New Topics in Food Engineering

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FOOD SCIENCE AND TECHNOLOGY

NEW TOPICS IN FOOD ENGINEERING

No part of this digital document may be reproduced, stored in a retrieval system or transmitted in any form or by any means. The publisher has taken reasonable care in the preparation of this digital document, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained herein. This digital document is sold with the clear understanding that the publisher is not engaged in rendering legal, medical or any other professional services.

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FOOD SCIENCE AND TECHNOLOGY

NEW TOPICS IN FOOD ENGINEERING

MARIANN A. COMEAU EDITOR

Nova Science Publishers, Inc. New York

Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers’ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book. LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA New topics in food engineering / editor: Mariann A. Comeau. p. cm. -- (Food science and technology) Includes index. ISBN 978-1-61209-896-8 (eBook) 1. Food industry and trade. I. Comeau, Mariann A. II. Series: Food science and technology series (Nova Science Publishers) TP370.N44 2011 664--dc22 2011002382

Published by Nova Science Publishers, Inc. © New York

CONTENTS Preface Chapter 1

Chapter 2

Chapter 3

Chapter 4

Chapter 5

Chapter 6

Chapter 7

Chapter 8

vii Tempering, Polymorphism and Fat Crystallization During Industrial Chocolate Manufacture: Regimes, Behaviours and their Effects on Finished Chocolate Quality Emmanuel Ohene Afoakwa and Alistair Paterson Non-linear Modeling of Quality of Cooked Ground Beef Patties with Visible-NIR Spectroscopy Sreekala G. Bajwa and Jason K. Apple Molecular Size Distribution in Long-aged Food Beverages and Alcoholic Drinks: A Preliminary Inquiry towards Understanding Physical-and Sensory-Related Properties Pasquale Massimiliano Falcone and Paolo Giudici Hyperspectral Waveband Selection for Detection of Almonds with Internal Damage Songyot Nakariyakul High Frequency Ultrasonic Techniques Dedicated to Food Physical Properties Assessment D. Laux, J. Y. Ferrandis, V. Cereser Camara, H. Blasco and M. Valente Trends in High Pressure Processing of Foods: Food Quality and Bioactive Components Shirani Gamlath and Lara Wakeling Thermodynamic and Kinetic Criteria to Study the Stability of Dried Foods Cesar I. Beristain, Eduardo J. Vernon-Carter and Ebner Azuara Development of Vacuum Spray Drying System for Probiotics Powder Yutaka Kitamura and Yukari Yanase

13

35

57

81

99

121

151

171

vi Chapter 9

Contents Application of Vacuum Impregnation and Edible Films to Improve The Quality of Raisin-Cereal Systems Pau Talens and María José Fabra

233

Chapter 10

Food Packaging: Innovative Concept and Necessities Kelen Cristina Dos Reis

249

Chapter 11

Predictive Modelling of Thermal Properties of Foods James K. Carson

261

Chapter 12

Applications of Membrane Contactors in the Food Industry Catherine Charcosset

279

Chapter 13

Possibilities for Removal of Glucose From Various Foodstuffs and Food Bioprocesses K. Bélafi-Bakó

Chapter 14 Index

Instant Rice Physicochemical Properties and Eating Quality Prisana Suwannaporn

289 301 313

PREFACE In the development of food engineering, one of the many challenges is to employ modern tools and knowledge to develop new products and processes. Simultaneously, improving quality, safety, and security remain critical issues in food engineering. Additionally, process control and automation regularly appear among the top priorities identified in food engineering. This book presents topical research in the study of food engineering, including: ozone technology in the food industry; current trends in drying and dehydration of foods; strategies for extending the shelf-life of foods using antimicrobial edible films; developments in high-pressure food processing; as well as tempering and polymorphism during chocolate manufacture. Chapter 1 - Tempering, a technique of shearing chocolate mass at controlled temperatures is used to promote cocoa butter crystallization in a thermodynamically stable polymorphic form. During chocolate manufacture, the process is used to obtain the stable form V (or ß2) of cocoa butter having a melting temperature of 32-34 °C, which gives the desired glossy appearance, good snap, contraction and enhanced shelf life characteristics. However, the tempering sequences, their behaviour during pre-crystallization, the consequential regimes attained and their effects on product quality characteristics are not very well understood. Variations in temper regimes attained during pre-crystallization of chocolates influence their crystallinity, polymorphic status and other physical quality characteristics. Over-tempering causes increases in product hardness, stickiness with reduced gloss and darkening of product surfaces. Under-tempering induces fat bloom in products with consequential quality defects in structure, texture, melting properties and appearance (colour and surface gloss). Thus, the different temper regimes attained during pre-crystallization result in wide variations in product quality attributes with varied influences on quality. In a modern competitive confectionery market, understanding the variables leading to chocolate pre-crystallization during tempering and effects of the regimes attained on the quality of the finished products are vital to assurances in quality and shelf characteristics. Chapter 2 - Chemometric models based on partial least square regression (PLSR) have been successfully used to estimate nutrient content of different raw meat products from spectroscopic measurements. Preliminary studies to establish a chemometric model for estimating nutrient concentration of cooked ground beef patties from spectroscopic data indicated that the linear PLSR models are not adequate to represent fat and calories. Therefore, this study was conducted to examine two non-linear modeling methods using PLSR and artificial neural networks (ANN). In this study, spectral absorbance in the visible and near infrared (VNIR) region along with data from proximate analysis was utilized to

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develop and validate the two non-linear models for predicting fat, calories, cholesterol and moisture content of cooked ground beef patties. When compared to a linear chemometric model based on PLSR, both non-linear models performed significantly better. The ANN model exhibited the best performance which was indicated by a validation R2 value of 0.93 and residual predictive deviation (RPD) of 3.3 and 3.4 for fat and calories respectively. Both non-linear models resulted in RPD ≥ 3 under validation, indicating that they are acceptable. However, the model performance was only fair for cholesterol and moisture content. Chapter 3 - The present study supports the idea that physical- and sensory-related properties of long-aged beverages and alcoholic drinks containing reducing sugars would be described not by an unique value rather as a distribution of values due to the time-dependent increase of molecular heterogeneity in molecular sizes and structure. A wide range of beverages and alcoholic drinks obtained after different aging periods at room temperature were fractioned by Size-Exclusion Chromatography (SEC), then the elution profiles were analyzed by using a chemical-groups sensitive detector, i.e. an ultraviolet-visible (UV-VIS), coupled to a mass-sensitive detector. i.e. a differential refractive device (DRI). The analysis of the probability density function as well as of the cumulative density function allowed comparing the distribution properties over a wide range among the investigated samples. This is because, unlike small molecules, such liquid matrices undergo accumulation of high molecular size biopolymers (melanoidins) throughout the aging period. In general, results proved that all the investigated matrices would be defined as heterogeneous mixtures of chromophore-labeled copolymers, uncolored and brown, highly polydispersed with respect to their molecular size (ranging between 0.2kDa to over 2000kDa) and their chemical structure. In particular, the molecular size distribution of the end-products was attributed to the raw materials used for their production; while, the relative content of the biopolymers is strictly related to the extent of the thermal treatment applied along to the making process (when it is applied) as well as to the length of the storage time at room temperature. Chapter 4 - Detection of concealed damage in almonds is an important production inspection application. Internally damaged almonds are not easily distinguished from normal ones by their external appearances, and, when cooked, they taste bitter. Prior study showed that using the whole spectrum of hyperspectral data from 700-1400 nm could distinguish internally damaged nuts from normal ones at an error rates as low as 12.4%. However, the hyperspectral system is rather slow and cannot achieve an inspection rate of 40 nuts/s required by almond processing plants. Thus, a feature selection algorithm is needed to choose only a small subset of useful wavebands from hyperspectral data for use in a real-time multispectral camera. In this study, author introduce two novel feature selection techniques; one method is developed to select an optimal subset of individual wavebands, while the other aims to find good sets of band ratios. Author thoroughly discuss the advantages and disadvantages of both algorithms. Experimental results demonstrate that the author proposed methods give higher classification rates than other state-of-the-art algorithms. Chapter 5 - Usually, viscoleastic properties of materials (complex shear moduli and viscosity) are evaluated with rheometers which can give G’, G’’ for instance, on wide bandwidths thanks to the Time Temperature Superposition principle. It is clear that the knowledge of such properties is very interesting on a fundamental point of view because information on material microstructure can be deduced from master curves. On a more practical point of view, it can be used to improve fabrication processes, to perform quality controls, especially in food industry and engineering. This powerful method can fail to give

Preface

ix

large bandwidth information in several cases: phase transition of the material with temperature, volume to be analyzed too small, bad morphology of the sample. In order to overcome such a difficulty, it is possible to use ultrasonic waves. This paper, dedicated to high frequency methods (from a few kHz to many MHz) presents a review of existing methods and improvements developed in the author labs. Several applications in the domain of food engineering will be given in order to prove the huge interest of high frequency approaches which are sometimes neglected compared to classical low frequency rheology. Chapter 6 - High pressure processing (HPP) is a non-thermal food processing technology that offers great potential for the processing of a wide range of food products. Application of HPP can inactivate micro-organisms, affect food-related enzymes and modify structures with minimal changes to nutritional and sensory quality aspects of foods. The effects of high pressure on the inactivation of micro-organisms in food have been thoroughly reviewed. Recent research on HPP has mainly focused on fruits and vegetables with an emphasis on food quality and bioactive components. This chapter highlights the current trends in HPP research and provides a summary of the available findings on the effect of HPP on chemical, nutritional and bioactive components and health related properties of a wider range of commodities. Strategies to maintain the quality attributes and health related components in HPP foods and identification of the gaps for future research in HPP are also discussed. Chapter 7 - In order to assure the quality of dry foods it is important to maintain a strict control over the moisture content and temperature conditions during storage. Quality loss in dry foods can be due to enzymatic and non-enzymatic browning, lipid oxidation, loss of nutrients, loss of flow and microbial contamination, among other factors properties. Determining the optimum moisture content and temperature conditions that minimize the detrimental processes of foods is a difficult task that requires a profound understanding of the interactions of water with other food ingredients. Despite the use of increasingly sophisticated analytical techniques that seek to shed information regarding water-food interactions and water-water interactions, the water sorption mechanism in foods is not still understood wholly. The majority of foods can be considered as complex colloidal systems in which amorphous and crystalline regions occur, with water acting as a plasticizer. Water is a solvent that may take part in detrimental reactions, but in most cases, acts as a medium that provides mobility to reactants allowing them to come into close contact and react. Thus, it is convenient to control the participation of water within foods. Up to date there is still not a 100% reliable method for predicting and controlling food stability. Both, the water activity and the glass transition, are parameters that have been accepted as of food stability criteria worldwide. However, several scientific studies have demonstrated that both parameters exhibit great limitations, and that it is necessary to approach this problem from a fresh point of view. Regarding this, two factors are worthwhile considering: (1) equilibrium or thermodynamic considerations, and (2) rate or kinetic processes. A reaction may not take place if the thermodynamic parameters are unfavorable. Thus, management of the thermodynamic parameters that describe the state of a food is a good starting point for achieving a better understanding of the stability of stored food. On the other hand, even when a reaction is thermodynamically feasible, it cannot occur if the process kinetics does not occur at a feasible rate. In this chapter the thermodynamic and rate processes are proposed as criteria for establishing the stability of stored dry foods. It will also be shown that these two factors are closely interrelated, as the equilibrium state of a system depends in great measure

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of the kinetics followed to reach it. Furthermore, it will be established that it is possible to improve food stability by controlling its microstructure. Chapter 8 - In recent years, health consciousness has grown in relation to health hazards associated with lifestyle and living environment, and various types of functional foods are attracting attention (Matsuda, 2002; Bureau of Citizens, Culture and Sports, Tokyo Metropolitan Government, 2005; Sashihara et al., 2005). In addition, the functionality of food is currently an important added value for the food industry, and the development and applications of functional foods are being actively advanced. Among various functional foods, probiotics is one of the materials that have attracted considerable attention (Sashihara et al., 2005). Probiotics are living microbes that exert healthful effects on the living body, lactic acid bacteria being a typical example. The wide-ranging health effects of various types of bacteria have been reported, as shown in Table 1.1. Further, epidemiological studies on probiotics for disease prevention and scientific study and commercial development involving useful lactic acid bacteria are being pursued (Watanabe et al., 2005). Probiotic foods are able to ameliorate the effects of environmental factors, and are useful in disease prevention; establishing the safety of probiotics is easy as compared to doing so for medical chemicals, because the bacterial cells of probiotics have long been used for storing and improving the flavor of food. Therefore, various probiotic foods are being researched, developed, and produced. These will be indispensable functional ingredients in the future food industry in Japan, where health consciousness is increasing. Chapter 9 - The shelf life of multicomponent food systems depends, among others things, on how fast the water transfer between components takes place. This moisture migration can result in undesirable physical and chemical changes in the system, affecting its quality and shelf life. Several factors influence the amount and rate of moisture migration in multicomponent foods. However, water activity equilibrium and rate of diffusion are the two main factors. To control this migration, several principles can be utilized. A raisin-cereal mixture is one of the multicomponent food systems whose quality and shelf life is affected by moisture migration between components. In this system, water is transported from the raisin to the cereals, resulting in quality deterioration to both components. One way to reduce the moisture migration in this system is to reduce the water activity of raisins. The problem is that the raisin texture, one of most important factors governing their quality, becomes unacceptably hard when their water activity decreases below 0.40. Another possibility for controlling moisture migration is to add an edible barrier between components. In this study, in order to try to reduce the water activity of raisins, while maintaining their softness, raisins were infused with a glycerol-water solution (5:1) applied by vacuum impregnation. Mechanical properties, weight changes and water activity were evaluated before and after infusion to study the effect of the glycerol on raisins. On the other hand, in order to try to reduce the moisture transfer between components, the raisins were coated by directly applying starch and beeswax to them or by using different film forming emulsions made with whey protein, beeswax and glycerol at different protein:lipid:plasticizer ratios. The results of these application procedures have shown that the use of combined solute infusion and vacuum impregnation methods are an effective way of reducing the water activity properties of the raisins as well as serving as an alternative formula towards maintaining raisins at their best possible conditions for keeping a homogenous raisin-cereal system. After 1 hour of treatment with glycerol, testing revealed that the water activity of the raisins decreased, thus decreasing the gradient of water activity between both components.

Preface

xi

Furthermore, testing has indicated that this treatment does not affect the texture of raisins. The hardness of the raisin skin was not influenced by the presence of glycerol, allowing for a produced softness inside the raisins. As regards to the testing of various coating effects, the direct application of beeswax seemed to be the best protection from water loss. Among the film forming emulsions based on whey protein, the higher plasticizer content lead to a decrease in the water loss protection; although, these differences were not significant. In spite of the fact that the tested films have different water vapour permeabilities when they are treated as independent structures, it seems that the interactions that transpired, between these films and the surface of the product, eliminated the above mentioned differences. Chapter 10 - The type of packaging used has an important role in determining the shelf life of a food and the main purpose of food packaging is to protect the food from microbial and chemical contamination, oxygen, water vapour and light. Innovative food packaging concepts has been introduced as a response to the continuous changes in current consumer demands and market trends. Chapter 11 - Thermal properties of foods are vital inputs for many food process models. With the recent advances in mathematical modelling and significant reduction in the cost of computational power, uncertainties in model inputs are more and more becoming the limiting factor in model accuracy rather than the model formulation or solution process. In this chapter methods and models are presented for predicting thermal properties based solely on data for the composition of the food in terms of its basic components (liquid water, ice, protein, fat, carbohydrate, ash and air). This type of model provides genuine predictions of thermal properties since no thermal property measurements are required, as is necessary with some effective property models that may be found in the literature. Foods are divided into different classes, depending on the difficulties they pose for thermal properties prediction. Simple guidelines for thermal property prediction are presented along with worked examples to serve as illustrations. Chapter 12 - Membrane contactors represent an emerging technology in which the membrane is used as a tool for inter phase mass transfer operations [Sirkar et al. 1999, Drioli et al. 2003]. The membrane does not act as a selective barrier, but the separation is based on the phase equilibrium. This review specifically addresses to two membrane contactor processes: membrane distillation and membrane emulsification and their applications in the food industry. Chapter 13 - In many areas of food industry removal of glucose is considered as an important step in the processing line. In some raw materials – like eggs – glucose concentration should be reduced to avoid undesired co-reaction during drying process. In the beverage industry glucose level of certain fruit juices needs to be controlled/lowered either to produce low-caloric beverages or to get low-alcohol wine after fermentation (e.g. grape must). In addition glucose removal is a significant step in some enzymatic processes like polysaccharide hydrolysis or fructo-oligosaccharide synthesis, where glucose is an inhibitory by-product. Separation methods applicable for glucose removal are discussed and compared in this chapter. Chapter 14 - Instant, or quick-cooking, rice is becoming more popular nowadays. However, it still poses problems with respect to rehydration time and quality. The effects of processing factors which are: moisture content, pressure and drying temperature has a significant effect on its physicochemical properties and eating quality. The hardness and chewiness of rice decreased as moisture content and pressure increased. Higher drying

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temperatures caused increases in hardness and chewiness. Only pressure and moisture content affected density, rehydration ratio, and increase in the volume of instant rice, which was due to the porosity of the kernels. Rehydration ratio had a negative correlation with density (r= 0.886) but a positive correlation with volume increase (r = 0.637). Pressure was the main factor influencing the pasting properties of instant rice. All pasting properties of instant rice were far lower than those of milled rice, but instant rice had higher cold paste viscosity, which is typical of pregelatinized flour. This indicated rapid water absorption and shorter cooking time. Instant rice processing also caused development of amylose-lipid complexes observed as the V-type pattern in an X-ray diffractometer

In: New Topics in Food Engineering Editor: Mariann A. Comeau

ISBN: 978-1-61209-599-8 © 2011 Nova Science Publishers, Inc.

Chapter 1

TEMPERING, POLYMORPHISM AND FAT CRYSTALLIZATION DURING INDUSTRIAL CHOCOLATE MANUFACTURE: REGIMES, BEHAVIOURS AND THEIR EFFECTS ON FINISHED CHOCOLATE QUALITY Emmanuel Ohene Afoakwa1* and Alistair Paterson2 1

Department of Nutrition and Food Science, University of Ghana P. O. Box LG 134, Legon – Accra, Ghana 2 Centre for Food Quality, Strathclyde Institute of Pharmacy and Biomedical Sciences, University of Strathclyde, Royal College Building, 204 George Street, Glasgow G1 1XW, U. K.

ABSTRACT Tempering, a technique of shearing chocolate mass at controlled temperatures is used to promote cocoa butter crystallization in a thermodynamically stable polymorphic form. During chocolate manufacture, the process is used to obtain the stable form V (or ß2) of cocoa butter having a melting temperature of 32-34 °C, which gives the desired glossy appearance, good snap, contraction and enhanced shelf life characteristics. However, the tempering sequences, their behaviour during pre-crystallization, the consequential regimes attained and their effects on product quality characteristics are not very well understood. Variations in temper regimes attained during pre-crystallization of chocolates influence their crystallinity, polymorphic status and other physical quality characteristics. Over-tempering causes increases in product hardness, stickiness with reduced gloss and darkening of product surfaces. Under-tempering induces fat bloom in products with consequential quality defects in structure, texture, melting properties and appearance (colour and surface gloss). Thus, the different temper regimes attained during * Corresponding author: [email protected] / [email protected] Tel: +233 (0) 244685893

14

Emmanuel Ohene Afoakwa and Alistair Paterson pre-crystallization result in wide variations in product quality attributes with varied influences on quality. In a modern competitive confectionery market, understanding the variables leading to chocolate pre-crystallization during tempering and effects of the regimes attained on the quality of the finished products are vital to assurances in quality and shelf characteristics.

Keyword: Chocolate, cocoa, cocoa butter, tempering, crystallization, polymorphism, melting, appearance, microstructure.

INTRODUCTION Chocolate manufacturing involves several complex physical and chemical processes requiring numerous technological operations and the addition of different ingredients, to achieve products of suitable physical and chemical attributes and an attractive appearance and taste. Most of the parameters involved influence the rheological characteristics, flavour development and sensory perception [1, 2]. During chocolate processing, a process known as tempering is used to promote cocoa butter crystallization in a thermodynamically stable polymorphic form. Temperature adjustment is utilized to promote formation of seed crystals in the correct polymorphic forms to effect good product snap, contraction, gloss and shelf life characteristics. Tempering involves pre-crystallization of a small proportion of triacylglycerols (TAGs), with crystals forming nuclei (1 – 3% total) for remaining lipid to set in the correct form, resulting from a nucleation process which is highly dependent on the process parameters used. The final crystal form depends critically on the shear-temperature-time process which the material has undergone. The tempered chocolate is then deposited in moulds and cooled so that subsequent crystal growth occurs upon the existing seed crystals. Tempering has four key steps: melting the chocolate mass to completion (at 50°C), cooling to point of crystallization (at 32°C), crystallization (at 27°C), and conversion of any unstable crystals (at 29-31°C) (Figure 1), and it is a function of recipe, equipment, particle size and the final purpose [2-8]. Poorly tempered chocolates result in unstable crystal growth and poor setting characteristics, making products more susceptible to fat bloom, a physical imperfection that often manifests itself as a white or greyish-white layer on the surface of the chocolate product during storage. Afoakwa et al. [9] noted that fat bloom occurs when a lower and unstable crystal form IV changes into a higher and more stable form VI. The most important physical and functional characteristics (i.e. texture, snap and gloss) of chocolates are dictated by the crystal network formed by its constituent lipid during crystallization [5, 10-12]. In industrial chocolate manufacture, tempering is vital, influencing quality characteristics such as colour, hardness, handling, finish and shelf-life characteristics [5, 12, 13-18]. Fat crystallization is a complex process influenced by processing conditions that determines chocolate microstructure and physical properties and thus crucially important to the final quality of finished chocolates. The control of crystallization is critical for texture, melting properties and other quality characteristics [11, 12, 16, 19-21]. Several authors have studied the melting profiles of chocolates using pulsed nuclear magnetic resonance (pNMR) and differential scanning calorimetry (DSC) [6, 8, 22-24].

Tempering, Polymorphism and Fat Crystallization …

15

50 °C Heat

Cool 32 °C 30 °C

Chocolate

Cool

Reheat 27 °C

Solid chocolate

All fats melted

Correct number of stable

Unstable crystals melted

Figure 1. Tempering sequence during lipid crystallization in chocolates [1].

POLYMORPHISM AND FAT CRYSTALLIZATION IN CHOCOLATES Polymorphism - the existence of two or more distinct crystalline forms of the same substance - is a critical concept in the study of fat crystal structure. In fat systems, TAG molecules are able to pack in different crystalline arrangements or polymorphs and exhibit significant melting temperatures [25]. Cocoa butter can crystallize in a number of different forms, as a function of triglyceride composition, with fatty acid composition influencing how the liquid fat solidifies. Six polymorphic forms (I – VI), have been identified, the principal being α, β and β' (Figure 2); following the two main identified nomenclature schemes [26, 27]. Form V, a β polymorph, is the most desirable form in well-tempered chocolate, giving a glossy appearance, good snap, contraction and resistance to bloom [1]. In cocoa butter, Forms VI is the most stable form and difficult to generate although formed on lengthy storage of tempered chocolate accompanied by fat bloom. In addition Form VI has a high melting temperature (36°C), and crystals that are large and gritty on the tongue. The unstable Form I has a melting point of 17°C and is rapidly converted into Form II that transforms more slowly into III and IV. Polymorphic triglyceride forms differ in distance between fatty acid chains, angle of tilt relative to plane of chain end methyl group and manner in which triglycerides pack in crystallization [3]. Polymorphic form is determined by processing conditions. Fatty acids crystallize in a double- or triple-chain form depending on triglyceride composition and positional distribution. All the polymorphic forms could be formed directly from melted TAGs, or via melt-mediated or solid-state monotropic phase transformations [28].

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Emmanuel Ohene Afoakwa and Alistair Paterson

Figure 2. Temperature regimes and degree of stability of six polymorphic forms of cocoa butter [3].

Phase transitions in cocoa butter polymorphs from less to more stable forms are irreversible and dependent on temperature and time. Polymorphism in relation to solid continuous phases of cocoa butter has a large impact on chocolate quality, dictating their structural properties [29]. Structural factors such as microstructural elements and microstructure characteristics can provide quantitative information about the mechanical properties of the network, and therefore information about the sensory hardness of the network [30]. Polymorphic changes can be observed as overall contraction of chocolate, appearance, or undesirable fat bloom formation dependent on relative stabilities of crystal forms and temperature. As information on cocoa butter isothermal phase behaviour during chocolate manufacture is important for optimizing production processes that maintain product quality, this chapter would provide vital information on current industrial tempering processes, polymorphic behaviours and pre-crystallization regimes during chocolate tempering, and their effects on the microstructure and melting properties of fat systems during industrial chocolate manufacture. Additionally, it would provide valuable quality control indicators to ensure the structure and other quality attributes of fat networks being produced on a production line during chocolate manufacture are consistent and would yield the desired mechanical and sensory qualities during post-processing handling, supply chain management and consumption. Understanding these processes is important for process design and assurances in quality of products.


17

TEMPERING PROCESSES DURING INDUSTRIAL CHOCOLATE MANUFACTURE Chocolate was hand-tempered before the advent of tempering machines, a strategy still occasionally used by Chocolatiers who produce relatively small quantities of hand-made confections. Currently, tempering machines are used and consist of multistage heat exchangers through which chocolate passes at widely differing rates making it difficult to identify optimum conditions. Time-temperature combinations are of paramount importance in process design and in continuous tempering; molten chocolate is usually held at 45°C then gently cooled to initiate crystal growth. Tempermeters are then used to measure the cooling curves on a chart recorder and the degree of temper determined by the shape of the curve based on operators experience. More recently Tricor Systems in the USA have produced a tempermeter that uses a built-in algorithm to calculate the degree of temper in chocolate temper units (CTUs) and slope (temper index); these can then be used numerically to define the state of temper. In recent times, a number of innovative technologies have been initiated in the confectionery industry to enhance process efficiency and product improvement. Two Swiss technologists Windhab (ETH Zurich) and Mehrle (Buhler AG, Uzwil), working with the Buhler "Masterseeder", found that increasing shear during seed tempering can be beneficial as the kinetics of fat crystal nucleation and polymorphic transformations (α → β2 → β'1) are greatly accelerated. The outcome is enhanced overall product quality with reductions in fat bloom. Chocolate can also be tempered by the use of high pressure with molten chocolate compressed to 150 bar. This increases chocolate melting point and causes it to solidify into solid crystals of all polymorphic forms. When pressure is released, lower polymorphic forms melt leaving behind tempered chocolate. Subsequent batches can be seeded with stable fat crystals. Cocoa butter equivalents (CBEs) and replacers (CBRs) may also find application in the chocolate industry. While cocoa butter equivalents are compatible with cocoa butter, cocoa butter replacers (CBRs), which do not require tempering, can only be used if almost all the cocoa butter is replaced. These CBRs melt in the same temperature range as cocoa butter, but crystallise only in the β' form [3, 33, 34]. As well, effects of shear on chocolate or cocoa butter tempering in a number of different flow geometries have been reported. Important studies of scraped surface heat exchangers with cocoa butter and chocolate [35], Couette geometries with milk chocolate [36] and cocoa butter [37], cone and plate systems with cocoa butter [37, 38], parallel plate viscometers with milk chocolate [39], and a helical ribbon device with cocoa butter [15], have been reported with significant application in modern chocolate confectionery industry. Tricor has recently introduced its latest Model 225 Chocolate Temper Meter: a single, compact, low-cost, easy-to-operate unit that can be used in the laboratory or on the production line. It allows operators to fill a sample cup with chocolate, place it in the unit and print or display the temper results within minutes, thereby allowing corrective action to be taken before production yield and quality or shelf life are affected. A specially designed thermoelectric cooling system combined with a design that controls sample size, probe depth and probe insertion temperature is said to eliminate measurement errors. In another development, the chocolate equipment specialist, Sollich, recently unveiled its latest TurboTemper Champ TCN technology, which is designed to improve the tempering process

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in all known chocolate and fat masses. It is fitted with a Tempergraph that measures and saves the tempering conditions throughout production for continuous monitoring of the temper quality. Sollich can supply the system with an integrated decrystallisation function or with a Turbo Temper AIRO for aeration of chocolate masses for fat-based fillings.

FAT CRYSTALLIZATION BEHAVIOURS DURING TEMPERING Four different regimes have been reported by several authors to exist during chocolate tempering, comprising un-tempering, under-tempering, optimal tempering and overtempering. Each of these regimes show different pre-crystallization behaviours, attain varied polymorphic status with some associated transformations and varied consequential effects on the structure and quality of finished chocolates during processing, post-processing handling and supply chain management [2, 5, 12, 40-44].

Optimal Tempering During the formation of optimal temper, the temperature of the chocolate being crystallized drops rapidly during cooling until it reaches thermodynamic equilibrium. At this point, the crystallization heat released is balanced by an equal amount of cooling energy rending a rather flat time-temperature curve (with a zero slope). The equilibration temperature attained promotes formation of stable fat crystals, which subsequently undergo further growth and maturity during cooling and storage to effect shelf stability of the product. The temperature of the chocolate then dropped further when the liquid cocoa butter is transformed into solid crystals resulting in solidification of the products (Figure 3). Fat crystallization process can also be followed by means of viscosity changes as function of time [31]. Before crystallization starts, the melt shows Newtonian behaviour but with the formation and growth of crystals, the viscosity increases almost linearly with the amount of crystals in the suspension until it reaches a thermodynamic equilibrium [45]. This technique has also been used to follow the isothermal crystallization of refined palm oil, chocolate and palm stearin in sesame oil [15, 46, 47]. Properly tempered chocolate leads to the formation of Form V (β2), the most desirable polymorphic form. Well tempered chocolate has the following properties; good shape, colour, gloss, good contraction from the mould, good weight control, good stability (harder and more heat resistant with fewer finger marks during packaging) and longer shelf-life. The tempering regime for milk chocolate slightly differs from that for dark due to the influence of milk fat molecules on crystal lattice formation. Milk chocolate contains a proportion of butter fat that causes eutectic effect, which prevents bloom formation, results in a low melting point, softening of texture and lowering of temperature to obtain crystal seed for the tempering process (around 29.4°C compared to 34.5°C for plain chocolate).


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Figure 3. Pre-crystallization curves of the different temper regimes in chocolate manufacture [5].

Under-Tempering and Untempering Under-tempering (insufficient tempering) is caused by the relatively higher temperatures released between multi-stage heat exchangers during tempering. The process causes development of more crystallization heat within the product during solidification, effecting quick cooling, as more liquid fat is transformed quickly into solid form. The distinct increase in temperature observed at the beginning of the crystallization, declined again after reaching a maximum point where most of the stable crystals formed were re-melted prior to cooling, resulting in the formation of very few stable fat crystals (Figure 3). Previous studies revealed that un-tempering – an insufficient temper regime, produces no stable fat crystals as the heat


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exchange system generated higher crystallization heat during cooling, resulting in consistent cooling of the completely melted product with no inflexion point for stable fat crystal formation [5]. The crystallization processes in both un-tempered and under-tempered chocolates lead to the formation of unstable Form IV (β'1) polymorph, which quickly transforms into Form V within a few hours and with further transformations into a more stable Form VI (β1) polymorph during storage. The phenomenon leads to fat bloom, appearance of whitish or dull-white particulate spots on the surface of chocolate, rendering products unacceptable for human consumption [1, 5]. Fat bloom arises from changes in the fat structure in chocolate and is caused by a variety of factors, including poor tempering of the chocolate, incorrect cooling methods and the presence of soft fats in the centres of chocolates. Warm storage conditions, and the addition of fats that are incompatible with cocoa butter, can also cause fat bloom. It frequently results in significant product losses for confectionary manufacturers as, although it does not affect the taste, the tell-tale sign of the bloom – a white frosting – is unacceptable to consumers. Additionally, it has been reported that untempering and under-tempering regimes exhibit different crystallization behaviours but results in similar unstable fat crystal nucleation and growth, with similar associated storage polymorphic transformations and defects in textural properties and appearance of products [5].

Over-Tempering Over-tempering occurs when relatively lower temperatures are exchanged between the multi-stage heat exchangers of the tempering equipment. This causes significant part of the liquid fat to solidify within the continuous phase of the chocolate, transforming the product into solid form when less liquid fat was available for pumping it through the multiple coolant regions of the temperer. The process effects very slow cooling as very little crystallization heat is released during the process, rendering a rather flat and slow cooling curve causing the chocolate to solidify very quickly (Figure 3). In over-tempering, the crystallization heat released is balanced by an equal amount of cooling energy causing nucleation of stable fat crystals (β2) to effect shelf stability of the product. However, the period of equilibrium is very short relative to that of optimal tempering, and this is suspected to affect the crystal size, mass (number), strengths and adequacy of the fat crystals formed and thus possible defects in structure and product shelf stability [41, 43]. As a substantial part of the phase transition (from liquid to solid) took place before the chocolate reached the mould, less contraction occurred in the mould, leading to demoulding problems with defects in final product texture and appearance (gloss and colour) and consequential effects on shelf life of products [5, 42].

TEMPERING EFFECTS ON FINISHED CHOCOLATE QUALITY Effects on Mechanical and Textural Properties The temper regime attained during pre-crystallization of chocolate has a dramatic influence on the mechanical properties (hardness and stickiness) of finished products. Previous reported findings showed varying degrees of hardness and stickiness of products


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with different temper regimes [5]. Under-tempered products had the greatest hardness (texture), attributable to the re-crystallization process undergone by the fat in the chocolates resulting in intense hardening of products. This trend in hardness was followed by overtempered samples with the optimal-tempered products possessing relatively lesser hardness levels. These suggest that over-tempering of chocolates leads to increased hardness in chocolates as compared to their respective optimally-tempered products. However, the degree to which these changes occur depend on the particle size distribution of the chocolate. Particle sizes have been reported to be important determinants of hardness of fat crystal networks in many confectionery products [10, 11, 16, 48]. Earlier studies showed inverse relationships of hardness in tempered dark chocolates with particle sizes at varying fat and lecithin levels [49], attributed to the relative strengths of their particle-to-particle interactions [11, 50]. Consistent reductions in hardness (texture) of milk chocolates with increasing particle sizes has also been reported [51]. Other important parameter defining the mechanical properties of chocolates is the level of stickiness. Stickiness in confectionery gives information about their deformability related to oral sensory characters, an index that defines the rate of melting of products during oral processing – lower stickiness levels is an indication of fast melting character whereas higher levels suggests prolonged melting [52]. Previous report explained that temper regime attained during pre-crystallization of chocolates has remarkable effects on their stickiness levels, with an inverse relationship with increasing particle sizes [5]. Over-tempered products had the greatest stickiness levels, followed by the optimally-tempered products with the undertempered samples having the least. The behaviour of fats during crystallization heavily influences the microstructure and physical properties of products such as margarine and chocolates, and ultimately affect the final product structure, texture and quality [20]. Attainment of optimal-temper during pre-crystallization of chocolate is therefore vital to controlling the mechanical properties (hardness and stickiness) during processing and postprocessing quality, the knowledge of which are important for quality control and in new product development.

Effect on Appearance (Colour, Gloss and Product Image) Appearance involves all visual phenomena characterizing objects, including gloss, colour, shape, roughness, surface texture, shininess, haze and translucency [53]. Work done on chocolates revealed that temper regime affects to varying levels all colour and gloss measurements [5]. Under-tempering has been reported to attain relatively higher L*-values than both the optimally-tempered and over-tempered samples within 14 days after processing, as a result of blooming effect on products. As well, under-tempering causes great reductions in C* and h° at all PS. Components of colour such as L*, C* and h° respectively represent food diffuse reflectance of light, degree of saturation and hue luminance, which are dependent on particulate distribution, absorptivity and scattering factors or coefficients. In a densely packed medium, scattering factor is inversely related to particle diameter [54, 55]. Chocolates with varying temper regimes differ in structure and particulate arrangements influencing light scattering coefficients and thus appearance [5]. Over-tempered chocolates were found to possess relatively lower L* values at all PS as compared to their corresponding optimallytempered products. These suggest that over-tempering reduces the degree of lightness in

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chocolates, effecting product darkening and thus affecting quality of finished chocolates. However, no noticeable effect on C* and h° were observed among the optimally- and overtempered products. Under-tempered (bloomed) chocolates tend to scatter more light, appear lighter and less saturated than over-tempered and optimally-tempered products. The blooming process results in higher scattering coefficients, with subsequent paleness (whitening) - higher L* values. The whitish haze in bloomed chocolate is caused by the dispersion of light of fat crystals [41]. Colour of foods may be affected by various optical phenomena among them are scattering and surface morphology, therefore an accurate understanding of the influence of appearance on measured colour is essential. Gloss relates to capacity of a surface to reflect directed light at a specular reflectance angle with respect to normal surface plane [56]. Differences in temper regime have been reported to influence gloss measurements in chocolates to varying levels. Blooming of undertempered samples result in drastic reductions in gloss values than their respective optimallytempered and over-tempered samples. In our previous work, under-tempered chocolates were found to possess the lowest gloss values, followed by the over-tempered and then optimallytempered products [5]. Under-tempering was shown to exhibit the greatest influence on appearance and gloss of products but differences between optimally- and over-tempered products were significant with the over-tempered showing relatively slightly reduced gloss, an indication that tempering is a key determinant of chocolate gloss. In under-tempered chocolates light scattering is affected by reductions in surface regularity. Gloss stability of edible coating formulations of chocolates have been studied [57-59]. Gloss is an important quality attribute in chocolate and tempering a key processing step to control it [60]. The relationship between colour and gloss of chocolates are of current interest to many manufacturers. Digital images of dark chocolates (18 µm PS) assembled to show surface appearances of the optimally-, under- and over-tempered products before and after the 14 days conditioning (Figure 4) showed similar initially smooth and glossy surface appearances soon after tempering but after 14 days, clear differences were apparent. The optimally- and overtempered chocolates maintained their characteristic glossy appearance and dark brown colour but the under-tempered samples bloomed, with appearance of surface whitish spots, rendering them dull and hazy in colour (Figure 4). Similar increases in whiteness in under-tempered and untempered (bloomed) chocolates have been reported [17, 42, 43]. This phenomenon has been attributed to re-crystallisation of fats from a less stable Form IV to a more stable Form VI polymorph, with changes in light dispersion on small surface fat crystals (> 5µm), consequently impacting on both appearance and textural attributes [12, 41]. Fat bloom development, mechanisms and effects on chocolate appearance, quality and marketability has been extensively studied [7, 9, 17, 19, 22, 23, 42, 43, 61]. Given that chocolate products are meant to respond to consumers acquired expectations, their appearance is one of the most important commercial attributes. Attention to tempering is therefore necessary for consistency in chocolate appearance during product development and quality control.


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Figure 4. Photographic images of (a) fresh and (b) matured (conditioned) optimally-tempered, undertempered and over-tempered dark chocolates (18 µm PS). [5].

Effects on Melting Properties Thermal properties of cocoa butter and chocolates have been studied using pulsed nuclear magnetic resonance (pNMR) and differential scanning calorimetry (DSC) and together they

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provide information on the phase behaviour of the inherent fats during both mechanical and oral processing [3, 6, 8, 22, 24]. In a publication, it was found that typical DSC thermograms of chocolates manufactured from the optimally-tempered, over-tempered and under-tempered regimes exhibited similar distinct single endothermic transitions between 15 and 55 °C with peak onset (Tonset,), corresponding to the temperature at which a specific crystal form starts to melt; peak maximum (Tpeak), that at which melting rate is greatest; end of melting (Tend), completion of liquefaction and enthalpy of melting (ΔHfat), the energy required to effect complete melting [12]. All these information relate to the crystal type, and predicts the polymorphic status of the product. Peak height, position and resolution are dependent on sample composition and crystalline state distribution [63]. Differences in temper regime result in varying degrees of crystallinity and melting properties using DSC (Figure 5). The observed differences in the peaks were explained to suggest that variations in crystallisation behaviour in chocolates exist during tempering and influence the degree of crystallinity and crystal size distribution (CSD) of their derived products. Under-tempered (bloomed) chocolates showed the greatest peak width, followed by the over-tempered samples having slightly wider CSD than the optimally-tempered products with resultant variation in their melting profiles (Figure 5). The distribution of crystal sizes in foods play key roles in final product quality, defined by the total and specific characteristics of their crystalline material. Number of crystals and range of sizes, shapes, and polymorphic stability, as well as arrangements in network structures dictates mechanical and rheological properties [2, 19]. Knowledge and control of CSD can be important for optimizing processing conditions.

Figure 5. Typical DSC thermograms of fat melting profile showing optimally-tempered, over-tempered and under-tempered (bloomed) dark chocolates [12].

Under-tempered chocolate were reported to complete melting at higher temperatures than optimally- and over-tempered products. The changing melting end (Tend) values the products showed that the crystallites in optimally and over-tempered chocolates were in ßV polymorph


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while that of under-tempered, ßVI. Similar melting temperatures and polymorphic status have been reported [41, 42]. However, these polymorphic statuses are best identified by powder Xray diffraction patterns and could be a subject for further investigation. The mechanism of identification and principle of the technique has been explained.20 Similarly, under-tempered (bloomed) chocolate had higher melting duration index than their corresponding optimal and over-tempered products, suggesting that the under-tempered chocolate might require longer time to melt than the optimally and over-tempered products. Likewise, over-tempered samples were noted to require longer melting durations than the optimally-tempered, with the prediction that the differences found would have likely impact on their behaviour during consumption, attributable to the relative strengths of their mechanical properties (hardness and stickiness), a significant finding for process quality control. Thermal behaviours and ratio of sugar/fat melting enthalpies in chocolates differing in temper regime were studied using DSC to provide information on differences in fat and sugar structure. The DSC thermograms (Figure 6) showed differences in fat melting profile, resulting from the widened peak width in the under-tempered (bloomed) sample; but no differences were noted in the sugar melting profiles, explaining the structural (polymorphic) transformations in the fat component in the under-tempered product. The report indicated that the DSC data on fat and sugar melting properties (Tonset, Tend, Tpeak, ΔHfat, ΔHsugar and ΔHsugar/ΔHfat) related to temper regime were similar to the trends for fat (Figure 4) - fat melting profiles suggested the ßV polymorph in both optimally- and over-tempered chocolates with Tend of 32.3 °C and 32.9 °C respectively, and a more stable ßVI polymorph in under-tempered sample with Tend of 35.8°C, with significant influences on Tonset, Tpeak, ΔHfat in chocolates.

Figure 6. Typical DSC thermograms showing (A) fat and (B) sugar melting profiles of optimallytempered, over-tempered and under-tempered (bloomed) dark chocolates at 18 μm PS [12].

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Contrary, results of the sugar melting properties showed only marginal differences in all the melting properties (Tonset, Tend, Tpeak, ΔHsugar) with the different temper regimes, suggesting that no structural change in sugar were found in products from the three temper regimes [12]. Similarly, the ratios of sugar to fat melting enthalpies in products from optimal, over- and under-tempered samples were 1.25, 1.24 and 1.17 respectively with no significant difference among them. These explain that the lower ΔHsugar/ΔHfat ratio noted in the undertempered sample resulted from the higher ΔHfat as a result of recrystallization of fat [19, 42]. These findings support our earlier report that fat and sugar components are present in similar quantities in both bloomed and optimally-tempered dark chocolates [12], but contrast with the report that the melting peak of fat in untempered (bloomed) chocolate was almost nonexistence with ΔHfat being ten-fold smaller than that obtained for optimally-tempered chocolate [43], concluding that the whitish spots in bloomed chocolates were mainly composed of sugar crystals and cocoa powder and nearly devoid of fat. The presence of fat components in bloomed dark chocolate has also been reported [64], suggesting the mechanisms of bloom development in chocolate involves phase separation associated with the growth of xenomorphic fat crystals.

Effects on Microstructure Microstructural examination using stereoscopic binocular microscopy after 14 days of conditioning showed clear variations in both surface and internal peripheries of chocolates from varying temper regimes (Figure 7) [12]. Over-tempered products had relatively darker surfaces and internal appearances than optimally-tempered confirming the reported relative differences in L*. Under-tempered products showed both bloomed surface and internal periphery with large whitish, and distinct smaller brown spots (Figure 7). The observed whitish appearance on surfaces and internal peripheries appear to be mixtures of fat and sugar crystals, and the small brown spots, cocoa solids. These whitish spots were primarily sugar crystals and cocoa powder and nearly devoid of fat [42, 43]. These differences in interpretation are recommended as the subject for further investigations. Microstructural examination using scanning electron microscopy after 14 days of conditioning showed clear variations in crystalline network structure, inter-particle interactions and spatial distributions of network mass among optimally-, over- and under-tempered samples, becoming well defined (Figure 8). Microscopy of the optimally-tempered chocolate showed an even spatial distribution of small number of dense crystalline network with well defined inter-particle connections among the crystals suggesting stable β-polymorph (Figure 8). Similarly, micrographs of the over-tempered chocolate showed a spatial distribution of a dense mass of smaller crystals (relative to those of the optimally-tempered) within a network structure of both well- and ill-defined particle-to-particles crystal connections suggesting their βpolymorph stability [12]. These larger numbers of small crystalline networks noted in the over-tempered samples is suspected to result from early nucleation and growth of seed crystals due to the slow cooling (Figure 8), leading to the formation of sub-micron primary crystallites from the melt, with the resulting fat crystal network stabilized by van der Waals forces, possibly with steric and Coulombic forces [10, 65, 66].


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Figure 7. Micrographs of surface (a) and internal (b) structures respectively of (1) optimally-tempered, (2) under-tempered and (3) over-tempered dark chocolate (18 µm PS) [12].


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(A)

(B)

(C) Figure 8. Scanning electron micrographs showing crystalline network microstructures at magnifications of x 1,500 of (a) tempered, b) over-tempered and (c) under-tempered (bloomed) chocolates at 18 μm PS. C shows some of the well-defined crystal structures; iC shows some of the ill-defined crystal structures; i shows some of the inter-crystal connections. The arrows indicate some of the pores, cracks and crevices; B shows some of solid bridges; L shows some of the large (crystal) lumps on the crystal structure [12].


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Under-tempered (bloomed) chocolates showed dissolution, re-arrangement and recrystallisation of the numerous small crystals noted in the over- and optimally-tempered products to a smaller number of larger (lumps) fat crystals (Ostwald ripening), and polymorphic transformation, nucleation and growth of new large crystals in a more stable polymorphic form. These observations induced formation of solid bridges with weak and less inter-crystal connections made up of pores, pits and crevices within the crystalline network structures (Figure 8). This phenomenon is attributed to the thermodynamic differences in equilibrium between large and small crystals within a network structure leading to recrystallization of unstable fat polymorphs [41]. In another study, surface imperfections pores, pits, in filled chocolates were reported on the microstructure of bloomed chocolate [67]. Similar findings were reported while studying fat bloom formation and development during storage of under-tempered dark chocolates [9]. Both reports explained that morphological changes on the surface of the chocolate were dominated by the growth of needle-like crystals and spherulites on the chocolate with large crystals ~ 100 µm in length, and concluded that from a microstructural perspective, both diffusion and capillarity appear to be involved in fat bloom formation and development, though temperature, particle size distribution of the product and the presence of a filling fat strongly dictate the rate and type of mechanism that dominate the process. Thus, differences in crystallization behaviour during tempering leads to formation of different microstructural organizations of crystal network structure with associated physical changes in chocolates. Characterizing the nature of crystals in confectionery is an important step in quantifying the physical and sensory properties, as the resulting three-dimensional fat crystal network along with the phase behaviour and structural arrangements impact on mechanical, rheological, and melting properties and shelf life [11, 16, 19]. Parameters such as cooling rate and thermal history (i.e., crystallization temperature and tempering) influence kinetics and ultimate physical properties of the crystallized fat systems during processing.

CONCLUSIONS AND RECOMMENDATIONS FOR PRODUCT QUALITY IMPROVEMENTS Fat crystallization behaviour during tempering of chocolates plays a key role in defining their ultimate structure, texture, appearance and melting properties. Variations in temper regimes attained during pre-crystallization of products influence their crystallinity, polymorphic status and other physical quality characteristics. Over-tempering causes increases in product hardness, stickiness with reduced gloss and darkening of product surfaces. Under-tempering induces fat bloom in products with consequential quality defects in texture and appearance (colour and surface gloss). Structure of under-tempered products causes dissolution of a large number of small crystals through re-arrangement and recrystallization, into a small number of larger (lumps) fat crystals (Ostwald ripening). In this process there is polymorphic transformation, nucleation and growth of new large crystals in a more stable polymorphic form with formation of solid bridges with weak and fewer intercrystal connections within the chocolate matrix. Thus, attainment of optimal temper regime during pre-crystallization of chocolate is necessary for the achievement of premium quality products and avoidance of defects in structure, texture, appearance and melting character.

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With the competitiveness in modern confectionery market, manufacturers want to eradicate or minimise the occurrence of fat bloom during chocolate manufacture, and have been involved in rigorous research to resolve this problem. Fat bloom caused by temperature damage is more or less under control, where manufacturers know that their chocolate needs to be stored at a controlled temperature. However, fat bloom or fat migration due to inappropriate tempering (untempering and under-tempering) is still a global problem and causes some product losses during storage, largely linked to the quality of the distribution chain. Even though taste is not affected by this bloom as it is in the case of sugar bloom (bloom resulting from moisture defects during storage of products under high humidity conditions), the ‘mouth-feel' of the product changes, melting differently in the mouth due to the higher melting point. Most manufacturers currently use traditional methods to combat fat bloom. For example, one key technique legally acceptable worldwide is the addition of full cream fat powder to milk chocolate to delay the migration of fat bloom. In dark chocolate – which only contains cocoa butter, 3-4% butter oil can lengthen the shelf-life and the mechanism involved has been explained.2,40,44 Fat bloom is a common problem in the confectionery industry. However, the reported research findings confirm that when chocolate is properly/optimally tempered as described, fat bloom could be completely avoided, when stored in controlled ambient temperature (18-25 °C) and humidity (50-55%) conditions. These findings have significant commercial implications as they are essential to optimizing process development during chocolate tempering, and could lead to the control and/or improvements in product quality during their supply chain and thus cost savings for the global chocolate confectionery industry.

ACKNOWLEDGMENT The authors wish to thank the Government of Ghana and Nestlé Product Technology Centre (York, UK) for the Research Support that led to most of the findings in this chapter. We also want to thank Mark Fowler, Joselio Vieira, Steve Beckett, John Rasburn and Angel Manez (Nestlé PTC, York) for expert technical discussions.

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[43] Lonchampt P and Hartel RW, Surface bloom on improperly tempered chocolate. Euro J Lipid Sci Tech 108:159–168 (2006). [44] Beckett ST, The Science of Chocolate. Second Edition. London: Royal Society of Chemistry, (2008). [45] Breitschuh B and Windhab EJ, Parameters influencing cocrystallization and polymorphism in milk fat. J Amer Oil Chem Soc 75:897–904. [46] Loisel C, Lecq G, Keller G and Ollivon M, Dynamic crystallization of dark chocolate as affected by temperature and lipid additives. J Food Sci 63:73–79 (1998). [47] Chen CW, Lai OM, Ghazali HM and Chong CL, Isothermal crystallization kinetics of refined palm oil. J Amer Oil Chem Soc 79:403–410. [48] Marangoni AG and Narine SS, Identifying key structural indicators of mechanical strength in networks of fat crystals. Food Res Inter 35:957–969. [49] Afoakwa EO, Paterson A, Fowler M and Vieira J, Particle size distribution and compositional effects on textural properties and appearance of dark chocolates. J Food Eng 87:181 – 190 (2008). [50] Afoakwa EO, Paterson A, Fowler M and Vieira J, Microstructural and mechanical properties relating to particle size distribution and composition in dark chocolate. Inter J Food Sci Tech 44, 111–119 (2009). [51] Do T-AL, Hargreaves JM, Wolf B, Hort J and Mitchell JR, Impact of particle size distribution on rheological and textural properties of chocolate models with reduced fat content. J Food Sci 72:E541 – E552 (2007). [52] Narine SS and Marangoni AG, Elastic modulus as an indicator of macroscopic hardness of fat crystal networks. LWT – Food Sci Tech, 81:117–121 (2001). [53] Briones V and Aguilera JM, Image analysis of changes in surface color of chocolate. Food Res Inter 38:87–94 (2005). [54] Hutchings JB, Food Colour and Appearance. Blackie A & P., Glasgow, UK (1994). [55] Saguy IS and Graf E, Particle size effects on the diffuse reflectance of a sucrosecaramel mixture. J Food Sci 56:1117-1120 (1991). [56] ASTM, Standard test method for specular gloss. Designation D 523. In 1995 Annual Book of ASTM Standards. Volume 6.01: Paint-tests for chemical, physical and optical properties; appearance; durability of non-metallic materials. Philadelphia: American Society for Testing and Materials (1995). [57] Trezza TA and Krochta JM, The gloss of edible coatings as affected by surfactants, lipids, relative humidity and time. J Food Sci 65:658–662 (2000). [58] Talbot G, Chocolate temper. In Industrial Chocolate Manufacture and Use (pp. 218230) Beckett, S. T. (Ed.), Oxford, Blackwell Science, 3rd edition (1999). [59] Briones V, Aguilera JM and Brown C, Effect of surface topography on color and gloss of chocolate samples. J Food Eng 77:776–783 (2006). [60] Seguine E, Tempering – the inside story. Manuf Confectioner 71:118-125 (1991). [61] Bricknell J and Hartel RW, Relation of fat bloom in chocolate to polymorphic transition of cocoa butter. J Amer Oil Chem Soc 75:1609–1615 (1998). [62] Timms RE, Phase behaviour of fats and their mixtures. Progress in Lipid Res 23:1–38 (1984).

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[63] McFarlane I, Instrumentation. In S. T. Beckett (Ed.), Industrial Chocolate Manufacture and Use (pp. 347–376). New York: Chapman & Hall (1999). [64] Kinta Y and Hatta T, Composition and structure of fat bloom in untempered chocolate. J Food Sci 70:S450–452 (2005). [65] deMan JM, Relationship among chemical, physical, and textural properties of fats. In N. Widlak (Ed.), Physical properties of fats, oils and emulsions (pp. 79–95). Champaign, IL, USA: AOCS Press (1999). [66] Tang D and Marangoni AG, Modified fractal model and rheological properties of colloidal networks. J Coll Interface Sci. 318:202 – 209 (2008). [67] Rousseau D and Smith P, Microstructure of fat bloom development in plain and filled chocolate confections. Soft Matter 4:1706 – 1712 (2008).



Chapter 2

NON-LINEAR MODELING OF QUALITY OF COOKED GROUND BEEF PATTIES WITH VISIBLE-NIR SPECTROSCOPY Sreekala G. Bajwa1* and Jason K. Apple2 1

Department of Biological & Agricultural Engineering, University of Arkansas, 203 Engineering Hall, Fayetteville, AR 72701, USA 2 Department of Animal Science, University of Arkansas, B103C Agricultural, Food & Life Sciences Building, Fayetteville, AR 72701, USA

ABSTRACT Chemometric models based on partial least square regression (PLSR) have been successfully used to estimate nutrient content of different raw meat products from spectroscopic measurements. Preliminary studies to establish a chemometric model for estimating nutrient concentration of cooked ground beef patties from spectroscopic data indicated that the linear PLSR models are not adequate to represent fat and calories. Therefore, this study was conducted to examine two non-linear modeling methods using PLSR and artificial neural networks (ANN). In this study, spectral absorbance in the visible and near infrared (VNIR) region along with data from proximate analysis was utilized to develop and validate the two non-linear models for predicting fat, calories, cholesterol and moisture content of cooked ground beef patties. When compared to a linear chemometric model based on PLSR, both non-linear models performed significantly better. The ANN model exhibited the best performance which was indicated by a validation R2 value of 0.93 and residual predictive deviation (RPD) of 3.3 and 3.4 for fat and calories respectively. Both non-linear models resulted in RPD ≥ 3 under validation, indicating that they are acceptable. However, the model performance was only fair for cholesterol and moisture content.

*

E-mail address: [email protected]

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Sreekala G. Bajwa and Jason K. Apple

INTRODUCTION In developed countries, the consumer's willingness to pay a premium price for meat products that maintain a consistent quality standard has resulted in a demand for fast and efficient methods for estimating meat quality. In the US, the increasing consumer demand for food products in the ready-to-eat form has resulted in many processed food products that may be even partially cooked. There is a need for understanding the nutrient value of these various meat products to enable customers to make an informed purchase. The persistent problem of obesity has created great awareness among people about the nutrient value of the food they consume. Also, certain medical conditions may require people to choose food with a certain nutrient profile or caloric value. The new health care bill passed by the US government this year will require all restaurants to include calorie counts of all food items on the menus, menu boards and drive-throughs. Currently, the accuracy of such estimations may be questionable. Therefore, there is a growing need to develop methods and/or devices that can measure or estimate the caloric value and other quality parameters of cooked food products in a fast and accurate manner. Such methods can have applications in food processing lines for controlling the quality of food products, in making decisions regarding the end use of meat, and to understand the nutrient profile and energy content of cooked food products in various food outlets. Standard methods for assessing the nutritional profile of food materials are based on guidelines established by the Association of Official Analytical Chemists (AOAC)[1], and use laboratory-based chemical analyses. Since chemical analyses are often time consuming and expensive, many scientists have focused on rapid assessment of nutrients such as fat and protein in raw food, particularly using near infrared reflectance spectroscopy (NIRS) and chemometric modeling methods [2-33]. Optical spectral sensing, particularly NIRS, has proven to be a reliable tool for assessing quality of raw meat products. The advantages of indirect methods such as spectral sensing include speed, non-destructive nature of the tests, reliability and ability to be incorporated into food processing lines for real-time process control. Some of the studies on spectral sensing of food quality have also led to the establishment of online monitoring systems for quality control in food processing lines [23,34-35]. A review of the literature on the application of NIRS to estimate quality of meat and meat products is provided in Table 1 and also by [36]. Past research on this topic focused on estimating protein, intra-muscular fat (IMF), moisture content (MC), dry matter (DM), gross energy (GE) or calories, specific fatty acids or fatty acid groups (FAG), myoglobin (Mb) and minerals in meat products using chemometric models based on partial least square regression (PLSR) or modified PLSR (mPLSR) (Table 1). The meat products addressed in these studies included beef, pork, chicken, lamb and fish in various forms including steak, minced and homogenized, sausages and surimi. It is evident from these past studies that the NIRS works remarkably well for raw meat products in minced form, particularly for estimating proteins, IMF, MC and DM, but not that well for intact muscles and cooked meat products [2-33].

Table 1. Summary of research reported in the last 10 years on chemometric modeling of nutrient value of food products from spectral measurements, in reverse chronological order. The model performance indicated is for independent prediction or cross-validation or calibration in that order of preference, based on availability Study author [2] Bajwa et al., 2009

[3] Ripoll et al., 2008 [4] GaitanJurado et al., 2008 [5] Andrés et al., 2007 [6] Khodabux et al., 2007 [7] OrtizSomovilla et al., 2007 [8] Pla et al., 2007

Meat product Beefground patties (raw) Beef-ground & cooked patties Beef

Spectral sensor (wavelength) ASDLabSpec Pro spectroradiometer (400-1075 nm)

Model PLSR

Nutrients studied IMF, calories, cholesterol, MC

Model performance R2 = 0.94 (IMF), 0.94 (calories), 0.94 (MC), 0.80 (cholesterol)

ASDLabSpec Pro spectroradiometer (400-1075 nm) FOSS NIR System 6500 (408-2492.8 nm)

PLSR PLSR, mPLSR

IMF, calories, cholesterol, MC Protein, IMF, MC, Mb

R2 = 0.85 (IMF), 0.86 (calories), 0.72 (MC), 0.79 (cholesterol) R2 = 0.16(protein), 0.76 (IMF), 0.72 (MC). 0.91(Mb)

Pork sausage

Perten 7000 Diode Array NIR /VIS sensor (400-1700 nm)

mPLSR

Protein, IMF, MC

R2 = 0.95-0.96 (protein), 0.981(IMF), 0.88-0.99(MC)

Lamb

FOSS NIR System 6500 (408-2498 nm)

PLSR

IMF, MC

R2 = 0.41 (IMF), 0.69 (MC)

Fish - Tuna

ASD LabSpec Pro NIR Sensor(350-2500 nm)

PLSR

Protein, IMF, MC

R2 = 0.99 (protein), 0.95 (total IMF). 0.96 (free fat), 0.98 (MC)

Pork sausage minced

Perten 7000 Diode Array NIR/VIS Sensor (400-1700 nm)

mPLSR

Protein, IMF, MC

R2 = 0.93 (protein), 0.98 (IMF) 0.98 (MC),

Rabbitground


PLSR

Fatty acids

R2 = 0.5 – 0.9 (each ), 0.83-0.92 (grouped)

Table 1. (Continued) Study author [9] Viljoen et al., 2007 [10] Barlocco et al., 2006 [11] Locsmánd i et al., 2006 [12] Prieto et al., 2006 [13] Savenije et al., 2006 [14] Uddin et al., 2006 [15] Berzaghi et al., 2005 [16] HovingBolink et al., 2005

Meat product Mutton

Pork LT intact & minced Goose liver -ground

Spectral sensor (wavelength) InfraAlyser 500 Bran + Luebbe GmbH Sensor (1100-2500 nm) FOSS NIR System 6500 (400-2500 nm)

FOSS NIR System 6500 (11002500 nm)

Model PLSR

Nutrients studied Protein, IMF, DM, ash

Model performance R2 = 1.00 (protein), 1.00 (IMF), 0.96 (DM), 0.97 (ash)

PLSR

IMF, MC

R2(intact/minced) = 0.30/0.87 (IMF), 0.66/0.90 (MC)

PLSR

Protein, IMF, DM, FAG

R2 = 0.63 (protein), 0.81 (IMF), 0.72 (DM), 0.79-0.81 (FAG)

R2 = 0.87 (protein), 0.92 (IMF), 0.93 (GE), 0.87 (DM), 0.17 (ash), 0.44 Mb R2 = 0.40-0.58 (IMF), 0.31-0.35 (DL), 0.40-0.71 (pH)

Beefground LT muscle Porklongissimus muscle

InfraAnalyzer 500 Spectrophotometer (1100-2500 nm)

PLSR


mPLSR

Protein, IMF, GE, DM, ash, Mb IMF, DL, pH

Fish Surimi


PLSR

Protein MC,

R2 = 0.98 (MC & protein)

Poultry breast meat

Foss NIR System 5000 (11002498 nm)

PLS-based discriminan t analysis

Protein, IMF, DM, cholesterol, FAG

R2 = 0.91 (protein), 0.99 (IMF), 0.91 (DM), 0.34 (cholesterol), 0.940.98 (FAG)

Pork muscles

Zeiss MCS 511/522 diode array VIS/NIR system (380-1700 nm)

Linear regression

IMF

R2 = 0.35 (IMF)

[17] Kadim et al., 2005 [18] McDevitt et al., 2005 [19] Prevolnik et al., 2005 [20] Viljoen et al., 2005 [21] Xiccato et al., 2004 [22] Alomar et al., 2003 [23] Anderson & Walker, 2003 [24] Geesink et al., 2003

Poultry

Foss NIR System 5000 (800-2800 nm)

PLSR

Protein, IMF, DM, Ca and P

R2 = 0.96(protein), 0.99 (IMF), 0.82(DM), 0.90(Ca), 0.91(P)

Poultry dried & ground

Foss NIR System 6500 (400-2498 nm)

mPLSR

Protein, IMF, ash

R2 = 0.86 (protein), 0.93 (IMF), 0.71 (ash)

mPLSR

IMF

R2 = 0.84-0.99

PLSR

Protein, IMF, DM, ash

R2 = 0.94(protein), 0.98 (IMF), 0.71(DM), 0.50(ash)

Pork & beef muscle


Ostrichminced, freeze dried Fish – minced sea bass Beef – minced & homogeniz ed Beef minced

FOSS NIR System (11002500 nm)

Pork

InfraAlyser 500 Bran + Luebbe GmbH (1100-2500 nm) FOSS NIR System 6500 (400-2500 nm)

PLSR

Protein, IMF, MC, GE

R2 = 0.30-0.68 (protein), 0.47-0.97 (water), 0.48-0.97 (IMF), 0.28-0.96 (GE) R2 = 0.82 (protein), 0.82 (IMF), 0.77 (DM), 0.66 (ash), 0.18 (collagen)

PLSdiscrim. analysis

Protein, DM, IMF, ash, collagen

Perten DA-7000 Diode Array NIR /VIS spectrometer (400-1700 nm)

PLSR

IMF

R2 = 0.83-0.93 (IMF)

Spectrum One NTS FTIR spectro-photometer (10002500 nm)

Stepwise MLR & PLSR

DL, color, pH, shear strength

R2 = 0.51 (DL)

Table 1. (Continued) Study author [25] Togerson et al., 2003 [26] Windham et al., 2003 [27] Chan et al., 2002 [28] Cozzolino & Murray, 2002

[29] Cozzolino et al., 2002 [30] Abeni &Bergogl io, 2001

Meat product Beefground, semifrozen Poultrymuscle

Pork

Spectral sensor (wavelength) InfraAnlyzer 500 Bran + Luebbe GmbH (1100-2500 nm)

Model PLSR

FOSS Model 1265 Meat Analyzer (850-1050 nm)

PLSR

Perten DA-7000 Diode Array NIR /VIS Sensor (400-1700 nm) FOSS NIR System 6500 (400-2500 nm)

Nutrients studied IMF, MC, protein

IMF

Model performance R2 = 0.97 (IMF), 0.96 (MC), 0.80 (protein)

R2 = 0.95-0.99 (IMF)

PLSR

Protein, IMF, MC

R2 = 0.70 (protein), 0.61 (IMF), 0.69 (MC)

mPLSR

Protein, IMF, MC

R2(intact/minced) = 0.26/ 0.73(protein), 0.79/0.89 (IMF), 0.01 /0.87(MC) R2(intact/mined) = 0.49/0.79 (protein), 0.18/0.71 (IMF), 0.36/0.72(MC) R2(intact/mined) = 0.71/0.97 (protein), 0.29/0.87-0.92 (IMF), 0.38/0.96 (MC) R2 = 0.54-0.71 (protein), 0.87-0.92 (IMF), 0.09-0.41 (MC)

Beef LD: intact & minced Lamb: intact & minced


mPLSR

Protein, IMF, MC

Poultry: intact & minced


mPLSR

Protein, IMF, MC

Beef LD muscle minced


mPLSR

Protein, IMF, MC

Poultry breast minced


mPLSR

Protein, IMF, MC, ash

R2 = 0.97 (IMF)

[31] Brondum et al., 2000 [32] Cossolino et al., 2000 [33] Rodbotten et al., 2000

Pork -loin muscle

OceanOptic FOP (500-980 nm), FOSS NIR System 6500 (802-2500 nm)

PLSR

IMF, MC (with different instruments)

R2 = 0.02-0.59 (IMF), 0.03-0.45 (MC)

Lambminced


PLSR

Protein, IMF, MC

R2 = 0.20-0.84 (protein), 0.26-0.88 (IMF), 0.29-0.96 (MC)

Beef -LD muscle

Infraanlyzer 500 Bran + Luebbe GmbH (1100-2500 nm)

PLSR

IMF

R2 = 0.61-0.72

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There is limited research conducted on the application of NIRS for estimating quality of cooked meat products. The cooking process denatures the Mb and hemoproteins, resulting in a reduction in the corresponding absorbance peaks [2]. Also, the color of the meat products, which is indicative of the nutritional constituents in the raw form, changes into different shades of brown and light pink after cooking. Yet, the need for characterizing the nutrient value of cooked meat is only increasing due to the increased demand for “heat-and-eat” or “ready-to-eat” meat products that are accurately labeled. Also, the few studies that addressed cholesterol in meat products indicated that the NIRS method does not work well for indicating cholesterol [2,15]. Preliminary research [2] focusing on the estimation of the quality of cooked ground beef patties showed that visible-NIR (VNIR) reflectance spectroscopy in combination with chemometric modeling holds great potential for rapid detection of fat and caloric content (Table 2). The R2 values were high and standard error of cross-validation (SECV) and prediction (SEP) were relatively low for both fat and calories. While the residual predictive deviation (RPD), an indicator of model performance, for fat, calories and MC for raw patties were all above 4 for raw patties under calibration and validation, the RPD for cooked ground beef patties were less than or equal to 3.0 under independent validation. A model with an RPD below 3 is considered unacceptable for online screening applications [37]. Therefore, the linear PLSR model for cooked ground patties was only borderline acceptable. Table 2. Performance of the full and refined PLSR models developed for predicting fat, calorie, cholesterol and MC in cooked ground beef patties Model Performance

Full PLSR model with 220 bands of difference spectra Fat % Calorie Chole MC Kcal/g mg/g % Calibration: Cross-validation R2-value 0.93 0.92 0.80 0.64 SECV 2.2 0.09 10.8 3.6 RPD 3.6 3.3 2.2 1.6

0.91 2.2 3.2

0.90 0.09 3.1

0.78 10.5 2.0

0.65 3.5 1.6

Independent Testing or Prediction R2-value 0.87 0.87 SEP 3.2 0.06 RPD 2.9 3.0

0.85 3.5 2.6

0.86 0.07 2.7

0.79 5.8 2.2

0.72 1.6 2.0

0.76 6.2 2.1

0.70 1.7 1.9

Refined PLSR with 50 bands of difference spectra Fat Calorie Chole MC % Kcal/g mg/g %

Copyright: Bajwa et al., 2009.

The denaturing of hemoproteins and changes in the appearance of the meat during cooking could change the spectral absorbance of patties. Another reason for the poor performance of the PLSR model for cooked ground beef patties was the decrease in the range and standard deviation of all four response variables for the cooked meat samples compared to the raw meat samples [2]. As the variability in the data set decreases, the performance of an empirical model deteriorates. Except for cholesterol, the standard deviation of cooked patty samples was approximately half as much as that of raw samples. Compared to raw meat samples, the coefficient of variation (ratio of standard deviation to mean) of cooked meat

Non-linear Modeling of Quality of Cooked Ground Beef Patties…

43

samples decreased by approximately 11% for fat, 6% for calories, 3% for cholesterol and 5% for MC. Another reason for the relatively poor performance of the PLSR model for cooked meat was the error in model specification for fat and calories in cooked ground beef patties. Almost all of the past studies have utilized either PLSR or mPLSR for developing empirical models to estimate the quality trait of interest in specific meat products (Table 1). The PLSR is a bilinear modeling method, that decomposes the high-dimensional spectral data into partial least squares or principal components, and develops an optimal model for predicting one or multiple response variables from the PLS factors. An analysis of the residuals of the PLSR model for fat and calories from [2] showed parabolic trends (Figure 1), indicating that the model requires higher order terms to adequately describe the relationship between response variables and spectral data. Based on the residuals, we hypothesized that the model relating fat and calories to spectral data should be non-linear for cooked ground beef patties. The common model structure used in PLSR is linear. However, it is possible to develop non-linear PLSR models mainly by transforming the Y variables to higher order terms. Although it is possible to also transform X variables into higher order terms in order to develop a non-linear PLSR model, the large number of X variables in spectral data makes this a quite complex and time consuming task.

Figure 1. Residuals of a linear PLSR model (Bajwa et al., 2009) developed for predicting fat, calories, MC and cholesterol of cooked ground beef patties.

Apart from PLSR and mPLSR, there are other methods for modeling the characteristics of a target material using high-dimensional spectral data. Radiative Transfer models (RTM) employ a process-based approach to study the chemical concentrations of compounds of interest in a target material. However, RTMs are too complex to be implemented in a processing line, or for quick nutrient profile analysis by non-technical users. Popular nonlinear empirical modeling methods that can be implemented for estimating the chemical

44


constituent concentration in a target material from spectral data include (1) non-linear PLSR models that use transformed higher order X or Y variables, (2) artificial neural networks (ANN), and (3) support vector machines (SVM). There are only a few studies that have attempted the use of non-linear chemometric models for estimating the quality of meat products. One such study compared a linear PLSR model with back propagation (BP) and counter propagation type ANN models for estimating drip loss from pork muscle samples, and indicated that all three model performed similarly [38]. Another study used a combination of NIRS with principal component analysis and ANN modeling to successfully estimate the color and doneness of meat undergoing the cooking process [39]. This study was conducted with the objectives of testing two non-linear chemometric models, (1) a non-linear PLSR model with transformed higher order Y variables (fat and caloric content), and (2) a simple ANN model, for estimating the quality of cooked ground beef patties.

MATERIALS AND METHODS Lab Experiment A laboratory experiment was conducted with 8 different preparations of ground beef patties with fat content varying from 5 to 40% (wet basis). Ground beef patties were made by mixing lean muscle and fat at proportions of 95:5, 90:10, 85:15, 80:20, 75:25, 70:30, 65:35 and 60:40. The experiment was a completely randomized block design with 120 samples, which included 8 fat levels (treatments), 3 blocks and 5 replications under each treatmentblock combination. The beef patties were prepared by mixing peeled knuckles (quadriceps muscle) and fat trimmings in appropriate proportions, as explained in [2]. Weighed proportions of fat and lean muscle were coarse ground together through a 7.6-mm break plate and then fine ground through a 3.2-mm break plate in a Hobart grinder (Model 310; Hobart Inc., Troy, OH). The ground homogenized mixture was then fed into a Hobart patty machine (Model E-103; Hobart Inc., Troy, OH) to make patties of 151 g each. The raw patties were wrapped in a PVC film (O2 transmission rate of 1400 cc/m2/24h/atm) and stored frozen at -20ºC till cooking. Prior to cooking, the frozen patties were thawed to room temperature, and weighed to record the thawed weight. Then, they were pan-fried to an internal temperature of 71ºC according to AMSA cookery guidelines [40]. Patties were turned every 2 min during the cooking process, and subsequently cooled for 5 min before scanning. The experimental procedure is explained in detail in [2]. The same data set was used in this study.

Data Collection An ASD Field Spec Pro dual sensor spectro-radiometer (Analytical Spectral Devices, Inc., Boulder, CO) was used for spectral data collection. It had two sensors made of Si photodiode arrays, both with a wavelength range of 350-1100 nm, spectral resolution of 3 nm, and record interval of 1.5 nm. The two sensors simultaneously detected the reflected light

Non-linear Modeling of Quality of Cooked Ground Beef Patties…

45

from a patty sample as well as from a reference panel called spectralon panel that had 98% reflectance in the 350-1100 nm range. The light reflected from the spectralon panel was used to estimate the incoming radiance. Spectral data from the 401 to 1064 nm range, sub-sampled at 3 nm interval was used in this study. Thus, reflectance recorded at 222 individual wavebands was used for building and testing the non-linear models to predict nutrient value of ground beef patties. A 14.5V, 50W artificial tungsten halogen light (LowelPro, Lowel Light Inc., Brooklyn, NY) was used as the light source. The light source was mounted at a distance of 1.2 m vertically above the sample such that the intensity of light over the patty surface was somewhat uniform. The cooked patties were longitudinally split to avoid the effect of surface abnormalities in the scan. Five NIR readings were measured from random locations on the inner side of each half. Cooked patties were packaged and stored at -20º C until preparation for chemical analyses. Both sensors were set to average 10 scans, and 5 dark readings for each data point. Each patty was scanned at 10 random points distributed throughout the inside surface of the cooked and split patty, and averaged to obtain a representative reading for each patty. Therefore, each radiance spectra representing a patty was an average of 100 readings. The simultaneous radiance measurements from the patty and the reference panel were radiometrically calibrated to radiance values using the calibration files provided by the instrument manufacturer. The absorbance of the patty was calculated using equation (1) below.

(1) where, A is the absorbance, IR and IO respectively are the reflected and incoming radiance in W/m2/sr, and R is reflectance as a ratio. The scanned samples of cooked patties were analyzed for fat and caloric contents at the University of Arkansas Central Analytical Lab (UACAL). The UACAL followed the ether extraction method (Method 920.39C AOAC, 1990) to determine the total crude fat. The MC of patty samples was determined by AOAC Method 934.01 [1]. Both fat and MC were calculated as a percentage of dry weight of samples. The caloric content of the samples were measured with a bomb calorimeter as cal per g of sample. The cholesterol content was measured in mg per g of dry sample using AOAC Method 976.26 [1] at the Missouri Agriculture Experimental Station Analytical Laboratory at Columbia in Missouri.

Data Analysis The absorbance values are sensitive to base effects such as thickness of patties and variation in particle size. To minimize the base effects, the absorbance spectra were converted to difference spectra using a finite difference method indicated in equation (2) below. A 15point high pass filter was used for calculating the difference spectra. The difference spectra had 220 bands, which were then used for model development.

46


(2) where, A: absorbance, and dA: difference spectra, all at ith wavelength λi.

Non-Linear Partial Least Square Regression The PLSR method is a bilinear modeling method that has been widely used to develop empirical models relating chemical constituent concentration of a target object to spectral data. Spectral data are often high dimensional (220 difference spectra and 120 observations in this study) and multicollinear. The PLSR method decomposes the spectral data into orthogonal partial least square (PLS) factors such that the covariance between the response variables and the spectral data is maximized [41]. Similar to multivariate principle components, the PLS factors are computed as linear combinations of the spectral bands. Thus the PLS factors eliminate the multi-collinearity problem in the spectral data and reduce the number of independent variables to a manageable size. Another advantage of PLSR is that more than one response variable can be modeled simultaneously with one model. In this study, a PLSR model was developed with (fat2+fat), (calorie2+calorie), cholesterol and MC as response variables and difference spectra in 220 wavelengths as independent variables. Many transformations, including square, square root, logarithmic, exponential, etc were attempted using a trial and error method before choosing the above transform, which gave the best performance. Since the residual for cholesterol and MC in the original model showed a random distribution (Figure 1), and none of the attempted transformations improved the model performance for these two variables, they were left as such in the model. The data were processed in SAS using the PROC PLS option [42]. In the first run of PLSR, the number of PLS factors that significantly contributed to the model variability were identified through a full cross-validation. The initial PLSR model was further modified by eliminating the bands that had limited contribution to the model. Two factors, the regression coefficient and variable importance for projection (VIP) were used to evaluate the contribution of the 220 difference bands to the PLSR model. The VIP represents the value of each predictor in fitting the PLSR model to both predictor and response variables [43]. A predictor variable with a low regression coefficient close to zero and a low VIP is considered non-contributing or redundant, and eliminated from the model. The 120 samples were divided into two groups for calibration and testing. The calibration set included 96 observations and was used for calibrating the model. The remaining 24 observations were used for model validation. To select the validation set, the data set was first sorted by replication, block and then by treatment. Since there were 5 samples in each treatment-block combination, every fifth observation was selected for validation. After data decomposition into PLS factors in the refined model, the model was calibrated to optimize the number of PLS factors used in the model. A full cross validation procedure was used to identify the optimum number of PLS factors that will ensure stability of the model by avoiding over fitting [41]. The full cross validation method was used to identify the minimum number of PLS factors that explained significant (P> 1 the viscoelastic material is said to be more viscous than elastic . Inversely, if Tan(δ) 20% moisture content) can be considered of poor quality according to the European standards, while good quality honeys will have a TVPB around 14°C (< 18 % moisture content). Using the ultrasonic shear reflectivity method, the water content of honey samples was related to the temperature of the vitreous plateau beginning for a constant operating frequency of 10 MHz. This ultrasonic shear method is extremely sensitive because it is possible to separate two honeys whose water content varies from less than 0.2 %.

3.3. Viscoelastic Properties of Water / Sorbitol Solutions Historically, this study has begun in order to find a coupling fluid well adapted for longitudinal and shear waves. We present here major results because they clearly demonstrate the tight complementarities between longitudinal and shear high frequency data around glass transition. More details can be found in references [13] and [33]. In literature, the maximum longitudinal velocity found for pure liquids is 1980 m.s-1 for glycerin [34]. Weissler et al. in the short note [35] obtained an “unusually high velocity” for Sorbitol : 3000 m.s-1. In order to check and complete the above short note, we prepared Water /Sorbitol solutions for both longitudinal and shear investigations. We used Delalande Sorbitol manufactured by Sanofi synthelabo for solutions preparation. For 0 % (pure water) to a concentration of 85 % of Sorbitol in mass, we just put Sorbitol powder into water and mixed until we obtained a homogeneous liquid. From 85 to 100 % of Sorbitol in mass it was not possible to apply the same procedure because the dissolution was too slow. In this case we heated the solutions. In all the cases a homogeneous transparent highly viscous liquid was obtained. Results are presented in Figures 9 and 10.

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The rapid increase of longitudinal velocity is clearly explained regarding the values of G’ and G’’ versus Sorbitol content in water. Over 85 % of Sorbitol in water, G’ becomes greater than G’’. Hence the solution tends to a solid behavior for high frequencies. So, even if it could be surprising, this solution which appears as a liquid during the experiments, acts as a material over the glass transition for high frequency ultrasonic waves. Over glass transition the attenuation will decrease as presented in figure 7b for honey, and Sorbitol will become an ideal coupling fluid with high acoustical impedance and small attenuation. This special behavior for high frequency experiments around room temperature would not be the same for smaller frequencies.

Figure 9. Longitudinal 5 MHz velocity in Water /Sorbitol solutions. T=25°C.

Figure 10. G’ and G’’ values measured at 25°C for an operating frequency of 5 MHz from 75 to 100% of sorbitol concentration in the aqueous solutions.

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3.4. Mangos [36] The objectives of the present study were: (1) to examine the potential use of resonant acoustic method presented in 2.3.1 to characterize mango tissue firmness; (2) to compare and to correlate the acoustic parameter values obtained from a batch of mangoes with a wide range of maturity, to the related firmness values measured by a puncture test. Tests were performed on commercial mango fruit (Mangifera indica L., cv. Amelie) imported from the Ivory Coast and purchased on wholesale market. Forty-five fruit were selected, covering a wide range of maturity. Pulp firmness Fp (N) was assessed by driving a flat-tipped 2 mm diameter cylindrical plunger into the mesocarp of the equatorial fruit slice. The depth and rate of penetration of the plunger into the pulp tissue were 10 mm and 1 mm/s, respectively. Special care was taken to penetrate the pulp perpendicularly to the cut surface. Penetrometer measurements were carried out using a TA-XT2 texture analyzer (Stable Micro Systems, Surrey, U.K.). The firmness index of the pulp was the average force Fp measured between 1 and 10 mm penetration depth, so as to take local pulp heterogeneity due to mango fibers into account. This parameter was calculated from the experimental force/displacement curve. Acoustic measurements were made by inserting the sensor tip (see paragraph 2.3.1.) into the mango up to 7 mm depth. Penetration depth was controlled using a micrometer (10 µm resolution). Each acoustic measurement point was about 4 mm from the adjacent puncture point. Average values were calculated for these parameters to characterize each fruit. Δf was very sensitive to the quality of the probe-medium interface, especially for unripe fruit, and poorly correlated with puncture test values. In contrast, the acoustic parameter Δ(1/Z) was significantly correlated with mango pulp firmness Fp assessed by puncture test (Figure 11). Hence, resonant acoustic technique in its basic form (no viscoelastic model known) constitutes an interesting tool for mangos and certainly for fruit texture evaluation during storage or ripening.

Figure 11. Correlation between the acoustic parameter Δ(1/Z) and pulp firmness.

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CONCLUSION In this chapter we have presented three different ultrasonic approaches (echography, reflectometry, resonant method) especially dedicated to viscoelastic properties of material determination. Regarding results presented in this work and literature it is clear that enormous complementarities exist between classical rheological methods and ultrasonic approaches. Ultrasonics techniques have been applied on fruits (mangos) or liquid materials (Glycerin, Honey, Sorbitol). The method to be employed is adapted to the nature of the sample. Furthermore, as matter is non opaque to ultrasonic waves if the frequency is correctly chosen, investigations can be planed through pipes or storage tanks during fabrication process. Then, results obtained in a research context could be at the cost of minor modifications transferred to industrial media when food is prepared, transferred (in pipes for instance) or conditioned. Regarding the calibration law obtained on Honey versus moisture content it is also clear that ultrasonic waves could be usefull for non destructive quality controls.

REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18]

Mason, W.P. Physical Acoustics. Ed. Academic Press, New York, 1964; Vol.1, Part A. Chow, A.W; Bellin, J.L. Polymer Engineering and Science, 1992, vol. 32(3), 182-190. Freemantle, R.J; Challis, E. Meas Sci Techn 1998, vol. 9, 1291-1302. Frigone, M; Maffezzoli, A; Acierno, D; Luprano, V.A.M; Montagna, G. Polymer Engineering and Science, 2000, vol. 40(3), 656-664. Alig, I; Fedtke, M; Häusler K; Tänzer, W; Wartewig, S. Progress in Colloid & Polymer Science, 1988, vol.78, 54-58. Alig, I; Tadjbakhsch, S; Zosel, A. Journal of Polymer Science: Part B: Polymer Physics, 1998, vol. 36, 1703-1711. Alig, I; Lellinger, D. Chemical Innovation 2000, vol. 30(2), 12-18. Alig, I; Lellinger, D. Sulimma, J; Tadjbakhsch, S. Rev. Sci. Instrum. 1997, vol. 68(3), 1536-1542. Sun, Z; Voigt, T; Shah, S.P. Cement and Concrete Research, 2006, vol. 36, 278-287. Rose, J.L; Ultrasonic waves in solid media. Cambridge University Press. 2004 Gasparoux, J; Laux, D; Ferrandis, J.Y; Attal, J; Tordjeman, P. Journal of Non Newtonian Fluid Mechanics, 2008, vol. 153, 46-52. Ferry, J.D. Viscoelastic Properties of Polymers. John Wiley & Sons. 1961. Cereser Camara, V; Laux, D. Ultrasonics 2010, vol.50, 6-8. Lévêque, G; Rosenkrantz, E; Laux, D. Measurement science and technology, 2007, vol. 18, 3458-3462. O’Neil, H. T. Physical Review 1949, vol.75(6), 928-935. Mason, W.P.; Baber, W.O.; McSkimin, H.J; Heis,s J.H. Physical Review, 1949, vol. 75(6), 936-946,. Yoneda, A; Ichihara, M. Journal of Applied Physics 2005, vol. 97, 054901 Longin, P.Y; Verdier, C; Piau. M. Journal of Non-Newtonian Fluid Mechanics, 1998, vol. 76, 213-232.

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[19] Challis, R.E; Unwin, M.E; Chadwick, D.L; Freemantle, R.J; Partridge I.K; Dare, D.J; Karkanas, P.I. Journal of Applied Polymer Science, 2003, vol. 88, 1665-1675. [20] Hull, D.R; Kautz, H.E; Vary, A. Material Evaluation 1985, 43, 985. [21] Cereser Camara, V; Laux, D; Arnould, O. Ultrasonics 2010. Accepted. To be published. doi:10.1016/j.ultras.2010.02.007 [22] Lévêque, G ; Ferrandis, J.Y. ; Van Est, J. ; Cros, B. Rev. Sci. Instrum. 2000, vol. 71, 1433. [23] Blackstock, D.T. Fundamental of physical acoustics. Ed. Wiley Interscience, 2000. [24] Masson, W. Proceeding of the Institute of Radio Engineers 1935, vol. 23, 1252. [25] Viswanath, D.S; Ghosh, T.K.; Prasad, D.L; Nidamarty, V.K. ;Dutt N.V.K. Viscosity of Liquids.Springer 2007. [26] Marini, F.; Magrì, A. L.; Balestrieri, F.; Fabretti, F.; Marini, D.(2004). Analytica Chimica Acta 515(1), pp. 117-125. [27] Radovic, B. S.; Goodacre, R.; Anklam, E. (2001). Journal of Analytical and Applied Pyrolysis 60(1), pp. 79-87. [28] Zhenbo Wei; Jun Wang; Wenyan Liao.(2009). Journal of Food Engineering. Volume 94, Issues 3-4, October 2009, Pages 260-266. [29] Wedmore, E. B. (1955). Bee World, 36(11), pp. 197-206. [30] Kantor, Z.; Pitsi, G.; Thoen, J. (1999). Journal of Agricultural Food Chemistry, 47, pp. 2327–2330. [31] Sopade, P. A.; Bhandari, B.; Halley, P.; D’Arcy, B.; Caffin, N. (2001). Food Australia 53, pp. 399–404. [32] Cereser Camara, V; Laux, D. J. Food. Engeneering. 96 (2010) 93-96 [33] Laux, D . ; Levêque, G.; Cereser Camara, V. Ultrasonics 49 (2009) 159-161. [34] Kinsley, L.E. Fundamentals of acoustics. Third Edition. 1984. [35] Weissler, A.; Del Grosso, V.A. The Journal of the Acoustical Society of America. Vol 23, number 5. September 1951. [36] Valente, M; Ferrandis, JY. Postharvest Biology and Technology, 2003, vol. 29, 219228.



Chapter 6

TRENDS IN HIGH PRESSURE PROCESSING OF FOODS: FOOD QUALITY AND BIOACTIVE COMPONENTS Shirani Gamlath1 and Lara Wakeling2 1

School of Exercise & Nutrition Sciences, Faculty of Health, Medicine, Nursing & Behavioural Sciences, Deakin University, Victoria, 3125, Australia 2 School of Science & Engineering, University of Ballarat, Ballarat, Victoria, 3353, Australia

ABSTRACT High pressure processing (HPP) is a non-thermal food processing technology that offers great potential for the processing of a wide range of food products. Application of HPP can inactivate micro-organisms, affect food-related enzymes and modify structures with minimal changes to nutritional and sensory quality aspects of foods. The effects of high pressure on the inactivation of micro-organisms in food have been thoroughly reviewed. Recent research on HPP has mainly focused on fruits and vegetables with an emphasis on food quality and bioactive components. This chapter highlights the current trends in HPP research and provides a summary of the available findings on the effect of HPP on chemical, nutritional and bioactive components and health related properties of a wider range of commodities. Strategies to maintain the quality attributes and health related components in HPP foods and identification of the gaps for future research in HPP are also discussed.

INTRODUCTION High pressure processing (HPP) has gained much attention in recent years due to a number of advantages: the retention of fresh taste and texture in products such as fruit and vegetable juices, shell fish, sauces and guacamole; an increase in microbiological safety and shelf-life by inactivation of pathogens, spoilage organisms and some quality related enzymes; production of novel products by modifying the existing food structures; low energy

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consumption and labour requirements, and uniform isostatic pressure distribution throughout the product, irrespective of size and geometry (Patterson, 2006; Rastogi et al., 2007). A number of publications have demonstrated the application of HPP in relation to microbiological safety and keeping quality of foods, with optimal pressure and exposure times to validate the process conditions for fruits, vegetable, dairy and meat products. Some quality attributes, particularly the effect on quality related enzymes in food matrices and buffer systems, have also been extensively studied. There is a significant commercial interest in both the local and global markets for new food products particularly fresh-like food products with extended shelf life and high quality. The interest of consumers in the consumption of fresh fruit and vegetables with high antioxidant levels has also become a current trend. High pressure processing has attracted local and global interest due to its mild effect on food products, while maintaining high nutritional value and fresh like properties compared to thermal processing. However, the existing knowledge on pressure stability of nutritional and bioactive components in HPP foods and the optimum conditions to retain the beneficial properties of foods are limited. This chapter aims to explore the current literature around the effect of HPP on nutritional, chemical and bioactive components and health related properties of a wider range of commodities with an emphasis on identifying suitable HPP regimes to retain the nutritional and healthful properties of foods.

EFFECT OF HPP ON FOOD QUALITY It is now well known that HPP can be used to inactivate micro-organisms, while maintaining organoleptic and nutritional qualities of the food. Much of this quality work has focussed on colour and texture in food, as these are the properties that consumers base their food choices on. The effect of HPP on colour and texture has been extensively covered in fruit and vegetables over many years, with comprehensive reviews available by GuerreroBeltran et al., (2005), Rostagi et al., (2007) and Norton and Sun (2008). Most texture related investigations have focussed on the effect of high pressure on enzymes such as pectin methylesterase and polygaluctonase, although interest in assessing texture by instrumental means is now increasing (Norton and Sun, 2008, Perera et al., 2010). In muscle foods increased pressures are thought to result in changes to the muscle proteins, resulting in changes to functional properties and therefore to texture. This was found to be the case in fish where pressures ≥450 MPa resulted in higher hardness, gumminess and chewiness (Yagiz et al., 2007). Colour has been assessed via either instrumental techniques or individual pigments, such as the carotenoids, have been assessed. Table 1 summarises some very recent findings in this area. There is a decrease in redness in all muscle foods after HPP (Andres et al., 2006, Cava et al., 2009) with a corresponding increase in lightness of fish, often associated with a cooked appearance (Ramirez-Suraz and Morrissey, 2006, Yagiz et al., 2007). A decrease in the lightness of HPP cow’s milk and ewe’s milk has also been observed (San Martin-Gonzalez et al., 2006). It has been suggested that the changes in the lightness of these animal products are due to protein structural changes that occur after HPP.

Table 1. The effect of HPP on colour- examples from recent studies Commodity

Method used

HPP conditions*

Iberian ham

Colour

200 & 400 MPa/20 °C/15 min

200 & 300 MPa/15-30 min

200 & 300 MPa/15-30 min

Iberian loin

Rainbow trout (whole muscle)

Colour (up to 6 days)

150, 300, 450, 600 MPa/RT/15 min

Mahi Mahi (whole muscle)

Colour (up to 6 days)

150, 300, 450, 600 MPa/RT/15 min

Albacore tuna (minced muscle) Cows and Ewe’s milk

Colour

275 & 310 MPa /RT/2, 4, 6 min

Melon

Colour

∆E 600 MPa/RT/10 min

Compared to the experimental control Lower initial redness (a*) then stable Lightness ↑ with storage (39 days at 5 °C)

Reference Andres et al., 2006

Cava et al., 2009 ↓ redness; lightness and yellowness unchanged. Similar effect after 90 days storage (4 °C) Cava et al., 2009 ↓ redness; lightness and yellowness unchanged. Similar effect after 90 days storage (4 °C), except yellowness ↑ ↓ redness (a*) >150 MPa cooked appearance (↑ lightness) ↓ redness (a*) Slight ↑ in lightness & yellowness with pressure. Lighter and whiter with ‘cooked appearance’; (L* and b* ↑; a* ↓) ↓ in lightness ↑ in lightness, redness and yellowness

Yagiz et al., 2007

Yagiz et al., 2007

Ramirez-Suraz and Morrissey, 2006 San Martin-Gonzalez et al., 2006 Wolbang et al., 2008

Table 1. (Continued) Commodity

Method used

HPP conditions*

Apple – Granny Smith

∆E

600 MPa/ 22 °C/1-5 min (medium: pineapple juice)

Pink Lady Blackberry puree Strawberry puree

Colour & ∆E

400, 500 & 600 MPa/10-30 °C/15min

Tomato puree Carrot puree

Colour

400-600 MPa/20 °C/15 min

Tomato juice and Carrot juice

∆E

250 MPa/35 °C/15 min

* RT = Room temperature

Compared to the experimental control ↓ at HPP for 3 & 5 min + 25 & 50 % pineapple juice ↓ at HPP for 1 min + 25 % pineapple juice Minor changes. Redness ↓; 96 % retention in strawberries at 600 MPa Redness and colour intensity retained. Lightness ↑ in carrots but ↓ in tomatoes Minor change with HPP. Change ∆E≤15 units after storage for 30 days (4 & 25 °C)

Reference Perera et al., 2010

Patras et al., 2009a

Patras et al., 2009b

Dede et al., 2007

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Minimal changes occur to the colour of HPP fruits (Dede et al., 2007; Patras et al., 2009a,b; Perera et al., 2010), although changes may occur in individual pigments. Further information about the affect of HPP on individual pigments is given in the section on bioactive compounds. It is generally accepted that HPP does not alter the flavour of food. However a recent application of HPP regarding flavour has been the combined use of enzyme immobilisation and HPP to de-bitter grapefruit juice (Ferreira et al., 2008). A pressure of 160 MPa/37 °C/20 min resulted in a reduction in the naringin content and therefore a reduction in bitterness.

EFFECT OF HPP ON CHEMICAL AND NUTRITIONAL COMPONENTS IN FOOD Macronutrients Some recent studies highlighting the effect of HPP on macronutrients in food are shown in Table 2. Generally the total protein and total lipid contents are not affected by HPP. Lipid tends to be of greatest interest in terms of the effect of HPP on lipid oxidation. Total sugars, sucrose, glucose and fructose are not affected by HPP. However sucrose levels dramatically decreased in pressure-treated (600 MPa/25 °C/6 min) raspberry puree, with a corresponding increase in glucose and sucrose levels, most likely due to invertase activity (Butz et al., 2003). Very few studies are available that have investigated the effect of HPP on dietary fibre. In cabbage, no effect of HPP (up to 500 MPa and 80 °C) on total dietary fibre was evident, however soluble fibre increased, while insoluble fibre decreased at 400 MPa (Wennberg and Nyman, 2004). A similar effect was evident in longan fruit pericarp for water soluble polysaccharides, while other fibre components were not affected by HPP (Yang et al., 2009). HPP has been shown to enhance glucose retardation/binding in tomato puree (Fernandez Garcia et al., 2001; Butz et al., 2002a), suggesting that this technique might be used to develop diabetic foods. Overall, as HPP has a limited effect on covalent bonds, macro- and micro-nutrients tend to not be affected by HPP except at conditions of high pressure and high temperature.

Micronutrients The effect of HPP on vitamins has mainly focussed on ascorbic acid (Vitamin C) content, although thiamine (B1), riboflavin (B2), pyridoxal (B6) and folate have also been investigated. The majority of these studies have been in fruits and vegetables or model systems. Generally all of these water soluble vitamins are stable to high pressure processing, with folate showing higher sensitivity (Sancho et al., 1999; Indrawati et al., 2002; Oey et al., 2008; Sanchez-Moreno et al., 2009). A summary of recent studies assessing ascorbic acid content is shown in Table 3.

Table 2. The effect of HPP on Macronutrients Commodity

Macronutrient

HPP conditions

Beef

Total lipid

Ham (frozen)

Total protein

Albacore tuna

Total lipid

0.1, 200 & 800 MPa/60 ºC/20 min 400 & 600 MPa/~15 °C/10 min 275 & 310 MPa/2, 4, 6 min

Milk

Total lipid Total protein

400 MPa/20 °C/20 min

No change No change

Cheese

Total lipid Total protein

400 MPa/20 °C/20 min

No change No change

Cheese – using HP milk

Total lipid Total protein Glucose binding (retardation)

400 MPa/20 °C/20 min 600MPa/20 °C/60 min

Significantly ↓ Significantly ↑ Significant retention (28 %)

600MPa/25 °C/60min

↑ of 14.34-27.13 %

Butz et al., 2002a

0.1, 400 & 500 MPa/20, 50 & 80 °C/10 min

Slight change in TDF. Soluble fibre - ↓ all temp at 400 MPa; Insoluble fibre – concurrent ↑

Wennberg and Nyman, 2004

Tomato puree

White cabbage

Dietary fibre

Compared to the experimental control No change

Reference

Tume et al., 2010

No significant change

Serra et al., 2007

Significantly ↑

Ramirez-Suarez and Morrissey, 2006 Sandra et al., 2004

Fernandez Garcia et al., 2001

Longan fruit pericarp

Raspberry puree

Strawberry Raspberry Orange juice

Orange/lemon/carrot mixed juice

Water-soluble polysaccharide Alkali-soluble polysaccharide Cellulose Lignin Sucrose

0, 200, 300, 400, 500 MPa/25 °C/30 min

↓ with ↑ pressure

Yang et al., 2009

No significant difference

600 MPa/25 °C/6 min 600 & 800 MPa/44 °C/6 min

Glucose & fructose

600 Mpa/25 °C/6 min

Sucrose

600 MPa/25 °C/6 min

Fructose, glucose, sucrose, total sugar

500 & 800 MPa/20 °C/ min

Total sugar

No significant difference No significant difference >90 % loss during storage at 4 °C for 30 days at 600 MPa

Butz et al., 2003

40 % and 60 % ↑ during storage at 4 °C for 30 days at 600 MPa 100 % retained >95 % retained No difference

Butz et al., 2003

500 & 800 MPa/20 °C/ min

100 % retention after 21 days storage (4 °C)

Butz et al., 2002b

Sucrose

600 MPa/25 °C/6 min

100 % retention

Butz et al., 2003

Sucrose

600 MPa/25 °C/6 min

100 % retained

Butz et al., 2003

Butz et al., 2002b

Table 3. The effect of HPP on Micronutrients Commodity

Micronutrient

HPP conditions*

Beef

Tocopherol

0.1, 200 & 800 MPa/60 ºC/20 min

Fatty acids

Iberian ham

α-tocopherol

200 & 400 MPa/20 °C/15 min

Dry-cured pork loin

Total free amino acid

Orange juice

Ascorbic acid

300, 350 & 400 MPa/20 °C/10 min 600 MPa/40 °C/4 min

Compared to the experimental control No change Significant ↑ myristic (14:0); palmitic (16:0); trans-vaccenic acid (18:1trans-11) Significant ↓ linoleic acid (18:2n-6), cis-vaccenic acid (18:1cis-11) No effect of HPP ↓ correlation with ↑ TBARS after 39 days storage (5 °C) No change

Reference Tume et al., 2010

Andres et al., 2006

Campus et al., 2008

Retained

Polydera et al., 2005

500 & 800 MPa/20 °C/ min

No change. 90% retention after 21 days storage (4 °C)

Butz et al., 2002b

100 MPa/60 °C/5 min 350 MPa/30 °C/2.5 min 400 MPa/40 °C/1 min

90 % retention No change

Sanchez-Moreno et al., 2003a

93 % retention. No further loss after 10 days storage (4 °C)

Orange/lemon/carrot mixed juice Tomato juice Carrot juice

Tomato puree Carrot puree Cowpea

Melon

Blackberry puree Strawberry puree * RT = Room temperature

Ascorbic acid

Ascorbic acid – 4 days germination 6 days germination Ascorbic acid

Ascorbic acid

600 MPa/25 °C/6 min

95 % retained

Butz et al., 2003

600 MPa/25 °C/6 min 250 MPa/35 °C/15 min

>95 % retained No change. After 30 days storage (4 & 25 °C) 70 % & 45 % retained respectively

Butz et al., 2003 Dede et al., 2007

400-600 MPa/20 °C/15 min 300, 400 & 500 MPa/RT/15 min

90 % retained

Patras et al., 2009b

600 MPa/RT/10 min

400, 500 & 600 Mpa/10-30 °C/15min

Doblado et al., 2007 90-72% retained 91-59% retained 50 % retained. Cultivar dependent with 15-74 % retention. No significant change (>90 % retained)

Wolbang et al., 2008

Patras et al., 2009a

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Ascorbic acid has been shown to be stable to high pressure processing, unless it is subjected to high pressure and high temperature (>65 °C) conditions, where oxidation reactions are enhanced (Oey et al., 2008). In addition to its role as a vitamin, ascorbic acid also plays an important role as an antioxidant. Ascorbic acid has been shown to protect folate against the effects of pressure and heat (Oey et al., 2008). Further information about the antioxidant role of ascorbic acid can be found in the section on HPP and antioxidant activity. Most studies of the effect of HPP on fat soluble vitamins have been limited to carotene, Vitamin A (retinol) and Vitamin E (tocopherol). Again, HPP has minimal effect on these vitamins (Table 2) (Indrawati et al., 2002; Oey et al., 2008). The effect on carotenoids is expanded upon in the section on antioxidant activity. There is still limited information available about the effect of HPP on niacin, cobalamin, and Vitamins A, D, E and K. Information about the effect of HPP on minerals is scarce, with most discussion of minerals focussing on possible relationships between iron and lipid oxidation. This is an area that requires further investigation. As with the other micronutrients mentioned, few studies have been reported that investigate amino acid or fatty acid content except in meat products. HPP (up to 400 MPa) of dry-cured pork loin has no effect on the total free amino acid content (Campus et al., 2008). Some variation in individual fatty acids occurs when beef is subjected to HPP (up to 800 MPa) (Tume et al., 2010). Further investigation into the effect of HPP on individual fatty acids is necessary, especially in relation to essential fatty acid content.

Proteins and Enzymes Proteins are usually denatured by high pressure however the protein type, processing conditions and pressures applied are all important considerations. Generally, at low protein concentrations and low pressures (300 MPa) induce irreversible and extensive effects on proteins (Guerrero-Beltran et al., 2005; Rastogi et al., 2007). HPP is most commonly used to inactivate deleterious enzymes, thereby ensuring the high quality characteristics of the food are maintained (Rastogi et al., 2007), but it can also be used to stabilise and activate other enzymes (Eisenmenger and Reyes-de-Corcuera, 2009). These changes tend to have little effect on the nutritional content of the food, but are important with respect to food quality especially in relation to colour (polyphenoloxidase) and texture of food (pectic enzymes), plus some influence lipid oxidation (lipase and lipoxygenase). Thus most investigations have focused on monitoring the effect of high pressure on these quality related enzymes, and there are a number of comprehensive review articles available summarising this work (Guerrero-Beltran et al., 2005; Rastogi et al., 2007; Eisenmenger and Reyes-de-Corcuera, 2009). Table 4 shows a summary of the effect of HPP on proteins and enzymes in various commodity groups. Future work may focus on expanding the knowledge of HPP on antioxidant enzymes as another means of maintaining food quality and nutrition.

Table 4. The effect of HPP on Proteins Commodity

Protein type

HPP conditions*

Cows Milk

Casein miscelle

Whey proteins

Goats milk

β-lactoglobulin α-lactalbumin BSA Casein miscelle

Soy milk

Lipase Lipoxygenase

250 MPa >400 MPa 500 & 800 MPa 500 & 800 MPa ≤400 MPa/RT/60 min 300-350 MPa / 45 °C 400-500 MPa 300-400 MPa/0-180 min >800 MPa 600 MPa/60 °C ≤300 MPa/9°C/20 min

Cold-smoked salmon Lupin Meta (bovine) Ham (frozen)

Dry-cured pork loin

Proteolytic enzymes (cathepsin and calpains) Protein digestibility (invitro) Antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidise) Proteolytic enzymes (cathepsin B, cathepsin B+L) Cathepsins

amino-peptidases dipeptidyl peptidases

* RT = Room temperature

Compared to the experimental control Size temp dependant Size altered 70 % & 90 % denatured 10 % & 50 % denatured Not denatured ↑ Size Smaller size ↑ activity Inactivated Inactivated Reduced activity

Reference

200 & 500 MPa/10 °C/10 min

Most hyrolysed at 500 MPa

De Lamballerie-Anton et al., 2002

400 & 600 MPa/~15 °C/10 min

Significant ↓, but still active

Serra et al., 2007

San Martin-Gonzalez et al., 2006 San Martin-Gonzalez et al., 2006 San Martin-Gonzalez et al., 2006 Van der Ven et al., 2005 Lakshmanan et al., 2005

No significant change

300, 350 & 400 MPa/20 °C/10 min

20 % ↓ for 400 MPa; Significant ↓ after 45 days storage Significant ↓ Significant ↓

Campus et al., 2008

Table 5. The effect of HPP on Lipid Oxidation Commodity

Lipid oxidation test

HPP conditions*

Chicken (minced thighs)

TBARS (to 9 days)

500 MPa/50 ºC/30 min (air storage)

TBARS (7 days) Beef

TBARS (up to 6 days)

500 MPa/-10, 5, 20, & 50 ºC/30 & 60 min (vacuum stored)

Raw – no significant difference after 9 days

0.1, 200, 400, 600 & 800 MPa/20-70 °C/ 20 min 0.1, 200 & 800 MPa /60 ºC/20 min

↑ at >400MPa regardless of temperature ↑ in 6 day samples Low at 200 MPa

Reference

Beltran et al., 2004

Ma et al., 2007 Tume et al., 2010

↓ at 6 days

Peroxide Value

Iberian ham

Compared to the experimental control Raw – significant ↑ at 6 & 9 days Overcooked – significant ↑ from day 1

TBARS (7 days)

0.1, 200, 400, 600 & 800 MPa/20-70 °C/ 20 min

TBARS (90 days storage)

200-300 MPa/20-30 min

TBARS (39 days)

200 & 400 MPa/20 °C/15 min + MAP

At 20 & 40 °C - 5 fold ↑ at ≥400MPa. Little additional effect at > temperatures No differences

Significant ↑ at 39 days (5 °C) for 400 MPa No O2 = low TBARS

Ma et al., 2007

Andres et al., 2006

Dry-cured pork loin

TBARS (up to 45 days storage)

300, 350 & 400 MPa/20 °C/10 min

No difference

Campus et al., 2008

Ovine Milk

Free Fatty Acid value

500 MPa /4, 25, 40 °C

No change or ↓

Norton and Sun, 2008

Rainbow trout (red muscle)


150, 300, 450, 600 MPa/ 5 min

Yagiz et al., 2007

Mahi Mahi (red muscle)


150, 300, 450, 600 MPa/RT/15 min

Sardine (cold smoked)

TBARS & Peroxide Value TBARS (22 days/4 °C & 93 days/-20 °C)

300 MPa/20 ºC/20 min

No change at 150 MPa ↑ with ↑ pressure 300 MPa ideal ↑ with ↑ pressure, with max at 300MPa then ↓; 450 MPa ideal Little change over 2 wk storage (air) Lower immediately after HPP. Slight increase with storage

Albacore tuna (minced muscle) * RT = Room temperature

275 & 310 MPa/2, 4, 6 min

Yagiz et al., 2007

Gomez-Estaca et al., 2007 Ramirez-Suraz and Morrissey, 2006

134


Lipid Oxidation The effect of HPP on lipid oxidation is important from a nutritional perspective due to the loss of polyunsaturated lipids and the production of undesirable oxidation products. Most studies have focussed on meat, some on seafood, and a few on dairy products. The focus on muscle foods is primarily due to reports that lipid oxidation is enhanced at processing pressures >400 MPa and is more prevalent in red meat due to the higher myoglobin levels (Ma et al., 2007). It has also been suggested that free metal ions are released by the pressure treatment, again promoting lipid oxidation. Some recent studies investigating lipid oxidation in HPP foods are summarised in Table 5 and they reiterate the importance of keeping the processing pressure at Thm the process was enthalpy controlled, but if TB< Thm the process was entropy controlled. Even though these results are interesting, for them to be useful in the study of dry foods stability, it is still necessary to obtain the compensation between the integral enthalpy, which can be interpreted as a latent heat, and the integral entropy, which is related to the order of the adsorbed water molecules in the food. The compensation obtained from plotting the integral enthalpy vs integral entropy of four different yogurts, showed that water vapour adsorption was controlled at low moisture contents by entropy, but at high moisture contents by enthalpy [12]. Processing induced changes in the microstructure of natural yogurt (Y), concentrated yogurt (CY), freeze-dried yogurt (FDY) and concentrated freeze-dried yogurt (FDCY) powders, producing four different isokinetic temperatures in the moisture content zone controlled by entropy, but only one isokinetic temperature in the moisture content zone controlled by enthalpy (Figure 9). These results indicate that the enthalpy controlled zone depended on food composition, whereas the entropy controlled zone was a function of food microstructure. The enthalpyentropy compensation plots of the four yogurt powders showed that the change in the control mechanism from entropic to enthalpic occurred at the point of minimum integral entropy, suggesting that it is possible to produce stable foods with higher moisture contents, if we are able to increase the moisture content range that corresponds to the entropy controlled zone.

Hue angle H* (°)

80

60

a

40

a a

w w w

= 0 .2 1 5 = 0 .4 3 6 = 0 .6 2 8

20

0 0

1

2

3

4

5

6

T im e ( w e e k s )

Figure 5. Effect of water activity on the hue angle of macadamia nut stored at 35 ºC [9].

7

164

Cesar I. Beristain, Eduardo J. Vernon-Carter and Ebner Azuara

In order to prove that entropy barriers exist in the low moisture contents zone, Azuara and Beristain [12] calculated the micropores volume of the four dry yogurt products and compared them with the moisture contents corresponding to the minimum integral entropy (Table 1). Their results showed that the minimum integral entropy occurred when the food micropores (< 2 nm) filled-up, so that in these small pores the steric and other effects associated with the close proximity to pore walls (entropic effects) are predominant and diffusion is controlled by interactions between the water molecules and the pores walls [34]. 3.5 a = 0.215 w

3

a = 0.436 w

a = 0.628 w

Penetration (mm)

2.5 2 1.5 1 0.5 0 0

1

2

3

4

5

6

7

8

T im e (w eeks)

Figure 6. Effect of water activity on the texture of macadamia nut stored at 35 ºC [9]. 5000 288 303 318 333 288 303 318 333

-5 00 0 -1 00 0 0

dif T

Enthalpy (ΔH ) (J / mol)

0

K K K K K K K K

P ru n es

A p ricots

-1 50 0 0

T = 31 7.6 ± 4 .6 K B

2

r = 0 .99 6

-2 00 0 0 -2 50 0 0 -3 00 0 0 -3 50 0 0 -1 00

-8 0

-6 0

-4 0

E n trop y (Δ S )

d if T

-2 0

(J / m o l K )

Figure 7. Enthalpy-entropy relationship for water sorption in dried fruits [11].

0

20

Thermodynamic and Kinetic Criteria to Study the Stability of Dried Foods

165

0 293 303 323 333 313 323 333 343

-10000

dif T

Enthalpy (ΔH ) (J / mol)

-5000

K M acadam ia N uts K T = 382.5 ± 7.3 K K B 2 K r = 0.997 K Potatoes K K K T = 265.0 ± 18.8 K B

-15000

2

r = 0.999

-20000 T = 272.0 ± 57.7 K B

2

-25000

r = 0.987

-30000 -80

-70

-60

-50

-40

-30

-20

-10

0

Entropy (ΔS ) (J / mol K) dif T

Figure 8. Enthalpy-entropy relationship for water sorption in potatoes and macadamia nuts [11].

Effect of Pore Blockage For designing and optimizing the water vapour sorption in foods it is of the utmost importance to know and understand the sorption kinetics process. Pore sizes in foods influence the sorption kinetics because it determines the relative humidity (RH) at which a resistance is formed at the pores mouth (or opening).The effect of pore blockage in foods has not been studied previously as far as we know, and this theory probable allows to explain the relationship between the sorption kinetics at different RH with the equilibrium state and stability of the foods. The stability of the food will depend on the amount of water sorbed in the surface interacting with the more active sites of the polymeric matrix, which forms a protective layer against oxidation, and that on turn serve as a medium for allowing other detrimental reactions. Food micropores finish filling-up at a specific water activity, and from that moment a resistance is created at the pores mouth, which diminishes the water molecules sorption rate. At the same time, at the pores mouths, water molecules begin to interact at a lower energy level with other water molecules, forming a second layer that possesses higher mobility which increases the integral entropy. From the above explanation, we may assume that as filling up of the micropores proceeds, diffusion is controlled by the interactions between the water molecules that are diffusing and the pores walls; i.e., adsorption occurs by entropic mechanisms and the driving force is the difference between the water activity in the food and in the environment (RH). Within the micropores the water molecules will accommodate themselves in an orderly fashion, at least while enough micropores volumes are available, decreasing their integral entropy. The minimum in integral entropy will occur at the RH where all the food pores fill-up, and immediately afterwards, and increase in resistance at the

166


pores mouths will happen, decreasing the velocity of water vapour sorption. The RH and moisture contents values at which the minimum integral entropy occurs will depend on food microstructure. It goes without saying that during all the sorption process enthalpic mechanisms (attraction bonds or forces due to the chemical nature of water and food) also take place, but that at low moisture contents entropic mechanisms prevail. After the filling-up of the micropores, the water molecules interact with other water molecules at the pores mouths, and the filling-up of the mesopores falling within a range of 2 nm to 5 nm commences, with surface and capillary forces controlling the diffusion. In this zone the integral entropy begins to increase and the process is controlled by enthalpic mechanisms. Macropores with sizes larger than 5 nm affect very little the adsorption process. Some foods rich in sugars, such as dry fruits, present only one enthalpy-entropy compensation straight line, where the adsorption is controlled by enthalpy because they possess few micropores. In order to experimentally validate the pore blockage theory in foods, it is necessary that the RH corresponding to the minimum integral entropy obtained with thermodynamic 10000 Y

-10000

FDY

293 K

308 K

308 K

323 K

323 K

CY 293 K

FDCY 293 K

308 K

308 K

323 K

323 K

T

B2

B2

Y

) Enthalpy ( Δ H

= 327.4 ± 0.7 K T

int T

(J / mol)

0

293 K

CY FDCY

-20000

Y: T = 208.7 ± 4.8 K

FDY

B

CY: T = 178.9 ± 7.1 K B

-30000

FDY: T = 241.1 ± 1.4 K B

FDCY: T = 216.1 ± 3.1 K B

-40000 -120

-100

-80

-60

Entropy (Δ S )

int T

-40

-20

(J / mol K)

Y= Yogurt, CY= Concentrated yogurt, FDY= Freeze dried yogurt, FDCY= Freeze dried concentrated yogurt

Figure 9. Enthalpy-entropy relationship for water sorption in yogurt products [12].

0


167

Table 1. Dubinin-Radushkevich parameters for sorption isotherms of yogurt products and moisture content at the minimum integral entropy at 35°C [12]

Product

no (g water/100 g dry solids)

B

r

Moisture at the minimum (ΔSint)T (g water/100 g dry solids)

Yogurt Concentrated Yogurt Freeze-Dried Yogurt

9.3 4.3 5.6

0.3273 0.3995 0.2900

0.995 0.996 0.993

9.0 3.8 5.7

Freeze-Dried Concentrated Yogurt

3.5

0.3829

0.995

3.3

2

equations be equal to the RH where pore blockage occurs during adsorption. Figure 3 shows that for macadamia nut the thermodinamically calculated minimum integral entropy occurs at RH= 0.4 at 35°C. Applying the pore blockage kinetic theory to water vapour adsorption in macadamia nut by plotting − ln(1 − M ∗ ) against t for different RH, in accordance to equation (22), we can observe in Figure 10 that the kinetic adsorption data fit straight lines, except when RH=0.4, where a sharp decrease in the straight line slope indicates the fill-up of the micropores and the appearance of a resistance at the pores mouths. The pores volume in macadamia nut calculated with the Dubinin-Radushkevich (equation (14)), was of 1.4 g H2O/100 g D.S which corresponds to aw= 0.4. It is important to notice that for this product the thermodynamic criterion and the kinetic criterion indicate that the maximum stability during storage was achieved at RH= 0.4 at 35°C. Occasionally, when food microstructure is very heterogeneous, the filling-up of the pores is not likely to occur simultaneously, which causes a gradual slow increase in the resistance, making difficult to observe with clarity the pore blockage. Δ 3 R H = 0 .1 0 R H = 0 .2 1 2 .5

R H = 0 .3 1

*

-ln (1-M )

R H = 0 .4 3 P o r e b lo c k a g e

2

1 .5

1

0 .5 -1 0

0

10

20

30

40

T im e (m in )

Figure 10. Effect of pore blockage during water adsorption on macadamia nut at 35°C.

50

168


CONCLUSION The minimum integral entropy and the pore blockage kinetic theory are two useful methodologies for determining the point of maximum stability of dry foods during storage. The enthalpy-entropy compensation is an important tool for recognizing the mechanisms that control water sorption in foods. It is possible to enhance the stability of foods without modifying their composition, if we are capable of modifying their microstructure producing a larger zone where sorption is controlled by entropic mechanisms.

REFERENCES [1] [2] [3] [4]

[5]

[6]

[7] [8]

[9]

[10] [11] [12] [13]

Hill, P.E. & Rizvi, S.S.H. (1982). Thermodynamic parameters and storage stability of drum dried peanut flakes. Lebensmittel-Wissenschaft und-Technologie 15, 185-190. Rizvi, S.S.H. & Benado, A.L. (1984). Thermodynamic properties of dehydrated foods. Food Technology 38(3), 83-92. Beristain, C.I. & Azuara, E. (1990). Maximal stability of dried products. Ciencia(México) 41: 229-236. Diosady, L.L., Rizvi, S.S.H., Cai, W. & Jagdeo, D.J. (1996). Moisture sorption isotherms of canola meals, and applications to packaging. Journal of Food Science, 61, 204-208. Gabas, A.L., Menegalli, F.C. & Telis-Romero, J. (2000). Water sorption enthalpyentropy compensation based on isotherms of plum skin and pulp. Journal of Food Science 65, 680-684. Beristain, C.I., Azuara E. & Vernon-Carter E.J.(2002). Effect of water activity on the stability to oxidation of spray-dried encapsulated orange peel oil using mesquite gum (prosopis juliflora) as wall material. Journal of Food Science 67, 206-211. Nunes, R. & Rotstein E. (1991). Thermodynamics of water-foodstuff equilibrium. Drying Technology 9, 113-117. Beristain, C.I., Díaz, R., García, H.S. & Azuara, E. (1994). Thermodynamic behavior of green whole and decaffeinated coffee beans during adsorption. Drying Technology 12, 1221-1233. Domínguez, I.L., Azuara, E., Vernon-Carter, E.J. & Beristain, C.I. (2007). Thermodynamic analysis of the effect of water activity on the stability of macadamia nut. Journal of Food Engineering , 81, 566-571. Labuza, T.P. (1980). Enthalpy/entropy compensation in food reactions. Food Technology 2, 67-77. Beristain, C.I., García H.S. & Azuara E. (1996). Enthalpy-entropy compensation in food vapor adsorption. Journal of Food Engineering 30, 405-415. Azuara, E. & Beristain, C.I. (2006). Enthalpic and entropic mechanisms related to water sorption of yogurt. Drying Technology, 24, 1501-1507. Bathia, S.K., Liu, F. & Arvind, G. (2000). Effect of pore blockage on adsorption isotherms and dynamics: anomalous adsorption of iodine on activated carbon. Langmuir, 16, 4001-4008.


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[14] Mannheim, C.H., Liu, J.X. & Gilbert, S.G. (1994). Control of water in foods during storage. Journal of Food Engineering 22, 509-532. [15] Johnston, K.A. & Duckworth, R.B. (1985). The influence of soluble components on water sorption hysteresis. In D. Simatos and J.L. Multon (Eds.), Properties of water in food (pp. 65-82). Dordrecht, Netherlands: Martinus Nijhoff Publishers. [16] Beristain, C.I., Azuara, E. & Vernon-Carter, E.J. (2002). Thermodynamic analysis of the sorption process of mesquite gum. Chemical Engineering Communications, 189, 115-123. [17] Van den Berg, C. (1986). Water activity. In Concentration and Drying of Foods, ed. D. Mac Carthy, 11-36. London: Elsevier. [18] Slade L. & Levine, H. (1991). Beyond water activity: recent advances based on an alternative approach to the assessment of food quality and safety. Critical Reviews in Food Science and Nutrition 30, 115-360. [19] Peleg, M. (1997). A dissenting view on glass transition summary. Food Technology 51, 30-31. [20] Ma, Y., Reineccius, G.A., Labuza, T.P. & Nelson, K.A. (1992). The stability of spraydried microcapsules as a function of glass transition temperature [Abstract]: In : IFT Annual Meeting Book of Abstracts; 1992 June 20-24; New Orleans, La. Chicago, Institute of Food Technologists, p 217, Abstract nr 858. [21] Bell, N.L. & Hageman, M.J. (1994). Differentiating the effects of water activity and glass tran sition dependent mobility on a solid-state chemical reaction: aspartame degradation. Journal of Agricultural and Food Chemistry, 42, 2398-2401. [22] Chirife, J. & Buera M.P. (1994). Water activity, glass transition and microbial stability in concentrated/semimoist food systems. Journal of Food Science 59, 923-926. [23] Lum, K., Chandler, D. & Weeks, J.D. (1999). Hidrophobicity at small and large length scales. Journal of Physical Chemistry B 103, 4570-4577. [24] Chandler, D. (2002). Two faces of water. Nature 417: 491. [25] Sansom, M.S.P. & Biggin, P.C. (2001). Water at the nanoscale. Nature 414, 156-159. [26] Bizot, H. (1983). Using the G.A.B. model to constructing sorption isotherms. In Physical Properties of Foods, ed. R. Jowitt, F. Escher, B. Hallstrom, H.F.Th. Meffert, W.E.L. Spiess and G. Vos, 43-54. New York: Applied Sciences Publishers. [27] Rockland, L.B. (1969). Water activity and storage stability. Food Technology 23,12411248. [28] Iglesias, H.A., Chirife, J. & Viollaz, P. (1976). Thermodynamics of water vapor sorption by sugar beet root. Journal of Food Technology 11,91-101. [29] Hill, T.L., Emmett, T.L. & Joyner, L.G. (1951). Calculation of thermodynamic functions of adsorbed molecules from adsorption isotherm measurements: Nitrogen on graphon. Journal of the American Chemical Society 73, 5102-5107. [30] Othmer, D.F. (1940). Correlating vapor pressure and latent heat data. A new plot. Industrial and Engineering Chemistry 32, 841-856. [31] Aguerre, R.J., Suarez, C. & Viollaz, P.E. (1986). Enthalpy-entropy compensation in sorption phenomena: Application to the prediction of the effect of temperature on food isotherms. Journal of Food Science, 51, 1547-1549.

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[32] Wexler, A. (1976). Vapor pressure formulation for water in range 0 to 100oC. A Revision. Journal of Research of the National Bureau of Standards. A. Physics and Chemistry 80, 775-785. [33] Sonwane, C.G. & Bhatia, K. (2000). Characterization of pore size distributions of mesoporous materials from adsorption isotherms. Journal of Physical Chemistry B 104, 9099-9110. [34] Fletcher, A.J. & Thomas, K.M. (2000). Compensation effect for the kinetics of adsorption/desorption of gases/vapors on microporous carbon materials. Langmuir 16, 6253-6266. [35] Krug, R.R., Hunter, W.G. & Grieger, R.A. (1976). Enthalpy-entropy compensation. 2Separation of the chemical from the statistical effect. Journal of Physical Chemistry 80, 2341-2351. [36] Ferro-Fontan, C., Chirife, J., Sancho, E. & Iglesias, H.A. (1982). Análisis of a model for water sorption phenomena in foods. Journal of Food Science, 47, 1590-1594. [37] Leffler, J.E. (1955). The enthalpy-entropy relationship and its implications for organic chemistry. Journal of Organic Chemistry 20, 1202-1231.



Chapter 8

DEVELOPMENT OF VACUUM SPRAY DRYING SYSTEM FOR PROBIOTICS POWDER Yutaka Kitamura and Yukari Yanase* Graduate School of Life and Environmental Sciences, University of Tsukuba, Ibaraki, Japan

1.1. INTRODUCTION In recent years, health consciousness has grown in relation to health hazards associated with lifestyle and living environment, and various types of functional foods are attracting attention (Matsuda, 2002; Bureau of Citizens, Culture and Sports, Tokyo Metropolitan Government, 2005; Sashihara et al., 2005). In addition, the functionality of food is currently an important added value for the food industry, and the development and applications of functional foods are being actively advanced. Among various functional foods, probiotics is one of the materials that have attracted considerable attention (Sashihara et al., 2005). Probiotics are living microbes that exert healthful effects on the living body, lactic acid bacteria being a typical example. The wide-ranging health effects of various types of bacteria have been reported, as shown in Table 1.1. Further, epidemiological studies on probiotics for disease prevention and scientific study and commercial development involving useful lactic acid bacteria are being pursued (Watanabe et al., 2005). Probiotic foods are able to ameliorate the effects of environmental factors, and are useful in disease prevention; establishing the safety of probiotics is easy as compared to doing so for medical chemicals, because the bacterial cells of probiotics have long been used for storing and improving the flavor of food. Therefore, various probiotic foods are being researched, developed, and produced. These will be indispensable functional ingredients in the future food industry in Japan, where health consciousness is increasing. Drying is an important operation to increase the added value, such as the storability, transportability, and convenience, of food containing functional ingredients. First, one purpose of drying food, including functional food, is to ensure that the food is of a quality that * Present: Nisshin Flour Milling Inc., 25, Kanda-Nishiki-cho 1-chome, Chiyoda-ku, Tokyo 101-8441, Japan

172

Yutaka Kitamura and Yukari Yanase

satisfies consumer requirements. The other benefits are food storage stability, wide-area transportability, safety, and sanitization. Drying also results in convenience in terms of the place of consumption and distribution, along with giving products commercial value and having positive sales effects (Kimura et al., 1993). Furthermore, in order to give added value to target food, it is also important to be able to retain functionality during drying and subsequently, retain the effectiveness and functionality of the food for a long time. Therefore, the importance of processing functional components of food highly efficiently will surely increase (Sawaoka, 1997). It is an important challenge for the future food industry to overcome existing problems related to drying technology and equipment in dealing with a wide variety of functional foods for drying. Table 1.1. Health effects of probiotics (excerpt from Sashihara et al., 2005) Effect Improvement of constipation or diarrhea Prevention for infection (Investment of immunity) Prevention and improvement of allergy Reduction of stress Bowel disease Enhancement of infant growth Improvement of fat metabolism Inhibition of cavity formation Aniti-virus

Probiotics L. rhamnosus 19070-2, L. reuteri DSM 12246 B. lactis HN019 L. rhamnosus GG L. casei DN-114001 B. breve, B.bifidum, L.acidphilus YIT 0168 B. bifidum Bb 12 L. acidophilus 145, B. longum 913 L. rhamnosus GG L. gasseri OLL2716

L,: Lactobacillus , B,: Bifidobacterium

1.2. CURRENT SITUATION AND CHALLENGES OF SPRAY-DRYING AND FREEZE-DRYING METHODS Spray drying is very important in the food industry because it is essentially suited to the powderization of liquid food containing thermosensitive ingredients. Spray drying is a method used to obtain dry powder by allowing hot air to directly make contact with small droplets in a drying tower and vaporize water instantly (Okawara, 1993a; Matsuno et al., 1991a;; Figure 1.1). Spray drying can process liquid raw materials quickly and continually, and is characterized by excellent drying and cost efficiencies. It is widely used for the production of products such as powdered milk, powdered seasonings, powdered spices, and starch (Tsujimoto, 2003). It is considered that spray droplets come into contact with hightemperature hot air in the early phase of drying, and that the dry particle temperature lowers as the hot air temperature decreases through the drying process. Clearly, the drying time of droplets is strongly influenced by how the sprayed droplets are heated in the hot air in the drying tower. There may be undesirable changes, that is, the degradation or the loss of thermosensitive ingredients, such as the depletion of volatile (fragrant) ingredients, denaturation of protein, and oxidation of lipids (Yamamoto, 2003; Matsuno et al., 1991a). It is considered that the heat denaturation of thermosensitive ingredients occurs due to the high temperature of the dry air used in spray drying. The spray droplet is instantly dried near the nozzle, and is exposed to a high exit temperature; therefore, the target ingredient decreases

Development of Vacuum Spray Drying System for Probiotics Powder

173

before it is collected by the cyclone. If the exit temperature is high, the powder collection rate increases; however, the target ingredient decreases significantly. Therefore, it is important to set an optimized exit temperature that can retain the activity of target ingredients (Yoshii et al., 2007). Feed Blower

Air filter Heater

Spray nozzle

Cyclone

Drying tower Air filter

Micro powder

Heater

Product Vibrating cooler Air filter

Cooler

Figure 1.1. Schematic of spray dryer (excerpt from Matsuno et al., 1991a)

With regard to powdering thermosensitive ingredients using spray drying, mixing them with various glucide compounds, gum, protein, modified starch, or synthetic polymers is a useful way of retaining target ingredients. For example, hydrophobic flavor or liquid lipids are converted into an O/W emulsion using an emulsifier such as Arabian gum, modified starch, or milk protein and then mixed with an excipient such as maltodextrin, before being spray dried (Furuta et al., 2005). For the nonvolatilization of volatile ingredients, we spray dry a liquid mixture in which a clathrate compound is formed with cyclodextrin, which has large intermolecular spacing, and takes in liposoluble materials in the hydrophobic molecules within molecules (Kitabatake et al., 2003). Further, Yoshii et al. (2007) conducted a study on maintaining enzyme stability until after spray drying by mixing in trehalose, which has a cluster structure resembling that of water. Watanabe et al. (2006) spray dried a mixture in a suspended form of nongelatinized starch and bifidus culture (to suppress gelatinization), and efficiently obtained bifidus powder with a good survival rate. Another measure has been to develop a spray nozzle as part of a spray dryer to suppress the loss of thermosensitive ingredients. This method uses a 4-fluid nozzle spray dryer that can spray micron-sized droplets (Mizuguchi et al., 2002). In this method, contact with dry air is more efficient because of the large surface area per unit weight of sprayed droplets. The time required for drying the droplets is less, the drying temperature can be set lower than that for existing dryers, and the loss of target ingredient (bifidus) is low. In fact, although spray

174


drying was achieved at lower temperatures in their study, a remarkable increase in the survival rate of bifidus was not demonstrated. Thermosensitive ingredients are also produced by freeze drying. Freeze-dried, highquality powders are produced using long and costly drying and equipment specifications, and the resulting products are considered to have high added value. In the freeze-drying method, various types of materials are frozen at a temperature lower than freezing point, and dried as is by sublimation (Matsuno et al., 1991b; Figure 1.2). Few physical and chemical changes are induced in the materials by this method, and the food experiences almost no material change due to heat, loss of flavor of ingredients, or enzyme deactivation. In addition, water is removed under the frozen condition, and the dried product becomes porous; therefore, the original quality can often be restored by simply adding water. However, the drying speed is very low because of the low drying temperature; usually, more than a day is required for drying the product. In addition, due to factors such as the cost of operation and equipment, the freeze-drying method is costly; in other words, the product price is high as compared to that of products produced using other drying methods (Matsuno et al., 1991b; Table 1.2).

Vacuum pump Condenser

Freezer

Drying Chamber Water tank

Heater Material plate

Figure 1.2. Schematic of freeze dryer (excerpt from Matsuno et al., 1991b)

Table 1.2. Cost comparison of spray drying and freeze drying (excerpt from Hayashi, 1992)

Initial cost (Yen/k-vapor) Energy cost (Yen/kg-vapor) Energy ratio (%) Drying cost ratio (-)

SD 26 38 59 1

FD 270 63 19 5.2

Although there have been many reports on various ways of treating raw materials or additives to retain thermosensitive ingredients, there have been few studies on improving spray-drying or freeze-drying techniques to retain thermosensitive ingredients effectively. It is necessary to develop processing techniques and equipment for the production of powdered liquid food containing thermosensitive ingredients efficiently and inexpensively.


175

1.3. PREVIOUS STUDIES ON FOOD USE OF LACTIC ACID BACTERIA In recent years, health consciousness has increased in relation to issues such as the prevention of lifestyle related diseases. A typical practice is the intake of various types of lactic acid bacteria with the function of probiotics. Among various types of useful fermented foods produced using various types of lactic acid bacteria (Figure 1.3; Table 1.3), yogurt is expected to exhibit effects such as the regulation of intestinal functions, relief from pollinosis symptoms, and cancer prevention. Yogurt is a popular health food, and many yogurt products are sold as such; in particular, some popular products are marketed as “food for specific health uses” (MyVoice Communications, 2005; Do House, 2005). milk

Inoculate with Lactococcus lactis and Lactococcus cremoris

Inoculate with Lactobacillus bulgaricus and Storeptococcus thermophilus

Inoculate with Lactococcus cremoris and Lactococcus lactis subsp. diacetylactis

Press curd to remove whey

Stir fruit or other flavoring into the coagulated milk

Stop fermentation by cooling to 5℃ (prevents coagulation)

Ripen (may involve salting)

Package (fresh cheese)

Package (yogurt)

Package (buttermilk)

Package (e.g., cheddar) Figute 1.3. Milk-fermented foods using lactic acid bacteria (quoted from Johnson-Green, 2002)

Lactic acid bacteria, including yogurt starters, are stored for long periods by methods such as sub-cultivation, freeze drying, or L-drying. In a subculture, bacteria are repeatedly transferred onto a new nutrient medium every two or three months in a refrigerator. The freeze-drying technique is adopted in many types of culture collection; while storage over 30 years is possible, this requires equipment such as a vacuum dryer and an ampoule filling and sealing machine. In the L-drying method, cells are not frozen and water is directly vaporized for drying; this technique is applied to microbes to which freeze drying cannot be applied without difficulty. In all of these methods, loss or denaturalization of the target material during storage should be avoided, and the material should be preserved for long periods and retain proper functions after drying (Yaeshima, 2002).

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Yutaka Kitamura and Yukari Yanase Table 1.3. Probiotics used in dairy products (quoted from Yaeshima, 2002)

Dairy product Species Fermented milk, Fermented milk beverage Streptococcus salivarius subsp. thermophilus Lactococcus lactis subsp. lactis Lactococcus lactis subsp. cremoris Leuconostoc mesenteroides subsp. cremoris Lactobacillus delbrueckii subsp. bulgaricus Lactobacillus helveticus Lactobacillus acidophilus Lactobacillus gasseri Lactobacillus johnsonii Lactobacillus casei Lactobacillus rhamnosus Lactobacillus reuteri Lactobacillus plantarum Bifidobacterium bifidum Bifidobacterium longum Bifidobacterium breve Bifidobacterium lactis Streptococcus salivarius subsp. thermophilus Cheese，Fermented butter Lactococcus lactis subsp. lactis Lactococcus lactis subsp. cremoris Leuconostoc mesenteroides subsp. mesenteroides Leuconostoc mesenteroides subsp. cremoris Lactobacillus delbrueckii subsp. delbrueckii Lactobacillus delbrueckii subsp. bulgaricus Lactobacillus delbrueckii subsp. lactis Lactobacillus helveticus Lactobacillus casei

As a thermosensitive biological material with food functionality ingredients, lactic acid bacteria are classified into mesophilic and thermophilic families depending on their optimum temperature. The powderization of a culture fluid of lactic acid bacteria using spray drying allows for high-efficiency, low-cost drying; however, many studies, pioneered by Rogers in 1914, reported low survival rates and the storage instability of lactic acid bacteria in drying (Teixeira et al., 1995; Table 1.4). For example, it has been reported that in the powderization of liquid containing lactic acid bacteria using spray drying, the number of living bacteria in the powder increases by lowering the exit temperature; however, when this technique is used, the water content in the powder is high (Johnson et al., 1995; Lian et al., 2002; Ananta et al., 2005). Furthermore, there have been many studies on drying media (drying substrates) and protective agents to shield the target lactic acid bacteria from heat (Table 1.4). In this approach, the sensitivity depends on the species or the strain of lactic acid bacteria, even if the drying temperature is low or a protective agent is added, and the loss of target lactic acid bacteria cannot be prevented (Conrad et al., 2000; Desmond et al., 2002).


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Table 1.4. Studies on the spray drying of probiotics (quated from (1) Johnson et al., 1995; (2) Kim et al., 1990; (3) To et al.; (4) Lian et al., 2002; (5) Ananta et al., 2005; (6) Gardiner et al., 2002; (7) Corcoran et al., 2004; (8) Desmond et al., 2002; (9) Fu et al., 1995; (10) To et al., 1997a) Probiotics

Diluent

L. helveticus CNRZ-32

[1]

19% maltodextrin solution

S. thermophilus[2]

*1

L. bulgaricus[2]

*1

L. cremoris D11[3]


S. thermophilus CH3TH[3]


L. pseudoplantarum UL137[3] 30% maltodextrin solution B. longum B6[4] B. infantis CCRC14633[4] L. rhamnosus GG ATCC53103[5]

10% gelatin 10% gum arabic 10% RSM 10% gelatin 10% gum arabic 10% RSM 20% RSM

L. paracasei[6] L. rhamnosus GG[7] L. rhamnosus E800[7] L. salivarius UCC500[7] L. paracasei NFBC338[8]

20% RSM 10% RSM / 10% polydextrose 10% RSM / 10% oligofructose 20% RSM 20% RSM 10% RSM / 10% polydextorose 20% RSM 10% RSM / 10% polydextorose 20% RSM 10% RSM / 10% polydextorose 20% RSM 10% RSM / 10% gum acacia

L. lactis C2[9] B. linens ATCC9174

30% RSM [10]

30% RSM

Inlet temp./Outlet temp. (℃) 220/82 220/120 150/*1 170/*1 *1/60 *1/90 150/*1 170/*1 *1/60 *1/90 220/65 220/90 220/65 220/90 220/65 220/90 100/60 100/60 100/60 100/60 100/60 100/60 *1/70 *1/100 *1/80 *1/80 *1/80 175/68 170/85-90 170/85-90 170/85-90 170/85-90 170/85-90 170/85-90 170/95-100 170/100-105 170/95-100 170/100-105 220/77 220/120 220/70* 220/90* 220/60** 220/90**

Survival ratio (%) 0.08 15 3 1.8 0.01 3 1.6 0.6 0.0003 1 3 0.3 30 5 15 0.5 8.2 23 63 0.01 0.06 1.64 70 5 65 55 65 84.5 50 31 25.4 41 0.7 0.12 1.7 0.01 1.4 0.9 4.3 0.2 20 1.5 80 5

RSM: Reconstituted skim milk, *1: not described, *; 4.5 L glass chamber, **; 12.5 L glass chamber

Because the freeze-drying of lactic acid bacteria is a gentler process than spray drying, a high percentage of lactic acid bacteria are retained in the form of freeze-dried powder, depending on the species or strain of the bacteria and the type of protective agent added (Champagne et al., 1996). However, it has been reported that the damage to lactic acid

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bacteria that occurs through freezing or drying can be further suppressed through various techniques such as rapid freezing at the first stage of freeze drying and a smaller size of bacteria (Meng et al., 2008). Although both spray drying and freeze drying are established methods for producing lactic acid bacteria powder, such processes may subject live bacteria to considerable great stress because of the use of high or low temperatures, exposure to oxygen, and osmotic pressure. It is necessary to control conditions such as the drying of the culture fluid, protective agent, and humidity in order to ease such stress (Meng et al., 2008); however, a quality powder retaining lactic acid bacteria could be produced if a good drying process that will minimize the stress on living bacteria is developed, as discussed below.

1.4. VACUUM SPRAY DRYING (VSD) In this study, a vacuum spray-drying (VSD) technique is proposed to powderize liquid food containing thermosensitive ingredients. In VSD, evaporated water is removed while the drying tower is decompressed using a vacuum pump with a cold trap. The drying temperature is controlled by a far-infrared heater and a heating system with an outside jacket. The raw materials are sprayed from a two-fluid nozzle at the top of the drying tower and powdered in the drying tower. The details of VSD are discussed in Chapter 2.

Solution 溶液

噴霧乾燥経路 Drying pathway in SD VSDpathway 経路

溶解曲線 curve Dissolution

Temp. (℃) 凍結乾燥経路 Drying pathway in FD

0

Drying food

Rubber area

Freezing curve

Glassガラス転移曲線 transition cutve

Water 100%

Glass ガラス Solute 100%

Water＋Solute (%) Figure 1 4. Model food state diagram (based on Takai, 2000)


179

In decompressing the drying tower, the VSD method realizes drying at relatively low temperatures (40–60°C) as compared to existing methods (Figure 1.4). It is expected that the loss (or extinction) of thermosensitive ingredients will be smaller than in the existing spraydrying method, and the technique can provide efficient and inexpensive drying as compared to even freeze drying. Honda (2005) and Kitamura et al. (2006) stated that VSD is suited for powdering liquid food containing thermosensitive ingredients. They constructed a VSD system to powderize fermented milk; the analysis of the influence of temperature on the fermented milk powder showed that approximately 80% of the lactic acid bacteria were retained at a drying temperature of 35°C. However, they also mentioned problems such as too much inner-wall adhesion in the drying tower, low powder recovery rates, and high water content in the powder. Therefore, they have suggested that it will be necessary to improve the system. As a result, in this study, the relationships among the VSD conditions, recovery rate, and powder properties are examined in order to understand the physical phenomena governing these problems and to provide solutions for the same.

1.5. PURPOSE OF THIS STUDY In order to clarify the relationships among VSD conditions, the recovery rate, and powder properties, experiments are conducted to powderize liquid food and obtain basic data on the design and operation of a VSD system used to retain the functional food ingredients. First, using sugar-free condensed milk as a target material, the techniques used to construct a vacuum spray-drying system, and the influence of factors such as drying tower capacity, drying temperature, spray pressure, and spray liquid concentration, on the powder properties are examined. Furthermore, using sugar-free condensed milk containing lactic acid bacteria as a target material, a retention test for functional food ingredients was conducted to evaluate the applicability of VSD.

2. DEVELOPMENT OF A VACUUM SPRAY-DRYING TECHNIQUE 2.1. Construction of Vacuum Spray-Drying System In this study, a vacuum spray-drying (VSD) method is proposed as a drying technique that will suppress the damage or loss of thermosensitive functional ingredients such as biological materials, vitamins, and enzymes. Via the decompression of the drying tower (Figure 1.4), this method allows for drying at lower temperatures (40–60°C) as compared to existing spray-drying systems. Therefore, the loss of thermosensitive ingredients is smaller than in the spray-drying method, and an efficient and inexpensive drying system will be realized even in comparison with the freeze-drying method.

180


Figure 2.1. SD-10001)

A VSD system was constructed by improving the spray dryer used for research purposes (Tokyo Rikakikai, SD-1000). Figures 2.1 and 2.2 show a photograph and the schematics of the SD-1000. The equipment is a two-liquid nozzle spray dryer in which atomization is induced by causing both compressed air and the material to flow simultaneously. The operation panel, as shown in Figure 2.3, controls the flow rate of the supply fluid and the spray pressure.


181

Compressed air

Inlet

Exhaust

Outlet

1 2 3 4 5 6 7 8 9 10

Spraying air line valve (Solenoid valve) Three way solenoid Regulator Pressure sensor (Spraying air) Spray nozzle Feeding pressure sensor Feeding pump Magnetic stir Aspiration filter Air flow sensor

11 12 13 14 15 16 17 18 19 20

Heater Inlet temp. sensor Drying chamber Cleaning hatch Separator Outlet temp. sensor Cyclone Receiving bin Aspiration blower Exhaust filter

Figure 2.2. Flow sheet of SD-10002)

The system was modified as described below. Figures 2.4 and 2.5 show a photograph and the schematics of the constructed VSD system. The major modifications/improvements can be seen in the heating system and the decompression system.

182


Figure 2.3. Operation panel

Figure 2.4. External appearance of the VSD system. 1. Feeding material, 2. Stir with heater, 3. Degital monometer, 4.


183

Figure 2.5. Schematic of decompression spray drying equipment

2.1.1. Heating System In VSD, where spray drying is conducted at low temperatures under reduced pressure, water does not evaporate unless latent heat is supplied for evaporation, even if the temperature of this heat is low. However, if we use hot air, as in existing systems, the drying tower becomes an open system, and decompression becomes more difficult. We need a new system to supply heat in the drying tower using a method other than hot air. In this study, two heating methods are used together. One involves winding a vinyl tube around the drying tower wall; warm water flows through the tube and gently heats the drying tower. The other method involves placing a far-infrared heater inside the drying tower to heat the drying tower from the inside. The advantages of far-infrared heating are as follows (Amemiya et al., 1990): •

• •

The heating effect is greater in far-infrared heating than in indirect heating, where the air, the heat medium, is heated just as in the hot air method and then heat is conducted from the air to the target material. Heating through irradiation accelerates water evaporation, even in a vacuum. The energy level of the electromagnetic wave is too low to cause chemical action; heating does not cause a change in the properties of the target material. There is no power, as in ultraviolet rays, that can destroy DNA; thus, the method can safely deal with microbes.

184

Yutaka Kitamura and Yukari Yanase • •

• • •

Heating does not appreciably depend on the hue of the heated material, and the heating is stable under any hue conditions. Drying does not cause a loss in minor ingredients or flavor, nor does it cause brown discoloration, and burning finishes without an appreciable amount of water evaporation. The recovery rate is high. Further, many studies on far-infrared rays have shown that far-infrared drying influences food in various favorable ways (Shibukawa, 1990; Shimizu et al., 1986; Sugiyama et al., 1993; Yoshikawa et al., 1993). Heating is pollution-free, hygienic, and clean. The method does not create waste gas, soot, or a gas smell. Far-infrared heaters are long-lived, durable, and convenient to use. Hot-wind heating heats up everything. In contrast, far-infrared rays are linearly emitted, and heat is conducted only to a target directly facing the heat source.

The far-infrared heater supplies heat from the upper part of the drying tower (Figure 2.6), and the vinyl tube that circulates warm water for heating is installed to heat the central and lower parts of the drying tower, which are difficult for the heat from the far-infrared heater to reach (Figure 2.7). The temperature is measured inside the tower using thermocouples placed from the outside of the drying tower into the inside; thus, the temperature is measured at several positions (Figure 2.8). In addition, a temperature controller is situated so that the farinfrared heater is cut off if the measurement of the temperature sensor in the upper part exceeds a preset level.

Figure 2.6. Far-infrared heater on the upper part of drying tower


185

Figure 2.7. Warming system for VSD

Figure 2.8. Thermocouple arrangement for temperature measurement

2.1.2. Decompression System In the decompression system, an exhaust hose is connected to the lower part of the drying tower, and the inside of the tower is decompressed using an oil-sealed rotary vacuum pump (Ulvac Kiko, GLD-101). A cold trap (Tokyo Rikakikai, UT-1000) is installed between the pump and the drying tower to capture the evaporated water; an improved lid (with a nozzle attached), which is designed based on a lid dedicated to use with a cold trap, is employed in the experiment. A leak valve is installed between the cold trap and the pump; it is used to return the decreased pressure in the drying tower to atmospheric pressure (Figure 2.9). Pressure in the drying tower is measured using a digital manometer (SHIBATA, DM-10) connected to the upper part of the drying tower.

Figure 2.9. Decompression system for VSD

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2.1.3. System for Supplying and Spraying Liquid The raw material is preheated to 35–40°C using a heater stirrer, and the liquid is sent to the atomization system using a peristaltic pump. The surface area of the liquid is increased by atomization to such a degree that drying is instantaneous (Okada, 1984a). There are three types of atomization devices used for spray dryers: the rotary disk, pressure nozzle, and twofluid nozzle type; the former two are used more often for practical applications (Okada, 1984b). In this study, compressed air and supply liquid are sent through the nozzle simultaneously, and a two-fluid nozzle is used in which the shear force between liquid and air is used for spraying. In the two-fluid nozzle, steam collides at high speed with the liquid flow to tear up the liquid column for atomization, and small droplets of 10–65 µm3) are obtained even with a high-viscosity liquid (Matsuno et al., 1991a). 2.1.4. Drying and Separation System In the SD-1000 spray dryer, the standard drying tower is made of hard glass of φ 15 cm × 50 cm (height) in the cylinder portion and 5 cm in the conical portion. In the drying tower, thermocouples are installed to measure the inside temperature of the drying tower, as will be discussed below. A vinyl tube is wound around the drying tower to warm it, as discussed above. A cyclone separator can be installed in the drying tower. A cyclone separator is a dust collector that centrifuges dust from the dust-containing airflow (mixture of solid particles and gas) (Ogawa, 1980). A vinyl tube circulating warm water is also installed around the cyclone separator. 2.1.5. Temperature Measurement System Temperatures are measured at the upper, central, and lower parts of the drying tower, and at the upper and lower parts of the cyclone separator. Using model T thermocouples and a temperature measurement system (Handy Logger MR2041-MU, CHINO), the temperature is measured at the four positions shown in Figure 2.8 at the central and lower portions of the drying tower, and at the upper and lower parts of the cyclone separator. The positions are 40, 10, 30, and 3 cm from the lower part of the drying tower or cyclone separator. The temperature sensor on the upper part of the drying tower is connected to the temperature controller in the subsequent stage of far-infrared heating.

2.2. Operation of VSD System The VSD system is operated by the procedure shown in Figure 2.10 and 2.11: (1) First, the far-infrared heater and warm water circulator operate until the tower reaches a preset temperature. (2) The cold trap is used to cool the water condensation unit sufficiently, and (3) the vacuum pump utilized for decompression is operated until the internal pressure of the drying tower becomes stably low. (4) A beaker containing water is preheated to approximately 40°C with a heater stirrer. (5) The switches of the atomizer (for spray-pressure adjustment) and fluid flow are turned on to start spraying. (6) After confirming the spray at the nozzle, (7) the raw material, approximately 200 g in weight and preheated to approximately 40°C, is sent out. (8) After confirming that all raw materials left in the tube have been sent out for the spray, (9) the fluid flow, atomization, and far-infrared heating are


187

brought to a halt. (10) The vacuum pump is brought down, and the valve is thrown open to let the pressure in the drying tower rise back to the atmospheric pressure. (11) The cyclone separator and the drying tower are removed from the dryer, and the powder is collected using a silicon spatula (Figure 2.12). In this study, what is referred to as “powder” is only the material collected by sliding the spatula along the inner wall of the drying tower. (The solid body adhering to the inner wall of the drying tower cannot be removed with a spatula.)

Figure 2.10. VSD startup operation

Figure 2.11. VSD closing operation

188


Figure 2.12. Silicon spatula

3. CHARACTERIZATION OF POWDERIZATION BY VACUUM SPRAY DRYING 3.1. Introduction The purpose of this study is to powder liquid food under various drying conditions to examine the characteristics of powderization by vacuum spray drying (VSD). In particular, we discuss the design and the specifications of VSD and the influence of drying temperature, spray pressure, and spray liquid concentration on the physical and chemical properties and the recovery rate of the produced powder.

3.2. Materials and Techniques 3.2.1. Spray Liquid To clarify the characteristics of VSD, in this study, we use milk powder, which powderizes easily and has a long history as a dry powder food. Powdered milk products include whole milk powder, powdered skim milk, and baby milk powder. Milk, among other liquid food products, is relatively easy to powder. Sugar-free condensed milk (Evamilk, Snow Brand Milk Products) is chosen as a test material. Usually, condensation is used as a preprocessing step before powderizing liquid food; we use condensation in VSD, as discussed below. Sugar-free condensed milk having a concentration of approximately 26% is used in this study to reduce the condensation time. 3.2.2. Drying Tower Two types of drying towers are used. One is the standard spray dryer, and the other is the trial type. Here, the standard spray dryer is called drying tower A, and the trial type is called drying tower B. Table 3.1 shows the specifications of drying towers A and B. The cylinder portions of drying towers A and B are φ 15 cm × 50 cm (height) and φ 29 cm × 25 cm (height), respectively, and the conical section of drying tower B is 25 cm in height. Therefore, in drying tower B, the distance that a spray droplet covers from the nozzle to the inner wall of


189

the drying tower in the barrel portion is twice that of a spray droplet in drying tower A, and approximately 1.3 times the distance in the conical section (Figure 3.1). Therefore, a spray droplet can stay in drying tower B longer than in drying tower A. It is expected that dry powder can be collected without sticking to the inner wall in drying tower B, even under conditions where powderization is difficult in drying tower A. Table 3.1. Specifications of the two types of drying towers

Cylindrical part Conical part Volume Material Inner vacuumed pressure Inner vacuumed and sprayed pressure *

*

Tower A φ15 cm×hight50 cm 5 cm 9.6 L Hard glass 2～5 kPa

Tower B φ29 cm×hight25 cm 25 cm 25.2 L Hard glass

13～16 kPa

22 kPa

約6 kPa

：Feeding rate ca. 2 mL/min，Spray pressure 100 kPa

10 cm Figure 3.1. Projected spray pattern of drying towers A and B

190


On the other hand, the capacities of drying towers A and B are 9.6L and 25.2L, respectively. The capacity of drying tower B is 2.6 times greater than that of drying tower A, creating a difference in the level of decompression. In other words, drying towers A and B are maintained at 2–5 kPa and 6 kPa, respectively, if the tower is decompressed by a vacuum pump with a displacement of 100 L/min. Furthermore, 13–16 kPa and 22 kPa are maintained in drying towers A and B respectively, if the minimum flow rate of the spray liquid is used at a spray pressure 100 kPa. In the preliminary experiment, as shown above in relation to the VSD temperature, the tower’s internal pressure is greater in drying tower B, and the relationship[ between spray pressure and tower internal pressure is different between the two drying towers. Although the drying conditions may be different in the two drying towers depending on the tower’s internal pressure, we adopt the spray pressure as the primary experimental parameter.

3.3. Measurement and Analysis 3.3.1. Preparation and Measurement of Physical/Chemical Property of Spray Liquid

Figure 3.2. Experimental procedure

As shown in Figure 3.2, the procedure of this experiment is as follows: [1] Measurement of concentration of soluble solid content First, a sample of 2–3 g is placed in an aluminum can, heated at 105˚C in a drying machine for more than 3 h, and cooled in a desiccator; then, the weight of the residual solid content is measured. Assuming that the weight loss is due to water, the concentration of soluble solid content (w/w %) is calculated by:


C=

W × 100 W0

191 3-1,

where C is the concentration of soluble solid content (%); W, the mass (g) of the sample after drying; and W 0 , the mass (g) of the sample before drying. [2] Control of concentration of soluble solid content The concentration of the soluble solid content is controlled using a rotary vacuum evaporator (Tokyo Rikakikai, N-1000S) for decompression and condensation. The condensation conditions are a water bath temperature of 40°C and a coolant water temperature of 5°C. After condensation, the concentration of the soluble solid content is measured using the abovementioned method, and the concentration is controlled using pure water to realize solid contents of 30, 40, and 45% for the experiment. [3] Measurement of density

Figure 3.3. Pycnometer

The density of the sample is measured against the temperature using a Gay-Lussac pycnometer (Figure 3.3). First, the volume of the pycnometer is measured using pure water, and the density (g/cm3) is obtained from the mass of the liquid sample of the same volume as

ρ=

W − W0 × ρw W w − W0

3-2,

where ρ is the density (g/cm3) of the sample; W 0 , the mass (g) of the pycnometer container; W w , the mass (g) when the pycnometer is filled with pure water; W , the mass (g) when the pycnometer is filled with the sample; and ρ w , the density of pure water (g/cm3).

192

Yutaka Kitamura and Yukari Yanase [4] Measurement of viscosity

Using an Ubbelohde viscometer (SU-7811, SU-4133, Figure 3.4), a capillary tube viscometer, the temperature dependence of kinetic viscosity is measured, and the viscosity is calculated using the density value.

NM L

m1 m2

m3 m4

Figure 3.4. Ubbelohde viscometer

First, the sample is sent from pipe L up to the middle of the gauge lines m3 and m 4 (approximately 15mL), and dipped into the constant temperature water tank to set the temperature. Then, after pipe M is closed, the sample is pulled up across the gauge line m1 through pipe N. Pipe N is closed and pipe M is opened. If the sample begins to flow from the bottom end of the capillary tube, pipe N is opened to let the sample flow naturally. The time required for the sample to move from gauge line m1 to m 2 is called the efflux time. From the efflux time and the viscometer constant for the viscometer, the kinetic viscosity is calculated as

v = R × Ft

3-3,

where v is the kinetic viscosity (mm2/s); R, the viscometer constant(-); and Ft , the efflux time (s). Then, viscosity (mPa·s) is calculated from the derived kinetic viscosity and density, as measured above. The viscosity is calculated by


η = v× ρ

193 3-4,

where η is the viscosity (mPa·s); v, the kinetic viscosity (mm2/s); and ρ, the density (g/cm3).

3.3.2. Powderization Experiment By VSD In drying tower A, two drying temperatures (40 and 60°C), three spray pressure conditions (20, 60, and 100 kPa), and three spray liquid (sugar-free condensed milk) concentration conditions (30, 40, and 45%) are adopted, for a total of 18 conditions. In drying tower B, two drying temperatures (40 and 60°C), two spray pressure conditions (60 and 100 kPa), and three spray liquid (sugar-free condensed milk) concentration conditions (30, 40, and 45%) are adopted, for a total of 12 conditions (Table 3.2). In drying tower B, because the internal pressure of the drying tower is too great for drying large-size spray droplets, a powderization experiment at a spray pressure of 20 kPa has not been conducted; it has been assumed that it would be too difficult to obtain a meaningful recovery rate. Table 3.2. Experimental conditions Drying temp. (℃)

Spray pressure (kPa) 20* 60

40

100

20* 60

60 100

Solution Concn. (%) 30* 40* 45* 30 40 45 30 40 45 30* 40* 45* 30 40 45 30 40 45

＊：Only in tower A

The spray liquid (sugar-free condensed milk) is powderized following the VSD operation method described in Chapter 2.

3.3.3. Evaluation Techniques Of Powder Products [1] Measurement of moisture content Powder (2–3 g) is placed in an aluminum can and heated at 105°C in a drying machine for more than 3 h; the weight of the sample measured after drying is divided by that before drying, and the water content is given as

194


Wc =

Wb × 100 Wa

3-5,

where Wc is the moisture content of the powder (%); Wb, the weight (g) of the powder before drying; and Wa, the weight (g) of the powder after drying. [2] Calculation of recovery rate The recovery rate is the ratio of powder collected from the drying tower using a spatula when the spray liquid is powderized to the amount of spray liquid. The recovery rate is obtained from the solid content of the powder product and that of the spray liquid, excluding the water content, and is given by

Y=

Ps ×100 Fs

3-6,

where Y is the recovery rate (%); Ps, the solid powder content (g); and Fs, the solid content of the spray liquid (g). [3] Measurement of size distribution The size and weight basis distributions are obtained by screening using a set of ready-toassemble sieves with polypropylene frames, caps, and saucers and a phosphor bronze mesh. Eight types of mesh are adopted: 25, 35, 45, 60, 80, 120, 170, and 230 mesh/inch. The mesh opening is 710, 500, 355, 250, 180, 125, 90, and 63 µm, respectively, in conformity with the Japanese Industrial Standards. First, a sample (approximately 5 g) is thrown onto the uppermost sieve, and sieved by vibration and tapping. Then, the weight of the content of each sieve is measured to obtain the cumulative undersize distribution. By plotting the values against the particle size on the x-axis and the cumulative weight percent on the y-axis, a double-logarithmic Rosin-Rammler distribution is obtained. The Rosin-Rammler distribution is a distribution function expressed by Eq. (3-7), and the cumulative undersize distribution should give a straight line on the Rosin-Rammler plot. In order to compare the particle size of the prepared powder, the size D50, which gives a 50% cumulative distribution, is defined as the typical particle size (Arai et al., 1976; Hirota, 2006). n ⎪⎧ ⎛ x ⎞ ⎪⎫ Q( x) = exp⎨− ⎜ ⎟ ⎬ ⎪⎩ ⎝ x e ⎠ ⎪⎭

3-7.

Here, Q(x) is the cumulative weight percent (-); x, the particle size (µm); xe, the characteristic coefficient of granularity (-); and n, the shape parameter (-).


195

Figure 3.5. Sieve

[4] Measurement of water activity Water activity is closely related to the storage stability of food. As shown in Table 3.3, water takes two forms in food: bound water and free water. Bound water directly combines with a hydrocolloid such as protein and stabilizes the colloid; free water is the remaining water that is not in a bound form and is relatively close to pure water in terms of its characteristics. Because the water content of a material depends on the environment, the water content of food is expressed by water activity, Aw, which is based on a concept similar to that of relative humidity (Eq. 3-8; Murao et al., 2003; Nagashima, 1983). This is given by

Aw =

P Rh = . P0 100

3-8.

Here, AW is the water activity (-); P, the water vapor pressure of the material in an airtight container (Pa); P0, the maximum vapor pressure of water at the temperature (Pa); and Rh, the equilibrium relative humidity (%) in the container.

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Table 3.3. Degree of water bonding in food and living bodies (based on Kumagai et al., 2005a; Nagashima, 1983) Type of water combination Condition of water Capillary condensation area (Fully Pure water active) Physically captured water among membranes, Capillary condensation area (Slightly lower activity) capillaries (φ1 μm)；close to ideal solution Molecular multi layers absorption Directly hydrated water in solute，multiarea (Low activity and strong layered hydrated water near to solute, water in binding energy） capillary (φ1 μm)；far from ideal condition Molecular single layer absorption Chemically hydrated water,water hydrated to area (Lower activity and stronger ，hydrated water strongly bound to dipole ion binding energy）

Water activity 0.28-0.55 for breakfast cereals (Peleg, 1994; Labuza & Hyman, 1998), with resulting rejection by consumers (Nielsen, 1979). For this reason, a way to maintain good quality in a cereal-raisin system is to reduce the water activity of raisins. The problem is that the raisin texture, one of most important factors governing their quality (Lewicki & Spiess, 1995), becomes unacceptably hard when their water activity decreases below 0.40 (Lewicki & Wolf, 1995). In this sense, it is desirable to reduce the water activity of the raisins while, as much as possible, maintaining their mechanical properties at the same time. Infusion is an approach method for reducing the water activity of raisins while maintaining an acceptable soft texture. Infusion resembles a process known as osmotic dehydration. Osmotic dehydration removes substantial amounts of water from a product while adding minimal solids. As an alternative to only removing water, infusion maximizes the osmotic movement, in both directions, so solutes move into the food. This yields a different set of characteristics in the finished product. Infusion takes advantage of the existent concept that within a multi-phase food system, both solutes and water, seek equilibrium. The use of an applied vacuum is recommended to shorten the time needed to reach equilibrium (Iglesias & Chirife, 1976). Vacuum impregnation (VI) consists of exchanging the internal gas or liquid occluded in open pores for an external liquid phase, due to the action of hydrodynamic mechanisms promoted by pressure changes (Fito,1994; Fito & Pastor, 1994).The operation is carried out in two subsequent steps after the product immersion has taken place inside the tank containing the liquid phase. In the first step, vacuum pressure must be imposed for a short time (for this specific research analysis, the pressure applied was 80 mbar during 15 minutes) in the closed tank, thus promoting the expansion and outflow of the product’s internal gas. The process of releasing this internal gas transfers the innate liquids out from the pores of the product along with this corresponding gas emission. In the second step, atmospheric pressure must then be restored inside the tank for the predisposed period of time determined, in turn having effects resulting in compression, which leads to a great volume reduction of the remaining gas in the pores and consequently in the subsequent inflow of the external liquid in the porous structure (Fito, Chiralt, Barat, Andres, Martinez-Monzo & Martinez-Navarrete, 2001). When the water activity and solute concentrations between the food and infusing mixture reach equilibrium, both water and solute migration stop. By using infusion, water can be encouraged to migrate out of a piece of food while at the same time allocating space for it to be replaced by solutes, these usually being some type of soluble carbohydrate or carbohydrate derivative. Smaller molecules are used for infusion, since higher molecular weight compounds migrate into the product more slowly and at lower levels, increasing the tendency toward osmotic dehydration rather than infusion. Among the different solutes used in infusion, some control water activity better than others. Humectants ingredients; such as, sugar alcohols, glycerol, propylene glycol, and similar ingredients, have a marked effect on water activity and can change the product texture. Altering the types of solutes and their ratios can create a product that is very plastic, or rubbery, or with alternative variables, something that is more firm or soft.

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Pau Talens and María José Fabra

The main interest in edible films and coatings is generally based on their potential to control moisture, oxygen, carbon dioxide, lipid, flavor and/or aroma transfer; either between food components or to/from the atmosphere surrounding the food, all desired controlled properties resulting in an increase of quality and in shelf-life. The film-coating composition is chosen as a function of the desired application of the edible film selected for the food in mind; for example, when the purpose is to control the moisture balance within a heterogeneous food, as raisin-cereal systems, hydrophobic materials are required to make a film with good water barrier properties. The aim of this work was to apply a solute infusion to reduce the water activity of raisins, while maintaining their softness. Accomplishing this would contribute to obtaining a cerealraisin system with better sensory characteristics, by reducing the driving force for moisture migration from the raisins to cereal flakes. On the other hand, in order to try to reduce the moisture transfer between components, the raisins were coated by directly applying starch and beeswax to them or by using different film forming emulsions made with whey protein, beeswax and glycerol at different protein:lipid:plasticizer ratios.

MATERIALS AND METHODS Materials Sun-Maid® Natural California Raisins were used as raw material for the experiments. Glycerol, C3H803 (Panreac Quimica, S.A., Castellar Del Vallés, Barcelona, Spain) was used as infusion agent. Whey protein isolate (Llorella S. A., Barcelona, Spain), beeswax (Brillocera S. A., Valencia, Spain), Glycerol and Starch (Roquette Laisa, S.A., Valencia, Spain) were used for the preparation of the coating forming solutions. Magnesium Nitrate Mg(NO3)2.6H2O (Panreac Quimica, SA, Castellar del Vallés, Barcelona), Potassium Carbonate K2CO32H2O (Panreac Quimica, SA, Castellar del Vallés, Barcelona) and Potassium Acetate CH3COOK (Panreac Quimica, SA, Castellar del Vallés, Barcelona) were used to create a saturated salt solutions to keep chambers for pre-conditioning samples at 50%, 40% and 20% Relative Humidity, respectively.

Infusion Treatment of Raisin Samples Infusion treatment was carried out at 25 ºC in a glycerol solution made with 5 parts of glycerol to 1 part of water. The infusion solution:sample weight ratio was high enough (10:1) to avoid any significant change in the infusion solution concentration. Prior the infusion the raisin samples were pre-conditioned by adjusting their water activity to a starting desired level of 0.5. The conditioning took place in a closed chamber over saturated Magnesium Nitrate salt solutions (Spiess & Wolf, 1983). The pre-conditioned raisins, with aw = 0.500 ± 0.006 at 25º C, were immersed in the glycerol solution with a aw = 0.402 ± 0.001 at 25 º C. A vacuum pressure of 80 mbar was applied for the first 15 minutes of treatment. Afterwards, atmospheric pressure was restored; and after different times of treatment (15 minutes and 1, 2, 4, 6, 8, 24, 48 and 72 hours), the raisins were withdrawn from the solution. To perform the experiments, 2 batches of raisins were used for each condition. Weight changes, water activity values, and mechanical properties were analyzed at each time variable in triplicate.

Application of Vacuum Impregnation and Edible Films…

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The weight changes were determined using a using an analytical balance (± 0.001 g). Water activity (aw) was measured using a dew point hygrometer (Decagon®, model Aqualab CX2, Decagon Devices, Inc., Pullman, Wash., U.S.A.). Mechanical properties of fresh and impregnated samples were analyzed through a penetration test (strain rate 2.5 m/s) by using a universal test machine (TA.XT2 Texture Analyser, Stable Micro Systems, Haslemere, England). Each measurement was carried out for 6 samples at 25 ºC. The force(F)-distance(d) curves obtained from the penetration test were transformed into force(F)-relative deformation(ε) curves (Dobraszczyk & Vincent, 1999).

Preparation of Coating Forming Solutions Coating forming solutions with different whey protein isolate (WPI): beeswax (BW): glycerol (Gly) ratios (1:1:1; 1.5:1.5:1; 2:2:1, 2.5:2.5:1, and 3:3:1) were prepared according to the method described previously by Talens & Krochta (2005). An aqueous solution of 10% (w/w) WPI were prepared and heated in a 250-mL Erlenmeyer flask for 30 min in a 90 °C water bath to denature the protein. The amount of BW required was melted in the hot denatured protein solution, and each solution was homogenized with a high-shear probe mixer (Ultraturax T25, Janke & Kunkel, Germany) for 1 min at 15000 rpm, followed by 3 min at 22000 rpm. The temperature of homogenization was 90 °C. The emulsions were then placed in an ice bath for cooling. Gly was added in the amount required to get the desired final film composition, and the film-forming solutions were degassed at room temperature with a vacuum pump. Coating of Raisins Samples The raisins were coated by directly applying starch and beeswax to them or by using the different coating forming solutions described previously. 140 raisins were used for the experiment: 70 fresh raisins and 70 raisins submitted to an infusion treatment during 4h. Before coating the samples, the fresh and the infused raisins were pre-conditioned by adjusting their water activity to a starting desired level of 0.5 and 0.4, respectively. The conditioning took place in closed chambers over saturated Magnesium Nitrate and Potassium Carbonate salt solutions (Spiess & Wolf, 1983). When the samples were conditioned, 10 samples of fresh raisins and 10 samples of infused raisins were used as control specimens (uncoated samples), 10 samples of fresh raisins and 10 samples of infused raisins were coated with starch and were dipped in melted BW for 2 minutes, and 50 samples of fresh raisins and 50 samples of infused raisins were dipped in five different coating forming solutions (1:1:1; 1.5:1.5:1; 2:2:1, 2.5:2.5:1, and 3:3:1 WPI:BW:GLY) for 2 minutes. The applied coatings were dried by natural convection at room temperature and all the samples were stored again in the closed chambers to make sure that the water activity values of the raisins were 0.5 and 0.4, respectively. Half of the coated and uncoated raisins were transferred to a cabinet with 20% relative humidity supported by a Potassium Acetate-saturated solution and homogenized constantly by fan (CPU COOLER. Y.S. TECHs). Before being placed in the same cabinets, the other half of the coated and uncoated raisins were placed in a gyratory drum spinning at controlled rotations, this was done with the objective of providing the test material with conditions similar to the shocks, accidents and possible damage suffered by raisins inside the cereal packaging in which they are prepared for the consumer and in which they are transported during their whole logistic chain of storage and distribution. After different time

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intervals were set and checked (24, 48, 72, 96, 372, 554 y 734 hours), the raisins were withdrawn from the cabinet and were weighed. Figure 1 shows a scheme of the experiment procedure for the reduction of moisture transfer.

Figure 1. Scheme of the experiment procedure for the reduction of moisture transfer.

Changes in total mass were calculated by applying the equation 1, where mt and m0 indicates the sample weight at time t and 0, respectively.

ΔM =

m t − m0 m0

(1)

Statistical Analysis Statistical analysis of data was performed through analysis of variance (ANOVA) using Statgraphics Plus for Windows 5.1 (Manugistics Corp., Rockville, MD).

Applicationn of Vacuum Impregnation I n and Edible Films… F

239

RESULTS AND A DISCU USSION In nfusion Treeatment Study. Figure 2 shhows the channges of weightt for raisins suubmitted to thee infusion treaatment. The raaisins gain weeight at each tiime interval, indicating i thatt the samples gain glycerol faster than loose water. Thaat means thatt glycerol is a better infusiion agent thann an osmotic agent. The w water activity of o raisins withh glycerol-wateer infusion solution, were monitored m throoughout the 1,, 2, 4, 6, 8, 24, 2 48 and 722 hour intervaals of the expperiment. The average valuues, for the raaisins used in the experimennts, are plotteed in Figure 3. The line inddicates the waater activity vaalues for the infusion solutiion. Figure 3 illustrates i the development of aw within the samples annd their corressponding valuues of glycerol-water infusion solution. The T same valuue for both, raaisin sample and a infusion solution, s weree reached verry quickly at about 1 h off treatment. A After that, the water activityy of the raisinns was constannt at each tim me interval. Thhese results inndicate that thhe infusion soolution:samplee weight ratio was enough to avoid any significant chhange in the infusion soluution concentrration and that the vacuum m impregnatioon process faavors the gain of glycerol diiminishing thee water activityy of the raisins.

Fiigure 2. Percenttage of weight gain g for raisins after infusion trreatment.

In order to o determine thhe effect of the t glycerol innfusion on thhe texture of raisins, r the mechanical pro m operties of frresh and infuused raisins were w measureed. Figure 4 shows the chharacteristic penetration p currves of untreaated raisins andd the characteeristic penetrattion curves off infused raisinns, having waater activities of o 0.500 ± 0.0006 and 0.402 ± 0.001, respeectively. In thhese curves, th he first peak shows s the skinn rupture poinnt and the seccond peak reppresents the m moment that the t raisin is fully penetraated. Betweenn these peakss, the curve shows the peenetration of the t internal raaisin flesh. The mechanical parameters annalyzed were: the failure foorce at the firsst peak (forcee values at thee skin rupture,, Fskin); the faiilure force at the second peeak (F2Peak); thhe force valuee required to penetrate p the raisin r (Fflesh); the relative deformation d inn the first peaak (ε); the areea until the second peak iss reached (A)); and the ratiio of force

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Pau Talens and a María Jossé Fabra

reequired to peenetrate the flesh f and thee force reachhed at the moment m of skkin rupture (((Fflesh/Fskin). Taable I shows thhe values of all a these param meters for freshh and infused raisins. An annalysis of variiance (ANOV VA) for these studied s valuess, at each timee interval, shoows that no siignificant diffe ferences were observed betw ween the failuure force at thee first peak moment m and att the second peak p momentt, and neither were any siggnificant diffeerences observved for the reelative deform mation values at a their first peeak moment. These T results indicate i that thhe infusion trreatment does not affect the skin of the raisin. A decreaase in the Ffleshh, A and Fflesh/F Fskin values w observed during was d the infuusion treatmennt. This decrease is more efffective at thee beginning off the process.

Fiigure 3. Changees in the water activity a of raisinns during the innfusion treatmennt. The illustrateed line inndicates the watter activity valuues for the infusiion solution.

Fiigure 4. Characteristic penetrattion curve for fresh fr and infusedd raisins.


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Table 1. Mea an values and d standard deeviation of meechanical parrameters anallyzed for fresh an nd infused raiisins Fskkin (N)

F2Peak (N) 2

ε

Ffleesh (N)

Fflesh / Fskin f

A (J) Area

Frresh

4.22 (0.8)a

2.6 (0.6)a

0..6 (0.2)a

1.88 (0.1)a

500 (7)a

12.7 (1.0)a

IV V

4.66 (1.1)a

2.8 (0.9)a

0..6 (0.1)a

1.88 (0.2)a

433 (8)a

12.6 (1.4)a

1hh

4.66 (1.0)a

2.0 (0.6)a

0..6 (0.1)a

1.77 (0.2)ab

399 (5)ab

11 (2)ab

2hh

4.55 (0.7)a

2.44 (0.7)a

0..6 (0.2)a

1.66 (0.2)ab

366 (4)b

11 (2)ab

4hh

4.44 (0.8)a

2.3 (1.0)a

0..6 (0.1)a

1.55 (0.3)bc

344 (5)bc

10 (2)ab

6hh

4.22 (0.5)a

2.3 (0.8)a

0..6 (0.1)a

1.33 (0.3)bc

322 (5)bc

9.8 (0.7)b

8hh

4.11 (0.7)a

1.7 (0.6)a

0..6 (0.1)a

1.33 (0.2)c

311 (4)c

9.8 (1.0)b

244h

4.22 (0.7)a

1.9 (0.5)a

0..7 (0.1)a

1.33 (0.2)c

311 (3)c

10 (2)b

488h

4.22 (0.5)a

2.1 (1.0)a

0..6 (0.1)a

1.33 (0.1)c

322 (3)c

9.9 (1.2)b

722h

4.22 (0.4)a

2.5 (1.5)a

0..6 (0.1)a

1.33 (0.2)c

300 (5)c

10.3 (1.2)b

a–cc

Different supeerscripts within a column indiccate significant differences d amoong samples (p < 0.05).

Figure 5 shows s the meean force valuues at the skkin rupture pooint for untreeated raisin saamples compaared to infusion-treated raiisin samples at a each infusiion time. No significant diifferences amo ong all samplees were observved.

Fiigure 5. Force values v in the skiin rupture pointt for untreated and a treated sampples throughoutt time inntervals measureed.

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In order to determine if the t glycerol innfusion affecteed the internall raisin flesh, the ratio of foorce required to t penetrate thhe flesh (Ffleshh) was dividedd by the force in the skin (F Fskin). High vaalues for this parameter woould mean thaat the raisin flesh f became tough, t while low values w would mean th hat the raisinn became sofft. Figure 6 shows s the rattio Fflesh/Fskin values for unntreated and treated t raisins. Two groups of samples can c be observeed. The untreaated raisins (sshown as “Fresh”) and the innfused raisinss under observvation for up too four hours of o treatment (sshown as barss VI, 1h, 2h and 4h) dennote one of thhese groups; and, the infuused raisins obbserved until the end of thee study denotees the other group g (shown as bars 6h, 8hh, 24h, 48h annd 72h). Untreated raisins show s the highhest Fflesh/Fskinn values, whichh decrease proogressively w when the glyceerol solution is i infused intoo the raisins. After A 4 hours of treatment,, this value reemained statisstically constaant until the end e of the expperiment. Thiss behavior inddicates that gllycerol affecteed the flesh of o raisins. As observed earrlier in Figuree 5, Fskin is constant for trreated raisins throughout thhe study. Thhus, the decreease in Fflesh/F Fskin shown inn Figure 6 inndicates that th he raisin flesh softens due too glycerol infuusion, even as aw decreases. This study w done for tw was wo batches of raisins, and sttatistically no significant diffference betweeen batches w found. was To confirm m that the raisiin flesh was sooftened due too infusion, thee area betweenn the initial pooint of observ vation and the second peak was w determineed for untreateed and treated samples. If raaisins were softened due to infusion, the area betw ween the skinn rupture peaaks should deecrease. Figurre 7 shows thaat untreated raaisins and raissins after vacuuum infusion and during thhe following 4 hours had the highest area values. Afterwards, the area decrreased and reemained consttant during thee remaining tim me of the expeeriment. Thuss, both the Fflessh/Fskin ratio annd the area between b skin penetration peaks indicatte that approxximately afteer 4 hours, inncreased raisin n softness is achieved. Affter this time,, the internal raisin texturee does not chhange. Thus, additional a infuusion time is not n necessary. The low moleecular weight of glycerol deecreases the molecular m weigght of the soluutes in the liquuid phase diminnishing the viscosity and thhe mechanical resistance in the system.

Fiigure 6. Fflesh/Fskin values for unntreated and treaated raisins throoughout time inntervals. s


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The infusio on treatment study s shows thhat glycerol iss a good infussion agent for decreasing thhe water activvity of raisinns, being onee alternative for f maintaininng raisins at their best coondition, and preserving a homogenous h r raisin-cereal system. After 1 hour of treaatment with gllycerol, the water activity of o raisins decreeased, thus deecreasing the gradient g of waater activity beetween both components. At A this one houur time intervaal, Fflesh/Fskin annd area valuess were 38.7 ± 5.3 and 11.0 ± 1.9 J, reespectively. However, H Fflessh/Fskin and arrea values coontinued to th urably up untill the 4 -hour interval, whenn the values were w 33.8 ± 4.99 and 9.9 ± deecrease measu 1..8 J, respectively. This treattment does nott affect the texxture of raisins which increaases during thhe first 4 hou urs and keepss constant aft fter this time.. For this reaason, the mosst efficient trreatment woulld be to keep raisins in thee solution witth glycerol forr up to 4 houurs, thereby siimultaneously reducing the raisin water activity a and maintaining m or increasing itss properties off softness wheen compared too its untreatedd raisin counteerpart.

Fiigure 7. Area vaalues for untreaated and treated samples througghout time interrvals.

C Coating of Raisins R Samp ples w the waterr loss of the samples) s of Figure 8 shhows the weight loss (relatted directly with frresh and infused raisins storred at 20ºC inn a cabinet with 20% relativve humidity. The T weight looss of fresh raaisins was higgher than the weight w loss of o infused raisins, probably due to the exxposure of thee fresh raisinss to a higher average a RH thhan that foundd with the infuused raisins (550-20% vs.: 40-20%) 4 and because b glyceerol has the capacity c of maaintaining waater content (L Lee, Dangarann and Krochta, 2002) and thhat can contribbute towards decreasing d thee water loss off the raisin. The weight loss calculattion was not taken t into connsideration duue to the valuee of the m0 beeing higher in n infused raissins than the value found in fresh raisiins; therefore,, the water vaapour resistannce (WVR) of the uncoated and coated raiisins was estim mated (Equatioon 2) using

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thhe weight losss versus storrage time datta calculationn and Fick’s modified difffusion law (A Avena-Bustillo os, Cisneros-Z Zevallos, Krocchta, & Saltveit, 1993). In thhis equation, WVR W is the w water vapour resistance, r h//cm; aw the water w activityy of raisins; RH R the cabinnet relative huumidity; Pv the water vapour presssure, mmHgg; R the universal u gass constant 3 (m mmHg·cm /g·K K); T the cabiinet temperatuure, K; A the average a surfacce area of raissins, cm2; J thhe slope of thee weight loss curve, c g/h.

RH ⎞ ⎛ ⎜aw − ⎟PV A 100 ⎠ ⎝ WVR = RT J

(2)

Nevertheleess, due to the difficulty of determining d thhe area of the raisin (the dennsity of the raaisin could be measured andd made it relaative to its vollume, then thee area of the raisin r could haave been calcuulated and determined by means m of undeerstanding its mass, assumiing that the geeometric shap pe of a raisin is calculated as that of a sphere); s and, the t possible error e in the esstimation of th he WVR, the slopes of thee weight loss versus storage time data cuurves were ussed where anaalyzed. Workiing with the hypothesis thatt the area of a raisin was sim milar in all thhe samples, thhe first segm ment of the slope s was theen correlated with the waater vapour reesistance of th he samples, where w we hennce, after anallysis, reached the conclusioon that the hiigher the slopee of a curve, thhe higher the water w vapour resistance behhavior.

Fiigure 8. Weightt loss of fresh annd infused raisiins stored at 20ººC in a cabinet with w 20% relatiive huumidity.

Figure 9 an nd 10 show the t slope valuues in g/h of the t different raisins r studiedd. Figure 9 shhows the values of fresh raiisins, those without manipuulation (a) andd those manipuulated with shhock movemeent (b); wherreas figure 10 1 shows thee values of infused i raisinns, without m manipulation (aa) and those manipulated m w shock movvement (b). Inn the first casee (figure 9), with


245

one can observe that the best treatment to apply is to directly coat the fresh raisins with starch and BW, being that this coating offers the lowest slope values to commence the study; meanwhile, the fresh (untreated with starch and BW) raisins have the least water vapour resistance attributes. No significant differences were observed among the different emulsions used. On a different note, the shocks provoked by the gyratory spinning drum did not seem to affect the interaction between the coating and the surface of the raisin. In the second case (figure 10), can be observed that the presence of glycerol infused in the raisin made the effect of the starch-BW coating (directly applied over the glycerol infused raisin) to be less effective. This effect could be due to the glycerol causing an increased hydrophilic surface on the raisin, thus making adhesion more difficult between the beeswax and the surface of the raisin. It was also observed that the shocks provoked on the glycerol infused raisins by the spinning gyratory drum did seem to affect the interaction between the coating and the surface of the glycerol infused raisin. This appears to indicate that induced shocks most likely broke up the wax coating over the surface of the glycerol infused coated raisins; and in this case study, provoked a more rapid rate of water loss on the samples under observation. The problem observed when analyzing these slopes is that these values are not able to compare the effect derived from the glycerol infusion treatment, being that the driving force behind the glycerol infused treatment process is different. Therefore, making the hypothesis that the interchange area (skin of the raisin) is not modified by the infusion treatment (effect justified in the infusion treatment study), and by substituting, in Equation (2), the values corresponding to the driving force of the yield process for each example, equation 3 can be obtained. This equation permits us to compare the water vapour resistance values of untreated and infused raisins.

WVRFresh = β ·WVRInfused

(3)

For untreated raisins, and for the raisins coated with the different emulsions, the set value of β is equal or higher than 1. This value indicates that the raisin skin resistance to water vapour decreases as an effect of the infusion treatment and that the coating emulsions are not affected by the presence of glycerol on the surface of the raisins. In contrast, the effect of directly applying the starch and beeswax coating is quite more perceptible (set value of β is equal to 3) when demonstrating reduced adhesive qualities of the beeswax due to the presence of glycerol on the raisin skin. These evaluated results showed that the glycerol infusion treatment decreased the driving force of water transfer within the system, but also seemed to contribute to the decrease of the water vapour resistance of the skin, a loss of water vapour resilience that did not improve when the tested coatings were applied. The different coating emulsions did not seem to affect the water vapour resistance of the samples in a distinguishable manner being that the slopes observed were very similar. Even though these films present distinct permeable qualities when they are treated as independent structures (Talens & Krochta, 2005), it seems that the interactions that take place between these and the surface of the studied product diminish those very same considered permeable distinctions. Each emulsion has its own unique adhesive quality relative to its mixture composition and applicable in a specific/dissimilar manner depending on the type of raisin it coats; emulsions all having specific details reaffirming the necessity of continued investigation regarding microemulsion formulations

246


with smaller sized particles or bi-layered coatings that will achieve better water barrier qualities for food products. (a) Raisins (aw=0.5)

(b) Shocked Raisins (aw=0.5)

8

7 BW

6 3:3:1

0

8

BW 7

6 3:3:1

5 2.5:2.5:1

4 2:2:1

0,0

3 1.5:1.5:1

0,0

2 1:1:1

0,1

Fresh 1

0,1

5 2.5:2.5:1

0,2

4 2:2:1

0,2

0,3

3 1.5:1.5:1

0,3

0,4

2 1:1:1

0,4

Fresh 1

Slope·-10-3 (g/h)

0,5

0

Slope·-10-3 (g/h)

0,5

Figure 9. Values of the slopes (g/h) for fresh raisins, without (a) and with shocks (b). (b) Shocked Raisins (aw=0.4)

0,5

0,5

0,4

0,4

Slope·-10-3 (g/h)

0,3 0,2 0,1 0,0

0,3 0,2 0,1

8

7 BW

6 3:3:1

5 2.5:2.5:1

4 2:2:1

3 1.5:1.5:1

2 1:1:1

Fresh 1

8

BW 7

6 3:3:1

5 2.5:2.5:1

4 2:2:1

3 1.5:1.5:1

2 1:1:1

Fresh 1

0

0,0

0

Slope·-10-3 (g/h)

(a) Raisins (aw=0.4)

Figure 10. Values of the slopes (g/h) for infused raisins, without (a) and with shocks (b).

WVRFresh = β ·WVRInfused

(4)

CONCLUSION The use of combined solute infusion and vacuum impregnation methods are an effective way of reducing the water activity properties of the raisins as well as serving as an alternative formula towards maintaining raisins at their best possible conditions for preserving a homogenous raisin-cereal system. After 1 hour of treatment with glycerol, testing revealed that the water activity of the raisins decreased, thus decreasing the gradient of water activity between both components. Furthermore, testing has indicated that this treatment does not affect the texture of raisins, which increases in area during the first 4 hours and keeps constant after this time. The hardness of the raisin skin was not influenced by the presence of glycerol, allowing for a produced softness inside the raisins. As regards to the testing of


247

various coating effects, the direct application of beeswax seemed to be the best protection from water loss. Among the film forming emulsions based on whey protein, its higher plasticizer content lead to a decrease in its water loss protection; although, these differences were not significant. In spite of the fact that the tested films have different water vapour permeabilities when they are treated as independent structures, it seems that the interactions that transpired, between these films and the surface of the product, eliminated the above mentioned differences.

ACKNOWLEDGMENT The authors acknowledge the financial support from the Conselleria de Educacion de la Comunidad Valenciana through the Project GVPRE/2008/355 and from Vice-rectorate for Research from UPV through the project PAID-06-08-3242.

REFERENCES Avena-Bustillos, R.J., L.A. Cisneros-Zevallos, J.M. Krochta & M.E. Saltveit. (1993). Optimization of edible coatings on minimally processed carrots using response surface methodology. Transactions of the ASAE (American Society of Agricultural Engineers) 36(3), 801-805. Bolin H.R. (1976) .Texture and crystallization control in raisins. Journal of Food Science, 41, 1316-1319. Dobraszczyk, B. J.; Vincent, J. F. V. (1999). Measurement of mechanical properties of food materials in relation to texture: The materials approach. In: A., Roosenthal (Ed.), Journal of Food Texture: Measurement and Perception. Chapter 5 (pp. 99-147): An Aspen Publication. Fito P. (1994).Modelling of Vacuum Osmotic Dehydration of Food. Journal of Food Engineering,22, 313-328. Fito P & Pastor R. (1994). On some non-diffusional mechanism occurring during vacuum osmotic dehydration. Journal of Food Engineering,22, 313-328 Fito P.,Chiralt A., Barat J.M., Andres A., Martinez-Monzo J. & Martinez-Navarrete N. (2001). Vacuum impregnation for development of new dehydrated products. Journal of Food Engineering, 49, 297-302. Iglesia H & Chirife J.(1976). Equilibrium moisture contents of air dried beef.Dependence on drying temperature. Journal of Food Technology, 11, 556. Lagrange V.& Payne J.T. (1988). Shelf- Life Extension of Food Products Containing Raisins and Raisins Products. Cereal Food World, 33(2), 211-214. Labuza T.P.& Hyman C.R.1998.Moisture migration and control in multi- domain foods. Trends in Food Science & Technology, 9, 47-55. Lee S.Y., Dangaran K.L. & Krochta.J.M. (2002). Gloss Stability of Whey-Protein/Plasticizer Coating Formulations on Chocolate Surface. J Food Sci.,65 (4):658-662. Lewicki P.& Spiess W.E.L.(1995).Rheological Properties of Raisins: Part I. Compression test. Journal of Food Engineering, 24, 321-338.

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Lewicki P. & Wolf, W. (1995). Rheological Properties of Raisins: Part II. Effect of Water Activity. Journal of Food Engineering, 26, 29-43. Nielsen A.C.Company. (1979). Product and Package Performance:The consumers View. A.C. Nielsen Company, Northbrook, IL. Payne J.T. (1987).The Role of Raisins in High-Fiber Muesli-Style Formulations. Cereal Food World, 32(8), 45-547. Peleg M. (1994). A Mathematical Model of Crunchiness/Crispness Loss in Breakfast Cereals. Journal of Food Science,25, 403-410. Risbo J.(2003). The dynamics of moisture migration in packaged multi-component food systems I:shelf life predictions for a cerealraisin system. Journal of Food Engineering,58, 239-246 Sapru V.& Labuza T. (1996). Moisture Transfer Simulation in Packaged Cereal- Fruit Systems. Journal of Food Science, 27, 45-61. Spiess, W.E.L. and Wolf, N.R. (1983). In: R. Jowitt, F. Escher, B. Hallstrom, H.F.Th. Meffert, W.E.L. Spiess and G. Voss, Editors, Physical Properties of Foods, Applied Sci. Publ., London , pp. 65–87. Talens, P., & Krochta, J. M. (2005). Plasticizing effects of beeswax and carnauba wax on tensile and water vapor permeability properties of whey protein films. Journal of Food Science, 70 (3), E239–E243. Watter G.G & Brekke J.E. (1961). Stabilized raisins for dry cereal products. Food Technology, 15 (5), 236-238.



Chapter 10

FOOD PACKAGING: INNOVATIVE CONCEPT AND NECESSITIES Kelen Cristina Dos Reis Dept. of Food Science, Universidade Federal de Lavras, Lavras, Brazil

1. INTRODUCTION The type of packaging used has an important role in determining the shelf life of a food and the main purpose of food packaging is to protect the food from microbial and chemical contamination, oxygen, water vapour and light. Innovative food packaging concepts has been introduced as a response to the continuous changes in current consumer demands and market trends. The growing demands for ready-to-eat and easy to consume products are enhancing the necessity to increase the control on quality and food safety, and then a new tendency in food technology packaging emerging and it consist in using active packaging. Beyond their action as a barrier against external agents, they interact with the product in a manner to preserve the quality, reducing risks of pathogens and prolonging the shelf life of food. The active packaging can act absorbing oxygen, humidity and ethylene, incorporating taste and flavor, and reducing/inhibiting the microbial activity. The next generation of food packaging may include materials with antimicrobial properties. These packaging technologies could play a role in extending shelf-life of foods and reduce the risk from pathogens. Antimicrobial polymers may find use in other food contact applications as well [1]. In addition, actually a new concept with food-packaging materials that are more natural, disposable and biodegradable have a great interest in the world. Therefore, it is evident that the interest in active food-packaging systems in which the polymer matrix has low environmental impact is growing significantly. Biopolymers are environmental friendly but they show some limitations in terms of performance like thermal resistance, barrier and mechanical properties, associated with the costs. Then, this kind of packaging materials needs more research, more added value like the introduction of smart and intelligent molecules which is the nanotechnology field and to be able to give information about the properties of the food inside the package like quality, shelf-

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life, microbiological safety and nutritional values. It is necessary to make researches on this kind of material to enhance barrier properties, to ensure food properties integrity, to incorporate intelligent labeling, to give to the consumer the possibility to have more detailed product information than the current system.

2. BIOPOLYMERS FOR FOOD PACKAGING Depending on the production process and on the source, biopolymers can have properties similar to traditional ones. PLA is becoming a growing alternative as a green food packaging materials because it was found that in many situations it performs better than synthetic ones, like oriented polystyrene (OPS) and PET materials [2]. There are several other types of biopolymers on the market and same coming from petrochemical monomer, like certain types of polyester, polyester amides and polyvinylalcohol, produced by different manufacturer, used principally as films or moulding. Other bio polymers are starch materials, cellulose materials and polyesters (polylactic acid, PLA; polyhydroxy acid, PHA). Until now, the PHA polymer is a very expensive polymer because it is commercially available in very limited quantities but different types of materials can be combined to form blend or compounds or semifinished products such as films [3]. Many bioplastics are mixes or blends containing synthetic components, such as polymers and additives, to improve the functional properties of the finished product and to expand the range of application. It is important to study the change that can occur on the characteristics of the bioplastics during the time of interaction with the food [4]. It is important to understand not only the physical and mechanical properties of such materials for the task but also the compatibility with the food, which has been recognized as a potential source of loss in food quality properties. Polyhydroxyalkonoates (PHAs) have attracted much attention as biocompatible and biodegradable and these biopolymers are polyesters of various hydrocarboxylic acids, which are accumulated as an energy/carbon storage or reducing power material by numerous microorganisms under unfavourable growth conditions in the presence of excess carbon source [5]. PHAs exhibit material properties similar to various synthetic thermoplastic and elastomers currently in use, from polypropylene to synthetic rubber. Besides, upon disposal, they are completely degraded to water and carbon dioxide (and methane under anaerobic conditions) by micro-organisms in various environments such as soil, sea lakes and sewage. However, widespread industrial use has been limited due to the high cost of these polyester polymers. Blends of two or more polymeric materials or copolymers represent a good alternative for reducing the final cost of industrial products and an effective alternative way to acquire a new material with desired properties [6]. Biopolymers like starch present some drawbacks, such as the strong hydrophilic behavior (poor moisture barrier) and poorer mechanical properties than the conventional nonbiodegradable plastic films used in the food packaging industries [7,8,9,4]. Nevertheless, nanotechnology research is entirely multidisciplinary and can be applied to improve current products. A new approach has been developed, which use hybrid materials consisting of polymers and layered silicates the nanocomposites. In the nanocomposites technology, a layered silicates, such as montmorillonite (MMT) clay mineral, result from the stacked arrangement of negatively charged silicate layers and contain a platelet thickness of about 1

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nm with a high aspect ratio (ratio of length to thickness) is filled in a polymer matrix and the final product after processing exhibit extraordinary enhancement of mechanical, thermal and physicochemical properties at a low level of filler concentration in comparison to pure polymer and conventional microcomposites. So, incorporation of nanoclay in biopolymers like starch can improve its properties such as barrier and mechanical properties, furthermore can improve optical properties. In particular, these nanocomposites have excellent barrier properties because the presence of clay layers delays the diffusing molecule pathway due to tortuosity [10-12]. However, most work done on polymer/clay nanocomposites has focused mainly on synthetic polymers [13, 14]. Biopolymer-based nanocomposites have been examined in few studies [15; 17]. Another interesting aspect of nanocomposite technology is the significant improvements of biodegradability of biodegradable polymers after nanocomposite preparation with organoclay. So, a comprehensive review of biopolymer nanocomposite film applications in food packaging industry is necessary. In particular, these nanocomposites have excellent barrier properties because the presence of clay layers delays the diffusing molecule pathway due to tortuosity [18-20].

3. ACTIVE AND ANTIMICROBIAL PACKAGING Active packaging is new concept of packaging that changes the condition inside of the packaging to extend shelf-life or improve safety or sensory properties while maintaining the quality of the food. Fresh foods just after harvest are still active biological systems then the atmosphere inside a package constantly changes during metabolic processes. Research have shown that each fresh food has its own optimal gas composition and humidity level for maximizing its shelf life and active packaging offers promise in this area; it is difficult with conventional packaging to optimize the composition of the headspace in a package. The great challenged in the active biodegradable films and to incorporate the active agent material in the biodegradable matrix and to produce active films in conventional industry processing. So, for this new innovative concept packaging is very important specific properties from the biopolymers and it is important study how the antimicrobials can be incorporated in the biopolymer matrix. The active agents that can be added is very diverse like organic acids, enzymes, bacteriocins, fungicides, natural extracts, ions, ethanol, etc. and the systems can be in contact only with the atmosphere surrounding the food, in contact with the food surface or placed inside the food itself (for liquid foods). Some of the food packaging applications are postulated, such as intelligence, sensing and signaling microbiological and/or biochemical change; or active. Edible coating is an excellent vehicle to enhance the nutritional value of fruits and vegetables by carrying basic nutrients and/or nutraceuticals that are lacking or are present in only low quantity in fruits and vegetables. The application of cassava starch film in the highest concentration (4%), provided to the cucumber a better aspect of conservation, turning the most attractive product [21]. The functional properties of biopolymer-based edible films or coatings have been shown to act as barrier to solute and gas and enhance food quality and

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shelf life [22-23]. However, these films do not display good mechanical and water vapor barrier properties due to their hydrophilic characteristics. Again the active packaging from biopolymer is an innovative concept but for this new innovative concept packaging is very important specific properties from the biopolymers and it is important study how the antimicrobials can be incorporated in the biopolymer matrix. The nanotechnology can be the potential solution for this because nanosctructures display a high surface-to-volume ratio and the nanofiller can be use for the incorporation of the active agents. It is necessary to study the incorporation of the active agent in the nanofiller and then the nanofiller in the biopolymer matrix. The nanobiocomposites are able to enhance desired properties or to introduce new additional effective functionalities with small amount of nanofillers [24] Recent studies also show that nano-particles can be tailored for both controlled release and/or specificity in the action of the active agent having moisture or temperature as triggering mechanisms (second generation of nano-structured materials). Recently, Rhim et al. [25] found that chitosan-based nanocomposite films blended with some organically modified MMT, such as Cloisite 30B, exhibited antimicrobial activity against Gram-positive bacteria. In another study they conclude that the PLA/Cloisite 30B composite film showed a bacteriostatic function against Listeria monocytogenes. Miyagawa et al [26] reported the preparation of novel biobased nanocomposites from functionalized vegetable oil and organically-modified layered silicate clay. Wibowo et al. [27] have investigated on cellulose acetate (CA) nanocomposites. Biobased nanocomposites based on cellulose have been extensively applied to delay loss of quality in fresh products such as tomatoes, cherries, fresh beans, strawberries, mangoes and bananas. Petersson & Oksman [28] compared the mechanical and barrier properties of two different types of biopolymer based nanocomposites. The two nanoreinforcements chosen for this study were bentonite a layered silicate and microcrystalline cellulose (MCC). The polymer matrix was poly lactic acid (PLA). PLA is linear aliphatic thermoplastic polyester. The PLA/bentonite nanocomposite showed a 53% increase in tensile modulus and a 47% increase in the yield strength compared to pure PLA. The PLA/S-MCC system on the other hand showed no increase in tensile modulus and only a 12% increase in yield strength compared to pure PLA. These results were lower than expected. Also, the bentonite nanocomposite is able to reduce the oxygen permeabilityof the PLA while the MCC nanocomposite drastically increased the oxygen permeability of the PLA. No et al. [29] in the study showed the applications of chitosan for improvement of quality and shelf life of various foods from agriculture, poultry, and seafood origin. The hydrophilic nature of such packaging materials, which produces a loss of barrier properties or even a solubilization into foods with high-water activities, prevents their industrial applications [30]. In the study of Villalobos et al. [31] the syntheses of films with HPMC were reported. The water vapor permeability of films incorporates by Sorbitan monostearate and sucrose palmitate was minimal with a hydrocolloid/surfactant ratio. Elsabee et al. [31] reported the syntheses of films formulated with polypropylene (PP) and Chitosan/pectin. They shown that chitosan forms complex compounds with pectin and this property was used to build up a stable multilayered structure on the PP film surface, to produce a much better antimicrobial film which can be used to fabricate excellent packaging materials for post-harvest crop protection. CS has the ability to gel spontaneously on contact


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with multivalent polyanions due to the formation of inter- and intramolecular cross-linkage mediated by these polyanions. The polyanions investigated tripolyphosphate (TPP) is the most popular because of its non-toxic property and quick gelling ability. The CS-TPP nano system exhibits some attractive features which render them promising carriers for the delivery of macromolecules [33]. The application of these nanoparticles in edible films is very promising due to the food-grade properties of both components. The aim of the present study was to investigate the effect of nanoparticles with chitosan on the HPMC films mechanical and water vapor permeability properties. In this paper, chitosan/tripolyphosphate nanoparticles were prepared and incorporated in hydroxypropyl methylcellulose films. Hydroxypropyl methylcellulose films with CS-TPP nanoparticles could then be a potential material for food packaging applications to extent the shelf life of foods and products. Research and development of bio-nanocomposite materials for food applications, such as packaging and other food contact surfaces is expected to grow in the next decade with the advent of new polymeric materials and composites with inorganic nanoparticles. The application of nanocomposites promises to expand the use of edible and biodegradable films [34-36]. Some works [37-38] has shown that, at relatively low nanoparticle loadings, polymer composites are reinforced because chains within these nanocomposites are restricted to confined domains between sheets of the films. For instance, the combination of chain confinement, alignment of nanoparticles (i.e., nanostructure) and strong surface interaction, results in improvements in mechanical properties, as well as in decreases in gas and liquid permeability. The incorporation of particles that carry antimicrobials into the polymer matrix may change the film’s mechanical, barrier and optical properties [39-42]. Plant extracts commonly impart color and opacity to polymers [39] and sorbates decrease transparency of LDPE films [40]. Oxygen and water vapor transmission rates increase in LDPE containing chitosan but decrease in LDPE containing benzoic acid. Other functional ingredients, such as antioxidants, antimicrobials, nutraceuticals, flavor, and color agents, can be carried by edible coatings and retained on the food surface for enhancing food quality, stability, and safety. Common antimicrobial agents used in food systems, such as benzoic acid, sodium benzoate, sorbic acid, potassium sorbate, and propionic acid, may be incorporated into coatings. Starch-based coatings containing potassium sorbate were applied on the surface of fresh strawberries for reducing microbial growth and extending storage life of the fruit . HPMC coating containing ethanol was effective in inactivating Salmonella montevideo on the surface of fresh tomatoes [43]. Lysozyme was incorporated into chitosan coatings for enhancing the antimicrobial activity of chitosan against Escherichia coli and Streptococcus faecalis [44]. In addition, chitosan coatings containing potassium sorbate were shown to increase antifungal activity against the growth of Cladosporium and Rhizopus on fresh strawberries [45]. A new patented edible film comprising organic acids, protein, and glycerol (for example, 0.9% glycerol, 10% soy protein; and 2.6% malic acid) can inhibit pathogen growth, including L. monocytogens, S. gaminara, and E. coli 0157:H7. Such film also provides a method for coatingcomestible products with edible films without masking the color but increasing the shelf life [46]. Antioxidants can be added into the coating matrix to protect against oxidative rancidity, degradation, and discoloration of certain foods. Nuts were coated with pectinate, pectate, and

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zein coatings containing BHA, BHT, and citric acid to prevent rancidity and maintain their texture [47]. Ascorbic acid was incorporated into edible coatings for reducing enzymatic browning in whole and sliced mushrooms [48]. Xanthan gum coatings mixed with α-tocopherol enhanced nutritional quality and improved the surface color of peeled baby carrots [49]. Carrageenan and whey protein coatings containing antibrowning agents such as ascorbic acid and citric acid effectively prolonged the shelf life of apple slices [50]. MC-based coatings containing ascorbic acid and sorbic acid were able to retard browning and to enhance texture of cut-pear wedges [51]. Chitosan-based coating containing α-tocopheryl acetate significantly delayed the color change of fresh and frozen strawberries [52,53]. Xanthan gum coating was utilized to contain a high concentration of calcium and vitamin E for not only preventing moisture loss and surface whitening, but also significantly increasing the calcium and vitamin E contents of the carrots [54]. The development of chitosan coatings containing high concentrations of calcium, zinc, or vitamin E also provided alternative ways to fortify fresh fruits and vegetables that otherwise could not be accomplished with common processing approaches [45]. This application has been successfully demonstrated on fresh and frozen strawberries [53]. Flavor and coloring agents may also be added to edible coatings to improve the sensory quality of coated products. However, very little has been reported regarding this application. Some antimicrobial coatings were developed as well by incorporation of nisin, lactoferrin (an antimicrobial peptide derived from bovine lactoferrin in cow’s milk), sodium diacetate, sorbic acid, and potassium sorbate into a coating material. Films containing sorbic acid were the most compatible with the resin solution and had the best physical appearance. The water vapor barrier of films containing sorbic acid was almost unchanged compared to the control film (no antimicrobial agent). Antioxidants are widely used as food additives to improve oxidation stability of lipids and to prolong shelf-life, mainly for dried products and O2-sensitive foods. Antioxidants can also be incorporated into plastic films for polymer stabilization in order to protect the films from degradation. It is well established that antioxidant concentrations in polymeric films decrease during storage due to oxidation but also because of diffusion through the bulk of the polymer towards its surface followed by evaporation [55]. In the US cerealindustry waxed paper has sometimes been used as a reservoir for antioxidant release [56].Recently, vitamins E and C have been suggested for integration in polymer films to exert their antioxidative effects. Vitamin E has proved to be very stable under processing conditions and has an excellent solubility in polyolefins. [57]. In Japan Ag-substituted zeolite is the most common antimicrobial agent incorporated into plastics. Ag-ions which inhibit a range of metabolic enzymes, have strong antimicrobial activity. The normal incorporation level varies from 1 to 3% [58]. Several other compounds have been proposed and/or tested for antimicrobial activity in food packaging including organic acids such as sorbate, propionate and benzoate or their respective acid anhydrides, bacteriocins e.g. nisin and pediocin , enzymes such as lysozyme, metals and fungicides such as benomyl and imazalil [58, 59-63]. The choice of the antimicrobial is often limited by the incompatibility of the component with the packaging material or by the heat lability of the component during extrusion. One per cent potassium sorbate in a LDPE film inhibited the growth of yeast on agar plates. The LDPE resin and potassium sorbate powder can be mixed, extruded and pelletized to produce a


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masterbatch. These pellets can be added to LDPE resin. The masterbatch should be produced at low temperature to prevent heat decomposition of the potassium sorbate [59]. The relatively polar sorbate, benzoate and propionatecan be incompatible with the apolar LDPE [65, 66]. Acid anhydrides were thought to be more compatible than free acids and their salts because of their lower polarity. Two commercial biocidal films are currently marketed. One is composed of a chlorinated phenoxy compound and the other consists of chlorine dioxide. A commercial antifungal coating containing chitosan is also sold as a shelf-life extender for fresh fruit [62].

4. FUTURE TRENDS AND NECESSITIES An industrial point of view, active films obtained by using classical polymer technological processes (such as extrusion) are generally preferred. Despite this great interest, in the literature very few works are reported dealing with the development of antimicrobial biodegradable films obtained by means of extrusion processes. This is mainly due to the fact that most antimicrobial activity deterioration can occur during the extrusion using high temperature, high shear rates, high screw velocities and thus, high pressure. So, during the process, in fact, the high temperature and pressure in the extruder barrel can affect the chemical stability of the embedded antimicrobial compounds (which generally are heat sensitive and thermally unstable) and reduce their efficacy on food-borne spoilage microorganisms. Research and development in the field of active and intelligent packaging materials should be developing and research for environment friendly packaging s packaging need a real challenge and will imply the use of reverse engineering approach based on food requirements and not anymore only on the availability of packaging materials. Nanotechnologies should be expected to play a major role here and can help in the development for active and biodegradable packaging for foods.

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[40] Han, J., Castell-Perez, M.E., Moreira, R.G., (2007). The influence of electron beam irradiation of antimicrobial-coated LDPE/polyamide films on antimicrobial activity and film properties. LWT 40, 1545–1554. [41] Han, J. H. (2005). In: J. H. Han (Ed.), Innovations in food packaging. Elsevier Academic Press. [42] Han, J. H., Ho, C. H. L., & Rodrigues, E. T. (2005). Intelligent packaging. In J. H. Han (Ed.), Innovations in food packaging. Elsevier Academic Press. [43] Zhuang, R., Beuchat, L. R. Chinnan, M. S. Shewfelt, R. L. & Huang, Y. W. (1996) Inactivation of Salmonella montevideo on tomatoes by applying cellulose-based edible films, Journal of Food Protection. 59: 808 . [44] Park HJ. (2005). Edible coatings for fruit. In: Jongen W, editor. Fruit and vegetable processing. Boca Raton, Fla.: CRC Press LLC. [45] Park SI, Daeschel MA, Zhao Y. (2004). Functional properties of antimicrobial lysozymechitosan composite films. Journal of Food Science, 69: 215–21. [46] Hettiarachchy NS, Satchithanandam E. inventors; (2007) The Board of Trustees for the Univ. of Arkansas, assignee. Organic acids incorporated edible antimicrobial films. U.S. patent 7,160,580 [47] Swenson HA, Miers JC, Schultz TH, Owens HS. (1953). Pectinate and pectate coatings. II. Application to nut and fruit products. Food Technology, 7:232–5. [48] Nisperos-Carriedo MO, Baldwin EA, Shaw PE. (1992). Development of an edible coating for xtending postharvest life of selected fruits and vegetables. Florida State Hort Soc. 104:122– 5. [49] Mei Y, Zhao Y, Yang J, Furr HC. (2002). Using edible coating to enhance nutritional and sensory qualities of baby carrots. J Food Sci. 67:1964–8. [50] Lee JY, Park HJ, Lee CY, Choi WY. (2003). Extending shelf-life of minimally processed apples with edible coatings and antibrowning agents. Lebens Wissen Technol 36:323–9. [51] Guadalupe IO, Rodriguez JJ, Barbosa-Cánovas GV. (2003). Edible coatings composed of methylcellulose, stearic acid, and additives to preserve quality of pear wedges. J Food Proc Pres 27:299–320. [52] Han C, Lederer C, McDaniel M, Zhao Y. (2004a). Sensory evaluation of fresh strawberries (Fragaria ananassa) coated with chitosan-based edible coatings. J Food Sci. 70:S172–8. [53] Han C, Zhao Y, Leonard SW, Traber MG. (2004b). Edible coatings to improve storability and enhance nutritional value of fresh and frozen strawberries (Fragaria × ananassa) and raspberries (Rubus ideaus). Postharvest Biol Technol. 33:67–78. [54] Mei Y, Zhao Y, Yang J, Furr HC. (2002). Using edible coating to enhance nutritional and sensory qualities of baby carrots. Journal of Food Science, 67:1964–8. [55] Miltz, J., Hoojjat, P., Han, J., Giacin, J.R., Harte, B.R. and Gray, I.J. (1988) Loss of antioxidants from high density polyethylene-its effect on oatmeal cereal oxidation in Food and Packaging Interactions, ACS symposium, 365 (1989), 83-93. [56] Labuza, T.P. and Breene, W.M. (1989) Àpplications of active packaging'' for improvement of shelf-life and nutritional quality of fresh and extended shelf-life foods' in Journal of Food Processing and Preservation, 13, 1-69


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[57] Wessling, C., Nielsen, T., Leufven, A. and Jagerstad, M. (1998) `Mobility of _tocopherol and BHT in LDPE in contact with fatty food simulants in Food Additives Contaminants, 15, 709-715. [58] Ishitani, T. (1995) Àctive packaging for food quality preservation in Japan' in Foods and Packaging Materials-Chemical Interactions, (Ackerman, P., JaÈ gerstad, M., Oglsson, T., eds), pp. 177-188, Cambridge, Royal Society of Chemistry. [59] Han, J.H. and Floros, J.D. (1997) `Casting antimicrobial packaging films and measuring their physical properties and antimicrobial activity in J. Plastic Film and Sheeting, 13, 287-298. [60] Weng, Y.M. and Chen, M.J. (1997) Sorbic anhydride as antimycotic additive in polyethylene food packaging films in Food Science and Technology. 30, 485-487. [61] Ming, X., Weber, G.H., Ayres, J.W. and Sandine, W.E. (1997) Bacteriocins applied to food packaging materials to inhibit Listeria monocytogenes on meats in J. Food Sci. 62, 413-415 [62] Padgett, T., Han, I.Y. and Dawson, P.L. (1998) Incorporation of food-grade antimicrobial compounds into biodegradable packaging films' in J. Food Prot. 61, 1130-1335. [63] Halek, W. and Garg, A. (1989) Fungal inhibition by a fungicide coupled to an ionomeric ®lm' in J. Food Safety 9, 215-222. [64] Weng, Y.M. and Hotchkiss, J.H. (1992) Inhibition of surface moulds on cheese by polyethylene ®lm containing the antimycotic imazalil' in J. Food Prot. 55, 367-369. [65] Katz, F. (1998) New research in packaging' in Food Technology, 52, 56. [66] Weng, Y.M. and Hotchkiss, J.H. (1993) Anhydrides as antimycotic agents added to polyethylene films for food packaging' in Packaging Technol. Sci. 6, 123-128.



Chapter 11

PREDICTIVE MODELLING OF THERMAL PROPERTIES OF FOODS James K. Carson Department of Engineering, University of Waikato Private Bag 3015, Hamilton 3240, New Zealand

ABSTRACT Thermal properties of foods are vital inputs for many food process models. With the recent advances in mathematical modelling and significant reduction in the cost of computational power, uncertainties in model inputs are more and more becoming the limiting factor in model accuracy rather than the model formulation or solution process. In this chapter methods and models are presented for predicting thermal properties based solely on data for the composition of the food in terms of its basic components (liquid water, ice, protein, fat, carbohydrate, ash and air). This type of model provides genuine predictions of thermal properties since no thermal property measurements are required, as is necessary with some effective property models that may be found in the literature. Foods are divided into different classes, depending on the difficulties they pose for thermal properties prediction. Simple guidelines for thermal property prediction are presented along with worked examples to serve as illustrations.

Keywords: effective thermal conductivity, heat capacity, thermal diffusivity, density.

INTRODUCTION The World’s population is expected to pass the 7 billion mark within the next five years with about 85% of the population inhabiting developing countries [1]. Although the current rate of food production is sufficient, in theory, to feed every person adequately, the reality, according to the United Nations, is that worldwide 860 million people are undernourished. Thermal processes such as cooking, refrigeration and drying are capable of extending the shelf-life of foodstuffs significantly; in fact figures collated by the International Institute of

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Refrigeration show a correlation between rates of food wastage and malnutrition, and refrigeration storage capacity per capita [2]. For this reason much work has gone in to the development and implementation of mathematical modelling of thermal processes with the aim of improving their efficiency and reliability. Recently Datta suggested that the development of models for thermal processing of foods has reached the stage where accuracy is limited more by the availability of reliable input data than by an understanding of the physical mechanisms involved in the processes or computing power [3]. These input data include thermal properties such as specific heat capacity and/or specific enthalpy, and thermal conductivity and/or thermal diffusivity. In addition, related physical properties such as density and ice fraction data are required, depending on the thermal process in question. For primary, or minimally processed food products much of this data is available in the literature [4-7]; however, for more highly processed foods, it is probable that this data will need to be determined either by direct measurement or by predictive models such as the ones outlined in this chapter. The aim of this chapter, therefore, is to overview methods for predicting a food’s thermal properties based in its composition. The literature contains literally hundreds of effective thermal property models, many of which are purely empirical, and hence are limited in their range of applicability. Others have theoretical bases but contain empirical parameters whose values must be obtained by experimentation. Relatively few models solely require the foods’ composition data, and these are the focus of this chapter because they provide genuine predictions. Simple algebraic models for density, specific heat capacity, thermal conductivity and thermal diffusivity will be introduced, and worked examples illustrating their use is provided at the end of the chapter. Readers interested in surveys and reviews of thermal property models are directed to [4-6,12].

DENSITY AND POROSITY Density is defined as the mass of a substance divided by the volume it occupies:

ρ≡

m V

(1)

While density is, in principle, a relatively straightforward quantity to define and comprehend, in practice its measurement is not always convenient by a direct method. Hence when dealing with food, in particular when porosity is significant, several ‘types’ of density have been defined, depending on the actual quantities which are being measured. If a material contains no pores or air voids and both the mass and volume of the material may be measured directly, then the quantity measured by Eq. (1) would be referred to as its true density. However, in the case, for example, of a granular material where it is impractical to measure the mass and volume of an individual grain, it is common to determine its apparent or effective density by measuring the mass of the material within a container of known volume. The apparent density is related to the true density of the material by Eq. (2):

ρe = ρ aε + ρt (1 − ε ) ≈ ρt (1 − ε )

(2)

Predictive Modelling of Thermal Properties of Foods

263

where ε is the total porosity defined as the volume of the food which is occupied by air (or in some cases carbon dioxide) divided by the total volume (gas plus solids) of the food package or container. Observing that the product ρaε is negligible, rearrangement of Eq. (2) gives us a method for determining ε provided ρe and ρt are known:

ε ≈ 1−

ρe ρt

(3)

However often the true density of the food material is unknown and its porosity may be simpler to measure than to be inferred from Eq. (3). At this point it is instructive to consider different types of pores within a food. Figure 1 shows a blow-up schematic of a granular material. Carson [8,9] classified porosity as being either external (Figure 1a) or internal (Figure 1b), depending on whether the air forms a continuous or dispersed phase. This distinction is particularly useful for heat transfer calculations since for a given porosity and solid-phase thermal conductivity, the effective thermal conductivity will be higher if the air makes up the dispersed phase than it would if it made up the continuous phase [8]. Rahman [10] classifies pores as being open, closed or blind pores (Figure 1b). This classification is particularly useful for direct porosity measurement, since some techniques which rely on filling the pores with gas or mercury (e.g. pycnometry) will be not be suitable if a significant quantity of closed pores are present. It is worth noting that a food may contain all types of porosity described here (e.g. popped corn).

Open pore Closed pore

Blind pore a) External (interstitial) porosity

b) Internal porosity

Figure 1. Illustration of different types of porosity.

For all the equations outlined in this chapter it is assumed that ε includes the volumes of all pores present in the food (including closed pores). Clearly, therefore, it is important to have an awareness of the types of porosity that are contained within the food product of

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interest and how it has been (or might be) measured, since a significant number of closed pores will limit the types of suitable porosity measurement. Returning to the problem of density, we can extend and generalise Eq. 2 for i components:

ρ e = ∑ν i ρ i

(4)

i

An equivalent expression to Eq. (4) in terms of mass fractions (xi) is:

1

ρe

=∑ i

xi

(5)

ρi

In practice, mass fractional compositions are easier to determine for the condensed phase (i.e. solid and liquid) food components, whereas the volume fraction of air (i.e. ε) is easier to determine than its mass fraction, hence a hybrid of Eqs. (4) and (5) will often be the most useful:

1− ε

ρe

=∑ j

xj

(6)

ρj

where there are j components other than air (or carbon dioxide). Table 1 shows the densities of the major food components as a function of temperature between –40°C and 150°C. Table 1. Densities of major food components as a function of temperature (°C) between 40°C and 150°C [5,11] Food Component

Density (kg m-3)

Protein

ρ = 1.3299 x 103 – 5.1840 x 10-1T

Fat

ρ = 9.2559 x 102 – 4.1757 x 10-1T

Soluble carbohydrate

ρ = 1.5991 x 103 – 3.1046 x 10-1T

Fibre

ρ = 1.3115 x 103 – 3.6589 x 10-1T

Ash

ρ = 2.4238 x 103 – 2.8063 x 10-1T

Liquid Water

ρ = 9.9718 x 102 +3.1439 x 10-3T – 3.7574 x 10-1T2

Ice

ρ = 9.1689 x 102 +1.3071 x 10-1T

Air

ρ=

353 T + 273.15

In principle, the density of any food product may be determined by using Eq. (6) and the data in Table 1, as will be illustrated in the worked example later in the chapter.


265

SHRINKAGE AND ICE FRACTION Shrinkage During drying processes liquid water leaves biological material and is largely replaced by air. However, the replacement is usually not exact with some shrinkage caused by the collapse of cellular structure. The literature contains data and some empirical models for predicting shrinking during drying [6,10], but these are beyond the scope of this chapter, suffice to say that it is important to bear this factor in mind.

Ice Fraction Prediction Below the initial freezing temperature of a food product (which will usually be less than 0°C) the conversion of liquid water to ice proceeds with a non-linear dependence on temperature. Due to the difference in thermal properties between liquid water and ice and the strong dependence of ice fraction on temperature, the dependence of a food’s thermal properties on temperature will be more significant in the freezing range of temperatures than it is for above-zero temperatures. There are several different models relating ice fraction to temperature, but perhaps the simplest reliable one is Pham’s model [14]:

⎛ Tf xice = ( x w − 0.4 x pr )⎜⎜1 − T ⎝

⎞ ⎟⎟ ⎠

(7)

where xw is the total water content, and Tf is the initial freezing point of the food, for which data may be found in food properties databases [5-7]. The use of Eq. (7) will be illustrated in the worked example at the end of the chapter.

SPECIFIC HEAT CAPACITY The literature contains a large number of experimental data for the heat capacity of foods, as well as a number of empirical models that have been derived from them [5,6]. For predictions based on composition data we use the same approach as for density with the application of a weighted arithmetic mean:

C p ,e = ∑ xi C p ,i

(8)

i

Unlike density we can ignore the heat capacity contribution of air (or carbon dioxide) since the mass fraction of gaseous components are always small (even for high porosities). Table 2 shows the density and heat capacity of the major food components as a function of temperature between –40°C and 150°C.

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Table 2. Specific heat capacities of major food components as a function of temperature (°C) between -40°C and 150°C [5,11] Food Component

Specific Heat Capacity (kJ kg-1 K-1)

Protein

Cp = 2.0082+1.2089 x 10-3T – 1.3129 x 10-6T2

Fat

Cp = 1.9842+1.4733 x 10-3T – 4.8008 x 10-6T2


Cp = 1.5488+1.9625 x 10-3T – 5.9399 x 10-6T2

Fibre

Cp = 1.8459+1.8306 x 10-3T – 4.6509 x 10-6T2

Ash

Cp = 1.0926+1.8896 x 10-3T – 3.6817 x 10-6T2

Liquid Water below 0°C

Cp = 4.1289 – 5.3062 x 10-3T – 9.9516 x 10-4T2

Liquid Water above 0°C

Cp = 4.1289 – 9.0864 x 10-3T – 5.4731 x 10-6T2

Ice

Cp = 2.0623 + 6.0769 x 10-3T

Air

Cp = 1.0053 + 2.9799 x 10-5T+1.7095 x 10-7T2

THERMAL CONDUCTIVITY The thermal conductivities of the major food components are shown as a function of temperature in Table 3. Table 3. Thermal conductivities of the major food components a function of temperature (°C) between -40°C and 150°C [5,11] Food Component

Thermal Conductivity (W m-1 K-1)

Protein

k = 1.7881 x 10-1+1.1958 x 10-3T – 2.7178 x 10-6T2

Fat

k = 1.8071 x 10-1+2.7604 x 10-3T – 2.7178 x 10-6T2


k = 2.0141 x 10-1+1.3874 x 10-3T – 4.3312 x 10-6T2

Fibre

k = 1.8331 x 10-1+1.2497 x 10-3T – 3.1683 x 10-6T2

Ash

k = 3.2962 x 10-1+1.4011 x 10-3T – 2.9069 x 10-6T2

Liquid Water

k = 5.7109 x 10-1+1.7625 x 10-3T – 6.7036 x 10-6T2

Ice

k = 2.2196 – 6.2489 x 10-3T + 1.0154 x 10-4T2

Air

k = 2.364 x 10-2+7.2822 x 10-5T

Thermal conductivity and thermal diffusivity differ from density and specific heat capacity in that they are volumetric properties and have path dependence. Consider a layered two-component material as depicted in Figure 2:

Predictive Modelling of Thermal Properties of Foods Heat Flow

k1

267

Heat Flow

k1

k2

k2 Figure 2. Heat flow in parallel and series with layers of material having differing thermal conductivities.

For this material the effective thermal conductivity will be equal to:

k e = ∑ vi k i = v1k1 + v2 k 2 (9) i

if the direction of heat flow is parallel with the layers, while it will be equal to:

ke =

1 1 = v v v ∑i ki k1 + k2 1 2 i

(10)

if the direction of the heat flow is perpendicular to the layers (i.e. if the heat flows through the layers in series). In fact these two models, known as the Parallel and Series Models respectively (for obvious reasons), represent the upper and lower bounds of effective thermal conductivity of a mixture, sometimes referred to as the Wiener Bounds. For isotropic materials Hashin and Sthrikman [17] derived even narrower bounds:

k e = k1

2 k 1 + k 2 − 2( k 1 − k 2 ) v 2 2 k1 + k 2 + ( k1 − k 2 )v 2

(11)

ke = k2

2k 2 + k1 − 2( k1 − k 2 )v1 2 k 2 + k1 + ( k1 − k 2 )v1

(12)

Figure 3 shows plots of the Wiener and Hashin-Shtrikman bounds for a range of component thermal conductivity ratios (i.e. k1/k2): From Figure 3 we can see that the envelope bounded by the Hashin-Shtrikman bounds increases as k1/k2 increases. Since the Hashin-Shtrikman bounds represent the maximum and minimum values of thermal conductivity for an isotropic mixture it follows that the uncertainty in predicting the effective thermal conductivity of a mixture increases as k1/k2 diverges from unity. On the basis of this observation Carson [9,12] divided thermal conductivity problems into four classes based on the ratio of the highest component thermal conductivity to the lowest. Class I: Unfrozen, non-porous foods (kw/ksolids ≈ 3) (c.f. Figure 3a) Class II: Frozen, non-porous foods (kice/ksolids ≈ 12) (c.f. Figure 3b) Class III: Unfrozen, porous foods (kw/kair ≈ 25) (c.f. Figure 3c) Class IV: Frozen, porous foods (kice/kair ≈ 100) (c.f. Figure 3d)

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James K. Carson

k 1 /k 2 = 3

1

k 1 /k 2 = 10

1 Parallel

0.8

HS-Low er

HS-Upper HS-Low er

0.6

k e /k 1

0.4

Series

0.8

HS-Upper

0.6

k e /k 1

Parallel

Series

0.2

0.4 0.2

0

0 0

0.2

0.4

0.6

0.8

1

0

0.2

0.4

v2

1

(B)

k 1 /k 2 = 25

k 1 /k 2 = 100

1 Parallel

Parallel

Series

0.8

HS-Low er

0.2

HS-Upper HS-Low er

0.6

k e /k 1

0.4

Series

0.8

HS-Upper

0.6

k e /k 1

0.8

v2

(A) 1

0.6

0.4 0.2

0

0 0

0.2

0.4

0.6

v2

(C)

0.8

1

0

0.2

0.4

0.6

0.8

1

v2

(D)

Figure 3. Wiener and Hashin-Shtrikman thermal conductivity bounds for a range of component thermal conductivity ratios (k1/k2).

There are numerous models for predicting the thermal conductivity of heterogeneous materials, including many that have been applied to foods, and these are listed and reviewed elsewhere [4-6,9,12]. Some of these models are functions of the food’s composition data alone, while others contain one or more parameters whose value must be determined empirically. Although the latter category have the potential to provide greater accuracy, it is undesirable to have to perform any measurements which might be required to determine the value of the empirical parameter(s) since in many situations that will defeat the purpose of the prediction exercise in the first place. For this reason, as mentioned previously, only the former category are considered in this chapter.


269

Although there is an abundance of effective thermal conductivity models in the literature there is much less in the way of guidelines for deciding which models are most suitable for a given food undergoing a particular process. Carson [12] recommended models for each of the four different classes of foods described above. Cogné et al. [13] used a sequential, phase-byphase approach to model the thermal conductivity of ice cream successfully. A similar, generalised approach was proposed by Wang et al. [15] and is the method that will be outlined here. The principle of this method is to determine the thermal conductivity of each phase of the food sequentially, starting with the non-porous, unfrozen phase (containing liquid water, protein, fat, carbohydrates and ash). The thermal conductivities and volume fractions of these components are used to predict the effective thermal conductivity of the non-porous, unfrozen phase using the Parallel model (Eq. 9). For Class I foods this is the desired result (knpuf) and the method stops here. For Class II foods containing ice, knpuf is combined with kice using Levy’s model [16] to yield knpf:

k npf = kice

2kice + k npuf − 2(kice − k npuf ) F 2kice + k npuf + (kice − k npuf ) F

(13)

where:

F=

G=

2 / G − 1 + 2vnpuf − (2 / G − 1 + 2vnpuf ) 2 − 8vnpuf / G 2 (k ice − k npuf ) 2 (k ice + k npuf ) 2 + k ice k npuf / 2

(14)

(15)

For Class II foods knpf is the required result. For Class IV foods containing both air and ice, kpf, is obtained by combining knpf with ka using Maxwell’s model either with air as the dispersed phase, i.e.:

k pf = k npf

2k npf + k a − 2(k npf − k a )ε 2k npf + k a + (k npf − k a )ε

(16)

or alternatively with air as the continuous phase (e.g. in the case of particulate materials). This approach is represented diagrammatically in Figure 4, and is illustrated in the worked example later in the chapter. For Class III foods which contain air but not ice the second step is missed and knpuf instead of knpf is used to determine kpuf (or alternatively the method recommended by Carson [9,12] may be used).

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James K. Carson

k fa , x fa , ρ fa k fi , x fi , ρ fi k sc , x sc , ρ sc k pr , x pr , ρ pr k w , x w, ρ w

k ash , x ash , ρ ash Parallel Model (Eq. 9) k npuf , v npuf

k ice , x ice , ρ ice

Levy's Model (Eq. 13) k ice , ε

k npf , v npf

Maxwell's Model (Eq. 16) k pf Figure 4. Illustration of sequential application of thermal conductivities – phase by phase.

Wang et al. [15] applied this method to a variety of frozen foods and found that on average it provided prediction accuracies of within ±10% of measured values from the literature, while almost all were within ±20%. It should be noted that most of the data used in the analyses that resulted in the development of this method were high-water content foods such as meat, fish fruit and vegetables. The method will probably not be as accurate for low water-content foods such as, for example, butter and cheese.

THERMAL DIFFUSIVITY Thermal diffusivity is defined by Eq. (17):

α≡

k ρC p

(17)

Because of its dependence on thermal conductivity it has similar characteristics, and is more difficult to model than density or specific heat capacity. Since thermal conductivity data is often required for heat transfer analyses in addition to thermal diffusivity data one might well ask why α is used at all. The answer is, most probably, that often thermal diffusivity data


271

may be measured more directly than thermal conductivity data and would therefore be used preferentially, wherever possible, to thermal conductivity values derived from them via Eq. (17). Table 4 shows thermal diffusivity values for the major food components between –40°C and 150°C. Table 4. Thermal conductivities of the major food components as a function of temperature (°C) between -40°C and 150°C [5,11] Food Component

Thermal diffusivity (m2 s-1)

Protein

α = 6.8714 x 10-8 + 4.7578 x 10-10T – 1.4646 x 10-12T2

Fat

α = 9.8777 x 10-8 + 1.2569 x 10-11T – 3.8286 x 10-14T2


α = 8.0842 x 10-8 + 5.3052 x 10-10T – 2.3218 x 10-12T2

Fibre

α = 7.3976 x 10-8 + 5.1902 x 10-10T – 2.2202 x 10-12T2

Ash

α = 1.2461 x 10-7 + 3.7321 x 10-10T – 1.2244 x 10-12T2

Liquid Water

α = 1.3168 x 10-7 + 6.2477 x 10-10T – 2.4022 x 10-12T2

Ice

α = 1.1756 x 10-6 + 6.0833 x 10-9T – 9.5037 x 10-11T2

Air

α = 1.8210 x 10-5 + 1.2491 x 10-7T – 1.6785 x 10-10T2

The literature contains relatively few models for the prediction of thermal diffusivity of foods, most of which are empirical [6]. However, for Class I foods (as defined in the previous section) the effective thermal diffusivity may reasonably be determined from a weighted arithmetic mean:

α e = ∑ α i vi

(18)

i

since thermal conductivity (for Class I foods only), density and specific heat capacity may also be determined from weighted arithmetic means. For the other Classes of food it is best to use Eq. (17).

WORKED EXAMPLES Problem To illustrate the use of the models described above, consider a carton of meat which is cooled from an initial temperature of 10°C to a final temperature of –20°C. We want to determine the effective thermal diffusivity of the meat at the start of the process and at the finish, based on the following dimensions and composition data (note that the meat expands when it freezes).

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James K. Carson Table 5. Problem specifications Variable

Value

xpr

0.19

xfa

0.16

xw

0.64

Tf

–0.8°C

M

27.2 kg

Initial width

0.36 m

Initial length

0.52 m

Initial height

0.173 m

Final height

0.18 m

Solution Part 1: At 10°C (Start of the Process) At the start of the process the carton of meat represents a Class III food since it is unfrozen but contains pores. In order to determine αpuf we first need to determine ρe, Cp,e and kpuf. To begin with, we can work out the effective density using Eq. (1) since we have the mass of the meat and the dimensions of the carton:

ρe =

27.2 = 841 kg m −3 0.36 × 0.52 × 0.173

Since this value is well below the densities of water, fat or protein we know that the carton contains air voids, which is to be expected since a carton contains cuts of meat having irregular shapes which do not pack together without leavening interstitial gaps. It will be necessary for us to know the porosity in order to calculate the thermal conductivity of the meat in bulk, so we use a rearranged form of Eq. (6):

ε = 1 − ρe ∑ i

xi

ρi

where the xi were given in Table 5 and ρi may be determined for 10°C using the correlations in Table 1. Hence;

0 .1 ⎞ ⎛ 0.19 0.16 0.64 + + + ⎟ = 0.19 ⎝ 1325 921 997 2421 ⎠

ε = 1 − 841 × ⎜

Note that the mass fractions in Table 5 sum to 0.99; we may assume that the balance is made up of an equal mix of ash and carbohydrates.


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Next we determine Cp,e using Eq. (8) and the correlations in Table 2:

C p ,e = 0.19 × 2020 + 0.16 × 1998 + 0.64 × 4219 + 0.01 × 2000 = 3424 J kg −1 K −1 Note that this value for the specific heat capacity compares well with literature data for beef [4-7]. The determination of the thermal conductivity is a little more involved. Firstly we need to determine the volume fractions of each of the components within the non-porous unfrozen phase, i.e. we need to determine what volume of the meat itself (without any air voids) is occupied by protein, by water etc. e.g.

v pr =

x pr / ρ pr

∑x

i

/ ρi

=

0.19 / 1325 = 0.149 0.19 / 1325 + 0.16 / 921 + 0.64 / 997 + 0.01 / 2421

i

Similarly, vfa = 0.180, vw = 0.666 with the ash/carbohydrate making up the remainder. Now we determine the thermal conductivity of the condensed phase (i.e. the meat itself) using Eq. (9):

knpuf = 0.149 × 0.190 + 0.180 × 0.178 + 0.666 × 0.588 + 0.005 × 0.343 = 0.454 W m −1 K −1 Note that this value too compares well with literature data for beef [4-7]. knpuf represents the thermal conductivity of the meat itself; however, in a freezing process we are interested in the thermal conductivity of the contents of the carton (kpuf), which includes the entrained air that makes up 19% of its volume. k puf = k npuf

2k npuf + k a − 2(k npuf − k a )ε 2k npuf + k a + (k npuf − k a )ε

= 0.454

2 × 0.454 + 0.025 − 2(0.454 − 0.025) × 0.19 2 × 0.454 + 0.025 + (0.454 − 0.025) × 0.19

= 0.344 W m −1 K −1

Finally we use Eq. (17) to determine αpuf:

α npuf =

0.344 = 1.2 × 10 −7 m 2 s −1 841 × 3424

Solution Part 2: At –20°C (End of the Process) At the end of the process the carton of meat is a Class IV food since it contains both air and ice, and the property we are trying to determine is αpf. We will need to determine how much of the liquid water would be converted to ice and we also recall that due to thermal

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James K. Carson

expansion the carton has increased in height (although we will assume that the porosity does not change significantly). The effective density will be determined as in Part 1 of the solution based on the new carton height:

ρe =

27.2 = 807 kg m −3 0.36 × 0.52 × 0.18

The ice fraction will be determined using Eq. (7):

− 0 .8 ⎞ ⎛ xice = (64 − 0.4 × 0.19)⎜1 − ⎟ = 0.541 − 20 ⎠ ⎝ The remaining unfrozen water is the difference between the total water fraction and the ice fraction:

xufw = xw − xice = 0.64 − 0.541 = 0.099 We now calculate the volume fractions in the non-porous, unfrozen phase as we did for Part 1 of the solution:

e.g. v pr =

0.19 / 1325 = 0.34 0.19 / 1325 + 0.16 / 921 + 0.099 / 996 + 0.01 / 2421

Similarly, vfa = 0.41, vw = 0.098 with the ash/carbohydrate making up the remainder. To calculate the effective heat capacity we use the same procedure as for Part 1 of the solution, noting that we now include the ice fraction and have a reduced liquid water fraction:

C p,e = 0.19 × 1983 + 0.16 × 1952 + 0.099 × 3624 + 0.541×1940 + 0.01× 2000 = 2117 J kg−1 K −1 Next we calculate knpuf as in Part 1 of the solution:

k npuf = 0.34 × 0.154 + 0.41 × 0.186 + 0.098 × 0.533 + 0.004 × 0.3 = 0.259 W m −1 K −1 Note that because of the reduced liquid water content knpuf at –20°C is significantly lower than it was at 10°C. We now use Levy’s model (Eqs. 13-15) to calculate knpf based on vnpuf and knpuf:


vnpuf = 1 − ε − vice = 1 − ε −

275

xice / ρ ice ∑ xi / ρi i

= 1 − 0.19 −

0.541/920 0.19/1340 + 0.16/934 + 0.099/996 + 0.541/920 + 0.01/2429

= 0.414 G=

(2.385 − 0.259) 2 = 0.619 ( 2.385 + 0.259) 2 + 2.385 × 0.259 / 2

F=

2 / 0.619 − 1 + 2 × 0.414 − ( 2 / 0.619 − 1 + 2 × 0.414) 2 − 8 × 0.414 / 0.619 = 0.529 2

k npf = 2.385 ×

2 × 2.385 + 0.259 − 2 × (2.385 − 0.259) × 0.529 = 0.964 W m −1 K −1 2 × 2.385 + 0.259 + (2.385 − 0.259) × 0.529

Once again the values for Cp,e and knpf fall within the range of values of experimental data for frozen meat that may be found in the literature [4-7]. To calculate kpf we use Eq. (16) based on knpf: k puf = k npf

2k npf + k a − 2(k npf − k a )ε 2k npf + k a + ( k npf − k a )ε

= 0.964

2 × 0.964 + 0.025 − 2(0.964 − 0.025) × 0.19 2 × 0.964 + 0.025 + (0.964 − 0.025) × 0.19

= 0.723 W m −1 K −1

Finally we calculate αpf from Eq. (17):

α pf =

0.723 = 4.2 × 10 −7 m 2 s −1 807 × 2117

Due to the ice content which has higher thermal conductivity and lower volumetric heat capacity αpf is significantly greater than αpuf.

CONCLUSION In this chapter simple models have been introduced that provide predictions of the density, specific heat capacity, thermal conductivity and thermal diffusivity of foodstuffs based solely their composition data. These models are particularly useful for highly processed foodstuffs (e.g. cooked/baked products, convenience meals, snack-foods and desserts) for which thermal property data is unlikely to be available in the literature. As was illustrated in

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James K. Carson

the worked example, these models are also useful for determining the thermal properties of the food in its packaged state, which will often differ from the unpackaged state due to the presence of air voids. These models provide genuine predictions of thermal properties since no thermal property measurements are required, as is the case with some effective property models that may be found in the literature. In addition, it is worth noting that, particularly with minimally processed foods such as raw meat, fruit, vegetables and raw grains, biological variation due to species, cultivar, farming region and harvesting season will result in corresponding variations in physical properties which means that it is unlikely that a literature value of, for example an ‘apple’ or even a ‘granny smith apple’ will match experimental data for a different granny smith apple to within ± 10%. In this regard, the thermal properties predicted from the models in this chapter based on actual composition data for a given food might well provide better predictions than thermal property data found in the literature. However, it should also be recognised that, particularly in the case of thermal conductivity, these models are best suited for high-water-content foods, and will not be as accurate for high-fat foods such as, for example, butter and cheese. It should also be understood that these models really only provide first approximations and that it is possible to achieve greater prediction accuracy with models which contain some empirical data.

NOMENCLATURE Cp F G k m T v V x

specific heat capacity intermediate variable defined by (Eq. 14) intermediate variable defined by (Eq. 15) thermal conductivity mass temperature volume fraction volume mass fraction

α ε ρ

thermal diffusivity porosity density

Subscripts 1 2

component 1 component 2

a ash

property of air property of ash

(J kg-1 K-1) (W m-1 K-1) (kg) (°C) (m3)

(m2 s-1) (kg m-3)

Predictive Modelling of Thermal Properties of Foods e fa fi i ice j npf npuf pf pr puf sc t ufw w

277

effective property property of fat property of fibre ith component of food ice content of food jth component of food property of non-porous, frozen phase/food property of non-porous, unfrozen phase/food property of porous, frozen phase/food property of protein property of porous, unfrozen phase/food property of soluble carbohydrate true value unfrozen water content property of water

REFERENCES [1] [2]

United Nations. World Population Prospects: The 2008 Revision Population Database. 5th Informatory Note on Refrigeration and Food, International institute of Refrigeration (IIR), 2009 (http://www.iifiir.org/en/doc/1215.pdf) [3] Datta, A. K. Porous media approaches to studying simultaneous heat and mass transfer in food processes. II: Property data and representative results, Journal of Food Engineering, 2007, 80(1) 96-110. [4] Rao, M. A., Rizvi, S. S. H., Datta, A. K. Engineering Properties of Foods 3rd Ed. CRC Press, Boca Raton, Florida, 2005. [5] ASHRAE Handbook – Refrigeration, American Society of Heating, Refrigeration and Air-Conditioning Engineering, Atlanta, 2006. [6] Rahman, M. S. Food Properties Handbook 2nd Ed., CRC Press, Boca Raton, Florida, 2009 [7] www.nelfood.com [8] Carson, J. K., Lovatt, S. J., Tanner, D. J., Cleland, A.C. Thermal conductivity bounds for isotropic, porous materials. International Journal of Heat and Mass Transfer, 2005, 48(11), 2150-2158. [9] Carson, J. K., Lovatt, S. J., Tanner, D. J., Cleland, A.C. Predicting the effective thermal conductivity of unfrozen, porous foods. Journal of Food Engineering, 2006, 75(3), 297307. [10] Rahman M. S., Mass-Volume-Area-Related Properties of Foods, in : Rao, M. A., Rizvi, S. S. H., Datta, A. K. Engineering Properties of Foods 3rd Ed. CRC Press, Boca Raton, Florida, 2005. [11] Çengel, Y. A., Turner, R. H., Fundamentals of Thermal-Fluid Sciences, 2nd Ed., McGraw-Hill, New York, 2007. [12] Carson, J. K. Review of effective thermal conductivity models for foods, International Journal of Refrigeration, 2006, 29(6), 958-967.

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[13] Cogné, C., Andrieu J., Laurent P., Besson A., Nocquet J. Experimental data and modeling of thermal properties of ice creams, Journal of Food Engineering, 2003, 58 (4), 331-341 [14] Pham, Q.T., Calculation of bound water in frozen food, Journal of Food Science, 1987, 52(1), 210-212. [15] Wang, J. F., Carson, J. K., Willix, J., North, M. F., Cleland, D. J., Prediction of thermal conductivity for frozen foods with air voids, Proceedings of the 1st IIR Conference on Sustainability and the Cold Chain, Cambridge, UK, March 29-31, 2010. [16] Levy F. L., A modified Maxwell-Eucken equation for calculating the thermal conductivity of two-component solutions or mixtures, International Journal of Refrigeration, 1981, 4(4), 223-225. [17] Hashin, Z. Shtrikman, S., A variational approach to the theory of the effective magnetic permeability of multiphase materials, Journal of Applied Physics, 1962, 33, 3125-3131.



Chapter 12

APPLICATIONS OF MEMBRANE CONTACTORS IN THE FOOD INDUSTRY Catherine Charcosset* Université de Lyon, F-69622, Lyon, France ; Université Lyon 1, Villeurbanne ; CNRS, UMR 5007, Laboratoire d’Automatique et de Génie des Procédés ; ESCPE-Lyon, Villeurbanne

1. INTRODUCTION Membrane contactors represent an emerging technology in which the membrane is used as a tool for inter phase mass transfer operations [Sirkar et al. 1999, Drioli et al. 2003]. The membrane does not act as a selective barrier, but the separation is based on the phase equilibrium. This review specifically addresses to two membrane contactor processes: membrane distillation and membrane emulsification and their applications in the food industry. Membrane distillation is a thermally driven membrane process in which a hydrophobic microporous membrane separates a hot and cold stream of water. The hydrophobic nature of the membrane prevents the passage of liquid water through the pores while allowing the passage of water vapour. The temperature difference produces a vapour pressure gradient which causes water vapour to pass through the membrane and condense on the colder surface. The result is a distillate of very high purity which, unlike in conventional distillation, does not suffer from the entrainment of species which are non-volatile. On the other hand, membrane emulsification involves using a low pressure to force the dispersed phase to permeate through a membrane into the continuous phase. The distinguishing feature is that the resulting droplet size is controlled primarily by the choice of the membrane and not by the generation of turbulent droplet break-up.

*

Corresponding author: Catherine Charcosset tel : 00 33 4 72 43 18 67 Fax : 00 33 4 72 43 16 99 E-mail : [email protected]

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Catherine Charcosset

This review illustrates the fundamental concepts of these two membrane contactors: membrane distillation and membrane emulsification. The most significant applications in the food industry of these two membrane processes are presented and discussed, including membrane distillation for partial dealcoholization of wine, production of vegetable oil in milk emulsions using membrane emulsification, and membrane distillation for the recovery of volatile aroma compounds from black currant juice.

2. MEMBRANE DISTILLATION 2.1. Principles of Membrane Distillation Methods Membrane distillation is a thermally driven membrane process in which a hydrophobic microporous membrane separates a hot and cold stream of water [Hogan et al. 1991, Lawson and Lloyd 1997]. The hydrophobic nature of the membrane prevents the passage of liquid water through the pores while allowing the passage of water vapour (Figure 1). The temperature difference produces a vapour pressure gradient which causes water vapour to pass through the membrane and condense on the colder surface. The result is a distillate of very high purity which, unlike in conventional distillation, does not suffer from the entrainment of species which are non-volatile.

Membrane

Condensation plate

Hot feed solution

Coolant

Condensation channel Figure 1: Principle of the membrane distillation process.

Applications of Membrane Contactors in the Food Industry

281

Configurations A variety of configurations are employed to impose a vapor pressure difference across the membrane [Lawson and Lloyd 1997]. The permeate side of the membrane may consist of a condensing fluid in direct contact with the membrane (direct contact membrane distillation), a condensing surface separated from the membrane by an air gap (air gap membrane distillation), a sweeping gas (sweeping gas membrane distillation), or a vacuum (vacuum membrane distillation). The configuration employed dependents upon the permeate composition, the flux, and the volatility of the solutions. The direct contact membrane distillation configuration requires the least equipment and is simplest to operate. It is well suited for applications such as desalination or the concentration of aqueous solutions (orange juice), in which water is the major permeate component. Weeping gas membrane distillation and vacuum membrane distillation are used when a volatile organic or a dissolved gas is being removed from an aqueous solution. Air gap membrane distillation, is the most versatile membrane distillation configuration. It is applied to almost any application. Membranes The most suitable materials for membrane distillation include polyvinyldifluoride (PVDF), polytetrafluoethylene (PTFE) and polypropylene (PP) [Jiao et al. 2004]. The size of micropores can range between 0.2 and 1.0 μm. The membrane porosity ranges from 60% to 80% of the volume and the overall thickness from 80 - 250 μm, depending on the absence or presence of a support. The membrane configurations include flat sheet, spiral wound and hollow fiber, the latter being the most investigated.

2.2. Applications of Membrane Distillation Concentration of Fruit Juices Because membrane distillation can be carried out at the atmospheric pressure and at a temperature which can be much lower than the boiling point of the solution, it can be used to concentrate solutes sensitive to high temperature, also at high osmotic pressure. Therefore, membrane distillation has received a great attention for concentrating fruit juices. Drioli et al. [1992] investigated the concentration of orange juice by membrane distillation by studying the effect of various parameters on the permeate flux, including membrane types, feed juice concentration, operating temperature, and ultrafiltration pretreatment. Membrane distillation was further applied to concentrate fruit juices [Alves and Coelhoso 2006, Cassano et al. 2004] based on the use of a salty solution as stripping liquid that selectively extract the water from aqueous solutions under atmospheric pressure and at room temperature. Laganà et al. [2000] used a direct contact membrane distillation process to produce a highly concentrated apple juice using hollow fiber modules. A high 64°Brix concentration was achieved with fluxes of 1 kg/m2 h. Dealcoholization Membrane distillation was also used to reduce the ethanol content in alcoholic beverages without altering the organoleptic properties of the product [Hogan et al. 1998]. In this process, an aqueous phase containing the volatile components was circulated through a

282


hydrophobic hollow fiber membrane contactor while a second aqueous phase, used as stripping liquid, flew along the downstream side of the membrane. The stripping phase employed was degassed water that allowed the ethanol transfer but avoided the water transfer across the membrane. Diban et al. [2008] used a membrane contactor to partial dealcoholize wine (a 2% v/v reduction), without spoiling significantly its flavor characteristics.

Recovery of Volatile Aroma Compounds Aroma profiles of fruit juices usually comprise a mixture of a large number of volatile organic compounds. The individual aroma components differ according to their molecular structure, which in turn defines the solubility, the boiling point, and the volatility of each type of compound [Ramteke et al. 1990]. For example, the unique aroma profile of black currant (Ribes nigrum L.) juice comprises more than 60 constituents. Bagger-Jørgensen et al. [2004] evaluated the potential of vacuum membrane distillation to recover black currant juice aroma. They reported the influence of feed temperature and flow rate on the fluxes and concentration factors of seven characteristic black currant aroma compounds using a laboratory scale vacuum membrane distillation set up. Vacuum membrane distillation at feed flow from 100 to 500 l/h at 30 °C gave concentration factors from 4 to 15, calculated for each aroma compound as Cpermeate=Cfeed. The recovered levels of the highly volatile aroma compounds ranged from 68 to 83 vol.% with a feed volume reduction of 5 vol.% (10 °C, 400 l/h).

3. MEMBRANE EMULSIFICATION 3.1. Principles of Membrane Emulsification Methods Membrane emulsification has received increasing attention over the last 15 years [Peng and Williams 1998a and b, Joscelyne and Trägårdh 2000, Nakashima et al. 2000, Vladisavljević and Schubert 2005]. The membrane emulsification process is schematically shown in Figure 2. The dispersed phase is pressed through the pores of a microporous membrane, while the continuous phase flows along the membrane surface. Droplets grow at pore openings until they detach when having reached a certain size. Surfactant molecules in the continuous phase stabilize the newly formed interface, to prevent droplet coalescence immediately after formation. The distinguishing feature is that the resulting droplet size is controlled primarily by the choice of the membrane and not by the generation of turbulent droplet break-up. The apparent shear stress is lower than in classical emulsification systems, because small droplets are directly formed by permeation of the dispersed phase through the micropores, instead of disruption of large droplets in zones of high energy density. Besides the possibility of using shear-sensitive ingredients, emulsions with narrow droplet size distributions can be produced. Furthermore, membrane emulsification processes allow the production of emulsions at lower energy input (104-106 J/m3) compared to conventional mechanical methods (106-108 J/m3) [Altenbach-Rehm et al. 2002].


Continuous phase Tangential flow

283

Droplets/or particles

Membrane Dispersed phase permeation under applied pressure

Figure 2: Principle of the membrane emulsification process.

Configurations In conventional membrane emulsification, fine droplets are formed at the membrane/continuous phase interface by pressing the disperse phase through the membrane. In order to ensure a regular droplet detachment from the pore outlets, shear stress is generated at the membrane/continuous phase interface by recirculating the continuous phase using a pump or by agitation in a stirring vessel [Vladisavljević and Williams 2005]. The rate of mixing should be high enough to provide the required tangential shear on the membrane surface, but not too excessive to induce further droplet break up. Other systems use a moving membrane, in which the droplet detachment from the pore outlets is obtained by rotation or vibration of the membrane within the stationary continuous phase. Droplets can be spontaneously detached from the pore outlets at small disperse phase fluxes, particularly in the presence of fast adsorbing emulsifiers in the continuous phase and for a pronounced noncircular cross section of the pores. Rotating membrane devices are also tested to increase the performances of the membrane emulsification process, especially to increase the flux of the dispersed phase through the membrane [Aryanti et al. 2006, Schadler and Windhab 2006]. Membranes The most commonly used membrane for the preparation of emulsions is the Shirasu porous glass (SPG) membrane (Ise Chemical Co., Japan) because of its narrow pores size distribution and tubular shape [Nakashima et al. 1991]. The SPG membrane is synthesized from CaO-Al2O3-B2O3-SiO2 type glass, which is made from “Shirasu”, a Japanese volcanic ash. The SPG membrane has uniform cylindrical interconnected micropores, a wide spectrum of available mean pore sizes from 0.1 to 20 μm and a high porosity from 50 to 60 %. In addition to the SPG membranes, o/w emulsions were successfully prepared using silicon and silicon nitride microsieves membranes (Aquamarijn Microfiltration BV, The Netherlands) [Zhu and Barrow 2005, Geerken et al. 2007]. These membranes are made by photolithographic treatment of a silicon wafer and subsequent etching, or electrochemical metal deposition on a skeleton in an electrolysis bath, respectively. They have interesting properties, such as a smooth and flat surface, a very low membrane resistance and narrow pore size distribution. Different pore geometries (circular, square, slit shaped), pore size, pore edges and membrane porosities are available. Other commercial microfiltration membranes are attractive because of their availability in very large surface area, and their high flux through the membrane pores: ceramic aluminium

284


oxide (α-Al2O3) membranes [Schröder and Schubert 1999], α-alumina and zirconia coated membranes [Joscelyne and Trägårdh 1999], and polytetrafluoroethylene (PTFE) membranes [Suzuki al. 1998, Yamazaki et al. 2002]. W/o emulsions were successfully prepared using polytetrafluoroethylene (PTFE) membranes [Suzuki et al. 1998, Yamazaki et al. 2003], polyamide hollow fibers membrane [Giorno et al. 2003, 2005], and home made silica-based monolithic membrane [Hosoya et al. 2005].

3.2. Applications Simple Emulsions Various food emulsions were prepared by membrane emulsification. Katoh et al. [1996] prepared w/o food emulsions from a low fat spread with a fat content of 25 % (v/v). They showed that the dispersed phase flux was increased 100 times using a hydrophilic membrane pre-treated by immersion in the oil phase, and that the membrane emulsification process was suitable for preparation of large scale w/o food emulsions. Suzuki et al. [1998] prepared o/w and w/o food emulsions from vegetable oil by membrane emulsification combined with preliminary emulsification. Using hydrophilic (or hydrophobic) PTFE membranes, o/w (or w/o) emulsions were prepared with a narrow diameter distribution. The authors show that the higher the flux of the pre-emulsified emulsion via the membrane, the higher the monodispersity of the emulsion was. The preparation of emulsions with reconstituted milk is usually done by high-pressure homogenization. In such cases the molecular or ultrastructural status of the milk components (casein micelles, whey proteins, free milk fat globule membranes in buttermilk) may be changed. The structure and composition of the proteins at the fat surface play an important role in determining the functional properties of recombined milks. Using SPG membranes, Scherze et al. [1999] and Muschiolik et al. [1997] prepared o/w emulsions with liquid butter fat or sunflower oil as the dispersed phase and a continuous phase containing milk proteins. The emulsions so obtained were characterised by particle size distribution, creaming behaviour and protein adsorption at the dispersed phase. The advantage of membrane emulsification was pointed out to be the low shear forces on the physicochemical and molecular properties of the proteins. Loaded o/w emulsions were also prepared by membrane emulsification, e.g. astaxanthinloaded o/w emulsions by repeated premix membrane emulsification [Ribeiro et al. 2005]. Astaxanthin is a natural carotenoid product with exceptional antioxidant properties. In the emulsification process, a pre-emulsion is repeatedly pushed through a hydrophilic or hydrophobic membrane. Pre-emulsions were produced by dispersing palm oil containing dissolved astaxanthin in water [Ribeiro et al. 2005]. The oil droplets were stabilized with a combination of two emulsifiers. Each o/w passed the membrane 3 times under pressure of 5 to 15 bar and disperse phase fraction from 10 wt% to 40 wt%. Multiple Emulsions Double emulsions (e.g. w/o/w) can be produced by membrane emulsification [van der Graaf et al. 2005]. The primary emulsion may be produced by means of a conventional method or by membrane emulsification. The mild conditions of membrane emulsification are


285

especially useful for the second emulsification step in order to prevent rupture of the double emulsion droplets, which might even lead to inversion into a single o/w emulsion. In contrary to conventional emulsification methods, it becomes possible to produce small and monodisperse droplets without using high-shear stresses that cause escape of the internal droplets. For example, Mine et al. [1999] prepared w/o/w emulsions using egg yolk phospholipids and soybean oil without any coalescence of oil drops or breakdown of the emulsions. The particle size distribution of the multiple emulsion depended on the pore size of the microporous glass membrane. Phospholipids occur widely in nature (e.g. soybean and egg yolk), and are widely used as a stabilizing agent in food emulsions. Shima et al. [2004] investigated w/o/w emulsions to protect fragile bioactive compounds from stomach acid and intestinal digestive fluids. These authors prepared w/o/w emulsion as a carrier system for the daily uptake of a hydrophilic model compound of a bioactive substance (1,3,6,8pyrenetetrasulfonic acid tetrasodium salt). Membrane filtration of a coarse w/o/w emulsion prepared with a rotor/stator homogenizer produced a fine emulsion with a mean oil-droplet diameter below 1 μm and an encapsulation efficiency higher than 90 %. However, the authors observed that the included water-phase disappeared during the membrane filtration of the coarse emulsion when preparing the fine emulsion.

Encapsulation There has been considerable recent interest in probiotics for promotion of human health. The probiotic bacteria most commonly studied include members of the genera Lactobacillus and Bifidobacterium. Microorganisms used as probiotic adjuncts are commonly delivered in the food system. However, when these microorganisms are injected, their activity and viability are reduced under highly acidic conditions. Hence, there is a need for lactic acid bacteria that are resistant to the stressful conditions of the stomach and the upper intestine, which both contain bile. Song et al. [2003] prepared microcapsules with a narrow particle size distribution with the SPG membrane. For artificial gastric acid and bile, the viable count of encapsulated cells was constant through the incubation time, while the count of nonencapsulated cells was significantly decreased. A storage stability test at different temperatures resulted in a viability of encapsulated cells 3 to 5 log cycles higher than the viability of monoencapsulated cells. Aerated Food Gels Food gels are soft solids containing a high amount of an aqueous phase (i.e. >80 %) that have received much attention [i.e. Zúñiga and Aguilera 2008]. Aerated food gels were produced recently by membrane foaming [Bals and Kulozik 2003a and b]. The method is based on pressing the dispersed phase (gas) through the pores of a tubular membrane into the continuous phase. The bubbles formed are covered with surface-active substances of the continuous phase and they are detached from the membrane surface by the shear forces exerted by the phase flowing along the membrane surface. Bals and Kulozik [2003a] investigated the influence of pore size, foaming temperature and viscosity of the continuous phase on the properties of foams produced by membrane foaming. An important factor is that the added amount of gas must be stabilised as completely as possible in the foam. Raising the foaming temperature increased the quantity of stabilised gas. The whey proteins then diffused

286


faster to the bubble surfaces and stabilise these by unfolding and networking reactions to prevent the coalescence of the bubbles. Bals and Kulozik [2003b] also studied the effect of pre-heating on the foaming properties of whey protein isolate using a membrane foaming apparatus. These authors concluded that further improvement of the process conditions were needed to obtain stable foams with narrow bubble size distributions.

4. CONCLUSION This review article aims to present some aspects of the large range of membrane applications in the food industry, by focusing on two membrane processes: membrane distillation and membrane emulsification. Significant applications are presented including membrane distillation for partial dealcoholization of wine, production of vegetable oil in milk emulsions using membrane emulsification, and membrane distillation for the recovery of volatile aroma compounds from black currant juice. Limitations of membrane processes may be associated to the low fluxes due to fouling phenomena. These disadvantages may be solved by recent improvements in the devices, as premix membrane emulsification, and rotating or vibrating membrane devices. In order to gain a foothold in the food industry, studies on developments of highly selective, permeable membranes, robust and stable in long-term application for food processing, need to be carried out in detail. Improvements of process engineering including module design and process design and optimization are also highly needed.

REFERENCES Altenbach-Rehm J., Suzuki K., Schubert H., Production of O/W-emulsions with narrow droplet size distribution by repeated premix membrane emulsification. 3ième Congrès Mondial de l’Emulsion, 24-27 September 2002, Lyon, France. Alves V.D., Coelhoso I.M., Orange juice concentration by osmotic evaporation and membrane distillation: a comparative study, J. Food Eng. 74 (2006) 125-133. Aryanti N., Williams R.A., Hou R., Vladisavljevic G.T., Performance of rotating membrane emulsification for o/w production, Desalination, 200 (2006) 572-574. Bagger-Jørgensen R., Meyer A. S., Varming C., Jonsson G., Recovery of volatile aroma compounds from black currant juice by vacuum membrane distillation, J. Food Eng. 64 (2004) 23–31 Bals A., Kulozik U., The influence of pore size, the foaming temperature and the viscosity of the continous phase on the properties of foams produced by membrane foaming, J. Membr. Sci. 220 (2003a) 5-11. Bals A., Kulozik U., Effect of pre-heating on the foaming properties of whey protein isolate using a membrane foaming apparatus, Int. Dairy J. 13 (2003b) 903-908. Cassano A., Jiao B., Drioli E., Production of concentrated kiwifruit juice by integrated membrane process, Food Res. Int. 37 (2004) 139-148.


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Diban N., Athes V., Bes M., Souchon I., Ethanol and aroma compounds transfer study for partial dealcoholization of wine using membrane contactor, J. Membr. Sci. 311 (2008) 136-146. Drioli E., Criscuoli A., Curcio E., Membrane contactors and catalytic membrane reactors in process intensification, Chem. Eng. Technol. 26 (2003) 975-981. Drioli E., Jiao B., Calabrò V., The preliminary study on the concentration of orange juice by membrane distillation. In Proceedings of VII International Citrus Congress, Acireale, Italy, 1992. Geerken M.J., Lammertink R.G.H., Wessling M., Tailoring surface properties for controlling droplet formation at microsieve membranes, Colloids Surf. A 292 (2007) 224-235. Giorno L., Li N., Drioli E., Preparation of oil-in-water emulsions using polyamide 10 kDa hollow fiber membrane, J. Membrane Sci. 217 (2003) 173-180. Giorno L., Mazzei R., Oriolo M., De Luca G., Davoli M., Drioli E., Effects of organic solvents on ultrafiltration polyamide membranes for the preparation of oil-in-water emulsions, J. Colloid Interface Sci. 287 (2005) 612-623. Gryta M., Osmotic MD and other membrane distillation variants, J. Membr. Sci., 246 (2005) 145-156. Hogan P. A., Sudjito, Fane A.G., Morrison G.L., Desalination by solar heated membrane distillation, Desalination, 81 (1991) 81-90. Hogan P.A., Canning R.P., Peterson P.A., Johnson R.A., Michaels A.S., A new option: osmotic distillation, Chem. Eng. Prog. 94 (1998) 49-61. Hosoya K., Bendo M., Tanaka N., Watabe Y., Ikegami T., Minakuchi H., Nakanishi K., An application of silica-based monolithic membrane emulsification technique for easy and efficient preparation of uniformly sized polymer particles, Macromol. Mater. Eng. 290 (2005) 753-758. Jiao B., Cassano A., Drioli E., Recent advances on membrane processes for the concentration of fruit juices: a review, J. Food Eng. 63 (2004) 303–324. Joscelyne S. M., Trägårdh G., Food emulsions using membrane emulsification: conditions for producing small droplets, J. Food Eng. 39 (1999) 59-64. Joscelyne S.M., Trägårdh G., Membrane emulsification - a literature review. J. Membr. Sci., 169 (2000) 107-117. Katoh R., Asano Y., Furuya A., Sotoyama K., Tomita M., Preparation of food emulsions using a membrane emulsification system, J. Membr. Sci. 113 (1996) 131-135. Laganà F., Barbieri G., Drioli E., Direct contact membrane distillation: modelling and concentration experiments, J. Membr. Sci. 166 (2000) 1–11 Lawson K.W., Lloyd D.R., Membrane distillation, J. Membr. Sci., 124 (1997) 1-25. Mine Y., Shimizu M., Nakashima T., Application of size-controlled microporous glass membranes for designing simple and multiple emulsions, Recent Res. Devel. Agricultural Food Chem. 3 (1999) 131-137. Muschiolik G., Dräger S., Scherze I., Rawel H. M., Stang M., Protein-stabilized emulsions prepared by the micro-porous glass method, in Food Colloids: Proteins, lipids and polysaccharides, ed by Dickinson. Royal Society of Chemistry, Cambridge, pp 393-400 (1997). Nakashima T., Shimizu M., Kukizaki M., Membrane emulsification by microporous glass, Key Eng. Mat. 61-62 (1991) 513-516.

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Nakashima T., Shimizu M., Kukizaki M., Particle control of emulsion by membrane emulsification and its application, Adv. Drug Deliv. Rev. 45 (2000) 47-56. Peng S. J., Williams R. A. Controlled production of emulsions using a crossflow membrane, Chem. Eng. Res. Des. 76 (1998a) 894-901. Peng S. J., Williams R. A., Controlled production of emulsions using a crossflow membrane, Part. Part. Syst. Charact., 15 (1998b) 21-25. Ramteke R. S., Eipeson W. E., Patwardhan M. V., Behaviour of aroma volatiles during the evaporative concentration of some tropical fruit juices and pulps, J. Sci. Food Agri. 50 (1990) 399–405. Ribeiro H. S., Rico L. G., Badolato G. G., Schubert H., Production of O/W emulsions containing astaxanthin by repeated premix membrane emulsification, J. Food Sci. 70, 2 (2005) 117-123. Schadler V., Windhab E.J., Continuous membrane emulsification by using a membrane system with controlled pore distance, Desalination, 189 (2006) 130-135. Scherze I., Marzilger K., Muschiolik G., Emulsification using micro porous glass (MPG): surface behaviour of milk proteins, Colloids Surf. B 12 (1999) 213-221. Schröder V., Schubert H., Influence of emulsifier and pore size on membrane emulsification, Spec. Publ. –R. Soc. Chem. 227 (1999) 70-80. Shima M., Kobayashi Y., Fujii T., Tanaka M., Kimura Y., Adachi S., Matsuno R., Preparation of fine W/O/W emulsions through membrane filtration of coarse W/O/W emulsion and disappearance of the inclusion of outer solution, Food Hydrocolloids, 18 (2004) 61-70. Sirkar K. K., Shanbhag P. V., Kovvali A. S., Membrane in a reactor: a functional perspective, Ind. Eng. Chem. Res. 38 (1999) 3715-3737. Song S.H., Cho Y.H., Park J., Microencapsulation of Lactobacillus casei YIT 9018 using a microporous glass membrane emulsification system, J. Food Sci. 68 (2003) 195-200. Suzuki K., Fujiki I., Hagura Y., Preparation of corn oil/water and water/corn oil emulsions using PTFE membranes, Food Sci. Technol. 4 (1998) 164-167. van der Graaf S., Schroën C. G. P. H., Boom R. M., Preparation of double emulsions by membrane emulsification- a review, J. Membr. Sci. 251 (2005) 7-15. Vladisavljević G. T., Williams R. A., Recent developments in manufacturing emulsions and particulate products using membranes, Adv. Colloid Interface Sci. 113 (2005) 1-20. Vladisavljević G. T., Schubert H. Preparation and analysis of oil-in-water emulsions with a narrow droplet size distribution using Shirasu-porous-glass (SPG) membranes. Desalination, , 144 (2002) 167-172. Yamazaki N., Naganuma K., Nagai M., Ma G.-H., Omi S., Preparation of w/o (water-in-oil) emulsions using a PTFE (polytetrafluoroethylene) membrane- A new emulsification device, J. Dispersion Sci. Technol. 24 (2003) 249-257. Yamazaki N., Yuyama H., Nagai M., Ma G.H., Omi S., A comparison of membrane emulsification obtained using SPG (Shirasu Porous Glass) and PTFE [poly(tetrafluoroethylene)] membranes, J. Dispersion Sci. Technol. 23 (2002) 279-292. Zhu J., Barrow D., Analysis of droplet size during crossflow membrane emulsification using stationary and vibrating micromachined silicon nitride membranes, J. Membr. Sci. 261 (2005) 136-144. Zúñiga R.N., Aguilera J. M., Aerated food gels: fabrication and potential applications, Trends Food Sci. Technol. 19 (2008) 176-187.



Chapter 13

POSSIBILITIES FOR REMOVAL OF GLUCOSE FROM VARIOUS FOODSTUFFS AND FOOD BIOPROCESSES K. Bélafi-Bakó* University of Pannonia Egyetem u. 10., 8200 Veszprem, Hungary

ABSTRACT In many areas of food industry removal of glucose is considered as an important step in the processing line. In some raw materials – like eggs – glucose concentration should be reduced to avoid undesired co-reaction during drying process. In the beverage industry glucose level of certain fruit juices needs to be controlled/lowered either to produce lowcaloric beverages or to get low-alcohol wine after fermentation (e.g. grape must). In addition glucose removal is a significant step in some enzymatic processes like polysaccharide hydrolysis or fructo-oligosaccharide synthesis, where glucose is an inhibitory by-product. Separation methods applicable for glucose removal are discussed and compared in this chapter.

INTRODUCTION Glucose (C6H12O6) belongs to the group of monosaccharides and is considered as one of the key platform compounds in industrial biotechnology, since it is a raw material for numerous fermentation processes. Lactic acid, malic acid, citric acid and other acidic compounds, moreover many low molecular weight food industrial components can be fermented from glucose [Smith, 2004]. It is the monomer of starch and cellulose, which are – due to their high glucose content – the basic substances of biorefineries [Kamm, 2007]: the biomass based alternatives of fine chemical industry. *

Email: [email protected]

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Removal and/or recovery of glucose are therefore becoming highly important processes. Its separation is generally based on the size difference, e.g. in case of polysaccharide – glucose mixture. For this purpose membrane separation techniques seem attractive, due to their advantageous features (mild reaction conditions, no hazardous waste formed, low energy consumption and environmental-safe processes). Among membrane processes pressure driven techniques – where size of the molecules plays an important role – should be selected. The most promising technique is ultrafiltration, where porous membranes with a proper pore size can be applied. These ultrafiltration membranes are able to retain the polysaccharides, while glucose pass through the membrane [Drioli, 1999]. Glucose is usually difficult to separate from a mixture containing molecules with similar size and chemical character. In these cases special methods are needed. Among them one of the most successful methods is the enzymatic conversion, since the active centre of the enzymes is highly specific for the substrate, thus glucose can be selectively bound and converted by the given enzyme. Glucose oxidase (GOD, E.C. 1.1.3.4.) is the enzyme [Dixon, 1964] mostly used for the particular purpose. In the process glucose is converted into glucono-1,5-lactone, which spontaneously hydrolyses non-enzymatically to gluconic acid using molecular oxygen and releasing hydrogen peroxide. GOD β-D-glucose + O2

D-gluconic acid + H2O2.

Hydrogen peroxide, the by-product of the reaction is an effective bacteriocide [Tucker, 1995] on one hand, but has an inactivation effect on the GOD enzyme, on the other hand. Therefore it should be degraded or removed from the system. Another enzyme, catalase (E.C. 1.11.1.6.) is able to convert it to water and molecular oxygen: catalase H2O2

H2O + 1/2 O2.

For most applications the two enzymatic activities are not separated. Glucose oxidase and catalase may be used together when net hydrogen peroxide production is to be avoided. The enzyme mixture can be produced by various moulds (e.g. Aspergillus) and applied without separation. The method is useful for oxygen removal, as well, e.g. from the head-space above bottled and canned drinks and reducing non-enzymatic browning in wines and mayonnaises [Tucker, 1995].

REMOVAL OF GLUCOSE FROM FOODSTUFFS Eggs In food industry eggs are usually processed to manufacture powdered whole eggs by spray drying, or – after separation of the constituents – powdered egg whites and yolk. In all processes the problem is the Maillard browning caused by the reaction of glucose and egg

Possibilities for Removal of Glucose From Various Foodstuffs…

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protein (mainly mucin) [Nagodawithana, 1993]. Removal of glucose (desugaring) can be used to prevent the undesirable reaction. It is quite difficult to find a suitable separation process for glucose removal from a common, but natural substance like an egg, having special texture. Its conversion into gluconic acid seemed a promising method. Since gluconic acid has no reducing end group it can not take part in the Maillard reaction and browning can be avoided. In our laboratory glucose oxidase and catalase enzyme system was immobilized in an anion exchange resin and used in a three-unit, packed column (fluid bed) reactor, where egg white was flown through. Volume of the reactor was 46 l. Since the reaction needs oxygen, proper aeration had to be ensured in the system. However, the traditional aeration system caused severe foaming. To avoid it a special method was developed: a perforated silicon tube was placed inside the reactor in spiral wound and this provided the air (oxygen) for the enzymatic reaction (Figure 1).

Figure 1. Scheme of the bioreactor for glucose elimination from egg white. 1) bottom part of the reactor unit, 2) upper part with window 3) bottom closing part, 4) upper closing part, 5) stirrer motor, 6-7) inlet and outlet for the egg white, 8) outlet for recirculation of white egg, 9) inlet for addition of catalyst, 10) unload, 11) manometer, 12) oxygen electrode.

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The immobilized enzyme system in the reactor was able to reduce the initial 4 g/l glucose concentration down to 0.02 g/l, with 910 l/day capacity and the volumetric productivity of the reactor was 19.8 l white egg /day/l reactor volume.

Beverages Low-caloric, non-alcoholic valuable beverages – having valuable constituents to contribute to the healthier life and low-caloric diet– can be manufactured from fruit juices. The high-caloric monosaccharides (sugars) of these juices can be removed resulting in reduced caloric value. One of the most promising techniques is application of the glucose oxidise-catalase system for glucose removal – similar to grape must (see below). Low alcoholic beverages are becoming more and more popular recently. Alcohol-free bier and low-alcohol wine are two relevant examples among them. In both manufacturing process ethanol can be removed by some selective separation process. In case of wine, however, there is an alternative method: reduction of fermentable carbohydrate content of the grape must before fermentation, instead of wine treatment. The fermentable sugar content of wine consists of approximately 50 % glucose and 50 % fructose, depending on the maturation, climate, grape species and local conditions. To reduce sugar content harvesting of the grape prior to maturation can be used, but it results in higher acid level and weak aroma profile in the wine obtained after fermentation. Another process is the enzymatic treatment of the fermentable sugars. Glucose oxidase enzyme is able to convert glucose into gluconic acid, which can not be metabolised into ethanol by yeasts, thus less amount of ethanol is formed during fermentation [Heresztyn, 1987]. During the process of glucose conversion by glucose oxidase in grape must the most important factor is the low pH value, which is optimal for the enzymatic reaction [Pickering, 1999a]. In the experiments aimed to manufacture low-alcohol white wine 40 % reduction of ethanol content was achieved, but the ratio of non-volatile compound was a bit altered: higher amount of ester and oleic acid was present. Moreover, the colour of the wine obtained from treated must was deeper, its SO2 content increased compared to the reference wine [Pickering, 1999 b and c] The acid level of the wine was raising, as well, due to the gluconic acid formed. To compensate it, grape must of must concentrate can be added to the wine in order to enhance the organoleptic features [Pickering, 1999d and 2000]. Utilisation of glucose oxidise is not permitted in numerous countries, though its source, Aspergillus niger produces many types of enzymes for food industrial processes. This glucose removal technique nowadays are only applied for low-alcohol white wine production according to the literature, however it is possible to use is for red wines, as well, by slightly modifying the operational parameters. Comparing the quality of tradition and low-alcohol wines, experts found splitting of aroma-equilibrium and lack of “fullness” in low-alcohol wines [Howley, 1992]. Concerning organoleptic properties, the wines having less than 6 % alcohol are placed between the traditional wine and the grape must [Duerr, 1988]. These altered organoleptic properties are directly connected with the lower alcohol content. When alcohol is removed from the wine, especially by using thermo-processes, a characteristic boiled taste is appearing in the wine, moreover undesirable compounds may be formed due to the heat effect. Therefore the


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enzymatic glucose removal from the grape must (before fermentation) seems a promising and mild technique for low-alcohol wine production, which may result in higher quality.

RECOVERY OF GLUCOSE FROM ENZYMATIC FOOD PROCESSES Polysaccharide Hydrolysis Hydrolysis of polysaccharides like starch and cellulose results in glucose which is an important raw material for various food products. One of them is high-fructose corn syrup (HFCS), an alternative of sweetener and mainly applied in production of biscuits, cereal based food wares….. Moreover many different fermentation products (ethanol, organic acids…etc.) can be manufactured based on glucose. Degradation of polysaccharides can be carried out either by using strong acids or by enzymes. Nowadays the enzymatic way seems more attractive due to its environmental and economical advantages. The kinetics of the enzymatic starch hydrolysis by amylases has been studied for long and it was found that strong product inhibition occurred [Nagy, 1992; Law, 1993]. The mechanism of the inhibition caused by the glucose formed during the process by e.g., glucoamylase enzyme (1,4-α-D-glucan glucohydrolase, E.C. 3.2.1.3.) was described as a competitive inhibition and the inhibition constant (KI) was determined as 0.82 g/l [Koutinas, 2001]. Due to the strong inhibition effect – and since starch hydrolysis is carried out in continuous mode of operation – glucose should be removed during the hydrolytic reaction to enhance productivity. Separation is based on the different size of starch, enzyme and glucose. Since glucose is much smaller than the others, membrane separation seems suitable for it. Among pressure driven membrane processes ultrafiltration – as mentioned earlier – has a proper retention for the substrate and enzyme, while the membrane pores are able to let glucose pass through. Moreover – due to the desirable continuous operation – it is sensible to integrate the product separation step into the bioprocess, and ultrafiltration membrane modules can be easily inserted to these systems [Drioli, 1999]. Hollow fiber ultrafiltration membrane module for cassava starch hydrolysis by Aspergillus niger glucoamylase has been used by Spanish researchers [Lopez-Ulibarri, 1997], where the enzyme was in soluble form. Also cassava starch was the substrate in another work with membrane bioreactor [Paolucci-Jeanjean, 2000], but the enzyme used was an α-amylase from Bacillus licheniformis and Carbosep (50 kDa) membrane was applied. Glucoamylase from Aspergillus niger was immobilized onto a ceramic membrane in the hydrolytic process developed by Ida et al. (2000). Wheat starch and glucoamylase from Aspergillus awamori was used in the work of Frater (2005), where a flat ultrafiltration membrane module was applied as a membrane bioreactor and continuous hydrolysis was realised (Figure 2). During the starch hydrolysis by glucoamylase glucose was continuously removed and collected, thus pure glucose solution was obtained as a permeate and product inhibition was completely avoided, resulting in higher productivity.

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feeding vessel

overflow pipe

condenser membrane module

equalizer container

reactor

magnetic stirrer

Figure 2. Scheme of the membrane bioreactor for starch hydrolysis.

Hydrolysis of cellulose – the other highly important, abundant polysaccharide – is more difficult to achieve than that of the other polysaccharides (starch). The difficulties involve slow reaction rate, lack of an ideal reactor system, complexity of interfacial heterogeneous hydrolysis influenced by various factors, e.g. structure and composition of cellulosic materials, cellulase adsorption and desorption, enzyme inhibition by cellobiose and glucose [Wald, 1984; Lee, 1996; Mansfield, 1999]. The product inhibition – like in stach hydrolysis – can be solved by ultrafiltration membrane which are built into the system and operated as membrane bioreactors. Experimental data on cellulose hydrolysis in membrane bioreactor are summarized in Table 1. It is clear from these data that glucose/cellobiose inhibition could be reduced significantly by the use of suitable membranes, which are able to allow glucose through the membrane while retaining the macromolecules. All of the membranes applied were ultrafiltration membranes (polymeric or inorganic) having a cut off between 10 and 50 kDa. In most cases the solution of substrate and enzyme was recirculated in the primary side of the membrane reactor. It was found that the cellulose particles present in the substrate solution caused severe fouling in the membrane bioreactor resulting in remarkable flux decline. Therefore, in most papers in this area the main purpose was to reduce the fouling either by vigorous stirring in the primary side of the membrane (flat sheet modules) or by increasing the transmembrane pressure for higher permeate flux. Enzymatic saccharification of cellulose in a special tubular membrane reactor was studied [Belafi-Bako, 2006], where a hairy textile layer was wounded around the stainless steel tube membrane. It had a positive effect on the process, since simultaneous immobilisation of the biocatalyst and the substrate onto the surface (prior to the hydrolysis) was possible. Thus the special membrane reactor was able not only to retain the biocatalysts


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and to separate the inhibitory products (glucose and cellobiose), but to enhance the efficiency of the enzymatic reaction (conversion, productivity), as well. Table 1. Experimental data on enzymatic cellulose hydrolysis in membrane bioreactors Substrate Type Oven dried Solka Floc BW200 Solka Floc SW40, BW200, Sugarcane bagasse, Sorghum stubble, Peanut shell Pretreated sallow Salix Q 082

KC Floc (SanyoKokusaku Pulp. Co., Japan) α-cellulose Pretreated, milled olive mill solid residue (OMSR) α-cellulose (Sigma) Pretreated Mavicell

Initial Converconc. sion 1% 70 %

Membrane

Cut off Temp. o C kDa

Amicon PM 10

10

50

0.45 g/l

91 %

Amicon XM50 50 Romicon XM50

50

10 %

50-80 %

Polyamide BM100, Berghof Germany UP 20 (ToyoRoshi Co. Japan) Amicon Carbosep M5 (ZrO2 mineral)

10 %

55-60 %

4%

45%

2.5 % 53 % 1% 70 %

Amicon PM 10 Textile covered stainless steel tubular

40

References Howell, 1975 Henley, 1980

Ohlson, 1984

20

37

Kinoshita, 1986

10 10

50

Lee, 1993 Maneri, 2000

10 45

40 40

Gan, 2002 BelafiBako, 2006

As a summary, glucose removal during polysaccharide hydrolysis can be successfully carried out in membrane bioreactors, where ultrafiltration membranes are applied. The small molecular weight products, e.g. glucose is able to pass through the membrane, while the high molecular weight substrates and enzymes are retained. Moreover an important advantage of the membrane bioreactors is that they make recovery and reuse of biocatalysts possible and in such a system continuous uptake of substrate and release of product without loss of biocatalysts can be achieved.

Synthesis of Fructo-Oligosaccharides Nowadays the so-called functional foods are considered as important part of our diet and contain useful components that have beneficial effects on health conditions [Blandino, 2001]. Typical representatives of functional foods are fructo-oligosaccharides (FOSs). Their significance has raised recently in human and animal nutrition, mainly because of the

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advantageous effects on the intestinal bacterial population and general health conditions in the body [Bornet, 2002]. FOSs are able to reach the colon where they are fermented by the microbial flora (e.g. Bifidobacteria sp., Lactobacillus sp.) to lactate and short chain fatty acids, like acetate, propionate, butyrate. Consequently, FOSs stimulate the growth and vitality of these microbes and prevent spreading of the harmful pathogens. In addition, they have low sweetness intensity, their caloric value is low, approximately 8-9 kJg-1 and cause no caries. So they can be applied as alternative sweeteners, as well [Losada, 2002; Fooks, 1999]. Short chain FOSs are mainly composed of 1-kestose (GF2), nystose (GF3) and fructosylnystose (GF4), where two, three and four fructose units are bound to one unit of glucose, respectively (Figure 3). They can be found in plants and vegetables, including onion, asparagus, rice, sugar beet, wheat, etc. but generally in low concentration. The industrial scale recovery from these plants is not economical since their low concentration, for this reason, FOSs are produced commercially via biosynthetic as well as hydrolytic methods using fructosyl-transferase (FTF) enzyme. The raw material of the synthetic reaction is sucrose and the product mixture contains unconverted sucrose besides GF2, GF3 and GF4 and glucose as a by-product [Yun, 1996]. The latter component is a strong competitive inhibitor of the synthesis [Sheu, 2001]. Elimination of the formed by-product component can result an increase in the product yield. For this purpose special separation methods can be applied: e.g. chromatographic separation or enzymatic method like elimination by glucose oxidase.

Figure 3. Structure of short chain FOSs: 1-kestose (GF2), nystose (GF3) and fructosyl-nystose (GF4).

To realise the complex system, an immobilised FTF enzyme preparation for the synthesis of fructo-oligosaccharides (15.6 U g-1) was developed, on one hand; and for the elimination of glucose a co-immobilized glucose oxidase-catalase solid-phase biocatalyst was manufactured, on the other hand [Sisak, 2006]. Hydrogen peroxide formed in the reaction is an inhibitor for the enzyme, so it should be removed from the reaction mixture. In this system catalase was applied for the decomposition of H2O2. Based on the results of the shaken flask experiments a complex reactor system was constructed for the integrated fructo-oligosaccharides production and glucose elimination [Csanadi, 2008]. The reactor unit for fructo-oligosacharides production was tempered to 53°C, the other was operated at 25°C. In the system the two reactor units were connected. One of them was


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filled with 10 g immobilized Pectinex Ultra SP-L, the other was filled with 5 g coimmobilized glucose oxidase-catalase, and 130-130 cm3 sucrose solution (2 M, pH=5.6, 0.05 M acetate buffer) was added. The reaction mixtures were changed between the two reactor units in every second hour, so the reaction and glucose elimination were carried out consequently in numerous cycles. In the synthesis of fructo-oligosaccharides in shaken flask experiments with immobilized fructosyl-transferase enzyme ~60 % product yield was reached, while in the integrated reactor system for the simultaneous FOS synthesis and elimination of glucose higher (~74 %) product yield was achieved.

SUMMARY Removal possibilities of glucose from foodstuffs and food bioprocesses were discussed in this chapter. One of the separation processes presented was a membrane technique: ultrafiltration, which can be applied in case of significant size difference between the compounds of the mixture to be separated (e.g. glucose – polysaccharides). The other separation method is the application of glucose oxidase – catalase enzyme system, which is able to convert glucose selectively, thus it is possible to remove it from various mixtures.

ACKNOWLEDGMENTS The author would like to thank Ms Eva Lövitusz and Dr. Zsofia Csanadi for the technical help in the measurements and preparing the manuscript.

REFERENCES Alfani, F., Cantarella, M. & Scardi, V. (1983). Use of a membrane reactor for studying enzymatic hydrolysis of cellulose. J. Membr. Sci. 16, 407-416. Belafi-Bako, K., Koutinas, A., Nemestothy, N., Gubicza, L. & Webb, C. (2006). Continuous enzymatic cellulose hydrolysis in a tubular membrane bioreactor, Enz Microb Technol. 38, 155-161. Belafi-Bako, K. (2007). Enzymatic Processes and Fermentation. in Handbook of Waste Management and Co-product Recovery in Food Processing, ed. by Waldron, K., Woodhead Publishing Ltd, Cambridge. 198-216. Belafi-Bako, K. (2008). Simultaneous application of enzymes and membranes in food processing, in Food Engineering Research Trends, Ed. by Jerrod, M Cantor, Nova Science Publishers, New York. 263-279. Blandino, A., Macias, M. & Cantero, D. (2001). Immobilization of glucose-oxidase within calcium alginate gel capsules. Process Biochem. 36, 601-606. Bornet, F.R.J., Brouns, F., Tashiro, Y. & Duvillier, V. (2002). Nutritional aspects of shortchain fructooligosaccharides: natural occurence, chemistry, physiology and health implications. Dig. Liver Dis. 34, 111-120.

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Csanadi, Z. & Sisak, C. (2008). Production of short chain fructooligosaccharides. Hung. J. Ind. Chem. 36, 23-26. Dixon, M. & Webb, E.C. (1964). Enzymes. Longmans, London. Drioli, E. & Giorno, L. (1999). Biocatalytic membrane reactors. Taylor and Francis Group, London. Duerr, P. & Cuenat, P. (1988):.Production of dealcoholised wine In: Smart, R., Thornton, R. Rodriguez, S. & Young, J. (Eds.). Proc. 2nd Int. Symp. Cool Climate Viticulture and Oenology, Auckland, New Zealand, 363-364. Fooks, L., Fuller, R. & Gibson, G.R. (1999). Prebiotics, Probiotics and human gut microbiology. Int. Dairy J. 9, 53-61. Frater, T., Nemestothy, N., Gubicza, L. & Belafi-Bako, K. (2005). Enhancement of operation and storage stability of glucoamylase from Aspergillus awamori by a protease inhibitor preparation, Biocat. Biotrans. 23, 281-284. Frater, T., Gubicza, L., Szöllősy, A. & Bakos, J. (2006). Enantioselective hydrogenation in ionic liquids: Recyclability of the [Rh(COD)(DIPAMP)]BF4 catalyst in [bmim][BF4]. Inorg Chim Acta, 359, 2756-2759. Gan, Q., Allen, S.J. & Taylor G. (2002). Design and operation of an integrated membrane reactor for enzymatic cellulose hydrolysis. Biochem. Eng. J. 12, 223-229. Henley, R.G., Yang, R.Y.K. & Greenfield, P.F. (1980). Enzymatic saccharification of cellulose in membrane reactors. Enzyme Microb. Technol. 2, 206-208. Heresztyn, T. (1987). Conversion of glucose to gluconic acid by glucose oxidase enzyme in Muscat Gordo juice. The Australian Grapegrower and Winemaker, 4, 25–27. Howell, J.A. & Stuck, J.D. (1975). Kinetics of Solka Floc cellulose hydrolysis by Trichoderma viride cellulose. Biotechol. Bioeng. 17, 873-893. Howley, M. & Young, N. (1992). Low alcohol wines: the consumers choice? Int. J. Wine Marketing, 4, 45–46. Kinoshita, S., Wei Chua, J., Kato, N., Toshiomi, Y. & Taguchi, H. (1986). Hydrolysis of cellulose by cellulases of Sporotrichum cellulophilum in an ultrafilter membrane reactor. Enzyme Microb. Technol. 8, 691-695. Koutinas, A., Belafi-Bako, K., Kabiri-Badr, A., Toth, A., Gubicza, L. & Webb, C. (2001) Enzymatic hydrolysis of polysaccharides. Food Bioprod. Process 79(C1), 41-45. Law, C.S.R., Webb, C. and Williams, R.A. (1993) Kinetic studies on glucoamylase with maltodextrin as substrate, Chem. Eng. Res. Des. 71(A3), 296-298. Lee, X.G. & Kim, H.S. (1993). Optimal operating policy of the ultrafiltration membrane bioreactor for enzymatic hydrolysis of cellulose. Biotechnol. Bioeng. 42, 737-746. Lee, I., Evans, B.R., Lane, L.M. & Woodward, J. (1996). Substrate-enzyme interactions in cellulase systems. Bioresource Technol. 58, 163-169. Lopez-Ulibarri, R. and Hall, G.M. (1997) Saccharification of cassava flour strach in a hollow fiber membrane reactor. Enzyme Microbial Technol. 21, 398-404. Losada, M.A. & Olleros, T. (2002). Towards a healthier diet for the colon: the influence of fructooligosaccharides and lactobacilli on intestinal health. Nutrit. Res. 22, 71-84 . Maneri, N., Hamdache, F., Abdi, N., Belhocine, D., Grib, H., Lounici, H. & Piron, D.L. (2000). Enzymatic saccharification of olive mill solid residue in a membrane reactor. J. Membr. Sci. 178, 121-130. Mansfield, S.D., Mooney, C. & Saddler, J.N. (1999). Substrate and enzyme characteristics that limit cellulose hydrolysis. Biotechnol. Prog. 15, 804-16.


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Nagodawithana, T. & Reed, G. (eds) (1993). Enzymes in food processing, Academic Press, Harcourt Brace and Company, San Diego. Nagy, E., Bélafi-Bakó, K. & Szabó, P. (1992). A kinetic study of the hydrolysis of maltodextrin by soluble glucoamylase enzyme. Starch/Stärke, 44, 145-148. Ohlson, I., Tragardh, G. & Hahn-Hagerdal, B. (1984). Enzymatic hydrolysis of sodiumhydroxide pretreated sallow in an ultrafiltration membrane reactor. Biotechnol. Bioeng. 26, 647-653. Paolucci-Jeanjean, D., Belleville, M.P., Rios, G.M., Zakhia, N. (2000) Kinetics of continuous starch hydrolysis in a membrane reactor. Biochem. Eng. J. 6, 233-238. Pickering, G.J., Heatherbell, D.A. & Barnes, M.F. (1999A). Optimising glucose conversion in the production of reduced alcohol wines from glucose oxidase treated musts,.Food Res. Int. 31, 685–692. Pickering, G.J., Heatherbell, D.A. & Barnes, M.F. (1999B). The production of reduced alcohol wine using glucose oxidase-treated juice-composition, Am. J. Enol. Viticult. 50, 291–298. Pickering, G.J., Heatherbell, D.A. & Barnes, M.F. (1999C). The production of reducedalcohol wine using glucose oxidase-treated juice II., SO2-binding and stability, Am. J. Enol. Viticult. 50, 299–306. Pickering, G.J., Heatherbell, D.A. & Barnes, M.F. (1999D). GC-MS analysis of reducedalcohol Müller-Thurgau wine produced using glucose oxidase-treated juice, Trends in Food Sci. Technol. 34, 89-94. Pickering, G. J. (2000). Low- and Reduced-alcohol wine: A Review. J. Wine Res. 11, 129– 144. Sheu, D.C., Lio, P.J., Chen, S.T., Lin, C.T. & Duan, K.J. (2001). Production of fructooligosaccharides in high yield using a mixed enzyme system of betafructofuranosidase and glucose oxidase. Biotechnol. Lett. 23, 1499-1503. Sisak, C., Csanádi, Z., Rónay, E., Szajáni, B. (2006). : Elimination of glucose in egg white using immobilized glucose oxidase. Enz. Microbial Technol. 39, 1002-1007. Smith, J. S. & Hui, Y.H. (eds) (2004). Food processing: Principles and Applications, WileyBlackwell, New York. Tucker, G.A. & Woods, L.F.J. (eds.) (1995). Enzymes in food processing, Blackie Academic and Professional, London Wald, S., Wilke, C.R. & Blanch, H.W. (1984), Kinetics of the enzymatic hydrolysis of cellulose, Biotechnol. Bioeng. 26, 221-230. Yun, J.W. (1996). Fructooligosaccharides - Occurrence, preparation and application. Enz. Microbial Technol. 19, 107-117.



Chapter 14

INSTANT RICE PHYSICOCHEMICAL PROPERTIES AND EATING QUALITY Prisana Suwannaporn Kasetsart University, Bangkok, Thailand

ABSTRACT Instant, or quick-cooking, rice is becoming more popular nowadays. However, it still poses problems with respect to rehydration time and quality. The effects of processing factors which are: moisture content, pressure and drying temperature has a significant effect on its physicochemical properties and eating quality. The hardness and chewiness of rice decreased as moisture content and pressure increased. Higher drying temperatures caused increases in hardness and chewiness. Only pressure and moisture content affected density, rehydration ratio, and increase in the volume of instant rice, which was due to the porosity of the kernels. Rehydration ratio had a negative correlation with density (r= 0.886) but a positive correlation with volume increase (r = 0.637). Pressure was the main factor influencing the pasting properties of instant rice. All pasting properties of instant rice were far lower than those of milled rice, but instant rice had higher cold paste viscosity, which is typical of pregelatinized flour. This indicated rapid water absorption and shorter cooking time. Instant rice processing also caused development of amyloselipid complexes observed as the V-type pattern in an X-ray diffractometer

INTRODUCTION In modern lifestyles, instant food is becoming more popular. However, instant rice is still beset by the problems of long rehydration time and inferior quality compared to cooked milled rice . The texture of cooked rice is related to its amylose content and the fine structure of amylopectin. The intra- and/or intermolecular interactions of starch with other components in rice such as protein, lipid and non-starch polysaccharides results in a harder texture [1] (Ong and Blanshard, 1994). Moreover, processing conditions also affect the texture of cooked rice in a way similar to the parboiling process. The basic processes in preparing instant rice

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and parboiled rice are similar, consisting of soaking, steaming and drying. These processes have marked impacts on the organoleptic properties of cooked rice. Derycke et al. 2005a found that the heat-moisture conditions during parboiling, cooling and drying had impact on cooked parboiled rice [2]. They observed that the texture of cooked parboiled rice was usually firmer and less sticky than that of non-parboiled rice. This firmer texture was related to the level of crystalline amylose–lipid complexes formed during parboiling which were stable during the cooking process. According to Robert et al. (1972), dry grains of instant rice should be separate and should resemble milled rice in shape. Its bulk density should be 0.4-0.42 g/cm3 with a low percentage of broken kernels. After rehydration, the volume of instant rice should increase to 1.5-3 times that of dry grains, and its color, flavor and texture should be similar to cooked rice (Smith et al. 1985) with no hard core or ungelatinized center (Luh et al., 1980). Previous investigators tried to propose instant rice processes which were mainly concerned with three main factors: 1) the initial moisture content 2) the degree of gelatinization and 3) the drying or puffing method. The initial moisture content could be manipulated by the temperature of the water used in soaking and/or time. The initial moisture content has been reported to affect the product’s homogeneity (Baz et al., 1992), degree of gelatinization, percentage of broken kernels (Ahromit et al., 2006) and degree of starch leaching (Bello et al. 2004). Degree of gelatinization was related to cooking method, cooking time and/or temperature. Partial gelatinization (around 80%) (Smith et al., 1985) or complete gelatinization either by boiling or steaming have been proposed as necessary in the instant rice preparation process. High pressure cooking process resulted in more homogeneous gelatinization and reduced the percentage of broken kernels (Bhattacharya, 1985; Baz et al., 1992). Drying processes varied from single step drying at low temperature (70 ºC) for a long time (2-3 hours) to multi-step drying at high temperature for a short time to induce case hardening followed by low temperature drying for a long time to reduce moisture content (Robert et.al., 1972; OzaiDurrani, 1948). Other drying methods included the use of tray dryers or centrifugal fluidized bed dryers (Baz et al., 1992, Ramesh and Rao, 1996; Carlson et al., 1979), drum dryers (Robert et al., 1972; Lewis et al., 1991; Ando et al., 1980), a freeze-thaw process (Robert et al., 1972) and high pressure cooking (Leelayuthsoontorn and Thipayarat, 2006; Bhattacharya, 1985; Baz et al., 1992). Drying is a complex process involving simultaneous heat and mass transfer. Its results in significant changes in chemical composition, structure, and physical properties of foods. Heating process and loss of water cause stresses in the cellular structure that lead to changes in microstructure such as the formation of pores and shrinkage. (Banu et al., 2008) Instant food mostly invoved in freeze dried process which provide porous structure with little shrinkage, superior taste and aroma retention, and better rehydration. However, freeze dried process is uneconomical due to its large capital outlays, high operating cost and relatively long drying time. Several attempts have been made to reduce freeze-dried cost by applyng the combined drying process altogether with low atmospheric pressure drying or vacuum drying. Vacuum drying is an alternative method which is suitable for products that are sensitive to heat. However, heat transfer becomes difficult as convection is ineffective at low pressure (Giri and Prasad, 2007). Litvin et al. (1998) studied the combination of drying conditions by partial freeze drying of carrot slices followed by a short (50 s) microwave treatment and air or vacuum drying. The total process time was shortened considerably. The development of pores and shrinkage depended upon the variation in moisture transport mechanisms and the external

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pressure. The strength of the solid matrix can also be affected by ice formation, case hardening, permeability of crust, and matrix reinforcement (Rahman, 2003). Thus, the drying method and conditions applied has a significant effect on product characteristics such as porosity, shrinkage, and bulk density. The % rehydration of dehydrated foods depended on its water absorption capability and water holding capacity (Lewicki, 1998). Vacuum drying mostly used in fruit / vegetable accounted for its porous structure and high water holding capacity that ease heat transfer and promote water absorption during rehydration. ArévaloPinedo and Murr (2006) found that water penetration was highest in pumpkin slide which was frozen at -20 oC for 3 hrs prior to low pressure drying at 0.7 lb/in2 for 70 oC.

PROCESS OPTIMIZATION A five-level, three-variable central composite design (CCD) was applied to estimate the relationship between variables concerning texture and the whiteness index (WI) of instant rice. CCD consisted of eight factorial points, six axial points (two axial points on the axis of each design variable at a distance of 1.68 from the design center) and six center points, leading to 20 sets of experiments. The experiments were run in random order to minimize the effects of unexpected variability in the observed responses due to extraneous factors. Milled rice was soaked in water for various soaking times to obtain moisture contents of 35 – 60 % wet basis (X1; -1.68 to +1.68 level). After soaking, the rice grains were cooked under pressures of from 11.6 to 28.4 lb/in2 (X2; -1.68 to +1.68 level) for 5 min. Then, the cooked rice was dried using a tray dryer at temperatures from 166.4 to 233.6°C (X3; -1.68 to +1.68 level) to obtain a product with a moisture content of less than 12%. The variables and their process levels are shown in Tables 1. Table 1. Coded levels for independent variables used in developing experimental data

Factor Moisture Content (% wb) Pressure (lb/in2) Drying Temperature (°C)

Code X1 X2 X3

Level - α (-1.68) 34.90 11.60 166.36

-1 40 15 180

0 47.5 20 200

+1 55 25 220

+α (1.68) 60.10 28.40 233.64

The responses modeled as linear, quadratic and cubic functions of the three independent variables were tested for adequacy and model fitness using ANOVA. The selections of adequate models (Table 2) were determined using model analysis, lack-of fit test and Rsquare analysis (Chen et al., 2005). The ‘‘lack of fit test’’ compared the residual error to the pure error from replicated design points. The model with no significant lack-of-fit and high R2 was selected (Table 2). The results showed that hardness, chewiness, and whiteness index had high coefficient of determination (R2) which equaled 0.927 0.633 and 0.836, respectively, and no significant lack of fit (Table 3). Park et al. (2001) reported a high correlation between the instrumental texture parameters hardness and chewiness and the sensory attributes of cooked rice. Likewise, Prakash et al. (2005) found positive correlation between instrumental hardness and sensory

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hardness and chewiness in thermal processed rice. As a consequence, hardness and chewiness were used as the main responses in RSM for the texture of instant rice. Table 2. Regression coefficients of the polynomial function and the coefficients of determination (R2) Coefficient Hardness AdhesiveSpringiness Cohesive Gumminess Chewiness WI .4100 2,355.99* 78.24* 5,804.59* -943.58 .970 B0 2,439.98 .0219 -.013 0.17* -61.67* -378.58* 38.71 B1 -32.55 .0018 0.32* -82.90* B2 -287.67* -30.80 .005 -97.81 -.0029 -0.12* 97.82* 305.06* -38.35 .002 94.64 B3 .0024 -1.01* 157.06* 351.13* -41.34 .002 155.07 B12 .0133 .004 -0.34* -46.41* -276.76* 53.95 B13 -35.74 .0029 0.25* -32.79 .008 7.86* -18.85* -11.29 B23 -.0050 -.001 0.06* -106.56* -171.02* 52.59 -108.86 B11 -.0013 -.0006 -0.75* 9.10 -8.76* 4.24* -7.49 B22 -.0016 0.33* -26.86 .00005 19.00* 82.94* 17.15 B33 0.927 0.377 0.274 0.462 0.553 0.633 0.836 R2 0.425 0.113 0.043 0.032 0.062 0.054 Sig Lack-of0.072 Fit

INSTANT RICE TEXTURE Thirty grams of instant Jasmine rice was rehydrated with 110 ml. water and microwaved for 6 minutes. TPA was performed using a texture analyzer (TA-XT.plus, Stable Micro System, UK). Following Park et al. (2001). It was compressed to 60% with a rod-type probe (2.5 diameters) at a speed of 1.7 mm/sec. Hardness, adhesiveness, springiness, cohesiveness, gumminess and chewiness were determined.

1. Hardness Estimation of texture in terms of hardness and chewiness over independent variables X1, X2 and X3 is shown in Figure 1. Hardness of the rice decreased as the moisture content and pressure increased. But an increase in drying temperature caused a harder texture. The statistical analysis in Table 2 indicated that all variables had a significant effect on hardness, especially moisture content in linear, quadratic and interaction terms. At higher moisture content, thinner case hardening and bigger pore size were noticeable in the SEM images. High pressure induced high gelatinization, which also resulted in a softer texture in the rehydrated rice. The hardness of cooked instant rice had positive correlation with density (Table 3). Density was related to the porosity of the structure of processed rice seen in the SEM images. The cracks and pores in instant rice permitted rapid entry of water and heat transfer during cooking, resulting in a softer texture rehydrated rice.


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Figure 1. Contour plot of hardness of rehydrated instant rice as a function of instant rice process conditions

Table 3. Correlation coefficients between texture and physical properties of instant rice Texture Hardness Adhesiveness Springiness Cohesiveness Gumminess Chewwiness

Density .564 * -.123 .169 -.758** .102 .152

Rehydration Ratio -.291 .133 -.284 .756** .194 .125

Volumn Increase -.127 -.020 -.249 .481 .202 .144

*, ** significant at p < 0.05 and 0.01, respectively.

Figure 2. Contour plot of chewiness of rehydrated instant rice as a function of instant rice process conditions

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2. Chewiness Chewiness refers to number of chews required to masticate cooked rice before it was suitable for swallowing or the amount of work required to chew the sample for sensory evaluation. It was observed that pressure and drying temperature had main effects on chewiness. Initial moisture content affected chewiness in the interaction term and with pressure in the quadratic term (P < 0.05) (Table 2). Chewiness was decreased with increased pressure or drying temperature (Figure 2).

WHITENESS INDEX (WI) The whiteness of rehydrated rice was measured using a colorimeter (Chromameter model CR-300, Japan). Measurement was based on the Hunter system with color values of L, a and b. The measurements were performed in two replications and were repeated three times per replicate. The whiteness index (WI) was calculated as follows: WI = 100 – [(100 –L) 2 + a2 +b2]0.5 All factors influenced the whiteness index, especially pressure. At high moisture content, the whiteness index decreased when pressure increased (Figure 3). This result is in accord with the study on parboiled rice by Bhattacharya (1996), who found that pressure and steaming time had marked effects on product’s Hunter color. Yellowish color was prominent when paddy was parboiled for longer times. Islam et al. (2002) showed that brightness of parboiled rice decreased with the increase in steaming temperature. The deterioration of the whiteness of parboiled rice was more pronounced at higher temperatures. Leelayuthsoontorn and Thipayarat (2006) found that the WI of cooked rice decreased as the cooking temperature increased. The cooking temperature was clearly an important factor influencing WI. However, at low moisture content, the whiteness index also decreased with increased in pressure.

Figure 3. Contour plot of whiteness index of rehydrated instant rice as a function of instant rice process conditions


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INSTANT RICE GRAIN STRUCTURE drying temperature 220 °C

Pressure 25 lb/in

2

Pressure15 lb/in

2

drying temperature 180°C

Pressure 25 lb/in

2

Pressure 15 lb/in

2

(a) moisture content 40%

(b) moisture content 55%

Figure 4. Scanning electron micrographs transverse of instant rice (dry grain) at different pressure and drying temperature treatment at (a) 40% moisture content (b) 55% moisture content

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SEM of instant rice samples were taken with a Hitachi TableTop/Tischmikroskop model TM-1000 at magnitude x 80. The samples were prepared by breaking a rice kernel at the center and sticking it on the stub without a gold film coating. The SEM images showed that instant rice grains had a hollow structure and were case hardened (Figure 4). In the soaking step, the increase in grain dimensions has been attributed to the swelling of starch granules and subsequent widening of cracks in the grain by water diffusion (Ahromrit et al., 2006). Puffed kernels, in which could be seen larger hollow centers, occurred noticeably when both pressure and drying temperature increased altogether. The puffing phenomenon resulted from the sudden expansion of water vapor in the granule. In the drying step, moisture was removed from the surface of the rice grains faster than from the interior (Baz, 1992). The surface of rice became slightly harder than the center during drying (Lin, 2002). This caused case hardening, which blocked water vapor leaching during the drying process and resulted in puffing of the grain, giving it a larger, hollow structure in the center that allows easy rehydration.

DENSITY, REHYDRATION RATIO AND VOLUME INCREASE The results in Table 4 show that only pressure and moisture content affected density, rehydration ratio and volume increase. Leelayuthsoontorn and Thipayarat (2006) also found that high pressure caused larger pore size and thickness with a sponge-like texture. As a consequence, low density rice was obtained under conditions of high moisture and high pressure. The rehydration ratio had a negative correlation with density (r = -0.546) and a positive correlation with volume increase (r = 0.542). Rice was rehydrated more rapidly because of the increase in its surface area as its volume increased. Table 4. Analysis of variance showing the effect of variable as a linear terms and interaction (cross product) on response parameters. Source X1 X2 X3 X1*x2 X1*x3 X2*x3 X1*x2*x3

Density 18.590* 4.573* 0.444 0.022 2.319 3.641 3.572

Rehydration ratio 8.047* 0.619 1.457 2.322 0.160 0.017 0.906

Volume Increase 1.990 2.778 2.707 11.185* 0.953 1.509 1.124

* significantly different at the 95% confidence level

INSTANT RICE PASTING PROPERTIES Pasting properties of instant rice were determined using a Rapid Visco Analyzer (Rapid Visco Analyzer model RVA3D Newport Scientific Instruments and Engineering, Australia) according to AACC standard method no.61-02 (AACC, 1995). Paste viscosity plotted in arbitrary RVA units (RVU) versus time was used to determine the peak viscosity (PV),


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trough viscosity, final viscosity (FV), breakdown viscosity (BKD = PV- trough), and setback viscosity (SB = FV - trough). Result showed that the integrity of the starch granule and its hydration properties can be investigated easily by measuring the pasting behavior of rice flour before and after treatment. All pasting properties of instant rice were far lower than those of milled rice (Figure 5), but instant rice showed higher cold paste viscosity, which is the typical hydration property of pregelatinized flour (Lai, 2001).

Figure 5. Rapid Visco Amylograph showed pasting properties of milled rice flour and instant rice flour

The disruption of molecular order within starch granules during steaming caused loss of starch granule integrity and the destruction of crystallinity, resulting in cold soluble starch (Lai, 2001) and a decrease in the magnitude of all pasting properties. A similar observation was previously reported (Hagenimana et al., 2006). Unlike pregelatinized starch, peak viscosity was still observed in instant rice flour, which indicated the presence of partially ungelatinized starch polymers. Increase in pressure caused degradation and gelatinization of starch. The RVA profile of instant rice indicated that instant rice could absorb water more rapidly and required a shorter cooking time than milled rice. It indicated granule rigidity and molecular re-association, which were significantly enhanced by the hydrothermal treatment. The change in pasting properties depended mainly on the combined effects of moisture, pressure and drying temperature. However, the formation of disulphide bonds in the protein fraction and the complexation of lipid with amylose also had effects. Derycke et al. (2005b) suggested that the formation of disulphide bonds during the parboiling process restricted starch granule swelling capacity. Moreover, the formation of starch lipid complexes also restricted the swelling capacity, hence lowering the pasting properties.

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AMYLOSE - LIPID COMPLEXES X-ray diffraction patterns of instant rice flour were obtained with a diffractometer (JEOL, model JDX-3530, Japan) using monochromatic Cu-K α radiation 1.542 A˚. The diffractometer was operated at 40 kV, 45 mA and the spectra scanned over a diffraction angle (2θ) range of 5-40˚ at a step size of 0.02˚ 2θ per sec. Percentage of crystallinity was calculated as the percentage of peak area to the total diffraction area using this equation (Cheetam et al., 1998):

% Relative crystallinity

=

Area above the smooth curve × 100 Total diffraction area above the baseline

Amylose-lipid complex formation depended on both heat and moisture applied during the instant rice preparation process. A-type crystallinity was either greatly reduced or completely destroyed. The effect of process conditions on the formation of crystalline amylose–lipid complexes was investigated using XRD as shown in Figure 6.

Figure 6. X-ray diffraction of milled rice flour (A) and instant rice flour (B-E)

The X-ray patterns of milled rice showed the A pattern which disappeared in instant rice. Instant rice showed the V-type pattern, or the intensity of the reflections at 2θ =13 and 20º. This result indicated that the instant rice preparation process destroyed the crystalline structure of the starch granules. This result agrees well with Miyoshi (2002) and Shih et al. (2007) found that the formation of amylose-lipid complexes occurred during heat-moisture treatment of starch, as indicated by the occurrence of the V-type pattern. Before


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gelatinization, starch had limited binding capacity with lipid because most of the lipid in the system was unable to come into contacted with starch (Pilli et al., 2008). After gelatinization, the V-type pattern was detected either because more complexes were formed during heating or the crystalline regions had increased in size. The V-type crystal pattern was greatest when the highest pressure was used in the process. A similar result was also observed in the parboiling process, in which amylose-lipid complexes were created during the heating step. The diffraction lines of amylose-lipid complexes increased progressively with the degree of parboiling. (Priestley, 1976; Biliaderis et al., 1993; Derycke, 2005a).

CONCLUSIONS Processing conditions affected the physical and physicochemical properties of instant rice. The hardness and chewiness of rehydrated rice was decreased as moisture content and pressure increased. At high moisture content, the whiteness index decreased when pressure increased. Only pressure and moisture content affected density, rehydration ratio, and volume increase because they increased the kernel’s porosity, as demonstated by the SEM image. The cracking and puffing in the structure of instant rice were important to the texture of the rehydrated rice. Pressure was the main factor influencing the pasting properties of instant rice. All pasting properties of instant rice were far lower than those of milled rice. But instant rice showed higher cold paste viscosity, which is the typical hydration property of pregelatinized flour. The instant rice preparation process caused development of amylose-lipid complexes observed as the V-type pattern in the X-ray diffractometer.

REFERENCES American Association of Cereal Chemists. Approved Methods of the AACC (10th ed.) Method 61-02, (2000). A. Ahromrit, D.A., Ledward, and K. Niranjan, Journal of Food Engineering. 72, 225 (2006). M. Ando, J. Minami, M. Takata, F. Ohinishi, and S. Kawamoto. United State Patent No. 4,233,327, (1980). A.A.. Baz, J.Y. Hsu, and E. Scoville. United State Patent No. 5,089,281. (1992). M. Bello, R. Baeza, and M.P. Tolaba. Journal of Food Engineering. 72, 124 (2006). S. Bhattacharya. Journal of Food Engineering. 29, 99 (1996). C.G. Biliaderis, J.R. Tonogai, C.M. Perez, and B.O. Juliano. Cereal Chemistry. 70, 512 (1993). R.A. Carlson, R.L. Roberts, and D.F. Farkas. United State Patent No. 4,133,898 (1979). N.W.H. Cheetam, and L. Tao. Carbohydrate Polymers. 36, 277(1998). M.J. Chen, K.N. Chen, and C.W. Lin. Journal of Food Engineering. 68, 471(2005). V. Derycke, G.E. Vandeputte, R. Vermeylen, W. De Man, B. Goderis, M.H.J. Koch, and J.A. Delcour. Journal of Cereal Science. 42, 334 (2005a). V. Derycke, G.E. Vandeputte, R. Vermeylen, W. De Man, B. Goderis, M.H.J. Koch, and J.A. Delcour. Journal of Cereal Chemistry. 82, 468 (2005b). A. Hagenimana, X. Ding, and T. Fang. Journal of Cereal Science. 43, 38 (2006).

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INDEX A absorption, xii, 49, 104, 196, 204, 301, 303 accommodation, 155 accounting, 143 accuracy, xi, 36, 107, 261, 262, 268, 276 acetone, 61 acid, x, 15, 36, 67, 79, 125, 128, 129, 130, 143, 145, 146, 147, 152, 171, 175, 176, 177, 178, 179, 206, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 250, 252, 253, 254, 258, 285, 289, 290, 291, 292, 298 acidity, 212 acoustics, 120 activated carbon, 158, 168 active site, 165 additives, 31, 33, 153, 174, 212, 250, 254, 258 ADH, 230 adhesion, 179, 200, 207, 208, 210, 225, 245 adjustment, 14, 107, 112, 186, 234 adsorption, 152, 153, 155, 156, 158, 159, 160, 161, 163, 165, 166, 167, 168, 169, 170, 196, 284, 294 adsorption isotherms, 168, 170 advantages, viii, 36, 81, 121, 183, 293 aflatoxin, 82, 84, 97 agar, 213, 216, 217, 254 agriculture, 252 alcohols, 235 algorithm, viii, 17, 48, 81, 82, 83, 84, 85, 86, 87, 88, 89, 91, 92, 93, 95, 96, 97, 98 allergy, 172, 206, 230 allocating, 235 almonds, viii, 81, 82, 84, 88, 92, 96, 97 aluminium, 283 ambient air, 204 amino acids, 58

amplitude, 103, 104, 105, 106, 108 amylase, 293 ANOVA, 238, 240, 303 anthocyanin, 134, 147, 148 antioxidant, 58, 78, 79, 122, 130, 140, 142, 143, 144, 145, 146, 147, 148, 254, 284 apples, 82, 97, 143, 147, 258 aqueous solutions, 62, 117, 281 arithmetic, 265, 271 ascorbic acid, 125, 130, 143, 145, 146, 147, 152, 254 assessment, 36, 80, 97, 101, 103, 104, 169 atmospheric pressure, 185, 187, 209, 210, 235, 236, 281, 302 atomization, 180, 186 authors, 14, 18, 30, 54, 97, 100, 112, 247, 284, 285, 286 automation, vii avoidance, 29

B background, 225 bacteria, x, 171, 175, 176, 177, 178, 179, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 230, 252, 285 bacteriocins, 251, 254 bacteriostatic, 252 bacterium, 213 bandwidth, ix, 99, 104 barriers, 164 basic research, 209 beef, vii, 35, 36, 39, 42, 43, 44, 45, 48, 49, 50, 51, 52, 53, 54, 130, 146, 247, 273 beneficial effect, 134, 135, 295 beverages, viii, xi, 57, 58, 59, 60, 64, 72, 73, 74, 77, 79, 281, 289, 292

314

Index

bias, 47 bile, 285 binding energy, 196 biocatalysts, 294, 295 bioconversion, 60 biodegradability, 251 biological systems, 251 biomass, 289 biopolymer, 59, 64, 72, 251, 252, 256 biotechnology, 228, 289 biotic, 223, 224, 226 blend films, 255 blends, 31, 60, 250, 255, 256 bonds, 64, 125, 160, 166, 309 bone, 143 bounds, 115, 267, 268, 277 brain, 47 branching, 58, 85 Brazil, 249 breakdown, 285, 309 breast cancer, 143 bridges, 28, 29 Bulgaria, 211 bulk density, 302, 303

C cabbage, 125, 126, 148 cabinets, 237 caffeine, 58 calcium, 146, 254, 297 calibration, 37, 42, 45, 46, 47, 49, 50, 52, 53, 61, 62, 63, 64, 65, 67, 72, 74, 75, 77, 115, 119 calorie, 36, 42, 46, 53 calorimetry, 14, 23 cancer, 175 capillary, 166, 192, 196 carbohydrate, xi, 235, 261, 264, 266, 271, 273, 274, 277, 292 carbohydrates, 219, 269, 272 carbon, 158, 168, 170, 236, 250, 263, 264, 265 carbon dioxide, 236, 250, 263, 264, 265 carbon materials, 170 caries, 296 carotene, 130, 134, 136, 137, 138, 143 carotenoids, 122, 130, 134, 135, 143, 145, 147, 148 case study, 245 casein, 284 catalyst, 291, 298 category a, 153, 268

cellulose, 61, 250, 252, 257, 258, 289, 293, 294, 295, 297, 298, 299 ceramic, 109, 283, 293 challenges, vii, 147 character, 21, 29, 290 cheese, 148, 227, 259, 270, 276 chemical industry, 289 chemical properties, 145, 148, 188, 199, 209, 210, 225 chemical reactions, 58 chemical stability, 255 chicken, 36, 82, 145, 146 chlorination, 197 chlorine, 255 cholesterol, viii, 35, 37, 38, 42, 43, 45, 46, 47, 49, 50, 51, 52, 53, 54, 143 chromatograms, 67, 74 chromatography, 60, 62, 64, 77 circulation, 209 clarity, 115, 167 class, 64, 82, 87, 256 classification, viii, 81, 82, 84, 88, 89, 90, 91, 92, 94, 95, 96, 263 climate, 292 CMC, 229 coatings, 32, 33, 236, 237, 245, 247, 251, 253, 254, 256, 258 cobalamin, 130, 144 cocoa, vii, 13, 14, 15, 16, 17, 18, 20, 23, 26, 30, 31, 32, 33, 58 cocoa butter, vii, 13, 14, 15, 16, 17, 18, 20, 23, 30, 31, 32, 33 coefficient of variation, 42 coffee, 58, 60, 79, 160, 168, 205, 206 collagen, 39 colon, 296, 298 color, 33, 39, 42, 44, 69, 79, 253, 254, 302, 306 colostrum, 135 combined effect, 309 commodity, 130 compatibility, 250 compensation, 152, 158, 163, 166, 168, 169, 170 competitiveness, 30 compilation, 226 complexity, 87, 294 composites, 253 composition, xi, 15, 24, 30, 31, 32, 33, 58, 63, 64, 65, 66, 67, 69, 72, 77, 79, 114, 163, 168, 236, 237, 245, 251, 261, 262, 265, 268, 271, 275, 276, 281, 284, 294, 299, 302

315

Index compounds, 43, 58, 63, 67, 69, 74, 78, 79, 125, 134, 135, 143, 144, 148, 173, 234, 235, 250, 252, 254, 255, 259, 280, 282, 285, 286, 287, 289, 292, 297 compression, 235, 256 computing, 87, 90, 152, 262 condensation, 58, 63, 135, 155, 156, 186, 188, 191, 196 conditioning, 22, 26, 204, 236, 237 conduction, 199 conductivity, 261, 262, 263, 266, 267, 268, 269, 270, 271, 272, 273, 275, 276, 277, 278 configuration, 109, 214, 215, 281 confinement, 253 conformity, 194 conjugation, 67 consciousness, x, 171, 175, 224 conservation, 102, 251 constipation, 172 consumer demand, xi, 36, 249 consumption, 16, 20, 25, 122, 143, 148, 172, 224, 290 contamination, ix, xi, 151, 152, 153, 249 control condition, 178 cooking, xi, 42, 44, 76, 80, 81, 139, 149, 229, 261, 301, 302, 304, 306, 309 cooling, 14, 17, 18, 19, 20, 26, 29, 31, 237, 302 copolymers, viii, 57, 65, 77, 250 correlation, xii, 58, 107, 128, 262, 301, 303, 304, 308 correlations, 272, 273 corruption, 196 cost, xi, 17, 30, 82, 119, 172, 174, 176, 222, 225, 250, 261, 302 cost saving, 30 covalent bond, 125 CPU, 237 cross‐validation, 37, 42, 46, 50, 51, 53 crystal growth, 14, 17 crystal structure, 15, 28 crystalline, ix, 15, 24, 26, 28, 29, 151, 302, 310 crystallinity, vii, 13, 24, 29, 309, 310 crystallization, vii, 13, 14, 15, 16, 18, 19, 20, 21, 29, 31, 32, 33, 154, 160, 247 crystallization kinetics, 31, 32, 33 crystals, 14, 15, 17, 18, 19, 20, 22, 24, 26, 29, 32, 33, 115 cultivation, 175 culture, 173, 175, 176, 178, 212, 213, 217, 227 cycles, 135, 285, 297 cytochrome, 50 Czech Republic, 63

D damping, 101 danger, 114 data analysis, 49 data collection, 44 data distribution, 49 data set, 42, 44, 46, 49, 83, 198 database, 82, 83, 84, 87, 89, 91, 92, 94, 95, 96, 97 decomposition, 46, 255, 296 deduction, 107 defects, vii, 13, 20, 29, 30, 82, 97 deformability, 21 deformation, 100, 237, 239 degradation, 59, 61, 65, 67, 76, 135, 144, 152, 154, 169, 172, 253, 254, 309 degradation rate, 154 degree of crystallinity, 24 dehydration, vii, 58, 235, 247 denaturation, 130, 135, 172 depolymerization, 58, 77 deposition, 283 desorption, 153, 159, 170, 294 destruction, 309 detachment, 283 detection, 42, 61, 64, 77, 82, 84, 97, 98 detection system, 77 developed countries, 36 developing countries, 261 deviation, viii, 35, 42, 47, 53, 241 dew, 237 dialysis, 59 diarrhea, 172 diet, 227, 229, 230, 292, 295, 298 differential scanning, 14, 23 differential scanning calorimetry (DSC), 14, 23, 24, 25, 31, 114, 115 diffraction, 25, 104, 310, 311 diffuse reflectance, 21, 33 diffusion, x, 29, 146, 156, 164, 165, 196, 233, 234, 244, 254, 308 diffusivity, 261, 262, 266, 270, 271, 275, 276 digestibility, 58, 131, 143, 145, 148 dimensionality, 82 direct measure, 262 direct observation, 110 disadvantages, viii, 81, 286 discriminant analysis, 38, 95 discrimination, 92 disorder, 155, 160

316

Index

dispersion, 22 displacement, 111, 118, 190 distillation, xi, 279, 280, 281, 282, 286, 287 distilled water, 213 distribution function, 194 DNA, 183 double bonds, 64 drugs, 230 dry matter, 36 drying, vii, xi, 82, 83, 97, 171, 172, 173, 174, 175, 176, 177, 178, 179, 183, 184, 185, 186, 188, 189, 190, 191, 193, 194, 196, 198, 199, 200, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 214, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 229, 230, 231, 247, 261, 265, 289, 290, 301, 302, 304, 306, 307, 308, 309 durability, 33 dynamic viscosity, 109 dynamics, 168, 234, 248

E editors, 32 efficiency, 17, 176, 202, 226, 262, 285, 295 egg, 285, 290, 291, 292, 299 elastomers, 250 electric field, 148 electrolysis, 283 electromagnetic, 183 electron, 26, 28, 258, 307 electron microscopy, 26 emission, 229, 235 emulsions, x, xi, 34, 234, 236, 237, 245, 247, 280, 282, 283, 284, 285, 286, 287, 288 encapsulation, 285 endothermic, 24, 160 energy consumption, 122, 290 energy density, 282 energy technology, 228 engineering, vii, viii, 99, 100, 227, 228, 230, 255, 286 England, 146, 237 entanglement network, 113 entropy, 152, 153, 154, 155, 156, 157, 158, 160, 162, 163, 164, 165, 166, 167, 168, 169, 170 environmental factors, x, 171, 224 environmental impact, 249 enzyme inhibitors, 78 enzyme interaction, 298

enzymes, ix, 58, 121, 122, 130, 131, 143, 144, 146, 179, 223, 224, 226, 251, 254, 290, 292, 293, 295, 297 epithelial cells, 148 equilibrium, ix, x, xi, 18, 20, 29, 60, 101, 151, 152, 153, 156, 157, 159, 165, 168, 195, 204, 219, 233, 234, 235, 279, 292 equipment, 14, 17, 20, 159, 172, 174, 175, 180, 183, 209, 210, 224, 226, 229, 281 ESR, 78 essential fatty acids, 144 ester, 292 etching, 283 ethanol, 60, 107, 251, 253, 281, 292, 293 ethylene, 249 evaporation, 183, 184, 198, 199, 200, 201, 202, 204, 209, 254, 286 excitation, 108 exclusion, 64 execution, 87 exercise, 268 experiences, 174 experimental condition, 61, 202, 214, 222 experts, 292 exposure, 67, 122, 143, 144, 178, 243 extinction, 179, 225 extraction, 45, 60, 82, 95, 96, 135, 138, 143, 144, 147 extrusion, 254, 255

F fabrication, viii, 99, 119, 288 false negative, 88 false positive, 88, 93 fat, vii, xi, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 24, 25, 26, 29, 30, 31, 32, 33, 34, 35, 36, 37, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 53, 54, 130, 144, 172, 196, 212, 261, 269, 272, 276, 277, 284 fat soluble, 130, 144 fatty acids, 32, 36, 130, 134, 135, 144, 296 feature selection, viii, 81, 82, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98 feature subset selection, 98 fermentation, xi, 60, 114, 289, 292, 293 FFT, 104 fiber, 83, 281, 282, 287, 293, 298 fibers, 118, 284 films, vii, xi, 146, 234, 236, 245, 247, 248, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259

317

Index filters, 82 filtration, 60, 77, 285, 288 financial support, 247 fish, 36, 121, 122, 134, 135, 144, 153, 270 fitness, 303 flavonoids, 135, 143 flavor, x, 58, 69, 79, 171, 173, 174, 184, 206, 224, 236, 249, 253, 282, 302 flora, 135, 296 flour, xii, 298, 301, 309, 310, 311 fluid, 109, 113, 116, 117, 173, 176, 178, 180, 186, 205, 210, 225, 281, 291 fluidized bed, 302 fluorescence, 97 foams, 285, 286 folate, 125, 130 food additives, 153, 254 food industry, vii, viii, x, xi, 99, 100, 146, 171, 172, 224, 229, 279, 280, 286, 289, 290 food production, 261 food products, ix, 36, 37, 59, 61, 63, 67, 121, 122, 143, 163, 188, 246, 262, 293 food safety, 249 formula, x, 234, 246 fouling, 286, 294 fractional composition, 264 France, 99, 279, 286 free energy, 155, 158, 160, 161 free volume, 115 freezing, 174, 178, 216, 222, 224, 226, 228, 230, 265, 273 frequencies, 100, 101, 103, 104, 112, 113, 114, 115, 117 fructose, 60, 67, 125, 127, 292, 293, 296 fruits, ix, 119, 121, 122, 125, 134, 135, 143, 144, 164, 166, 251, 254, 258 FTIR, 39 functional changes, 80 furan, 64 fusion, 207, 208, 210, 225

G gel, 60, 62, 252, 297 gel permeation chromatography, 62 Germany, 32, 56, 147, 237, 295 germination, 129 glass transition, ix, 100, 113, 114, 115, 116, 117, 151, 153, 169, 212, 219

glass transition temperature, 115, 154, 169, 212, 219 global markets, 122 glucoamylase, 293, 298, 299 glucose, xi, 60, 67, 79, 125, 127, 146, 289, 290, 291, 292, 293, 294, 295, 296, 297, 298, 299 glucose oxidase, 291, 292, 296, 297, 298, 299 glutathione, 131, 148 glycerin, 112, 113, 116 glycerol, x, 233, 234, 235, 236, 237, 239, 242, 243, 245, 246, 253 glycol, 235 glycoproteins, 58 granules, 308, 309, 310 graph, 169, 196 gravity, 210 grouping, 59 guidelines, xi, 36, 44, 261, 269

H hair, 213 halogen, 45, 83 hardness, vii, xi, 13, 14, 16, 20, 21, 25, 29, 33, 122, 234, 246, 301, 303, 304, 305, 311 harvesting, 276, 292 hazards, x, 171, 224 haze, 21 health effects, x, 171 heat capacity, 58, 59, 63, 77, 261, 262, 265, 266, 270, 271, 273, 274, 275, 276 heat release, 18, 20 heat transfer, 263, 270, 302, 304 height, 24, 186, 188, 210, 272, 274 hemoglobin, 49 heterogeneity, viii, 57, 63, 64, 77, 118 high density polyethylene, 258 homogeneity, 302 honey bees, 60, 69 hue, 21, 160, 163, 184 human brain, 47 human milk, 135, 148 Hungary, 289 Hunter, 170, 306 hybrid, 250, 264 hydrogen, 113, 115, 290 hydrogen peroxide, 290 hydrogenation, 298 hydrolysis, xi, 78, 146, 289, 293, 294, 295, 297, 298, 299

318

Index

hydroxide, 299 hypothesis, 244, 245 hysteresis, 153, 169

isotherms, 152, 153, 154, 158, 163, 167, 168, 169, 170 Italy, 57, 61, 287 Ivory Coast, 118

I ice, xi, 234, 237, 261, 262, 265, 269, 273, 274, 275, 277, 278, 301, 303 ideal, 117, 133, 155, 196, 294 illusion, 113 image, 311 images, 22, 23, 97, 304, 308 IMF, 36, 37, 38, 39, 40, 41 immersion, 109, 235, 284 immunity, 172 immunoglobulin, 135 impacts, 302 impedances, 105 impregnation, x, 233, 234, 235, 239, 246, 247 incidence, 105, 108, 144 inclusion, 153, 288 incompatibility, 254 incubation time, 285 independent variable, 46, 303, 304 infrared spectroscopy, 32, 97 ingestion, 135 inhibition, 58, 259, 293, 294 inhibitor, 296, 298 insertion, 17, 109, 196 integration, 65, 67, 69, 75, 254 intelligence, 251 interface, 100, 105, 106, 107, 118, 155, 156, 282, 283 intermolecular interactions, 301 intestinal flora, 135 intestine, 285 intrinsic viscosity, 62, 63 inventors, 258 inversion, 285 iodine, 152, 158, 168 ionic strength, 212 ions, 58, 134, 251, 254 iron, 130, 147 irradiation, 183, 258 IRS, 36 Islam, 306, 312 isoflavone, 135, 139 isolation, 230 isothermal crystallization, 18

J Japan, x, 32, 61, 171, 224, 226, 227, 228, 229, 230, 231, 254, 259, 283, 295, 306, 310 Java, 56

K keyword, 14 kinetics, ix, 17, 29, 31, 32, 33, 152, 153, 154, 158, 159, 165, 170, 293

L labeling, 250 lactic acid, x, 171, 175, 176, 177, 178, 179, 211, 212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228, 230, 252, 285 lactobacillus, 230 lactoferrin, 135, 147, 254 lactose, 205, 206 lakes, 250 lattice formation, 18 leaching, 302, 308 learning, 47, 48 lecithin, 21 lens, 213 light scattering, 21, 22 limitations, ix, 144, 151, 154, 249 linear dependence, 265 linear model, vii, 35, 45, 51, 53, 54 linear polymers, 62 linearity, 51, 52, 53 lipid oxidation, ix, 125, 130, 132, 134, 144, 145, 146, 148, 151, 152 lipids, 33, 134, 172, 173, 205, 207, 219, 254, 287 liquid phase, 235, 242 liquids, 59, 103, 104, 109, 116, 235, 298 Listeria monocytogenes, 252, 259 lithium, 197 liver, 38 living environment, x, 171, 212, 224 low temperatures, 178, 179, 183, 222, 225 LTD, 226

319

Index lutein, 134 lycopene, 134, 143 lysine, 58 lysozyme, 254

M macromolecules, 58, 61, 69, 72, 253, 294 macronutrients, 125, 126 magnesium, 197 magnetic resonance, 14, 23 Maillard reaction, 67, 78, 79, 291 majority, ix, 53, 125, 151 malnutrition, 262 management, ix, 16, 18, 151 manipulation, 244 manufacture, vii, 13, 14, 16, 19, 30, 114, 147, 227, 290, 292 manufacturing, 14, 205, 288, 292 markers, 143, 148 marketability, 22 masking, 253 material surface, 203 matrix, 29, 65, 87, 91, 152, 153, 154, 160, 165, 223, 249, 251, 252, 253, 303 meat, vii, 35, 36, 38, 42, 43, 44, 49, 53, 122, 130, 134, 144, 145, 270, 271, 272, 273, 275, 276 mechanical properties, 16, 20, 21, 25, 31, 32, 33, 63, 100, 235, 236, 239, 247, 249, 250, 251, 253 media, 59, 100, 109, 119, 176, 213, 277 medium composition, 58 melon, 134 melt, 15, 17, 18, 24, 25, 26, 58, 59, 63, 77, 115 melting, vii, 13, 14, 15, 16, 17, 18, 21, 24, 25, 26, 29, 30, 31, 32 melting temperature, vii, 13, 15, 25 membranes, 196, 283, 284, 286, 287, 288, 290, 294, 295, 297 mercury, 263 mesoporous materials, 170 metabolism, 172 metals, 58, 254 meter, 61 methodology, 30, 247, 312 methylcellulose, 253, 257, 258 micelles, 284 microcrystalline, 252, 257 microcrystalline cellulose, 252, 257 microemulsion, 245 micrometer, 118

micronutrients, 128, 130, 144 microorganism, 152, 219 microscopy, 26 microstructure, viii, x, 14, 16, 21, 29, 31, 65, 99, 152, 153, 158, 163, 166, 167, 168, 302 microstructures, 28 migration, x, 30, 31, 32, 233, 234, 235, 236, 247, 248 mixing, 44, 173, 213, 283 model specification, 43 model system, 31, 32, 59, 125 modeling, vii, 35, 36, 37, 42, 43, 46, 53, 54, 278 modification, 257 modules, 281, 293, 294 modulus, 33, 100, 102, 104, 105, 106, 111, 112, 252 moisture, viii, ix, x, xi, 30, 35, 36, 82, 100, 114, 115, 116, 119, 151, 152, 153, 154, 157, 159, 160, 161, 163, 164, 166, 167, 193, 194, 204, 210, 233, 234, 235, 236, 238, 247, 248, 250, 252, 254, 301, 302, 303, 304, 306, 307, 308, 309, 310, 311 moisture content, viii, ix, xi, 35, 36, 100, 114, 115, 116, 119, 151, 153, 154, 157, 160, 161, 163, 164, 166, 167, 193, 194, 204, 247, 301, 302, 303, 304, 306, 307, 308, 311 moisture sorption, 152, 154 molecular oxygen, 290 molecular structure, 64, 282 molecular weight, 58, 59, 62, 63, 64, 65, 67, 69, 71, 72, 75, 76, 78, 79, 143, 157, 235, 242, 289, 295 molecules, viii, 15, 18, 57, 59, 63, 67, 72, 77, 115, 135, 152, 153, 154, 155, 159, 160, 163, 164, 165, 169, 173, 235, 249, 282, 290 momentum, 48 monitoring, 18, 36, 130 monolayer, 154, 155, 196 morphology, ix, 22, 99 motivation, 87 moulding, 250 mucin, 291 multilayered structure, 252 multiphase materials, 278 muscles, 36, 38 mutant, 143 MWD, 62, 63, 65, 67, 68, 69, 70, 71, 72, 73, 75, 76, 78 myoglobin, 36, 134

N nanocomposites, 250, 251, 252, 253, 256, 257 nanoparticles, 253, 257

320

Index

nanotechnology, 249, 250, 252 National Bureau of Standards, 170 Netherlands, 145, 169, 283 networking, 286 neural network, vii, 35, 44, 47, 48, 54 Neural Network Model, 52 neurons, 47, 48, 54 New Zealand, 261, 298 next generation, 249 niacin, 130, 144 NIR, v, 35, 37, 38, 39, 40, 41, 42, 45 nitrate, 61, 197 nodes, 85, 86, 87, 88 Norway, 56 nuclear magnetic resonance (NMR), 14, 23, 31 nucleation, 14, 17, 20, 26, 29 nuclei, 14 nutrients, ix, 36, 125, 144, 151, 251 nutrition, 130, 146, 295

O obesity, 36 objective criteria, 152 oil, 18, 30, 32, 33, 82, 154, 160, 168, 185, 196, 252, 257, 280, 284, 285, 286, 287, 288 oligosaccharide, xi, 289 omega‐3, 135 opacity, 253 opportunities, 147 optical properties, 33, 251, 253 optimization, 48, 49, 63, 286, 312 optimization method, 48 organ, 251 organic compounds, 282 organic solvents, 287 oscillations, 108 osmotic pressure, 178, 212, 281 Ostwald ripening, 29 oxidation, ix, 82, 125, 130, 132, 134, 144, 145, 146, 148, 151, 152, 153, 154, 165, 168, 172, 196, 254, 258 oxidation products, 134 oxidative damage, 135 oxygen, xi, 178, 236, 249, 252, 290, 291 ozone, vii

P packaging, xi, 18, 168, 237, 249, 250, 251, 252, 253, 254, 255, 256, 257, 258, 259 palm oil, 18, 33, 284 parallel, 17, 103, 267 parallelism, 234 parameter, 21, 51, 63, 88, 92, 109, 114, 116, 118, 153, 163, 190, 194, 207, 208, 242, 268 particle size distribution, 21, 29, 30, 32, 33, 206, 284, 285 pasteurization, 60, 69 patents, 145 pathogens, 121, 249, 296 pattern recognition, 84, 97 peptides, 134, 143, 148 performance, viii, 35, 37, 38, 40, 42, 43, 46, 47, 48, 49, 50, 51, 52, 53, 54, 83, 84, 87, 89, 90, 91, 92, 95, 249 performance indicator, 54 permeability, 135, 144, 248, 252, 253, 278, 303 permeable membrane, 286 permeation, 62, 282 peroxide, 160, 162, 290, 296 PET, 250, 257 phase transformation, 15 phase transitions, 32 PHB, 255 phenol, 137 phospholipids, 285 physical and mechanical properties, 250 physical mechanisms, 262 physical properties, 14, 21, 29, 59, 72, 77, 82, 100, 259, 262, 276, 302, 305 physicochemical properties, xi, 251, 301, 311 physics, 152 physiology, 297 pigments, 122, 125, 134, 135 plants, viii, 81, 82, 84, 296 plasticization, 204 plasticizer, ix, x, xi, 151, 234, 236, 247 plastics, 254 platform, 289 PLS, 38, 39, 43, 46, 56 polarity, 255 pollution, 184 polydimethylsiloxane, 106 polydispersity, 58, 62, 72 polyesters, 250 polyhydroxybutyrate, 255

321

Index polymer, 59, 60, 62, 63, 64, 67, 113, 249, 250, 251, 252, 253, 254, 255, 256, 257, 287 polymer composites, 253 polymer films, 254 polymer matrix, 65, 249, 251, 252, 253 polymer nanocomposites, 257 polymeric films, 254 polymeric materials, 250, 253 polymerization, 58, 63, 64, 69, 72, 76, 77 polymers, 58, 59, 61, 62, 63, 64, 106, 108, 173, 227, 249, 250, 251, 253, 255, 257, 309 polymorphism, vii, 14, 31, 32, 33 polyolefins, 254 polypropylene, 194, 250, 252, 257, 281 polystyrene, 250 polyunsaturated fat, 134 polyunsaturated fatty acids, 134 polyvinylalcohol, 250 poor performance, 42, 43 porosity, xii, 262, 263, 264, 272, 274, 276, 281, 283, 301, 303, 304, 311 porous materials, 277 positive correlation, xii, 301, 303, 304, 308 postmenopausal women, 143 potassium, 197, 253, 254 potato, 97 poultry, 53, 97, 252 prevention, x, 79, 171, 175, 224 principal component analysis, 44 probability, viii, 57, 77, 82 probability density function, viii, 57, 77 probe, 17, 109, 118, 237, 304 probiotic, x, 171, 227, 230, 285 process control, vii, 36 producers, 60, 77 productivity, 292, 293, 295 project, 247 propagation, 44, 47, 101, 103, 111 propylene, 235 proteins, 36, 122, 130, 131, 135, 143, 146, 223, 224, 226, 284, 285, 288 proteolysis, 211 proteolytic enzyme, 146, 148 PTFE, 281, 284, 288 pulp, 118, 168 pure water, 116, 155, 156, 191, 195 purity, 279, 280 PVC, 44

Q quadriceps, 44 qualitative differences, 69 quality control, viii, 16, 21, 22, 25, 36, 53, 99, 100, 116, 119 quartz, 83

R radiation, 67, 310 radical polymerization, 63 radiometer, 37, 44 rape, 292 raw materials, viii, xi, 58, 59, 60, 64, 172, 174, 178, 186, 210, 224, 289 RDP, 54 reactants, ix, 58, 151 reaction rate, 294 reactions, ix, 58, 59, 61, 67, 69, 72, 76, 77, 78, 130, 135, 151, 152, 160, 165, 168, 196, 286 reactivity, 58 reading, 45 reagents, 197, 198 real time, 36 reality, 261 recall, 92, 104, 273 recognition, 84, 97 recrystallization, 26 reducing sugars, viii, 57, 58, 59, 60, 61, 67, 77, 97 reflection, 100, 103, 104, 105, 106, 108, 210 reflectivity, 116 refractive index, 61, 63, 66, 67, 77, 78, 114 regression, vii, 35, 36, 38, 46, 54, 96 regression model, 54 rehydration, xi, 301, 302, 308, 311 reinforcement, 303 rejection, 235 reliability, 36, 262 relief, 175 reparation, 256, 298 replacement, 265 replication, 46 requirements, 122, 172, 224, 255 residual error, 303 residuals, 43, 51, 52 resilience, 245 resistance, 15, 152, 158, 165, 167, 203, 242, 243, 244, 245, 249, 283

322

Index

resolution, 24, 44, 61, 118 resonator, 100, 108 respect, viii, xi, 22, 51, 58, 59, 60, 61, 64, 67, 69, 72, 77, 130, 216, 222, 301 restaurants, 36 retardation, 125, 126 retention volume, 62 retinol, 130 rheology, ix, 31, 99, 100, 113 riboflavin, 125 room temperature, viii, 44, 57, 58, 60, 100, 101, 114, 117, 134, 141, 143, 237, 281 rotations, 237 roughness, 21 Royal Society, 30, 33, 259, 287 rubber, 219, 250

S salmon, 131, 146, 149 salts, 255 saturation, 21 savings, 30, 82 scaling, 82 scanning calorimetry, 14, 23 scanning electron microscopy, 26 scattering, 21, 22 scavengers, 78 schema, 180, 181 screening, 42, 50, 52, 53, 54, 194 seafood, 134, 252 SEC, viii, 47, 49, 51, 52, 53, 57, 59, 63, 64, 65, 77, 78 second generation, 252 SECV, 42 seed, 14, 17, 18, 26 sensing, 36, 251 sensitivity, 61, 125, 176 sensors, 44, 45, 104, 112, 113 sewage, 250 SFS, 85, 91, 92, 93, 94 shape, 17, 18, 21, 84, 194, 213, 244, 283, 302 shear, viii, 14, 17, 32, 39, 99, 100, 101, 102, 103, 104, 105, 106, 107, 109, 110, 111, 112, 115, 116, 186, 223, 237, 255, 282, 283, 284, 285 shear rates, 255 shear strength, 39 shock, 244 shrinkage, 265, 302 signal processing, 104, 107 signals, 61, 107

silica, 106, 108, 284, 287 silicon, 83, 187, 210, 283, 288, 291 skeleton, 283 skin, xi, 82, 84, 97, 168, 234, 239, 241, 242, 245, 246 sodium, 197, 253, 254, 299 software, 48, 63 solid matrix, 303 solidification, 18, 19 solubility, 254, 282 solvents, 287 sorption, ix, 151, 152, 153, 154, 155, 156, 158, 159, 160, 163, 164, 165, 166, 167, 168, 169, 170, 257 sorption isotherms, 153, 154, 163, 167, 168, 169 sorption kinetics, 152, 153, 154, 158, 159, 165 sorption process, 152, 153, 159, 166, 169 soybeans, 143, 146 soymilk, 135, 146 space, 82, 84, 222, 235, 290 Spain, 233, 236 species, 60, 63, 76, 176, 177, 223, 224, 226, 230, 276, 279, 280, 292 specific heat, 58, 59, 63, 77, 262, 266, 270, 271, 273, 275, 276 specifications, 174, 188, 209, 210, 225, 226, 272 spectrophotometer, 66 spectroscopy, 32, 36, 42, 52, 53, 97 sponge, 308 stabilization, 254 stabilizers, 153 standard deviation, 42, 47, 49, 53, 241 standard error, 42, 47, 50, 53 starch, x, 163, 172, 173, 234, 236, 237, 245, 250, 251, 255, 256, 257, 289, 293, 294, 299, 301, 302, 308, 309, 310 starch blends, 256 starch granules, 308, 309, 310 starch polysaccharides, 301 statistics, 63 steel, 108, 109, 202, 210, 294, 295 sterile, 217 stomach, 285 storage, viii, ix, 14, 15, 18, 20, 29, 30, 31, 32, 58, 59, 76, 105, 106, 112, 118, 119, 123, 124, 127, 128, 129, 131, 132, 133, 134, 135, 137, 138, 140, 141, 142, 143, 144, 145, 146, 147, 151, 152, 153, 154, 160, 167, 168, 169, 172, 175, 176, 195, 197, 209, 214, 215, 221, 222, 223, 224, 225, 226, 227, 237, 244, 250, 253, 254, 262, 285, 298 strategy, 17, 88 strategy use, 88

323

Index strontium, 197 structural changes, 122, 135, 144 substrates, 176, 295 sucrose, 33, 60, 125, 127, 252, 296, 297 sugar beet, 169, 296 Sun, 119, 122, 133, 146, 149, 236 supply chain, 16, 18, 30 surface area, 173, 186, 244, 283, 308 surface properties, 287 surfactant, 252 survival, 173, 174, 176, 218, 220, 221, 222, 224, 225, 227 survival rate, 173, 174, 176, 218, 220, 221, 222, 224, 225 swelling, 160, 308, 309 symptoms, 143, 175 synthesis, xi, 289, 296, 297 synthetic polymers, 58, 173, 251

T tanks, 119 tannins, 58 temperature dependence, 155, 192 test data, 49, 95 testing, x, 44, 45, 46, 152, 234, 246 textural character, 235 texture, vii, x, xi, 13, 14, 18, 20, 21, 29, 31, 118, 121, 122, 130, 147, 152, 160, 164, 233, 234, 235, 239, 242, 243, 246, 247, 254, 291, 301, 302, 303, 304, 305, 308, 311 Thailand, 81, 301 thermal analysis, 152 thermal expansion, 274 thermal properties, xi, 257, 261, 262, 265, 276, 278 thermal resistance, 249 thermal treatment, viii, 58, 67, 79, 141, 142, 146 thermodynamic equilibrium, 18, 152, 153 thermodynamic parameters, ix, 151 thermodynamic properties, 152, 154, 160 thermodynamics, 152, 154, 234 thermograms, 24, 25 tics, 180, 181 time periods, 143, 153 tissue, 118 topology, 48 toxicity, 143 TPA, 304 training, 47, 48, 49, 82, 83, 84, 87, 88, 89, 90, 91, 92, 93, 95

transducer, 103, 104, 106, 107, 115 transformation, 29, 32, 51 transformations, 15, 17, 18, 20, 25, 46, 51, 60 transition temperature, 115, 154, 169, 212, 219 translation, 229 transmission, 44, 82, 83, 84, 103, 104, 253 transmittance spectra, 84 transparency, 253 transport, 302 trial, 46, 47, 48, 188 triglycerides, 15, 32 trimmings, 44 trypsin, 148 tryptophan, 58 tumor, 97 tumors, 82 tungsten, 45, 83

U ultrasound, 61, 100, 101 uniform, 45, 122, 209, 283 United Nations, 261, 277 universal gas constant, 244

V vacuum, x, 132, 134, 175, 178, 179, 183, 185, 186, 188, 190, 191, 210, 225, 228, 233, 234, 235, 236, 237, 239, 242, 246, 247, 281, 282, 286, 302 Valencia, 145, 233, 236 validation, viii, 35, 37, 42, 46, 49, 50, 51, 52, 53, 84, 88, 92 valuation, 118 vapor, 155, 156, 157, 168, 169, 174, 195, 248, 252, 253, 254, 281, 308 variations, vii, 14, 24, 26, 84, 109, 115, 209, 231, 276 vector, 44, 88, 92, 101, 111 vegetable oil, 31, 252, 257, 280, 284, 286 vegetables, ix, 121, 122, 125, 134, 135, 143, 145, 146, 251, 254, 258, 270, 276, 296 velocity, 101, 102, 103, 104, 106, 111, 114, 116, 117, 166 vibration, 108, 194, 283 viscoelastic liquids, 103, 104 viscoelastic properties, 63, 109, 119 viscosity, viii, xii, 18, 58, 59, 61, 62, 63, 76, 77, 99, 109, 112, 186, 192, 193, 214, 219, 242, 285, 286, 301, 308, 309, 311

324

Index

vision, 97 vitamin C, 134, 135, 143, 145, 148 vitamin E, 254 vitamins, 125, 130, 134, 144, 148, 179, 223, 224, 226, 254 volatility, 281, 282 VSD, 178, 179, 180, 181, 182, 183, 185, 186, 187, 188, 190, 193, 198, 199, 200, 201, 202, 204, 205, 206, 209, 210, 211, 212, 213, 214, 216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226

wave vector, 101 wavelengths, 46, 61, 89 weight changes, x, 233, 237 weight control, 18 weight gain, 239 weight loss, 190, 243, 244 weight ratio, 236, 239 wholesale, 118 wood, 60

X

W waste, 184, 290 water absorption, xii, 301, 303 water activity, ix, x, 58, 151, 152, 153, 154, 162, 163, 164, 165, 168, 169, 195, 196, 197, 198, 199, 201, 202, 206, 208, 210, 211, 214, 218, 219, 220, 224, 225, 233, 234, 235, 236, 237, 239, 240, 243, 244, 246 water diffusion, 308 water evaporation, 183, 184, 199, 200, 202 water sorption, ix, 151, 163, 164, 165, 166, 168, 169, 170, 257 water vapor, 169, 195, 248, 252, 253, 254, 308 wave number, 102 wave propagation, 101

x‐ray, xii, 25, 301, 310, 311 x‐ray diffraction (XRD), 25, 310

Y yeast, 114, 254 yolk, 285, 290

Z zinc, 254 zippers, 214, 216 zirconia, 284

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