon that can simultaneously and profoundly influence various physical and functional properties, and hence quality and acceptability, of certain food products. Attention is focused on water (which is undeniably the most important diluent in foods) and glycerol (a commonly used humectant), and their interactive plasticizing-antiplasticizing effects.

Introduction Interactions of water molecules with one another and with other food components are yet to be fully understood despite extensive study and refinements in analytic techniques. In particular, that fraction of water close to biomacromolecular surfaces, generally referred to as bound water, in earlier food science studies, still remains somewhat of an enigma. The condition and properties of water closely associated with macromolecules clearly are detectably different from those of bulk water over definite time frames. Hence the classic differentiation between bound and free water based on sharp changes or discontinuities in some such properties (e.g., unfreezable water and nonsolvent water), whether or not true water binding actually prevails (Franks 1983, 1986; Slade and Levine 1991). 115

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The food polymer science approach to the study of water relationships in foods has, over the past 30 years or so, provided new perspectives to our basic understanding of structure-property relationships, thereby enhancing our ability to manipulate food properties to our advantage. The basic premise of food polymer science rests on the fundamental and generic similarities between synthetic polymers and food molecules. Most food materials may be regarded as partially amorphous, partially crystalline metastable polymeric systems, with water presumably acting as a ubiquitous or universal plasticizer (Levine and Slade 1988; Slade and Levine 1991, 1995). The primary effect of a plasticizer is to increase the workability, flexibility, ductility, and/or distensibility of a polymer (Sears and Darby 1982). However, initial humidification of certain partially crystalline food polymeric systems from the dry state is known, in many cases, to instead increase order, compactness, rigidity, modulus, and toughness. Further hydration beyond a critical limit decreases the same properties. Seow and others (1995, 1999) have suggested that such maxima in certain mechanical properties of such food polymer systems observed over low ranges of moisture content may be attributed to external mechanical antiplasticization by water, a phenomenon commonly observed in many synthetic glassy polymers where increased rigidity rather than flexibility results from the presence of very small amounts of added plasticizers. In some cases, concomitant decreases or minima in certain related properties may also result from antiplasticization, such as elongation at break and permeability to gases. Besides water, other low molecular mass (LMM) nonelectrolyte solutes, when present at low concentrations, may act as antiplasticizers in reduced-moisture food systems. Antiplasticization is essentially a polymer science–based interpretation to explain so-called anomalous mechanical behavior of glassy food systems in the presence of low concentrations of water (and other small molecules). The present review provides an updated overview of this fundamental phenomenon that not only influences the physical and textural, and hence eating properties of food systems at low- to intermediate-moisture levels, but may play an important role in the preservation of foods, biological tissues, antibodies, proteins, and drugs. Studies of the plasticizingantiplasticizing phenomena in foods and other biomaterials have undoubtedly enhanced our basic understanding of food polymer-diluent interactions.

Polymer-Diluent Interactions: Plasticization versus Antiplasticization Before extensive consideration of the antiplasticization effects of water (and other LMM diluents) in food polymer systems, it would be useful to recall briefly the types of relaxations that can occur within the glassy state. Such relaxations apparently exert profound influences on the physical properties of polymeric systems. Polymers exhibit a multiplicity of relaxational processes in the glassy state. It is customary to designate the primary or highest temperature transition (other than the crystallite melting temperature [Tm]) as an α transition. The α-relaxation process is generally recognized as the main glass transition, occurring over a limited range of temperatures. This transforms a relatively rigid or brittle glass into a comparatively

Antiplasticization of Food Polymer Systems by Low Molecular Mass Diluents

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pliant “rubber,” resulting in sharp changes in free volume, molecular mobility, and physicochemical and structural properties of the polymeric system (Roberts and White 1973; Slade and Levine 1991; Simatos and others 1995; Roos 1996). Below the normal glass transition temperature (Tg), amorphous or partially crystalline polymers also exhibit secondary relaxation regions that are normally given the notations β, γ, δ, etc. (in decreasing order of temperature of occurrence). These sub-Tg or secondary relaxation processes usually have amplitudes smaller than the α relaxation associated with major backbone-chain movements (i.e., the primary glass transition). Sub-Tg or secondary relaxations appear to be associated in some way with the brittle-ductile transition of synthetic amorphous or partially crystalline polymers (Roberts and White 1973; Wu 1992; Simatos and others 1995; Roos 1996). The existence of secondary relaxations is indicative of mobility at temperatures below the glass transition temperature (T < Tg). The physical reason or origin of a particular secondary relaxation, however, remains unclear. Secondary relaxation processes have been reported for certain food materials (Kalichevsky and others 1992; Le Meste and others 1992; Noel and others 1992, 1996, 2000; Gidley and others 1993; Lourdin and others 1998), but their relationships to mechanical properties of these materials have been increasingly explored and acknowledged (Le Meste and others 1999, 2002). The addition of a LMM compound or diluent to a glassy polymer generally increases free volume and segmental mobility, which leads to a lowering of the Tg (Sears and Darby 1982). Selective interpolymer bonds may be weakened or broken, thereby leading to a reduction in melt viscosity or elastic modulus, which is the classic macroscopic effect of a plasticizer on physical properties of a polymer. The amorphous regions become swollen, and the whole mass becomes softer. If the solvent power of the added diluent (plasticizer) is great enough, crystallites, if present, may disappear, resulting in a very soft gel or a viscous liquid. In many cases, however, the incorporation of small amounts of many types of plasticizers in polymers has been reported to produce effects opposite to those expected (Jackson and Caldwell 1967a, 1967b; Sears and Darby 1982). The polymer-plasticizer system, in the glassy state at temperatures sometimes well below its Tg, becomes harder and less flexible than the neat polymer, even though a decrease in Tg may be evident. This has been termed antiplasticization—it occurs over a range of diluent concentrations or below a plasticization threshold that must be exceeded before the conventional external plasticizing effects on physical properties can be manifested (Sears and Darby 1982). Figure 8.1 shows schematically the difference between an idealized modulus or tensile strength vs diluent concentration curve and one that exhibits antiplasticization. Sears and Darby (1982) pointed out that, in general, the more polar the diluent is, the broader is the antiplasticization range (or plasticization threshold). In general, antiplasticization has been hypothesized to involve a combination of several factors, but the actual mechanisms involved in mechanical antiplasticization are not exactly known. Various theories and models of antiplasticization in synthetic polymer systems have been proposed including the following:

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(a) IDEALIZED

(b) ANTIPLASTICIZED

Glassy (Log) modulus

Antiplasticization range

Rubbery

0

0 Diluent concentration

Figure 8.1. Representations of (a) an idealized and (b) an antiplasticized modulus versus diluent content curve of solid polymer-diluent blends. From Seow and others (1999).

1. Increased crystallinity induced by an increase in free volume (Sears and Darby 1982; Guerrero 1989). 2. “Hole filling” by the diluent, causing a decrease in free volume and a suppression of motion, particularly at the polymer-chain ends (Maeda and Paul 1987; Vrentas and others 1988; Anderson and others 1995). In the more specific case of polymerwater interactions, the increase in dynamic tensile modulus on humidification of nylon films, while the systems were still in the glassy state, has been ascribed to free-volume reduction (Prevorsek and others 1971). 3. Formation of mechanically stable bridges between water and amide groups postulated to explain antiplasticization by water in nylon at T < Tα (Starkweather 1980). 4. Relaxation of low-density–high-energy regions in a glass, referred to as “islands of mobility” by Johari (1985), by a low-Tg diluent, which enables the rearrangement of the polymer chains and causes densification of the glass (Liu and others 1990). 5. β-Suppression effect leading to the disappearance or decrease in intensity or amplitude of the β transition and a concomitant reduction in free volume and an increase in modulus of the polymer in the temperature region between Tβ and Tα (or Tg) (Butzbach and Wendorff 1991; Ngai and others 1991). The concept of antiplasticization should be strictly applicable only at low diluent concentrations (i.e., in the context of a polymer-rich, rather than a diluent-rich, matrix)


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and restricted to observable changes in the glass, determined at T < Tg. Note that food polymer systems containing high concentrations of water (above Wg′, the maximum content of plasticizing water rendered unfreezable), such as food gels, would have their Tg’s depressed to subzero temperatures (Slade and Levine 1991). Therefore, such systems would normally be in the leathery or rubbery state at ambient temperatures. Any occurrence of maximum hardness or modulus in such systems over the intermediate-moisture to high-moisture or water activity (aw) range, as has been reported (Kapsalis and others 1970; Hsieh and others 1990), may be attributed to increased crystallinity through association of polymer chains (such as starch retrogradation) induced or facilitated by enhanced macromolecular mobility in the rubbery state at intermediate moisture contents, prior to dilution at very much higher hydration levels. This should not be confused with antiplasticization effects. The present review does not delve into the question of whether, from a conceptual viewpoint, antiplasticization of food polymer systems could occur at Tg < T < Tm (i.e., in the rubbery state).

Water, the Ubiquitous Diluent, as Antiplasticizer at T < Tg A reduction in moisture content of a food polymer system would cause an increase in Tg. The Tg of reduced-moisture food systems is generally very much higher than the range of ambient temperature (T) over which they are normally stored and their properties determined. As such, most low-moisture foods at ambient temperatures are glassy or brittle solids. Even so, the glassy state (T < Tg) in foods, as in synthetic polymeric systems, need not necessarily be homogeneous in terms of mechanical and related properties (e.g., dielectric relaxation and gas barrier properties). These may be modified by the presence of diluents (such as water and sugars) acting as external plasticizers or antiplasticizers. Concomitant changes in the physicochemical properties of the diluents are also expected. Properties of the Food Polymer-Water Blend Mechanical Properties The rheological and textural properties of solid foods are inextricably linked. We would expect that addition of water should induce plasticization of polymeric chains and generally facilitate deformation, thereby decreasing hardness and crispness while increasing softness and extensibility. However, many published reports, covering a wide variety of food systems, have indicated that this has not necessarily always been the case, and that maxima or minima in mechanical properties do occur over the lowto-intermediate moisture (or aw) range. For water-compatible glassy polymers, the first-sorbed and earlier-sorbed water molecules appear more likely to cause a mechanical antiplasticizing effect independent of their kinetic effect in lowering the Tg of the polymer-water blend below the Tg of the neat polymer. For complex glassy food materials, moisture-induced antiplasticization typically increases hardness, stiffness, or toughness (usually referred to as moisture toughening) before the expected softening as moisture content is further elevated beyond a critical point where the material transforms from the glassy to the rubbery state (Kapsalis and others 1970; Reidy and

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Heldman 1972; Katz and Labuza 1981; Bourne 1986; Halek and others 1989; Harris and Peleg 1996; Le Meste and others 1996; Fontanet and others 1997; Li and others 1998; Roudaut and others 1998; Suwonsichon and Peleg 1998; Van Hecke and others 1998; Chang and others 2000a; Moraru and others 2002; Braga and Cunha 2004; Gondek and Lewicki 2006; Mandala and others 2006; Marzec and Lewicki 2006; Pittia and others 2007). Table 8.1 lists certain food products and mechanical properties antiplasticized by water, as well as the relevant references, even though some of the researchers may not have interpreted the effects observed as moisture-induced antiplasticization. Several factors (such as the type of food, the mechanical parameter measured, and the testing method employed) may affect the physical manifestation of the antiplasticization-plasticization phenomena, thus resulting in disparate responses of different mechanical properties of particular materials to moisture sorption. The following points regarding antiplasticization by water in food polymer-water blends are noteworthy: 1. The exact moisture content or aw location of maxima or minima in mechanical properties shows variations, not only with mechanical properties studied, but also with the food product and evaluation method (Table 8.1). 2. A high-density material may be more susceptible to antiplasticization than is a low-density one (Halek and others 1989). 3. Variations in mechanical behavior in response to moisture sorption may arise as a result of different mechanical testing methods employed. For example, Chang and others (2000a) observed that water exerted plasticizing effects on all mechanical parameters measured by the three-point bend test, but clearly caused antiplasticization of fracture stress and strain determined by uniaxial compression, suggesting that the latter method might be more sensitive in detecting the more subtle changes in fracture behavior arising from moisture-induced antiplasticization in a cellular, brittle glassy product such as dried bread. 4. The antiplasticization range or plasticization threshold depends on the type of system studied and on the physical property measured. It may extend over a relatively wide range of moisture content or aw and, in some cases, possibly beyond the glassy state into the rubbery domain. Some properties are more or less sensitive than others to antiplasticization, thereby altering the magnitude of the effect observed in a given system. For example, the antiplasticization range in extruded flat breads stretched over the range of aw from 0 to 0.8 (Marzec and Lewicki 2006) (Figure 8.2). Similarly, water apparently induced an antiplasticizing effect on fracture force and energy of raw and roasted coffee beans over a range of aw from 0.3 to 0.8 (Pittia and others 2007). 5. Certain mechanical parameters may be antiplasticized on humidification from the dry state, whereas others, determined using the same test method on the same material, may be plasticized immediately or remain practically unaffected until the glass transforms into rubber. Each mechanical property apparently has its own specific moisture dependency, as pointed out by Borges and Peleg (1997).

Table 8.1. Complex food products wherein water acts as an antiplasticizer on mechanical properties Food product

Property antiplasticized

Water activity or moisture content of antiplasticization maximum or minimum

Reference

Precooked, freeze-dried beef

Modulus, toughness

0.2 aw (max)

Kapsalis and others (1970)

Precooked, freeze-dried beef

Hardness, chewiness

0.4 aw (max)

Reidy and Heldman (1972)

Snack-food products

Compression work

0.2–0.4 aw (max)

Katz and Labuza (1981)

Air-dried apple

• Hardness • Springiness

0.11 aw (max) 0.33 aw (max)

Bourne (1986)

Cornmeal extrudates

Compressive strength

8.9%–15.3% moisture (max)

Halek and others (1989)

Brittle cereal foods

Compressive force • Cheese balls • French bread croutons

0.4–0.5 aw (max) ∼0.6 aw (max)

Harris and Peleg (1996)

Extruded flat breads

• Compressive fracture stress • Young’s modulus

∼9% moisture (max)

Fontanet and others (1997)

Crispy breads

• Stiffness modulus and fracture stress • Acoustic emission intensity

11% moisture (max)

Roudaut and others (1998)

Puffed cereals

Extruded corn-based snacks Corn cakes

Compressive force • Cheese balls • Cocoa puffs • Puncturing force • Specific force of Structural ruptures • Compressive peak force • Work required to break cake

9% moisture(max)

7%–8% moisture 6%–7% moisture 0.56 aw (max) 0.35 aw (max)

Suwonsichon and Peleg (1998) Van Hecke and others (1998)

9%–10% moisture (∼0.6 aw)

Li and others (1998)

Dried bread

• Compressive fracture stress • Compressive fracture strain

0.32 aw (max) 0.32 aw (min)

Chang and others (2000a)

Extruded meatstarch product

Storage modulus

∼0.2 aw (max)

Moraru and others (2002)

Extruded flat breads (wheat and rye)

• Compressive force • Compression work • Breaking force

0.53–0.59 aw (max)

Marzec and Lewicki (2006)

Corn and wheatbran flakes

• Compressive force • Compression work

∼0.65 aw (max)

Gondek and Lewicki (2006)

“Petite beurre” biscuits

Puncture force

0.32 aw (max)

Mandala and others (2006)

Raw and roasted coffee beans

Compression fracture force, energy, and strain • Raw coffee beans • Roasted beans

∼0.50 aw (max)

Pittia and others (2007)

∼0.75 aw (max) ∼0.84 aw (max)

aw, water activity; max, maximum; min, minimum.

121

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Figure 8.2. Compression-force–water-activity relationships for extruded flat breads showing a wide antiplasticization range. N, Newton. Redrawn from Marzec and Lewicki (2006).

6. It has been demonstrated that, in certain puffed cereal products, moisture hardening or toughening, detected instrumentally, can be perceived sensorily (Roudaut and others 1998; Suwonsichon and Peleg 1998). The so-called anomalous antiplasticization effects of water in relation to some mechanical properties have also been clearly demonstrated in biopolymer-based films, including wheat gluten (Gontard and others 1993), tapioca starch (Chang and others 2000b, 2006), konjac glucomannan (KGM) (Cheng and others 2002, 2006, 2007), poly(lactide-co-glycolide) (Blasi and others 2005), ethylene vinyl alcohol, copolymeric food packaging (Cabedo and others 2006), as well as pullulan and caseinate films and their composites (Kristo and others 2007). Gontard and others (1993) have reported that, during hydration of wheat-gluten films, the first fraction of water molecules to be sorbed improved film elasticity and puncture resistance, probably due to the formation of supplementary hydrogen bonds between protein chains. The later-sorbed water fraction made it easier to break such bonds (plasticization), and the behavior of the gluten film changed from elastic to viscous. Maximum puncture resistance of the films occurred at a progressively lower moisture content as temperature was increased. This is to be expected since elevating the temperature adds free volume to the system, often referred to as plastication. More detailed studies of tapioca-starch films in the glassy state conducted by Chang and others (2000b, 2006) confirmed that water plays a role either as a plasticizer or an antiplasticizer, depending on the physical property measured. Whereas Tg and tensile modulus were evidently plasticized on humidification of the films from the dry state, maxima in tensile strength, strain at break, and toughness were observed over an intermediate moisture content or aw range.


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Figure 8.3. Changes in (a) tensile strength and (b) strain at break of tapioca starch (TS), konjac glucomannan (KGM), and konjac glucomannan–carboxymethyl cellulose (KGM-CMC) films as a function of water activity (aw). Plotted from data of Chang and others (2000b) and Cheng and others (2002).

Of particular interest is that the same mechanical property of different biopolymer systems can respond differently to different levels of hydration. Figure 8.3 compares changes in (a) tensile strength and (b) tensile elongation as a function of aw for different biopolymer films (with data obtained from Chang and others 2000b; Cheng and others 2002). Minima in tensile elongation (normally taken as symptomatic of antiplasticization) were evident in KGM and KGM–carboxymethyl cellulose films, whereas a maximum in elongation was found in the case of tapioca-starch films. Attenburrow and others (1992) and Nicholls and others (1995) noted the occurrence of maxima in flexural fracture stress and strain of amorphous starch systems at 8%– 14% moisture, whereas no such peaks were exhibited by glassy gluten systems over the same range of moisture content studied (Figure 8.4). These findings reinforce the view that composition greatly influences the mechanical response of glassy biomaterials to moisture sorption. However, a cogent explanation for the aforementioned discrepancies has yet to be forthcoming. The antiplasticizing effects of water on other biomaterials have been similarly observed. In the 1970s, Hiltner and coworkers (Nomura and others 1977; Hiltner and others 1978) demonstrated that the first 16%–25% water was able to act as an antiplasticizer by increasing the rigidity of poly-L-hydroxyproline and native collagen to a maximum value. In a study on hot-pressed pullulan-starch blends containing 10%

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150

(a)

5

(b)

WHEAT STARCH WHEAT STARCH

100

Fracture strain (%)

Fracture stress (MPa)

4

50 GLUTEN

0

0

5

10

15

Moisture content (%)

3

2 GLUTEN

1

0

0

5

10

15

20

Moisture content (%)

Figure 8.4. Changes in (a) fracture stress and (b) fracture strain for gluten and starch as a function of moisture content. From Attenburrow and others (1992).

sorbitol or xylose, it was apparent that flexural or tensile stress was antiplasticized by water whereas Young’s modulus was plasticized (Biliaderis and others 1999). Dynamic mechanical thermal analysis (DMTA) data obtained by Pommet and others (2005) suggested that both water and 1,4-butanediol had antiplasticizing effects on the glassy storage modulus of wheat-gluten thermoplastic materials, although statistical significance of the data was not established. Thermal Properties Thus far, we have focused our attention on the antiplasticizing effects of water on macroscopic mechanical properties of the systems. We believe that such antiplasticizing effects may also lead to manifestations where thermal properties are concerned. For example, could the presence of the small endothermic event, in the range 50°– 70°C, typically observed on heating low-moisture (5%–25% wt/wt water) polysaccharide systems (Gidley and others 1993), be viewed as antiplasticization by water? Whereas the temperature of the endotherm exhibits no moisture dependency, the enthalpy shows a systematic increase with moisture content. Gidley and others (1993) suggested that this endothermic event might be due to the “cooperative thermal disruption of enthalpically-favourable interactions in the hydrogen-bonded network of solvent and solute in systems” (p. 308) where “polysaccharide chains are effectively immobilized either kinetically (below the glass transition) or thermodynamically (below the temperature of local order loss)” (p. 311). The intriguing question arises as to whether this thermal phenomenon is in any way related to the macroscopic


450

(a)

400

400

350

350 Melting enthalpy (J g–1)

Melting enthalpy (J g–1)

450

300 250 200 150 100 50 0 0

0% Glyc 10% Glyc 20% Glyc

10 20 30 40 Moisture content (% db)

250 200 150

50 50

(b)

300

100

30% Glyc 40% Glyc 50% Glyc

125

0 0

0% Sorb 10% Sorb 20% Sorb 30% Sorb 40% Sorb 50% Sorb

10 20 30 40 Moisture content (% db)

50

Figure 8.5. Melting-enthalpy–moisture-content relationships of konjac glucomannan films plasticized with (a) glycerol (glyc) and (b) sorbitol (sorb). Broken lines indicate the critical moisture content level. db, dry basis. Redrawn from Cheng and others (2006).

manifestations of antiplasticization by water commonly associated with such polysaccharide systems. Should sub-Tg rotational motions of the main chains of polymers be affected, it is to be expected that significant changes in mechanical properties (such as in brittle-ductile transitions) would be observed (Wu 1992; Le Meste and others 1999). Cheng and others (2006) investigated the thermal properties of KGM films, but restricted their attention to melting enthalpy. They discovered that the melting enthalpy (ΔH) (determined by differential scanning calorimetry) of KGM films, containing from 0 to 30% glycerol (weight of glycerol to weight of dry KGM), increased with increasing moisture content up to a peak or critical point before decreasing (Figure 8.5a). The ΔH peak occurred at progressively higher moisture contents (from 18% to 26%) as the glycerol content was increased from 0 to 30%, possibly reflective of the lowering of Tg and enhanced chain mobility with increasing additions of glycerol. The ΔH peak disappeared as glycerol content was further increased to 40% and 50%. Thus, at any hydration level below a critical level of ∼20% (dry basis), successive addition of glycerol progressively lowered ΔH, whereas the opposite was true at moisture levels higher than the critical level. In contrast to glycerol-containing films, sorbitolcontaining films exhibited no ΔH peak over the range of moisture contents studied (Figure 8.5b). However, the opposing effects of increasing amounts of sorbitol

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above and below a critical moisture content were still very much evident. The mechanisms behind such opposing influences of glycerol and sorbitol on thermal properties of cast KGM films remain unclear. It is possible that such polyols, depending on circumstances, could weaken or strengthen the long-range order of partially crystalline KGM films. Gas Transport Properties Gas transport behavior is an important practical consideration particularly relevant to biopolymer-based packaging films and coatings. Could mechanical antiplasticization of such materials by certain diluents affect their permeability to gases, such as carbon dioxide and oxygen? Antiplasticization of some synthetic polymers by certain diluents was accompanied by substantial reductions in permeability to gases (e.g., helium, carbon dioxide, and methane), consistent with reduced mobility in the glass (Sefcik and others 1983; Maeda and Paul 1987). Evidence of this in relation to biomaterials has more recently come to light. Benczédi and others (1998) provided evidence that, in amorphous potato-starch extrudates, water acted as an antiplasticizer, with the density of the starch passing maximum value at a low water concentration. It was suggested that antiplasticization may reduce gas-sorption and permeation rates and that such knowledge can be used to optimize gas barrier properties of polymers. Charmathy and others (2006) observed that low amounts of water (at a relative humidity equivalent to ∼5%) impeded its own permeation, as well as that of octane, through microcrystalline cellulose (MCC) before higher humidification began to facilitate permeation (Figure 8.6). Antiplasticizing effects of water were similarly observed for tensile strength and Young’s modulus (determined by three point-bending tests) of compacted MCC samples whereas crystallinity index (determined by Fourier transform infrared spectroscopy [FTIR]) increased with moisture content to a plateau (Figure 8.6b). Thus, in line with the theory of antiplasticization expounded by Guerrero (1989), those authors opined that small amounts of water increased free volume, thereby stimulating molecular rearrangement in the amorphous regions. The subsequent increase in crystallites translated into restricted mobility of the polymer, thereby leading to antiplasticization in mechanical properties and permeability to gases. The difference in plasticizer threshold observed was attributed to the different timescales of the properties measured, a macroscopic property such as tensile strength giving a higher or broader threshold than a microscopic property such as gas permeability. Considering that MCC is so commonly used in the pharmaceutical industry, especially for tablet manufacturing, it may be of some concern should its mechanical performance be altered significantly by moisture uptake during handling and storage. Properties of the Diluent (Water) Conceptually, antiplasticization refers strictly to the mechanical properties of a glassy polymer-diluent blend. These properties would be affected predominantly by the mobility of the polymer molecules in polymer-rich systems. Interactions between the polymer and the diluent must inevitably affect the mobility and physicochemical properties of the diluent itself. Thus, abrupt changes in properties of the diluent that result from such interactions may indirectly reflect mechanical antiplasticization of


127

5

4 0.05 3 Permeability of octane Permeability of water

2 0

5

10

15 20 25 Relative humidity %

30

35

(b) 700

3.0

500

2.5

400

2.0 Young’s modulus

300

Tensile strength Crystallinity index

200 0

20

40 60 Relative humidity %

80

0.94 Tensile strength (MPa)

Young’s modulus (MPa)

0.96

3.5

600

Permeability (Dp) of octame (cm2 s–1)

0.06

0.92 0.90 0.88 0.86 0.84

Crystallinity index

Permeability (Dp) of water × 1012 (cm2 s–1)

(a) 6

0.82 1.5 1.0 100

0.80 0.78

Figure 8.6. Moisture-induced antiplasticization of microcrystalline cellulose: (a) permeability of water and octane and (b) tensile strength, Young’s modulus, and crystallinity. Dp, bulk diffusion permeability. From Charmathy and others (2006).

the polymer. As pointed out earlier, such discontinuities in the physicochemical properties of water that are closely associated with macromolecules have given rise to the various classical definitions of bound water (e.g., unfreezable water and nonsolvent water). Would it be reasonable to equate the antiplasticization range of moisture content to bound water?

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In certain cases, abrupt changes in mechanical properties of the system and physicochemical properties of the diluent may show good correlation, particularly in terms of critical moisture contents at which such changes occur. Such was the case for freeze-dried beef, where maxima in negative entropy (−ΔS0) of water sorption and certain mechanical properties have been reported to occur at about the same critical moisture content (Kapsalis and others 1970). However, information on published correlations of this kind is scarce. Also note that, in many cases, because of different timescales in the experimental methods, changes in properties of the system need not exactly parallel each other. Thermodynamics of Water Sorption Complex foods have been treated as binary systems (i.e., solids and water) to facilitate thermodynamic analyses of water-sorption isotherms at different temperatures. Figure 8.7 shows the calculated isosteric heat of sorption (Qs)–moisture content plots of several food materials (Duckworth 1972). Any excess enthalpy over the heat of vaporization of free water was assumed to be indicative of a water-binding effect (Berlin and others 1970; Bettelheim and others 1970; Leung and Steinberg 1979). Simplistically, there is thus a division between two different fractions of water molecules. On a more fundamental basis, note that water-sorption studies are not reflective of true thermodynamic equilibrium situations (Kuntz and Kauzmann 1974; Levine and Slade 1988). Nevertheless, such an approach, despite its fundamental limitations and sizeable errors in the calculations, may be useful (practically) in the drying of foods. Quite substantial

Heat of binding of water (kcal mol–1)

Agar Gelatin

18

Starch Cellulose

16 14 12 10 Heat of condensation 0

0

10 20 Moisture content (% db)

30

40

Figure 8.7. Isosteric heat of sorption (Qs) versus moisture-content plots of food colloids exhibiting a maximum Qs value. db, dry basis. From Duckworth (1972).


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energy, over and above that for the evaporation of bulk water, is required to desorb the last traces of water. It is interesting to note that many food materials have been reported to exhibit maxima in Qs and minima in entropy (ΔS0) of sorption at some low moisture level. This would suggest a most stable pseudo-thermodynamic state, resulting from strong binding of adsorbate to the adsorbent surface at that hydration level (Berlin and others 1970; Bettelheim and others 1970; Duckworth 1972; Leung and Steinberg 1979; Rizvi and Benado 1984). Also, water in propinquity to macromolecular surfaces has been suggested to be more structured than that in the bulk (Etzler 1991). The existence of maximum enthalpy and minimum entropy of sorption, and hence possibly of mechanical antiplasticization, would depend on the nature of the polymer substrate and its ability to interact with water molecules. Such effects are unlikely to be manifested to any great extent when polymer-diluent interactions are weak. Water Diffusivity Seow and others (1999) hypothesized that mechanical antiplasticization of biopolymers by water may be accompanied by parallel changes in diffusivity of the diluent. The effective diffusivity (Deff) of water in starch-based systems has been observed to exhibit maximum values over the low-moisture range, although porosity of the materials was found to increase linearly with a decrease in moisture content (Marousis and others 1989; Leslie and others 1991; Kostaropoulos and Saravacos 1997). Qualitatively, the form of the Deff–moisture-content curve, as shown in Figure 8.8, resembles that of the modulus–moisture-content curve of an antiplasticized system (Figure 8.1b). This pattern is apparently neither affected by the method of sorption (adsorption or desorption) nor by the incorporation of sugars (Leslie and others 1991), but the nonlinearity was apparently suppressed at lower porosities (Marousis and others 1989; Kostaropoulos and Saravacos 1997). Deff values for any specific material have been, however, generally lower in the presence of sugars (Marousis and others 1989; Leslie and others 1991) and when determined from water adsorption, rather than desorption measurements (Leslie and others 1991). Leslie and others (1991) suggested that the observed maxima in Deff in the moisture-content region below 0.2 g/g dry solids, where vapor-phase diffusion predominates, were due to strong binding of water molecules by high-affinity binding sites of the macromolecules. They hypothesized that “as the material begins to be rather dry (moisture content, β-CD–thymol (8.5 mol water/mol complex) > β-CD–cinnamaldehyde (7 mol water/mol complex). The guest molecules displaced water molecules from inside the cavity of β-CD. At an RH of less than 84%, thymol and cinnamaldehyde were not released. The percent of released compound abruptly increased from 84% RH, coinciding with the abrupt increase of water. Water sorption significantly affected thymol and cinnamaldehyde complexes with β-CD, and complex stability was thus governed by the shape of the watersorption isotherm.

Introduction Cyclodextrins (CDs) are cyclic oligosaccharides consisting of glucose units linked by α1,4-glucoside bonds. The CDs composed of 6, 7, and 8 units are usually referred to as (α)-CD, (β)-CD, and (γ)-CD, respectively. They possess a hollow truncated cone shape with a nonpolar interior and two hydrophilic rims. Much of the interest in CDs arises from their ability to encapsulate hydrophobic molecules of suitable size inside their annulus to form inclusion complexes. The most probable mode of binding involves the insertion of the lipophilic portion of the guest molecule into the host cavity, and the 149

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displacement of the water molecules located inside the cavity (Uekama and others 1998). This ability has been used to increase the solubility, stability, and bioavailability of lipophilic drugs, vitamins, colorants, essential oils, and flavors in the food, cosmetic, and pharmaceutical industries (Loftsson and Brewster 1996; Uekama and others 1998; Hedges and McBride 1999; Buschmann and Schollmeyer 2002; Szente and Szejtli 2004). Also, their ability to alter physical, chemical, and biological properties of the guest molecule by the formation of inclusion complexes enabled their use as drug-carrier systems in pharmacology (Uekama and others 1998). β-Cyclodextrin (β-CD), because of its low cost and good complexation efficiency with a wide variety of drugs, has been the most used and studied among the cyclodextrins. The structure of hydrated β-CD is well known from X-ray studies (βcyclodextrin–12H2O [Lindner and Saenger 1982]), as well from neutron-diffraction studies (β-cyclodextrin–11H2O [Zabel and others 1986; Steiner and Koellner 1994]). About seven water molecules are located in the cavity. The rest of the hydration water is outside of the molecule and fills the interstices among CDs. Since most of the complexation reactions occur in an aqueous environment, the interaction between CDs and water is of fundamental importance, because the hydrophobic guest molecules compete with the water molecules in the cavity encircled by hydrogen bonding. Most research has been devoted to studying structures and the ability to encapsulate different compounds. However, no systematic studies have been conducted regarding the effects of environmental conditions on the stability of the formed complexes during storage. Thymol and cinnamaldehyde are the main constituents of thyme and cinnamon essential oils, respectively. Water content and water activity (aw) influence the structure of β-CD and affect the chemical and physical stability of complexed compounds. This work investigated the relationship between sorption characteristics of β-CD and complexes formed with thymol and cinnamaldehyde and their release.

Materials and Methods Materials β-CD was purchased from Sigma Chemical (St. Louis, MO, USA). Thymol and cinnamaldehyde were purchased from Carlo Erba (Milan, Italy). All other chemicals were of analytic grade and purchased from Mallinckrodt Chemical Works (St. Louis, MO, USA). Preparation of Solid Complexes Inclusion complexes of thymol and cinnamaldehyde (guest molecules) were prepared by the coprecipitation method (Mulinacci and others 1996). Thymol or cinnamaldehyde was added to a saturated solution of β-CD previously heated to 50°C, at equimolar concentrations with guest molecule–CD, and stirred for 4 h at that temperature. The solution obtained was allowed to cool to ambient temperature in contact with the guest

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molecule excess and was then stored overnight at 2°C. The precipitated complexes obtained were filtered, freeze-dried, and stored under vacuum over magnesium perchlorate until they were used. Sorption Isotherms Sorption isotherms were determined by the standard isopiestic static-gravimetric method. Aliquots of about 500 mg of β-CD or of the complexes (β-CD–thymol or β-CD–cinnamaldehyde) were distributed into glass vials and exposed to atmospheres of saturated salt solutions of aw from 0.22 to 0.97 in evacuated desiccators at 25°C. The aw values were taken from Greenspan (1977). The time required for equilibration was 1–2 weeks, depending on the aw. The equilibrium moisture content of samples was determined by the difference in weight before and after drying in vacuum ovens at 98°C for 48 h. These conditions had been proven to be adequate for assessing constant weight after drying. The determinations were performed in triplicate, and the average value was reported. Storage Study The release of encapsulated thymol or cinnamaldehyde was determined by DSC following the fusion enthalpies in the ranges 48°–50°C for thymol systems and −7.5° to −10°C for cinnamaldehyde. The measurements were performed as a function of time after equilibration and storage in the vacuum desiccators at constant aw at 25°C. Differential Scanning Calorimetry A differential scanning calorimeter (Mettler TA 4000 with a TC11 TA processor and Graph Ware TA72 thermal analysis software [Mettler Instruments, Highstown, NJ, USA]) was used for all the measurements. The instrument was calibrated by using indium, zinc, and lead. Analysis in duplicate involved 40-μL hermetically sealed aluminum pans (Mettler) containing samples (of 5–10 mg). An empty pan was used as a reference. The dynamic method was used to determine melting points (Tm) and heat of fusion (ΔHm) of β-CD, thymol, cinnamaldehyde, and the complexes. A Tm was taken to be the onset of the melting peak. Each sample was heated at a rate of 10°C/min from −100° up to 110°C. The percent of pure compounds released (%R) from complexes was calculated from the ratio of the fusion enthalpy of thymol or cinnamaldehyde in the complexes (corrected according to the water content of the samples) and the fusion enthalpy of the pure compound, as indicated in Equation 10.1. % Released (% R ) =

ΔH s ΔH o

(10.1)

where ΔHs is the heat needed to melt thymol or cinnamaldehyde in the complexes, and ΔHo is the heat needed to melt pure thymol or cinnamaldehyde.

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Results and Discussion Sorption Moisture Studies Figure 10.1a shows the sorption isotherm of β-CD. During the sorption process, water uptake occurred up to aw 0.5. After the first sorption stage, the water content was constant up to aw 0.75, corresponding to a hydrated form of approximately 10.5 mol of water per mole of β-cyclodextrin. At aw values beyond 0.75, the sorbed-water concentration rapidly increased, reaching a final sorption level of 12.5 mol of water per mole of β-cyclodextrin at aw 0.97. This behavior agrees with that reported by Marini and others (1995), who determined that the number of water molecules changed

Figure 10.1. Water-sorption isotherms of (a) β-cyclodextrin (β-CD) and (b) β-CD– cinnamaldehyde and β-CD–thymol complexes, expressed as mol H2O/mol dry solids vs water activity (aw).


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from 12.3 to 9.4 in a continuous and reversible way when aw changed from 1 to 0.15. Lindner and Saenger (1978, 1982), after crystallographic studies, reported that β-CD is associated with 12 water molecules forming dodecahydrate. The β-CD cavity is filled with 6.5 of those water molecules distributed statically over eight specific sites. The remaining 5.5 molecules are spread over eight other sites among β-CD molecules. The authors concluded that water in the β-CD is in an “activated” state and can be easily pushed out by a guest molecule and become part of the bulk water. Later, Fugiwara and others (1983) reported a new solvate form of β-CD with 11 molecules of water. Figure 10.1b shows the sorption isotherms of β-CD–cinnamaldehyde and β-CD– thymol complexes. It is noteworthy that, although both complexes exhibited a triphasic sorption profile globally similar to that of β-CD (Figure 10.1a), the amount of sorbed water at each aw was smaller. In fact, they formed hydrates with 7 (β-CD– cinnamaldehyde) or 8.5 (β-CD–thymol) water molecules. This indicates that the complexes were formed by displacement of water molecules from the β-CD cavity by the guest compound that was included. Differential Scanning Calorimetry The DSC thermograms for thymol and the β-CD–thymol complex are presented in Figure 10.2. Similarly, Figure 10.3 shows the DSC thermograms for cinnamaldehyde

^exo Thymol Complex b-CD–thymol

5

Complex b-CD–thymol (a w 0.97, 3 months)

wt/g

b-CD

°C -80

-60

-40

-20

0

20

40

60

80

100

120

140

160

Figure 10.2. Differential scanning calorimetry thermograms of the β-cyclodextrin (β-CD)–thymol system. From the top: pure component (thymol), inclusion compound, inclusion compound after 3 months at water activity (aw) = 0.97, and, finally, pure β-CD. Results are shown as heat flow (wt/g) vs temperature (°C). Exo, exothermic heat flow direction (upward); and wt/g.

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^exo

Cinnamaldehyde Complex b-CD–cinnamaldehyde freeze drying Complex b-CD–cinnamaldehyde (aw 0.97, 3 months)

2 wt/g

b-CD

°C

-80

-60

-40

-20

0

20

40

60

80

100

120

140

Figure 10.3. Differential scanning calorimetry thermograms of the β-cyclodextrin (β-CD)–cinnamaldehyde system. From the top: pure component (cinnamaldehyde), inclusion compound, inclusion compound after 3 months at water activity (aw) = 0.97, and, finally, pure β-CD. Results are shown as heat flow (wt/g) vs temperature (°C). Exo, exothermic heat flow direction (upward); and wt/g.

and the β-CD–cinnamaldehyde complex. The β-CD thermogram was included in each figure for comparative purposes. The β-CD thermogram shows an single peak a 93°C, indicating heat sorption probably caused by water evaporation. The absence of characteristic fusion peaks for thymol at 50°C (Figure 10.2) or for cinnamaldehyde at −7.5°C (Figure 10.3) in freezedried β-CD–thymol and β-CD–cinnamaldehyde samples, respectively, is strong evidence of the formation of the inclusion complexes.

Release of Thymol and Cinnamaldehyde During Storage At aw < 0.84, neither thymol nor cinnamaldehyde were released after 84 days of storage at 25°C. Figure 10.4a and b shows the %R of thymol or cinnamaldehyde from the complexes at aw 0.84 and aw 0.97, respectively. For the β-CD–thymol samples at aw 0.84, thymol release was very low after 70 days of storage and then increased slightly (Figure 10.4a). In contrast, at aw 0.97, the thymol release started from the beginning and increased almost linearly with storage of up to 70 days. For the β-CD–cinnamaldehyde samples at aw 0.84, cinnamaldehyde release began at 23 days of storage and increased linearly with time. However, after 75 days of storage, the %R was only 12. At aw 0.97, a different behavior was observed: The release started at 60 days of storage and the %R abruptly increased after that time (Figure 10.4b).


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Figure 10.4. Percent released of (a) thymol or (b) cinnamaldehyde from their complex with β-cyclodextrin (β-CD) at water activity (aw) = 0.84 and aw = 0.97. Results shown as % released vs time (days).

The results obtained here show that the guest molecules released from β-CD complexes were detectable from aw 0.84, which coincided with the abrupt increase of water sorption observed in the corresponding isotherm. Water sorption significantly affected the stability of β-CD complexes with thymol and cinnamaldehyde, and guest molecule release was governed by the shape of the water-sorption isotherm.

References Buschmann HJ, Schollmeyer E. 2002. Applications of cyclodextrins in cosmetic products: a review. J Cosmet Sci 53:185–91.

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Greenspan L. 1977. Humidity fixed points of binary saturated aqueous solutions. J Res Natl Bur Stand [A] 81:89–102. Hedges A, McBride C. 1999. Utilization of cyclodextrin in food. Cereal Foods World 44:700–4. Lindner K, Saenger W. 1978. β-Cyclodextrin dodecahydrate: crowding of water molecules within a hydrophobic cavity. Angew Chem Int Ed Engl 17:694–5. Lindner K, Saenger W. 1982. Crystal and molecular structure of cyclohepta-amylose dodecahydrate. Carbohydr Res 99:103–15. Loftsson T, Brewster ME. 1996. Pharmaceutical application of cyclodextrins. I. Drug solubilization and stabilization. J Pharm Sci 85:1017–25. Marini A, Berbenni V, Bruni G, Massarotti V, Mustarelli P. 1995. Dehydration of the cyclodextrins: a model system for the interactions of biomolecules with water. J Chem Phys 103:7532–40. Mulinacci N, Melani F, Vincieri FF, Mazzi G, Romani A. 1996. 1H-NMR NOE and molecular modelling to characterize thymol and carvacrol β-cyclodextrin complexes. Int J Pharm 128:81–88. Steiner T, Koellner G. 1994. Crystalline β-cyclodextrin hydrate at various humidities: fast continuous and reversible dehydration studied by X-ray diffraction. J Am Chem Soc 116:5122–8. Szente L, Szejtli J. 2004. Cyclodextrins as food ingredients. Trends Food Sci Technol 15:137–42. Uekama K, Hirayama F, Irie T. 1998. Cyclodextrin drug carrier systems. Chem Rev 98:2045–76. Zabel V, Saenger W, Mason SA. 1986. Neutron diffraction study of the hydrogen bonding in β-cyclodextrin undecahydrate a 120 K: from dynamic flip-flops to static homodromic chains. J Am Chem Soc 108:3664–73.

11 Beyond Water: Waterlike Functions of Other Biological Compounds in a Waterless System B. R. Bhandari

Abstract This chapter focuses on the possible increased biochemical reactions in absence of water because of the presence of other polar solvents that can solubilize reactant molecules and increase their molecular mobility. Some of these solvents can be polyols. Until lately, the leading concept to describe the stability of food systems has been the water-activity theory, and lately some relationships have been found between the stability and glass transition temperature of the biological system. This chapter highlights that we need to move further from the water activity–related reaction-rate theory because a physicochemical reaction can occur in the absence of water if the nonwater liquid component can dissolve the solid components in the mixture at a given temperature. The current glass transition temperature theory has also not been able to describe the Maillard reaction occurring in waterless complex systems. Some past and present findings in the context of biological (mainly food) materials are presented in this chapter. The Maillard reaction occurring in the absence of water has been used as an example.

Introduction Almost all biological systems contain water. Water helps to increase the molecular mobility of biological systems by acting as a plasticizer, solvent, and vehicle for all biochemical movements and reactions. All biological components interact with water either directly or through mediating molecules (such as emulsifiers and surfactants). Traces of water can also be present even in dehydrated biomolecules (such as protein or hydrate crystals) to maintain their molecular structure. It has already been established that there is an adverse effect on proteins’ native structure or on other long-chain biopolymers if this trace of water is removed. In the absence of sufficient water, some materials vitrify or crystallize. A live cellular system can become inactivated or die because of overdehydration or the crystallization of solutes. Many low molecular weight food materials have been used for the protection of biological materials, such as proteins, enzymes, and even live cultures, because of the waterlike behavior of these molecules (possibly partially occupying the hydrophilic sites that supposedly interact with water). Water is also a strong polar solvent capable of weakening hydrogen, covalent, or ionic bonds in solids, thus dispersing them into the bulk water. Now we can raise 157

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a question: Can other relatively weak polar food materials that are in a liquid state also function as a solvent like water? Logically, they probably should be able to. Lower-chain polyols have been popular in food and pharmaceutical systems because of their plasticizing and humectant properties. They are added in conjunction or in preference to other common sugars. Do some polar polyols dissolve water-soluble solids? If so, they will promote various chemical reactions in foods, in a way similar to water, by increasing the molecular mobility of the system.

Understanding Molecular Mobility Molecular mobility is the primary parameter in causing physical or chemical change in biological materials. Molecular entities have three motions: translational (threedimensional displacement from one location to another), rotational (movement around an axis), and vibrational (stretching and bending of the bonds between the atoms, which changes the shape of the molecules). Translational motion and rotational motion relate to the movement of the entire molecule, whereas vibrational motion occurs within the molecule. The magnitude of these motions depends on the physical state of the matter (liquid, solid, or gaseous), because of the different degree of intermolecular interaction and free volume (intermolecular space) between the molecules in each of those states. The possible interactions between the molecules involve covalent and noncovalent bonds. Noncovalent bonds encompass electrostatic forces such as hydrogen, ionic, and dipole interactions and van der Waals forces. Noncovalent bonds exist more often on macromolecules and are common in biological molecules such as proteins and carbohydrates. Noncovalent bonds are important in forming the secondary and tertiary structures of the molecules. Covalent bonds are formed by the equal or unequal sharing of one or more pairs of electrons between atoms. Nonpolar bonds, which involve an equal sharing of electrons, are described as nonpolar because of the nonaccumulation of electrons and the absence of dipole movement. Covalent bonds are stronger than noncovalent bonds. The state of the matter determines the extent of these intermolecular forces and molecular mobility. It should be noted that the prerequisite for any reaction to occur is the collision between molecules. The probability of collision will be higher at higher molecular mobility and closer proximity of the reacting molecules or atoms. Reactant molecules are in very close proximity if they are miscible or soluble in the same solvent. An entire molecule does not have to be mobile for a reaction to occur. Depending on the type of molecule, if a part of the molecular functional group(s) or segment of the molecule has some kind mobility, the molecule can take part in a reaction if the orientation of the reactant groups in the molecules is right. Small molecules or plasticizers can increase this mobility. Credit goes to Slade and Levine (1991) for explaining a great deal about molecular mobility in relation to biological material stability.

Water-Activity Theory on the Stability of Biological Materials Biological materials (food, agricultural, pharmaceutical, and so on) are normally dried into solid form by removing water to limit the molecular mobility of the reactant

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molecules and extend the shelf life of the product. The degree of interaction of water with the biological components determines the activity of the water or its availability for providing mobility in the biological system. Water that is present in noncondensed state in biological matter (which means that individual molecules of water can interact with the solid components’ hydrophilic sites) may not provide molecular mobility, although water migration may occur from weaker interaction sites to stronger interaction sites in multicomponent systems. Water at this stage is normally referred as monomolecular layer water. Many studies have been published about the relationships between water activity (aw) and the rate of various reactions and growth of microbes. In water-rich biological systems, many reactions are diffusion limited, where water acts as a diffusion medium. Water has also been a diluting factor, reducing the reaction rate of nonenzymatic browning, and a protection factor against increased oxidation at lower moisture levels. Many low molecular weight biological materials have been used to protect biological materials, such as proteins, enzymes, and even live cultures, in the dry state, because of the waterlike behavior of these molecules (possibly partially occupying the hydrophilic sites that were previously interacting with water).

Waterlike Solvation Property of Polyols Food and pharmaceutical products contain many compounds that can be in a liquid state and that can act as a solvent for other polar solids. This can result in the dissolution of polar solids into polar liquids when the attractive forces between the liquids and solids exceed the attractive forces between the solid molecules. Many food systems contain components that are either in a liquid or a solid state with a certain level of polarity, as listed in Table 11.1. The polarity of a solvent can be determined based on measurement of its dielectric constant. A highly polar solvent will have a dielectric constant (ε) of greater than 50, whereas a semipolar solvent will have an ε of around 20–50, and a nonpolar solvent will have an ε of less than 20. The

Table 11.1. Dielectric constants (relative polarity) of various compounds Compounds

ε, at 20°C

Relative polarity

Water

80

High

Sorbitol (79% wt/wt)

62

High

Glycerol

46

Semi

Dimethyl sulfoxide (DMSO)

47

Semi

Methanol

33

Semi

Propylene glycol

32

Semi

Ethanol

25

Semi

Acetone

21

Semi

Olive oil

3.1

Nonpolar

Benzene

2.2

Nonpolar

ε, dielectric constant.

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Table 11.2. Approximate solubility of some sugars in glycerol at 60°C after an equilibration period of 10 days Sugars

Solubility (g/100 g glycerol)

Fructose

50

Glucose

20

Sucrose

15

Maltose

40

Lactose

10

From Bhandari and others (2009a).

Figure 11.1. Microscopic photographs of a sucrose crystal dissolving in anhydrous sorbitol at 100°C (sucrose/sorbitol ratio, 30 : 100).

data in Table 11.1 show that sorbitol and glycerol can act as a solvent for sugars if the sorbitol or glycerol are in a liquid state. Bhandari and Roos (2003) found sucrose crystals dissolving in sorbitol above the melting point of sorbitol (when sorbitol remained in a liquid state) (Figure 11.1). The solubility of various sugars in an aqueous solution of glycerol was reported in early publications (Segur and Miner 1953). However, no previous work has been reported on the solubility of sugars in anhydrous glycerol, which is in the liquid state at room temperature (20°C). Polyols such as glycerol or sorbitol have been widely used as plasticizers, but all plasticizers do not necessarily behave as solvents would. Bhandari and others (2009a) found that common food sugars (lactose, sucrose, fructose, glucose, and maltose) are all soluble in pure glycerol at various levels (Table 11.2). Obviously, their solubility is a function of the solvent temperature, and the equilibrium time required in glycerol was longer than in water because the high viscosity of glycerol limits the diffusivity or dispersability of solvated molecules across the solution (results not shown) and because of their relatively lower polarity than water. The solubility of various pharmaceuticals in glycerol has been reported (Seedher and Bhatia 2003). The solubility of glycerol will certainly be enhanced by the presence of a small amount of strongly polar water. The important question here regards not only the solubility, but the molecular mobility of solute in a waterless environment, because nonwater solvents can also provide molecular mobility to a complex (multicomponent) system. The role of

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glycerol as plasticizer has been recognized, but plasticizers do not necessarily solvate molecules. They increase the free intermolecular space (free volume) in the system, resulting in higher molecular mobility. The reaction rate will be much faster if the reactants are solubilized. This has implications for many low-moisture dry-food formulations that may contain sugars and polyols and other reactant molecules such as protein. The dissolution of some components, crystallization, and an antiplasticizing (toughening) effect may also result from the waterlike behavior of polyols. This implies that reaction in a low-moisture dry-food system can occur even if the water activity is close to zero if other mobile components are in the system.

Glass Transition, Molecular Mobility, and Sub-Tg Relaxation Glass transition temperature (Tg) has been the best concept related to molecular mobility. The glass transition of a multicomponent system will depend on the intrasolubility, plasticizing, and compatibility or miscibility of components with one another. At a glass transition temperature, the backbone of the molecular structure is normally frozen, which is referred as α relaxation. However, depending on the rate of this change, β relaxation of molecules continues below this glass transition temperature (α relaxation). This sub-Tg event is called molecular relaxation or structural relaxation, which occurs due to the nonequilibrium amorphous system (created during α relaxation) trying to reach the low-energy equilibrium state. It should be noted that some translational and rotational motion of smaller molecules (such as water or other solvents) or the segment or functional group of a molecule continues, though, of course, at a slower rate. Vibrational motion still exists (until the temperature of absolute zero). Dissolution of solutes in a solvent will reduce glass transition temperature. Plasticization and dissolution may influence the overall glass transition temperature of multicomponent systems differently. In a number of pharmaceutical systems, the effect of β relaxation on the stability of drugs or bioactives has been reported, but no such work has been widely published about food systems, although the effect has been identified in a few recent publications. It has also been reported that β relaxation is enhanced by the presence of water, resulting in a toughening of the product (antiplasticizing effect) below the glass transition temperature. We can not rule out the possibility of β relaxation being affected by other waterlike solvents such as glycerol.

Molecular Mobility and the Maillard Reaction Nonenzymatic browning (the Maillard reaction) is the best example illustrating the importance of molecular mobility, since this is the most common phenomenon responsible for food deterioration and is also easy to analyze because the reaction rate is very fast at higher temperature. The Maillard reaction occurs due to the condensation between amino groups and reducing sugars, and consequently many color compounds (low molecular weight polar, and high molecular weight nonpolar compounds) are produced, depending on the temperature and time. It is a bimolecular reaction; therefore, the molecular mobilities of two different molecular species are essential.

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The Maillard Reaction in the Absence of Water But Below the Glass Transition Temperature Relating the reactions on the basis of water activity and glass transition temperature may still be crude ways of prediction, although the use of these parameters has yielded the highest level of certainty in the majority of food and pharmaceutical systems. The Maillard reaction was found to occur in dry pasta systems (Fogliano and others 1999). Creation of some small, mobile molecules due to deamidation of glutamine was attributed to this reaction even below the Tg. Schebor and others (1999) also reported a Maillard reaction below the glass transition temperature in powdered anhydrous milk systems. In this case, the authors suspected that other types of localized mobility, such as glass relaxation, the intermixing of reactants increasing the proximity of the molecules in the concentrated state, or localized mobility near the pores might have existed, since no other components were present in the milk. However, the milk still contained some fat, which would have been mobile; and protein, which can be a part of fat globule membrane, would still have some mobility at the interface of solid oil. It is not clear though whether such factors can influence aminocarbonyl condensation. Any preexisting smaller molecules (amino compounds) can still retain translational motion within the matrix. Dissolution of some protein or peptide in lactose cannot be ruled out as causing this effect. (Localized β relaxation can accelerate the condensation of amino and carbonyl groups.) In an early study, Kamman and Labuza (1985) found that the Maillard reaction was accelerated by the presence of liquid-phase oil in a powder starch mix containing glucose and glutamate. Their assumption was that the oil may act as a solvent for the reactants. However, it was not explained how a hydrophobic oil can solubilize these polar reactants. This is an important area that needs further investigation. The results of some earlier, as well recent, studies, have indicated that the presence of glycerol can promote the Maillard reaction (Warmbier and others 1976; Mustapha and others 1998; Cerny and Guntz-Dubini 2006). Some of these studies have used some amount of water (glycerol as a cosolvent). However, Mustapha and others (1998) presented some Maillard reaction results at near zero moisture content (aw = 0.01) in glycerol. They found that the Maillard reaction between lysine and the xylose system was higher in a glycerol, than in a water medium. However, the addition of water to glycerol enhanced the reaction rate presumably because of the increased solubility of reactants. Our preliminary work found that sugars and amino acids are dissolved in glycerol, and the Maillard reaction occurs in an anhydrous glycerol + sugar + glycine system (Bhandari and others 2009b). The data clearly indicated that there is a Maillard reaction, and its rate depends on the temperature and reaction time (Figure 11.2). The compounds produced during early and later stages of Maillard reactions are now being determined and evaluated.

Concluding Remarks Some of the changes that occur in biological materials can be described accurately by neither the water-activity nor the glass transition theories. In complex systems, intra-

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100°C

115°C

0 min

30 min

60 min

130°C 120 min 180 min 240 min

24 H

Figure 11.2. Color development due to nonenzymatic Maillard browning in a waterless environment at 100°, 115°, and 130°C (fructose-glycine solution in glycerol). Samples were incubated for 24 h.

solubility and localized molecular mobility of various components are possible; in particular, the solubility of components in a waterless system warrants further study. This understanding is particularly useful in biological systems (such as food and pharmaceuticals) with limited water content. In many food products (intermediate or dried foods), polyols and sugars may be added to improve the shelf life and textural, sensory, or nutritional quality of the food products. In pharmaceutical products, polyols and sugars are added as bulking compounds, functional agents, or carriers. Not only the plasticizing effect but also the solvation property of some components may influence the chemical and physical changes in products. The solvation capacity of low-melting-point food components (such as fat, polyols, and sugars) and their role in intracomponent reactions based on the molecular mobility concept need further attention, which may answer some of the controversial questions raised about changes occurring in dry biological materials with very low water activity.

References Bhandari B, Ling OE, Yap O. 2009a. Dissolution of sugars in glycerol. J Agric Food Chem (forthcoming). Bhandari B, Roos Y. 2003. Dissolution of sucrose crystals in the anhydrous sorbitol melt. Carbohydr Res 338:361–7. Bhandari B, Wang CW, Wijayanti HB. 2009b. Maillard reaction of sugars with glycine in glycerol system. Food Chem (forthcoming). Cerny C, Guntz-Dubini R. 2006. Role of solvent glycerol in the Maillard reaction of D-fructose and L-alanine. J Agric Food Chem 54: 574–7. Fogliano V, Monti MS, Musella T, Randazzo G, Ritieni A. 1999. Formation of coloured Maillard reaction products in a gluten-glucose model system. Food Chem 66:293–9. Kamman JF, Labuza TP. 1985. A comparison of the effect of oil versus plasticized vegetable shortening on rates of glucose utilization in nonenzymatic browning. J Food Proc Preserv 9:217–22.

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Mustapha WAW, Hill SE, Blanshard JMV, Derbyshire W. 1998. Maillard reactions: do the properties of liquid matrices matter? Food Chem 62:441–9. Schebor C, Buera MP, Karel M, Chirife J. 1999. Color formation due to non-enzymatic browning in amorphous, glassy, anhydrous, model systems. Food Chem 65:427–32. Seedher N, Bhatia S. 2003. Solubility enhancement of cox-2 inhibitors using various solvent systems. AAPS Pharm Sci Tech 4:1–9, article 33. Segur JB, Miner CS. 1953. Sucrose and dextrose in aqueous glycerol. J Agric Food Chem 1:567–9. Slade L, Levine H. 1991. Beyond water activity: recent advances based on an alternative approach to the assessment of food quality and safety. Crit Rev Food Sci Nutr 30:115–360. Warmbier HC, Schnickels RA, Labuza TP. 1976. Effect of glycerol on nonenzymatic browning in a solid intermediate moisture model food system. J Food Sci 41:528–31.

12 Water Sorption and Transport in Dry, Crispy Bread Crust M. B. J. Meinders, N. H. van Nieuwenhuijzen, R. H. Tromp, R. J. Hamer, and T. van Vliet

Abstract Water-sorption and dynamic properties of bread crust have been studied in gravimetric sorption experiments. Water uptake and loss were measured while relative humidity (RH) was stepwise increased or decreased (isotherm experiment) or varied between two adjusted values (oscillatory experiment). Experimental results were compared with the Fickian diffusion model and empirical models like the exponential and power-law model. The sorption curves that resulted from the isotherm experiments were best described by the Fickian diffusion model for low RH and by the exponential model for high RH. Transport rates depended on moisture content and showed a maximum around RH = 70%. Adsorption and desorption curves from oscillatory experiments were best described by the exponential model. From comparison of the experimental sorption curves and the power-law model for short times it followed for all bread crust that the diffusion coefficient n is close to 1. Normally, this is associated with so-called case II diffusion and water transport that are limited by relaxation of the solid material. However, additional observations suggest that this may not be a valid explanation and that a gradual, instead of stepwise change in RH and/or a kinetic barrier for water transfer to the solid matrix may explain the observed exponential behavior.

Introduction One of the most important factors on which consumers base their appreciation of dry cellular solid-food products is crispness (e.g., see Szczesniak 1971; Roudaut and others 2002; Luyten and others 2004). A dry, crispy product that is in contact with a more humid environment takes up water, and the crispy character is quickly lost when the water activity (aw) becomes higher than about 0.5 (Labuza and Hyman 1998; Luyten and others 2004; Payne and Labuza 2005). To control crispness and increase the shelf life of composite products that consist of a dry and crispy part and a more humid and soft part, fundamental knowledge about water-sorption dynamics and its dependence on ingredients and morphology is needed. However, water sorption in these products is complex and governed by various phenomena like migration of water vapor through mesoscopic open pores and microscopic capillaries, sorption and migration of water through the solid matrix, swelling and/or relaxation of the matrix, and hysteresis. 165

166


Most models that describe sorption dynamics in polymeric porous systems are based on diffusion (for a review, see Masaro and Zhu 1999). Two extreme cases can be distinguished in the literature: (a) Fickian diffusion, where the transport of a penetrant like water is controlled by its concentration gradient, and the dynamics can be described by Fick’s law; and (b) case II diffusion, where transport is controlled by the relaxation of the solid material. When sorption dynamics are controlled by both processes and the corresponding rates are similar, this is called anomalous diffusion. A way to distinguish between the sorption mechanisms is by analyzing the uptake behavior for short times. Then, Fickian diffusion behaves like t0.5, case II like t1, and anomalous diffusion like tn with 0.5 < n < 1. Various studies have been published about the sorption behavior in biopolymeric systems. Fickian diffusion including a water concentration–dependent diffusion coefficient was used to describe sorption dynamics of sponge cake (Guillard and others 2003), dry biscuit (Guillard and others 2004), and waxy maize starch (Enrione and others 2007). A single exponential was used to describe the sorption kinetics of wheat flours (Roman-Gutierrez and others 2002). For chitosan films, diffusion seems Fickian for aw < 0.4 and anomalous for aw > 0.4 (Despond and others 2001). Del Nobile and coworkers developed a model where Fickian diffusion, including a concentrationdependent diffusivity, and polymer relaxation were combined to describe sorption dynamics of spaghetti and films of nylon, chitosan, alginate, casein, and zein (Del Nobile and others 1997, 2000, 2003a, 2003b, 2004; Buonocore and others 2005). These studies gained much insight, but fundamental generic knowledge that enables crispness to be controlled is still lacking. Furthermore, no studies have been published about the sorption dynamics of crispy bread crust. Therefore, to obtain more insight into the water-sorption mechanisms and dynamics of bread crust, we conducted a detailed study. Gravimetric stepwise oscillatory and isotherm sorption experiments on model bread crusts were performed and compared with different sorption models such as Fickian diffusion, the exponential model, and the power-law model.

Materials and Methods Sorption experiments were performed on model bread crusts and crusts of a rusk roll. Model bread crusts were obtained by baking thin sheets of dough (diameter, 60 mm; and thickness, 2 mm) in a halogen heater. Dough was prepared from a protein-rich and starch-rich wind-sifted fraction of wheat flour. Rusk roll crusts were removed from rolls prepared from wheat flour and baked in an oven. Crust samples were milled and sieved afterward in three different fractions with sizes smaller than 63 μm, between 63 and 250 μm, and between 250 and 500 μm (called small, medium, and large, respectively). Gravimetric sorption experiments were performed on about 6 mg of these fractions by using a VTI-SGA 100 symmetric vapor-sorption analyzer (VTI, Hialeah, FL, USA) at a temperature T of 25°C. Samples were dried above phosphorus pentoxide for at least 3 days. Before sorption experiments started, a drying step was performed for 2 h at 50°C. Starch, protein, pentosan, and fat contents were also determined. A detailed description of the sample preparation and experimental methods,

Water Sorption and Transport in Dry, Crispy Bread Crust

167

as well as the results of the ingredient analysis, can be found elsewhere (van Nieuwenhuijzen and others 2007, 2008).

Models For Fickian diffusion, the weight change as a function of time t for a spherical particle having radius rs, initially having a homogeneous water concentration C0, a constant surface concentration Cs, and a diffusion coefficient D independent of concentration C is given by Crank (1975), 6 ⎛ m − m 0 = ( m ∞ − m 0 ) ⎜1 − 2 ⎝ π

∞

1

∑n n =1

2

⎞ exp ( − Dn 2 π 2 t rs2 )⎟ ⎠

(12.1)

with m = mt and mi = M0 + 兰Cidr (for i = t, 0, ∞) and M0 as the mass of the dry particle. This equation is fitted against experimental sorption curves, with D rs2 and m∞ as fit parameters. For all analysis, the first minute of the experimental sorption curve was excluded from the fit because during this time the system needs to settle after a sudden change in relative humidity (RH) and environmental conditions are uncertain. Furthermore, it is assumed that diffusion through the vapor phase is not limiting because the water diffusion coefficient in air is more than 5 orders of magnitude larger than that of the solid matrix. Sorption dynamics are also compared with single exponential behavior, where the weight change as function of time is described by m − m 0 = ( m ∞ − m 0 ) (1 − exp ( − kt ))

(12.2)

with k as the transport rate. Here k and m∞ are fit parameters. Exponential behavior may be used to describe the relaxation dynamics of the polymeric matrix (Berens and Hopfenberg 1978). For short times, sorption dynamics may also be described by the empirical powerlaw relation m − m 0 = at n

(12.3)

where the a is a constant and the n is the diffusion exponent. In the short time limit, the diffusion exponent n is evaluated from the sorption curves plotted on a log-log scale and is equal to the derivative of the first linear part in that plot. When n = 0.5, n = 1, or 0.5 < n < 1, the sorption mechanism is said to be Fickian, case II, or anomalous, respectively. Calculations were performed using Matlab (MathWorks, Natick, MA, USA).

Results and Discussion Figure 12.1a shows a typical example of the relative change in weight of bread crust (in this case, a starch-rich model crust, large fraction) together with the RH as


(a)

100 80 60

20

40 10

1

0.98 RH [%]

(m-m0)/m0 [%]

30

(b)

R2

168

0.96

0.94 20

0

(c)

2000

0

4000 t [min]

6000

0

0.92

(d)

6

40 60 RH [%]

80

100

RH: 60% 70%

5.5

(m-m0)/m0 [%]

(m-m0)/m0 [%]

20

14

RH: 30% 40%

5

4.5

4 1800

0

13

12

11

1900

2000 t [min]

2100

2200

10 3000

3100

3200

3300

t [min]

Figure 12.1. (a) Measured relative change in weight (m − m0)/m0 (thick line, left axis) of a starch-rich model crust and the adjusted external relative humidity (RH) (thin line, right axis) as a function of time t during an isotherm experiment. (b) R2 of the best fit between the measured (m − m0)/m0 and the diffusion model (Equation 12.1, open squares) and single exponential (Equation 12.2, open circles) as a function of RH. (c) Enlargement of an adsorption curve (open circles) and the best fit of the diffusion model (Equation 12.1, dashed line) and single exponential model (Equation 12.2, continuous line) as a function of t. The external RH changed from 30% to 40%. (d) Similar, but RH changed from 60% to 70%.

a function of t. The sorption curves for each step were analyzed and fitted against the sorption models described earlier. Equilibrium values (m∞ − m0)/m0 yield the isotherm. For all bread crusts, isotherms showed hysteresis and were best described by the Guggenheim-Anderson-de Boer (GAB) equation. This corresponds well with what has been observed for most food systems (Basu and others 2006). The diffusion exponent n (Equation 12.3) turned out to be close to 1, suggesting the sorption mechanism to be case II and controlled by the relaxation rate of the polymeric matrix. Figures 12.1c and d show examples of adsorption curves for two RH steps. Also, the best fits of the diffusion model (Equation 12.1) and the exponential model (Equation 12.2) are shown. Comparison between experimental and simulated sorption curves


169

shows that water sorption in the low-moisture regime is better described by the Fickian diffusion equation, whereas in the high moisture regime it may be more accurately described by an exponential. This is also illustrated in Figure 12.1b, where the R2 of the fits is plotted for the adsorption curves as a function of RH. It is seen that the transition point is around RH = 40%. This is similar to results found for chitosan films (Despond and others 2001) and waxy maize systems (Enrione and others 2007), although in those cases the results were based on evaluation of the diffusion exponent n. For the desorption curves, similar behavior is found, only the change in going from more exponential to diffusive behavior happens at around RH = 60% (results not shown). Figure 12.2 (left) shows the sorption rates k obtained from the fits by using a single exponential as a function of RH. Also, diffusion coefficients D are shown (right) obtained from the fits by using the Fickian diffusion model and assuming a particle radius rs = 190 μm. The figure shows that water-adsorption rates increase with RH up to a value of about 70% and decrease at higher RH. Similar behavior is observed for the other bread crust samples (results not shown) and has also been observed for other food systems (Guillard and others 2003, 2004; Enrione and others 2007). The increase in transport rate may be associated with an increase in free volume due to the plasticizing effect of water. The decrease at high humidities may be attributed to capillary condensation and/or, more likely, to collapse and caking of the polymeric structure due to a transition from the glassy state to the rubbery state. For the bread crusts, this transition occurs at room temperature at about RH = 80% (van Nieuwenhuijzen and others 2008). Collapse might result in a reduction of the effective area exposed to the solvent and therefore a decrease in sorption rate.

-11

0.08

10

0.06 2

D [m /s]

k [1/min]

-12

10 0.04

-13

10 0.02

0

-14

0

20

40 60 RH [%]

80

100

10

0

20

40 60 RH [%]

80

100

Figure 12.2. (Left) Adsorption rates (open circles) and desorption rates (solid circles) k obtained from the best fits between the relative change of weight of a starch-rich model crust during the isotherm experiment shown in Figure 12.1a and the single exponential model (Equation 12.2) as a function of relative humidity (RH). (Right) Effective diffusion coefficients D during adsorption (open squares) and desorption (solid squares) obtained from the best fits of the Fickian diffusion model (Equation 12.1) assuming rs = 190 μm.


6

6

5

5 (m-m0 )/m0 [%]

(m-m0 )/m0 [%]

170

4 3 2 1 0

4 3 2 1

0

1000

2000 t [min]

3000

0

0

1000

t [min]

2000

3000

Figure 12.3. (Left) Measured relative change in weight (m − m0)/m0 (thin line) of a starch-rich model crust because of an oscillatory stepwise change in adjusted relative humidity from 40% to 50% and the best fit of the diffusion model (Equation 12.1, dashed line) and single exponential model (Equation 12.2, continuous line) as a function of time t. Inset: Examples of experimental sorption curves (open circles) and best fits of the single exponential model. (Right) Simulated moisture uptake obtained by numerically solving the diffusion equation (D = 10−12 m2/s, rs = 190 μm) and an oscillatory stepwise change of surface concentration Cs between 4.4% and 6.1%. Inset: Calculated sorption curves (dashed line) and best fit of the single exponential model (continuous line).

For all RHs, desorption rates are found to be higher than adsorption rates. An explanation is that water-diffusion rates are higher than matrix relaxation rates so that during desorption, when the matrix is already swollen, the water transport is not limited by the matrix relaxation. However, then Fickian diffusion with n ≈ 0.5 is expected for the desorption steps, which is contrary to what is found in our study. It is also observed that the maximum desorption rate is at a lower RH than that of adsorption. This might be due to the hysteresis that shifts the glass-rubber transition to a lower RH. Figure 12.3 (left) shows a typical example of an oscillatory sorption experiment on bread crust. Here the relative moisture uptake is shown as a function of time for a starch-rich model crust (large fraction). The initially dry sample was exposed to an RH varying stepwise between 40% and 50% with an oscillation time of 25 min. It is seen that the moisture uptake seems to be a sum of a smooth curve that increases from zero to an equilibrium value and an oscillating one with the same frequency as the changes in RH. The figure also shows the best fits of the overall curve with the diffusion model (Equation 12.1) and the exponential model (Equation 12.2). The diffusion model turned out to describe the overall sorption curve best for low RH (oscillating between 40%–50% and 50%–60%) and the exponential model was best for higher RH (oscillating between 60%–70% and 70%–80%). This trend is similar to that found for the isotherm measurements. The fitted rate values are about a factor of 2 smaller than the rates found for the isotherm measurements because of the strong positive relation


171

between transport rates and moisture content. This causes an effective lower transport rate for the oscillatory experiments because the time-averaged moisture content of the crust particles during adsorption is lower compared to that during the isotherm measurements. The fitted equilibrium values correspond well to the adsorption branch of the isotherm. The inset in the left pane of Figure 12.3 shows the relative moisture uptake during an adsorption step and the best fit of the exponential model (Equation 12.2). All oscillatory experiments on bread crusts show that the diffusion exponent n is about 1 for all adsorption and desorption curves. Furthermore, all single sorption curves could be very well described by a single exponential (R2 > 0.98) and did not show the characteristic Fickian behavior with n = 0.5. This might be because during an oscillatory experiment the system is never in equilibrium and the moisture content at t0, when RH switches, is not homogeneously distributed. Thus, Equation 12.1 is not valid for describing the sorption curves of the oscillatory experiments. To check whether the exponential behavior is caused by the system not being in equilibrium when RH switches, we solved the diffusion equation numerically for a spherical particle with radius rs = 190 μm, initially dry (mt=0 = m0), and a stepwise oscillating surface concentration CS between 4.4% and 6.1% with an oscillation time of 25 min. Figure 12.3 (right) shows the results for a constant D = 10−12 m2/s. At first sight, there is a good correspondence between experimental and simulated water uptake. However, the simulated sorption curves for each oscillating step show the typical Fickian n ≈ 0.5 behavior, and poor correspondence is observed with a single exponential function, as can be seen in the inset in the figure. Calculations using a moisture-dependent diffusion coefficient taken from the isotherm measurements (Figure 12.2) show similar results and cannot explain the experimentally observed exponential behavior. Table 12.1 summarizes results of the comparisons between experiments, simulations, and model fitting. Figure 12.4 shows the mean sorption rates of starch-rich model crust during oscillatory sorption experiments in the stationary regime as a function of RH. Sorption rates kosc are obtained from best fits between experimental sorption curves and the single exponential model (Equation 12.2) for each oscillation step. The oscillatory

Table 12.1. Summary of fitted diffusional coefficient (n) and closeness of fits of the diffusion (D model) and exponential model (E model), for low and high relative humidity (RH), isotherm and oscillatory experiments, as well as isotherm and oscillatory simulation of Fickian diffusion in a sphere Experimental Isotherm

Simulation

Oscillation

Low

High

Low

High

D model

+

−

−

E model

−

+

n

∼1

∼1

RH:

Isotherm High

Low

−

++

++

++

++

+

+

−

−

−

−

∼1

∼1

∼0.5

∼0.5

∼0.5

∼0.5

++, +, and − correspond to R ≈ 1, ≈0.99, and

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