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Sensory evaluation and volatile compound analysis of strawberry fruit with and without modified atmosphere… Shamaila, Mawele M. 1992

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SENSORY EVALUATION AND VOLATILE COMPOUND ANALYSIS OF STRAWBERRY FRUIT WITH AND WITHOUT MODIFIED ATMOSPHERE PACKAGING (MAP) By MAWELE SHAMAILA B.Agric.Sci., The University of Zambia, 1981 M.Sc, (Plant Sci.) The University of Manitoba, 1985 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY m THE FACULTY OF GRADUATE STUDIES Department of Food Science We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA March 1992 © Mawele Shamaila, 19 92 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of fooj> Science The University of British Columbia Vancouver, Canada Date r/JMcH it im DE-6 (2/88) ABSTRACT In the last few years, packaging of horticultural commodities in polymeric film pouches as means of extending their shelf life has expanded at the retail level. The modified atmospheres in commodity-containing pouches which consist of elevated levels of C02 and reduced levels of 02 may influence the quality attributes of the edible tissues. In this study, strawberries were stored at 1°C for 10 days under modified atmosphere package (MAP) conditions in high barrier film pouches flushed with either carbon dioxide (100% C02) , mixed gas (11% C02 + 11% 02 + N2 as balance) or air to assess relationships between sensory attributes, chemical parameters and gas chromatographic data by applying multivariate statistical techniques. The first two principal components which accounted for 92% of variance indicated that the changes in sensory quality of strawberries evaluated by quantitative descriptive analysis (QDA) were mainly a contrast of desirable (strawberry odor, texture and sweetness) against undesirable attributes (off-odor, fermented odor, musty odor and bitterness). Strawberries stored for only a few days were associated with desirable attributes. Deteriorated samples due to treatment and/or storage time as a result of changes in C02 and 02 were associated more with undesirable attributes. There were statistical differences in nearly all attributes studied between different treatments over storage time. Packaged strawberries treated with air retained their desirable attributes for longer storage time than those treated with mixed gas or carbon n dioxide, while unpackaged fruit developed fungal growth after 6 days of storage at 1°C. As the storage time increased, the ethanol concentration increased in strawberries packaged in the different gases, with mixed gas treated samples showing the highest amounts. Significant correlations were obtained between desirable and undesirable attributes, and with soluble solids and ethanol content. Most of the fifty volatile compounds extracted by a dynamic headspace purge-and-trap (DHPT) technique and adsorbed onto Tenax GC were identified by gas chromatography/mass spectrometry (GC/MS) as esters. Total relative amounts of volatile compounds and total amounts of butanoates from strawberries stored under different MAP conditions were much lower than for unpackaged strawberries. Significant correlations were found between odor attribute values and volatile compounds such as methyl butanoate, 1-methylethyl hexanoate, 3,7 dimethyl-1,6-octadien-3-ol and ethyl heptanoate. Multiple regression of 25 selected volatile compounds with the odor attribute values accounted for up to 70% of the variation, while stepwise regression selected between 6 and 9 variables with up to 67% of variance being explained. The data for 25 selected volatile compounds for untreated and gas-treated strawberries were subjected to canonical variate analysis (CVA). Samples held in air, mixed gas and the unpackaged fruit and strawberries evaluated at day 0 were all initially separated from strawberries held in carbon dioxide. After 10 days in storage, all MAP strawberries were classified in close iii proximity, with the indication that quality attribute scores were low. This was attributed to elevated C02 and reduced 02 levels in packages containing the strawberries. Assessment of volatile compound data by CVA could be valuable in monitoring quality of strawberries and supplementing sensory evaluation of the fruit stored under various conditions. In a separate experiment, 6 strawberry cultivars, 'Mrak', 'Ranier', 'Redcrest', 'Selva', 'Sumas' and 'Totem' were compared for sensory and chemical properties, and selected volatile compounds. 'Redcrest' had the most intense sourness, lowest pH, high titratable acidity and lowest overall fruit quality. Two-dimensional partitioning (TDP) showed that the overall quality of the strawberries was primarily dependent on odor and sweetness level. Cultivars differed in all orthogonal variates except odor. While judges could not detect odor differences, the total relative amounts of volatile compounds were greatest for 'Mrak' and 'Selva'. Canonical variate analysis (CVA) based on volatile compounds classified the cultivars according to the region in which they were bred. IV TABLE OF CONTENTS ABSTRACT II TABLE OF CONTENTS V LIST OF TABLES VIII LIST OF FIGURES XI ACKNOWLEDGEMENT XV INTRODUCTION 1 A. SENSORY AND VOLATILE COMPOUND ANALYSIS OF STRAWBERRIES STORED UNDER MODIFIED ATMOSPHERE PACKAGING 4 LITERATURE REVIEW 4 Methods used to store strawberries 5 Modified atmosphere packaging (MAP) 6 Packaging of strawberries in polymeric films 6 Beneficial effects of modified atmosphere packaging (MAP). 7 Reduction in softening 8 Delayed microbial growth (fungal spoilage) 10 Reduced respiration rate 12 Reduced enzyme activity 13 Physiological effects of MAP on horticultural commodities. 13 Negative effects of elevated C02 and reduced 02 16 Strawberry flavor volatiles 17 Biosynthesis of flavor/aroma volatiles in strawberries.... 18 Volatiles of fruit kept under CA/MA conditions 21 Methods of volatile extraction and analysis 24 Liquid-liquid and steam distillation procedures 26 Headspace analysis of volatiles 28 Relationship between sensory and volatile compound data... 30 Multivariate analysis of sensory and flavor/aroma data.... 32 MATERIALS AND METHODS 34 Strawberry samples and preparation 3 4 Strawberry samples 34 Modified atmosphere packaging of strawberry samples 34 Gas treatment and storage of strawberry samples 35 Sampling procedure and analyses of MAP strawberry samples. 35 Sensory evaluation 35 Training of judges 3 6 Sample preparation for sensory evaluation 38 v Chemical analyses 40 Extraction and analysis of volatiles from strawberries 42 Solvent extraction of volatile compounds 42 Distillation extraction of volatile compounds 42 Headspace volatile extraction procedures 43 Headspace volatile extraction with solvent desorption from Tenax GC 43 GC analysis of volatile compounds desorbed by solvent .. 46 Headspace volatile extraction with thermal desorption from Tenax GC 4 6 Volatile compound extraction from model system 47 Identification of volatiles by GC/MS 48 Gas monitoring in packages with strawberry fruit 48 Statistical analyses 50 Analysis of variance and correlations 50 Multivariate statistical analysis 50 RESULTS AND DISCUSSION 54 a. Sensory evaluation of strawberries stored under MAP 54 Sensory quality attributes of strawberries kept in storage.. 54 General sensory evaluation 54 Reliability of judges in sensory evaluation 55 Examination of the performance of judges with PCA 57 Analysis of variance (univariate) for sensory data 57 Multivariate analysis of variance of sensory attributes... 59 Differences among treatments over storage time 61 Relationship between sensory attributes 74 Correlation coefficients among sensory attributes 74 Multivariate statistical analysis of sensory data 76 Principal component analysis (PCA) of sensory data 76 Changes in chemical parameters of strawberries 82 Relationship between sensory and chemical parameters 84 Changes in gas composition of fruit stored under MAP 86 Storage potential of strawberries kept under MAP 87 Conclusions 89 b. Flavor volatile analysis of strawberries stored under MAP. 91 Volatile compound extraction from strawberries 91 Direct solvent and simultaneous distillation extraction.. 92 Volatile extraction by dynamic headspace procedure 94 Evaluation of volatile extraction from a model system 97 Evaluation of strawberry volatile compound extraction by dynamic headspace technique 97 Identification of strawberry volatile compounds 105 Volatile compounds of strawberries stored under MAP 114 VI Multivariate statistical analyses of sensory and volatile data 119 Simple correlation of odor attributes with volatile data. 119 Multiple regression of odor attributes with volatile data. 123 Preliminary data analysis with principal component and discriminant analysis 125 Principal component analysis (PCA) of volatile data 130 Discriminant/Canonical variate analysis of volatile data. 135 Conclusions 154 B. QUALITY ATTRIBUTES OF STRAWBERRY CULTIVARS GROWN IN BRITISH COLUMBIA 157 INTRODUCTION 157 MATERIALS AND METHODS 158 Strawberry samples 158 Sensory and chemical evaluation 159 Volatile compound analysis 160 Statistical analyses 161 RESULTS AND DISCUSSION 162 Sensory evaluation of strawberry cultivars 162 Overall quality 165 Strawberry volatile compound analysis 165 Conclusions 170 GENERAL SUMMARY OF THESIS RESULTS 174 REFERENCES 177 vii LIST OF TABLES Table 1 Sensory attributes used to describe characteristics of strawberries stored under modified atmosphere packaging.... 37 2 Sensory score sheet used in quantitative descriptive analysis (QDA) of strawberry fruit 3 9 3 Influence of judges and replications on evaluation of sensory attributes of strawberries evaluated on day 0 56 4 Influence of gas treatment, storage time and judges on sensory attributes of strawberry fruit stored under modified atmosphere packaging for 10 days 60 5 Multivariate analysis of variance on all sensory attributes of strawberries stored for 10 days under modified atmosphere packaging conditions at 1°C 62 6 Mean score rating of odor attributes for strawberry fruit stored under modified atmosphere packaging for 10 days 63 7 Mean score rating of taste attributes for strawberry fruit stored under modified atmosphere packaging for 10 days 64 8 Mean score rating for texture and overall fruit quality rating of strawberry fruit stored under modified atmosphere packaging for 10 days 65 9 The changes in C02 and 02 levels in MA packages containing strawberries flushed with air, mixed gas and carbon dioxide and stored for 10 days at 1°C 72 10 Simple correlation coefficients between sensory attributes of strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C 75 11 Soluble solids, Ph, titratable acidity, sugars and ethanol in strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C 83 12 Correlation coefficients between sensory data of strawberries and chemical parameters 85 13 Reproducibility of peak areas of known volatile compounds in a model system 98 VI11 14 Reproducibility of peak areas of known volatile compounds extracted from an aqueous solution using dynamic headspace procedure 98 15 Means, standard deviations and coefficients of variation for specific volatile compounds extracted from strawberry fruit by the dynamic headspace technique 9 9 16 Influence of strawberry preparation on the peak areas of volatile compounds extracted by the dynamic headspace technique 101 17 Effect of nitrogen flow rate on the peak areas of volatile compounds extracted from strawberries using the dynamic headspace technique 103 18 Effect of purge-and-trap time (hr) on the peak areas of volatile compounds extracted from strawberries using the dynamic headspace technique 103 19 Effect of incubation temperature on the peak areas of volatile compounds extracted from strawberries using the dynamic headspace technique 104 2 0 Tentatively identified strawberry volatile compounds which were desorbed from Tenax GC adsorbent by diethyl ether 107 21 Tentatively identified strawberry volatile compounds which were thermally desorbed from Tenax GC adsorbent 110 22 Strawberry volatiles selected for statistical analysis 113 23 Relative amounts of selected volatiles of strawberry fruit evaluated at day 0 and at day 3 of storage at 1°C for unpackaged and MAP sample with input gases as air, mixed gas or carbon dioxide 116 24 Relative amounts of selected volatiles of strawberry fruit evaluated at day 0 and at day 6 of storage at 1°C for unpackaged and MAP samples with input gases as air, mixed gas or carbon dioxide 117 25 Relative amounts of selected volatiles of strawberry fruit evaluated at day 0 and at day 10 of storage at 1°C for unpackaged and MAP samples with input gas as air, mixed gas or carbon dioxide 118 26 Correlation coefficients between sensory attributes and quantity of volatiles peaks 122 IX 27 Summary of multiple regression of all volatile compounds and those selected by stepwise regression procedure against each of the odor sensory attributes 124 28 Regression equations developed from data volatiles compounds selected by stepwise regression regressed against each of the odor attributes 126 2 9 Principal component analysis of strawberry volatiles analyzed at days 3, 6 and 10 131 3 0 Strawberry volatile compounds selected by stepwise discriminant analysis for inclusion into models to predict the treatment and/ or quality category 13 6 31 Canonical variate analysis of strawberry volatile compounds evaluated at days 3, 6 and 10 13 8 32 Mahalanobis distances between different strawberry treatments analyzed by canonical variate analysis using 25 volatile compounds 142 33 Means of sensory attributes for strawberry fruit grown in British Columbia in 1989 and 1990 163 34 Mean soluble solids, pH, titratable acidity and sugars of strawberry cultivars grown in B.C 164 35 Correlation coefficients of sensory attributes of strawberry fruit grown in B.C. in 1989 and 1990 164 3 6 Two-dimensional partitioning of the total sum of squares for overall quality (%) of five strawberry cultivars grown in B.C 166 37 Relative amounts of selected volatile compounds of six strawberry cultivars grown in B.C 168 x LIST OF FIGURES Figure 1 Summary of proposed pathways for the formation of aldehydes and subsequent formation of carboxylic esters from lipid degradation 22 2 Set-up for the apparatus used to collect the headspace volatiles by trapping on the adsorbent Tenax GC 45 3 Principal component scores of nine judges who evaluated strawberries at day 0 58 4 Flavor profiles of strawberries evaluated at day 0 with unpackaged strawberries (4a), MAP strawberries packaged in air (4b), mixed gas (4c) and carbon dioxide (4d) and stored for 10 days at 1°C, respectively 67-70 5 Principal component loadings of sensory attributes of strawberries evaluated from different treatments and different storage times 78 6 Principal component scores of samples from different treatments evaluated at different storage times 80 7 The overall quality rating of strawberries from different MAP treatments kept in storage for 10 days at 1°C 88 8 Comparison of strawberry flavor profiles prepared by: direct solvent extraction (A); steam distillation (B) and vacuum steam distillation extraction (C) 93 9 Chromatograms obtained from strawberry volatiles extracted by headspace technique on a) charcoal adsorbent and b) Tenax GC eluted with solvent; and c) thermally desorbed from Tenax GC 95 10 Mass spectrum of methyl butanoate from a strawberry volatile extract and from mass spectra library 106 11 Typical GC chromatogram of a strawberry volatiles extract eluted from Tenax GC with diethyl ether 109 12 Flavor volatile profiles of unpackaged strawberry (A) and strawberry fruit packaged in air (B), mixed gas (C) or carbon dioxide (D) after 6 days storage at 1°C 115 13 Relative total amounts of volatile compounds extracted from strawberries stored under various MAP conditions for 10 days at 1°C 12 0 XI 14 Relative total amounts of butanoates extracted from strawberries stored under various MAP conditions for 10 days at 1°C 12 0 15 Predicted and observed scores of overall quality scores of strawberry fruit stored under MAP for 10 days using nine volatile compounds selected by stepwise regression.... 127 16 Principal component scores obtained from PCA of 25 volatile compounds from all strawberry samples evaluated from different treatments and storage times 128 17 Canonical variate scores obtained from CVA of 25 volatile compounds from all strawberry samples evaluated from different treatments and storage times 129 18 Principal component scores of strawberry samples from different treatments evaluated at day 0 and after 3 days in storage at 1°C 132 19 Principal component scores of strawberry samples from different treatments evaluated at day 0 and after 6 days in storage at 1°C 133 2 0 Principal component scores of strawberry samples from different treatments evaluated at day 0 and after 10 days in storage at 1°C 134 21 Canonical plot of the first two canonical variates for strawberries evaluated at day 0 and after 3 days in storage at 1°C 139 22 Canonical plot of the first three canonical variates for strawberries evaluated at day 0 and from different treatments evaluated after 3 days in storage at 1°C 140 23 Projection of canonical loadings of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments evaluated after 3 days in storage at 1°C 144 24 Canonical plot of the first two canonical variates for strawberries evaluated at day 0 and from different treatments evaluated after 6 days in storage at 1°C 146 25 Canonical plot of the first three canonical variates for strawberries evaluated at day 0 and from different treatments evaluated after 6 days in storage at 1°C 147 xii 26 Projection of canonical loadings of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments kept in storage for 6 days 1°C 149 27 Canonical plot of the first two canonical variates for strawberries evaluated at day 0 and from different treatments evaluated after 10 days in storage at 1°C 150 28 Canonical plot of the first three canonical variate for strawberries evaluated at day 0 and from different treatments evaluated after 10 days in storage at 1°C 151 29 Projection of canonical loadings of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments kept in storage for 10 days at 1°C 153 30 Relative amounts of some volatiles in the six cultivars of strawberry grown in B.C 169 31 Canonical plot of six cultivars grown in B.C. based on 25 selected volatile compounds 171 32 Projection of canonical loadings (correlations) of volatile data and centroid scores for six strawberry cultivars grown in B.C 172 Xlll Dedicated to my late father (13/10/89) and mother (23/09/91) for their love and patience through my studies. xiv ACKNOWLEDGEMENTS I wish to express my greatest appreciation and gratitude to my two major advisors, Dr. W.D. Powrie and Dr. B.J. Skura for their encouragement, wise words, guidance and valuable assistance during my studies, research and thesis preparation. I am also thankful to Dr. S. Nakai who first introduced me to multivariate statistical techniques and to Dr. P. Jolliffe both of whom served on my committee and offered constructive criticism to my work. Special regards are extended to my brothers Newton, Garneth, Moffat and Frank, and all family members and friends for their encouragement and support during my studies. I would also like to thank all members of my sensory panel whose participation helped complete this project. I extend my appreciation to the Canadian International Development Agency (CIDA), Ottawa and Pacific Asia Technologies, Inc., Vancouver, B.C. for having provided the financial assistance, and the University of Zambia (UNZA) for granting the study leave. xv 1 1.0 INTRODUCTION Strawberry [Fra.ga.ria. ananassa, Duchesne) is a highly perishable fruit with a limited post-harvest shelf life at room temperature. Although refrigerated storage is useful for extending shelf life of strawberries, mold growth is visible on the surfaces of the fruit within one week at 1°C (Sommer et al. , 1973; El-Kazzaz et al. , 1983) . During frozen storage, strawberries retain their flavor and color for several months, but upon thawing, the fruit becomes unacceptably soft with excessive drip loss (Skrede, 1983) . Irradiation is very effective for inactivating mold mycelium and spores (Zegota, 1988), but concern for safety by consumers has led to limited use in North America. Recently, the packaging of horticultural commodities in polymeric films with specific gas permeabilities in combination with low temperature storage has increased in North America (Forney et al., 1989; Kader et al. , 1989; Prince, 1989; Risse and McDonald, 1990). The development of a modified atmosphere within polymeric film pouches can bring about an extension of the shelf-life of a number of fruits and vegetables (Duan et al. , 1973; Han et al. , 1985; Smith et al.,1987; Kader et al. , 1989; Prince, 1989). Results have been documented for the benefits of storing strawberries under elevated C02 and/or reduced 02 levels (Woodward and Topping, 1972; El-Kazzaz et al. , 1983). Elevation of the C02 level and reduction in the 02 content of the microatmosphere around the commodities can suppress the decay of fruit (Woodward and Topping, 1972; El-Kazzaz et al., 1983; Harman and McDonald, 1983; 2 Han et al. , 1985), retard senescence and delay softening of the fruit (Kader, 1980; Knee, 1980; 1973; Arpia et al., 1984), minimize enzymic activity (Barmore and Rouse, 1976; Monning, 1983; Rosen and Kader, 1989) and reduce respiration rate (Li and Kader, 1989) . Although high C02 and/or low 02 levels in the microatmosphere of produce extend shelf life, the development of off-flavors/odors is of major concern. Off-flavors/odors may be induced by anaerobic respiration (Carlin et al., 1990) and accumulation of certain volatile compounds in commodities treated with low 02 and high C02 levels (Woodward and Topping, 1972). Burton (1982) reported that strawberries developed off-flavor in a 3% 02 microatmosphere and Browne et al. (1984) noted that, with 3-16% C02 in the gaseous environment around palleted strawberries with polyethylene covering, an off-flavor developed in the fruit during storage at 2°C. De Pooter et al. (1981; 1987) reported increases in volatile compounds in apples stored under controlled atmosphere (CA) after treatment with propionic acid. However, Paillard (1981) and Lidster et al. (1983) found that CA suppressed the aroma of apple fruit when stored under CA. It is therefore important to establish relationships between the volatile compounds and sensory attributes of fruit so that an objective measurement of quality changes can be undertaken. Such relationships could be useful for monitoring the quality of fruit during storage under various conditions. The general objective of this study was to investigate the relationship between sensory attributes and gas chromatographic (GC) data for strawberries stored under different MAP conditions. 3 The specific objectives of the first part of the study were: a) to use quantitative descriptive analysis (QDA) to assess the quality attributes of strawberries stored for periods up to 10 days under MAP at 1°C; b) to study the influence of MAP on chemical changes such as pH, soluble solids, titratable acidity and ethanol, and relate them to sensory changes; and c) to apply multivariate statistical analysis to relate fruit quality changes to the effects of MAP. The specific objectives of the second part of this study were: a) to identify the types and the relative amounts of volatiles of strawberries stored under different MAP conditions; b) to study the influence of MAP on the volatile profiles of strawberries kept in storage, and relate sensory attributes to GC data; and c) to classify the treatment category and quality of strawberries stored under MAP from the volatile compound data by applying multivariate statistical techniques. In a separate experiment, quantitative descriptive analysis (QDA), and the headspace purge-and-trap technique were used to evaluate strawberry cultivars grown in British Columbia (B.C.). The objectives of this part of the study were to evaluate sensory attributes of fruit quality and to determine their relative importance in strawberry fruit by applying two-dimensional partitioning (TDP). In addition, the volatile compounds of the cultivars were evaluated for potential classification purposes. 4 A. SENSORY AND VOLATILE COMPOUND ANALYSIS OF STRAWBERRIES STORED UNDER MODIFIED ATMOSPHERE PACKAGING (MAP). 2.0 LITERATURE REVIEW. Commercial production of strawberry {Fragaria ananassa, Duchesne) in North America is documented from as far back as 1800. As of 1979, major production of the fruit was concentrated in Europe, North and Central America, and Asia. Canada produced 1.4% of the world's total production. Strawberries are mainly produced for the fresh market, but a large quantity of the fruit also goes for processing into jams, jellies, preserves and marmalades (Salunkhe and Desai, 1980) . Strawberry is a highly perishable fruit characterized by a short post-harvest life at room temperature. This has mainly been attributed to the fruit's high respiration rate, susceptibility to fungal spoilage, and its delicate tissue (Woodward and Topping, 1972; Sommer et al., 1973) . These effects lead to rapid deterioration of the fruit and loss in quality. The rapid perishability of strawberries thus limits the distance and transit time of shipment as well as storage period. Although airfreight is an alternative to truck or rail transportation, the relatively high cost and especially the high temperatures of up to 15°C encountered in the cargo planes, may result in considerable losses due to fruit decay. 5 2.1 Methods used to store strawberries. Because of the limited shelf-life of strawberry fruit and its susceptibility to mold growth, a number of storage techniques have been applied to preserve the fruit. Low temperature storage or precooling is a common procedure used to remove field heat soon after harvest (Smith, 1963) . Salunkhe and Desai (1980) recommended the use of temperatures between -0.6 to 0°C and relative humidity (RH) between 90 to 95% for extending the shelf-life of strawberries for up to a week. Freezing is the most effective preservation method to store strawberries for several months (Douillard and Guichard, 1989; 1990). However, the extensive textural changes and drip loss that occur at thawing are undesirable (Skrede, 1983). Irradiation of strawberries can inhibit the incidence of gray mold. Maxie et al. (1971) found that sizeable losses from postharvest decay could be prevented when the strawberries were irradiated. Zegota (1988) found that irradiation, with a 2.5 kilogray (KGy) dose followed by cold storage, extended the shelf-life of 'Dukat' strawberries to a minimum of 9 days. However, the phobia surrounding irradiation and concern for safety have resulted in restricted use of this technology in North America. Thermal processing is another method used for preservation of strawberry fruit. However, this is accompanied by unattractive discoloration of the fruit due to the degradation of anthocyanin pigments (Wrolstad et al. , 1980). 6 2.2 Modified atmosphere packaging (MAP). 2.2.1 Packaging of strawberries in polymeric films. In the last few years, there has been increasing use of packaging of fruit and vegetables in polymeric films with specific gas permeability in combination with low temperature storage (Forney et al., 1989; Kader et al., 1989; Risse and McDonald, 1990). Packaging of horticultural produce in polymeric films is a common technique designed to prevent moisture loss, protect against mechanical damage, and provide better appearance (Henig and Gilbert, 1975; Bhowmik and Sebris, 1988) . Originally, the films were aimed at reducing water loss with minimal injury to the product. It is clear now that the primary function of the films in the form of package systems is to develop a modified atmosphere around fresh products during storage and extend their shelf life (Forney et al., 1989) . Controlled/Modified atmosphere (CA/MA) means that the atmospheric composition surrounding a perishable product is different from that of normal air. Prince (1989) defined CA as 'the intentional alteration of the natural gaseous environment and maintenance of that atmosphere at a specified condition throughout the distribution cycle, regardless of temperature or other environmental variations.' He also defined MA as 'the initial alteration of the gaseous environment in the immediate vicinity of the product, permitting the packaged product interactions to naturally vary their immediate gaseous environment.' Generally, under modified atmosphere packaging (MAP), 7 horticultural produce is sealed in a film pouch or container initially flushed with a specific gas mixture of varying proportion, especially in C02 and 02 levels, and stored at refrigeration temperature. Han et al. (1985) seal-packaged 'Fuji' apples in bags consisting of polyethylene (PE) films with different thicknesses between 0.02 and 0.06 mm, and stored the fruit for five months at about 0°C. They found that the bags, made with PE film effectively decreased weight loss and decay of the apples but the fruit developed a slightly higher degree of internal browning than unpackaged apples. Bhowmik and Sebris (1988) reported considerable reduction in weight loss of shrink-wrapped peaches and better sensory quality of the packaged fruit than the control. Forney et al. (1989) studied changes in quality of broccoli stored under MAP conditions. Water loss was decreased 17% by CA storage and 50% by film-wrapping the broccoli. Compared to the control, broccoli quality from both treatments was significantly better. 2.2.2 Beneficial effects of modified atmosphere packaging (MAP). Horticultural products continue as living organisms after harvest. Therefore, metabolic processes associated with maturation, ripening and senescence, such as respiration, continue into storage and lead to rapid quality deterioration of the fruit. Modified atmosphere packaging (MAP), controlled atmosphere storage and other storage techniques that result in high C02 and low 02 atmospheres are, however, known to extend the storage-life of a variety of horticultural products (Brecht, 1980; Kader et al. , 8 1989) . Maturation of apples and tomatoes was delayed under atmospheres low in 02 and high in C02 (Smith et al. 1987) . Shelf life of shredded lettuce, packed in 35 |im LDPE pouches flushed with 5% C02 and 5% 02, and stored at 5°C, doubled (Ballantyne, 1986). Other examples of extensions of shelf life of horticultural products stored under lowered 02 and increased C02 atmospheres have been reported for bananas (Duan et al., 1973), peaches (Kader et al., 1982; Bhowmik and Sebris, 1988), apples (Lau, 1985; 1988) and broccoli (Forney et al., 1989). The beneficial effects of modified/controlled atmosphere during storage have been attributed to delayed softening (Kader, 1980; Harman and McDonald, 1983; Arpia et al. , 1984), reduced respiration (Li and Kader, 1989; Kubo et al., 1989), delayed ripening (Salunkhe and Desai, 1980), less microbial spoilage (Woodward and Topping, 1972; El-Kazzaz et al. , 1983) and reduced enzyme activity (Monning, 1983; Barmore and Rouse, 1976; Rosen and Kader, 1989). Ke et al. (1990) found that 'Bartlett' pears tolerated atmospheres containing 1.0, 0.5 or 0.25% 02 and also 20, 50 or 80% C02 at 0, 5 or 10°C without detrimental effects on their quality attributes. They noted that the beneficial effects of exposure of the fruit to 02-reduced or C02-enriched atmospheres included reduction of respiration rates, lower ethylene production rates, and retardation of skin yellowing and flesh softening. 2.2.2.1 Reduction in softening. Effective reduction in weight loss of fruit and vegetables 9 under MAP is important in keeping product quality. MAP has been reported to delay fruit softening (Barmore and Rouse, 1976). Harman and McDonald (1983) reported that atmospheres, containing 4% to 10% C02, decreased softening of Kiwi fruit, but that higher C02 concentrations had no further additional effect on firmness. 'Spartan' apples kept in 1% 02 + 2% C02 microatmosphere at 0°C for 6-9 months were firmer and had higher acidity than apples kept at standard commercial atmospheres of 2.5% 02 + 2% C02 (Lau, 1983). However, reduction of the storage C02 level from 2% to 0.5% decreased firmness and increased the incidence of core browning while the fruit stored in 2.5% 02 microatmosphere developed scald. The rate of Kiwi fruit softening during storage was reduced by elevated levels of C02 and accelerated by ethylene (C2H2) (Arpia et al. 1984). 'Rabbiteye' blueberry cultivars stored in high C02 atmospheres resulted in greater percentages of marketable and firm fruit as well as better sensory ratings than blueberries stored in air (Smittle and Miller, 1988) . The reduction in softening of fruit kept under MAP may be attributed in part to reduced moisture loss (Henig and Gilbert, 1975; Risse and McDonald, 1990). Han et al. (1985) reported that a weight loss of 3.4% in non-packaged apples was sufficient to cause shrivelling and result in the loss of commercial value in 7 days. Forney et al. (1989) found that storage of broccoli under controlled atmosphere reduced water loss by 17% while film wrapping reduced water loss by 50% as compared to the control stored in air. They concluded that the reduced water loss in these treatments may 10 be related to their inhibitory effect on senescence, as evidenced by decreased yellowing and floret expansion relative to the control. 2.2.2.2 Delayed microbial growth (fungal spoilage). The main post-harvest pathogenic disorder of strawberries is the gray mold rot caused by Botrytis cinerea which may invade the floral parts in the field (El-Kazzaz et al., 1983). Although development of the pathogen after penetrating the tissues is slow at 2°C, it is very rapid at high temperatures (Sommer et al. , 1973). The spread of the fungus is also facilitated in storage by contact of sound and infected fruit. Elevation of C02 content of the storage atmosphere suppressed the decay of strawberries and extended their shelf-life (El-Kazzaz et al., 1983). Burton (1982) pointed out that modified atmospheres can decrease rotting of strawberries by pathogens, often by delaying ripening of fruit since ripe fruit is more susceptible to attack by pathogens. The success of controlled/modified atmosphere storage of strawberry fruit in delaying microbial growth can be attributed to the fact that the fruit can tolerate up to 2 0% C02 and 02 concentrations as low as 2% (Brecht, 1980; Kader, 1980; Kader et al. , 1989). Carbon dioxide, at concentrations greater than 5-10%, inhibits growth of microorganisms, especially aerobes, when strawberries are kept at refrigeration temperatures. King and Nagel (1975) attributed the inhibitory effect of C02 to alteration of microbial cell permeability. Follstad (1966) and Wells and Uota 11, (1970) found that growth of fungi decreased linearly with reduced 02 between 21 to 0% and also with increased C02 atmospheres (between 10 to 45%) containing 21% 02. However, Svircev et al. (1984) reported that inhibition by increased C02 varied with different fungi. The germination of Peronospora hyoscyami was reduced in the presence of 0.8% C02 while Botrytis cinerea and Aspergillus niger required 5 and 15% C02 in order to germinate, respectively. Woodward and Topping (1972) found that strawberries, stored at 3°C in air with 5, 10, 15 and 20% C02, remained in good condition for 10 days, with reduced mold rotting due to Botrytis. Of the many gas conditions studied by El-Kazzaz et al. (1983), air + 15% C02 and CA (2.3% 02 + 5% C02) + 10% CO were the most effective atmospheres for suppressing fruit rot. The presence of ethylene resulted in more decay development, which suggests that ethylene might enhance disease development or fungal growth, or cause tissue damage. Kim et al. (1986) studied the storability of strawberries in air supplemented with various levels of C02. They found 14% and 10% decay in fruit stored in air with 20% and 30% C02 for five weeks, respectively. However, the fruit stored in air for two weeks had 53% decay. Dixon and Kell (1989) reported that much of the value of C02 treatment of fruits is due to the delay of their rotting by fungi. But they also pointed out that lowering the temperature combined with partial pressures of C02 in the range of 0.2 to 0.5 atmospheres provided a strong check to fungal growth. 12 2.2.2.3 Reduced respiration rate. The single most important phenomenon occurring during storage that results in deterioration of vegetative produce is respiration. Fruit stored under CA/MA have been reported to have a reduced respiration rate (Kubo et al. 1989) . Forney et al. (1989) found that C02 production and 02 consumption of broccoli held in CA or plastic films was reduced by 30 to 40% relative to the controls. Li and Kader (1989) studied the residual effects of controlled atmosphere storage of strawberry fruit. Low levels of 02 (0.5-2%) and high levels of C02 (10-20%) and their combinations were found to reduce respiration of the fruit, but most importantly, had a residual effect. At the end of storage, fruit transferred to air maintained flesh firmness and color. The tolerance of fruit to different levels of C02 and 02 depends on the storage temperature, gas composition, and the fruit type (Porritt and Meheriuk, 1968; Bohling and Hansen, 1983; Kader, 1985). Kubo et al. (1989; 1990) found 60% C02, 20% 02 and 20% N2 reduced the respiration rate of a number of fruits and vegetables as measured by 02 uptake. Although they found a decrease in respiration rate of a number of climacteric fruits including apples, melons, tomatoes and bananas, little change in respiration was noted at the preclimacteric stage. Also, little change was found in non-climacteric fruit and vegetables including lemons, potatoes, sweet potatoes and cabbage. They concluded that the respiratory response to high C02 was quite different depending on the kind of horticultural crop and stage of maturity. 13 2.2.2.4 Reduced enzyme activity. Enzymes continue their metabolic activity after harvest and into storage. Some of their activities are detrimental to fruit quality. Tissue softening which has been attributed to disintegration of pectic substances and cellulose fibrillar materials, involves enzymes such as polygalacturonase and cellulase (Han et al., 1985; Abeles and Takeda, 1990). Although Han et al. (1985) found no significant differences in enzyme activity between apples packaged in different films, a highly significant and negative relation was obtained between enzyme activity and firmness. Pectinesterase is another important enzyme involved in softening of fruit. Barmore and Rouse (1976) suggested the use of pectinesterase activity to monitor the changes in softening time of fruit during controlled atmosphere storage. Succinate dehydrogenase and other enzymes have been found to be inhibited by CA/MA conditions (Frenkel and Patterson, 1973; 1977) . This may explain the increase in succinic acid noted in apples stored in atmospheres containing high C02 levels (Monning, 1983) . 2.2.3 Physiological effects of MAP on horticultural commodities. The effect of elevated carbon dioxide and decreased oxygen has been under investigation by a number of researchers. These gases may have a strong reduction effect on respiration due to their inhibitory effect on several respiratory enzymes of the Krebs cycle. Ke et al. (1990) found that exposure of 'Bartlett' pears to 0.5% or 0.25% 02 at 0°C significantly decreased respiration rates 14 as compared to those pears stored in air. Frenkel and Patterson (1973; 1977) suggested that low 02 and high C02 levels influence the mitochondrial enzymic activities since they noted the suppression of succinic dehydrogenase activity and ultrastructure alterations in various organelles that included mitochondria, plastids and also the tonoplast and cytoplasm of pears. Brecht (1980) reported that 02 levels between 3% and 21% had an influence on the Krebs cycle in the mitochondria, and that levels below 3% also inhibited the glycolytic system in the cytosol. Kerbel et al. (1988) studied the influence of C02 in air on the glycolytic pathway of peach fruit. Fruit kept under MA with elevated C02 levels exhibited decreased respiration rates and ethylene evolution rates compared to those for fruit stored in air. They also found that ATP:phosphofructokinase and PPi:phosphokinase-activities declined and thus concluded that C02 may have an inhibitory effect on the sites of both kinases in the glycolytic pathway. However, Burton (1982) suggested that the beneficial effects of storage of fruit in low 02 microatmospheres results more from suppression of the activity of comparatively low-02-af f inity enzymes such as polyphenolase, fi-type cytochromes, ascorbic acid oxidase and glycolic acid oxidase than from suppression of the basal metabolism mediated by cytochrome-c oxidase. Excessive levels of C02 may also be injurious to plant tissues. Frenkel and Patterson (1977) noted ultrastructural alterations of membranes in the tissues of pears stored under elevated C02. They suggested that high C02 may alter interfacial tension of lipid 15 layers and thus impair the ability of lipid-containing membranes to maintain structural continuity, resulting in membrane collapse. Also, excessive bicarbonate ions resulting from high C02 tensions was thought to form insoluble calcium carbonate salts, thus rendering calcium unavailable for maintenance of membrane structure and ultimately contributing to ultrastructural collapse. Apple fruit, suffering from C02-injury, have been reported to accumulate succinic acid in the tissues and this has been attributed to the inhibition of succinate dehydrogenase activity by C02 (Frenkel and Patterson, 1973; 1977). Monning (1983) reported that CA-storage of apples not only inhibited succinate dehydrogenase but other enzymes as well. They concluded that C02 may inhibit the glycolysis pathway, succinate dehydrogenase activity, and also possibly the formation of citrate/isocitrate and a-ketoglutarate. Frenkel and Patterson (1977) reported that the inhibitory effect of C02 on succinic dehydrogenase activity may lead to restricted turnover of respiratory metabolites, and this would result in limited ATP production (Siriphanich and Kader, 1986) or in reduced synthesis of essential intermediary metabolites. Exposure to high C02 may lead to a drop in pH due to the dissociation of carbonic acid to bicarbonate and hydrogen ions (Siriphanich and Kader, 1986) . This drop in pH beyond normal limits could result in a stage where normal physiological functions might not be sustained. Burton (1982) reported that increased C02 levels may influence reactions that involve reversible decarboxylation such as those that may involve pyruvate, citrate and a-ketoglutarate. 16 2.2.4 Negative effects of elevated C02 and reduced 02. Although storage of a number of horticultural products under CA/MA has been beneficial, high levels of C02 or low levels of 02 may induce anaerobic respiration which can lead to off-flavor/odor development (Carlin et al. 1990). Burton (1982) reported that strawberries, stored in MA having 3% 02, develop off-flavors. El-Kazzaz et al. (1983) detected off-flavors in strawberries treated with air + 15% C02. Woodward and Topping (1972) suggested that long-term storage of strawberries in MA with 02 levels of 1% or lower may lead to off-flavors, and that the use of high C02 concentrations in the microatmosphere may be restricted to the storage of strawberries for periods for up to 7 days where adequate refrigeration is unavailable. Browne et al. (1984) noted that strawberries, at 2°C in a microatmosphere of 3-16% C02 within patented polyethylene covers, developed off-flavor during fruit storage. With very low 02 concentrations (below 1%) in the microatmosphere, off-flavors caused by fermentative reactions can take place in a number of fruits such as bananas, apples, avocados and strawberries (Brecht, 1980). Bohling and Hansen (1983) reported that high C02 and low 02 concentrations in the microatmosphere of strawberries bring about reduced respiration rates. Carlin et al. (1990) reported that C02 levels higher than 30% or 02 levels less than 2% induced microbial spoilage of carrots 17 stored in low 02 permeable films. Atmospheres containing more than 4% C02 in air (15-20% 02) reduced the softening of Kiwi fruit (Harman and McDonald, 1983) . Fruit stored in atmospheres containing greater than 10% C02 for more than 16 weeks, developed abnormal texture, unacceptable appearance and off-flavor. 2.3 Strawberry flavor volatiles. During the maturation and ripening of strawberry fruit, a number of biochemical reactions are responsible for the development of aroma compounds (Tressl and Jennings, 1972; Paillard, 1981) . Volatile compounds such as aldehydes, alcohols and esters are well known as major contributors to the aroma of fruits and vegetables (Eriksson, 1979). In some fruits and vegetables, specific compounds have been identified as contributors to the unique flavor and aroma of each particular produce. Hexanol, trans-2-hexenal and 2-methylbutanoate contribute to typical apple aroma (Dimick and Hoskin, 1981) . Although it has been suggested that the strawberry has no 'character impact' compound (Yamashita et. al, 1976 a,b), most of the volatile compounds identified in this fruit include alcohols, aldehydes and esters (Teranishi et al. 1963; Honkanen and Hirvi, 1990) . McFadden et al. (19 65) combined gas chromatography (GC) and mass spectrometry (MS) to analyze the complex oil of strawberry volatiles. Among the 150 compounds isolated were alcohols, esters, acetals, aldehydes, furfural, aromatic aldehydes, ketones as well as terpenes and aromatic hydrocarbons. Schreier (1980) studied 18 volatiles of cultivated strawberries of Fragaria ananasa c.v. Senga Sengana, Senga Litessa and Senga Gourmella using GC/MS after the extraction of compounds by combined vacuum distillation-liquid-liquid extraction, and by prefractionation on silica gel. The main compounds isolated from the fresh and frozen fruit were methyl and ethyl butanoate, methyl and ethyl hexanoate, trans-2-hexenyl acetate, trans-2-hexenal, trans-2-hexen-l-ol as well as 2,5-dimethyl-4-methoxy-3-(2 if) -furanone. The compound, 2 , 5-dimethyl-4-methoxy-3- (2if) -furanone, in strawberry has been isolated and identified (Scheier, 1980; Pickenhagen et al., 1981), and is now recognized as the compound contributing to that unique flavor/aroma characteristic of strawberry fruit. Douillard and Guichard (1990) studied the aroma compounds characterizing six strawberry cultivars. Sixty compounds identified by GC-MS were mainly esters, but also compounds related to furanone such as 2,5-dimethyl-4-methoxy-2,3-dihydrofuran-3-one (mesifurane), 2,5-dimethyl-4-hydrofuran-3-one (furanoel) and nerolidol. However, Dirinck et al. (1981) also reported sulphur containing compounds that included methylthiol esters, methylthiol acetate and methylthiol butanoate in strawberry fruit. They indicated that these compounds had to be considered to explain the differences in the aroma of strawberry varieties. 2.4 Biosynthesis of flavor/aroma volatiles in strawberries. Formation of esters and other volatiles in fruits and vegetables have been at the center of flavor research in the last 19 few years (Salunkhe and Do, 1976). Weurman (1961) found that seven volatiles were formed when an enzyme mixture and a mixture of nonvolatiles prepared from different parts of raspberry fruit were added together. In many fruits and vegetables, the precursors of the volatiles have been identified. In bananas, the precursor to isoamyl alcohol and isoamyl acetate volatiles, which typify banana flavor, has been identified as the amino acid, leucine (Tressl and Drawert, 1973). They also found that other amino acids, such as valine and phenylalanine, and fatty acids, were converted to alcohols, esters and ketones by the fruit. The biosynthesis of carboxylic esters is thought to result from the esterification of aliphatic alcohols with organic acids in strawberry fruit tissue. Yamashita et al. (1975; 1976a; 1977) studied the formation of volatile esters in strawberries. Aldehydes, such as acetaldydes, propanal, butanal, pentanal and hexanal, were reduced to their corresponding alcohols upon incubation with the fruit. The aliphatic alcohols such as methyl, ethyl, isopropyl, isobutyl, 72-amyl and hexyl were subsequently converted to their respective esters i.e. acetate, propionate, n-butanoate, isovalerate and caproate during incubation with strawberry fruit. The headspace gas of 'Golden Delicious' apples, treated with propionic acid, C3- to C6-aldehydes or C2-to C6-carboxylic acid vapors, was analyzed by De Pooter et al. (1981; 1983). They found that propionic acid was esterified to propionates, and the aldehydes and acids to alcohols and esters, respectively. They suggested that the aldehydes were either 20 transformed into the corresponding alcohols and esterified with carboxylic acids present in the tissues or (to a small degree) oxidized into acids, which reacted with tissue alcohols. Conversion of aldehydes into alcohols and subsequent esterification to esters is thought to be enzyme catalyzed (Eriksson, 1979; Yamashita et al. 1979; Bartley and Hindley, 1980). Weurman (1961) could only obtain volatiles from a raspberry extract preparation when both the enzyme, alcohol dehydrogenase, and coenzyme I were present. Yamashita et al. (1976b and 1978) found two alcohol dehydrogenases in strawberry seeds. One enzyme was found to be NAD-ADH specific and reacted with ethanol and allyl alcohol while the other was NADP-ADH specific and reacted with benzyl alcohol and geraniol (Yamashita, et al., 1982). They concluded that the NAD-dependent alcohol dehydrogenase (alcohol:NAD oxidoreductase) reacted only with alcohols and aldehydes, while aromatic and terpene , alcohols were better substrates for NADP-dependent alcohol dehydrogenase (alcohol:NADP oxidoreductase) than aliphatic alcohols and aldehydes. Aldehydes are important compounds in the whole pathway leading to synthesis of esters. It has been established that aldehydes originate mainly from enzymic breakdown of linoleic and linolenic acids and other fatty acids (Galliard and Philips, 1972; Galliard and Philips, 1975; Galliard et al. 1976; Eriksson, 1979). Galliard and Matthew (1976) found an enzyme system in cucumbers that catalyzed the a-oxidation of fatty acids to shorter chain products. Galliard et al. (1976) reported the major aldehyde in the cucumber, 21 resulting from lipid degradation, was trans-2-nonenal. A lipoxygenase-type enzyme system was involved in the cleavage process. Galliard et al. (1976) and Galliard et al. (1977) proposed enzymic pathways for the biogenesis of aldehydes such as hexanal, cis-3- and trans-2-nonenal from lipids in tomato fruit (Figure 1) . They suggested that the main pathway involved the sequential activity of lipoxygenase, hydroperoxide cleavage and cis-3-:trans-2-enal isomerase enzyme. In addition to lipids, amino acids can be converted to volatile compounds. Yu et al. (1968) analyzed compounds produced from amino acids by enzyme extracts from tomato fruit. Carbonyl compounds such as propanal as well as alcohols were produced from alanine, leucine and valine as substrates. They suggested that the mechanism may involve transamination. 2.5 Volatiles of fruit kept under CA/MA conditions. Assessment of aroma of fruits and vegetables is an important aspect in the control of quality during storage of the fresh products. Modified atmosphere storage extends the storage life of a number of fresh products, but development of off-flavors/odors is of concern (El-Kazzaz, et al. 1983; Browne et al., 1984). With the identification of flavor/aroma compounds contributing to undesirable attributes, these compounds could be used as indicators of off-odor. Takeoka et al. (1986) studied the formation of artifacts in Kiwi fruit concentrate stored at -10°C. They found a number of degradation products that were considered to contribute Lipid 22 Linoleic acid Linolenic acid Lipoxygenase 9-Hydroperoxy 13-Hydroperoxy 9-Hydroperoxy 13-Hydroperoxy I cis-3-Nonenal Hexanal I trans-2-Nonenal I L cis-: K Hexi 3-Hexenal 1 cis-3,cis-6-Nonadienal trans-2-Hexenal J trans-2, cis-6-Nonadienal I trans-2- cis-3- Hexan-1-ol trans-2- trans-2, Nonen-1-ol Nonen-1-ol Hexen-1-ol cis-6-Nonadien-1-ol cis-3, cis-6-Nonadien-1-ol Alcohols + Carboxylic acid' Carboxylic esters Figure 1. Summary of proposed pathways for the formation of aldehydes and subsequent formation of carboxylic esters from lipid degradation (Galliard et al. 1976; Galliard et al. 1977; Eriksson, 1979). 23 to off-flavors in the Kiwi fruit concentrate. Synthesis of volatiles continues in harvested fruits and vegetables during storage (Tressl and Jennings, 1972) . The amounts and types of volatiles formed can be influenced by storage conditions. Johansson (1961) reported increased non-ethylenic volatiles in CA rooms containing stored apples, but water scrubbing of the gas mixture in the rooms prevented the increase of volatiles in the CA room atmosphere. De Pooter et al. (1981) compared the formation of volatiles in intact apple fruit that had been treated with propionic acid and kept under CA or air. Higher amounts of propionate and total propyl esters were formed in fruit kept under CA than in air. De Pooter et al. (1987) noted that apples kept under CA had increased concentrations of aldehydes derived from added carboxylic acids and suggested the presence of a reductive path for the conversion of carboxylic acids into aldehydes. They concluded that high carbon dioxide levels in CA-storage interferes with carboxylic acid metabolism and alcohol dehydrogenase activity, leading to a deterioration of aroma quality. Crouzet et al. (1985) found more volatiles in tomato fruit stored under CA than in artificially or field-ripened fruit. However, there appears to be contradictory evidence on the effects of CA/MA storage on fruits with regard to volatile compounds. This may be related to the type and maturity of fruit as well as the storage conditions under investigation. 'Cox's Orange Pippin' apples gradually lost their ability to ripen normally when stored in a 2% 02 microatmosphere at 3.5°C, but their 24 transfer to air at 20°C resulted in slight production of volatiles (Patterson et al., 1974). Paillard (1981) analyzed the headspace aroma compounds of 'Cox' apples placed in CA storage and showed a depressed rate of some volatile compound production during the ripening stage. Yahia et al. (1990) studied the effect of CA storage on volatiles of 'Mcintosh' and 'Cortland' apples. Controlled atmosphere storage (3% 02 + 3% C02 + 94% N2) of apples at 0°C for 19 weeks caused a 'residual suppression' effect on the production of propyl butanoate, butyl hexanoate and hexyl hexanoate. They concluded that CA may alter the metabolism of the fruit by blocking the normal production of some volatiles. Other researchers also found that apples stored under CA either failed to synthesize adequate amounts of desirable volatiles or had reduced production of overall volatiles (Guadagni et al. , 1971) . Lidster et al. (1983) found that the development of headspace ethanol, acetaldehyde, ethyl butanoate and hexenal was suppressed in apples stored in modified atmosphere at 2.8°C. Although placement of fruit in room air initially regenerated ethyl butanoate and hexenal, storage of fruit in 1.5% C02 + 1.0% 02 for 320 days completely suppressed the principal headspace volatiles and blocked their subsequent regeneration in room air. Willaert et al. (1983) also found that long term storage of apples under CA resulted in a decrease of aroma quality. 2.6 Methods of volatile extraction and analysis. A number of extraction methods have been used to study flavor 25 volatiles of strawberry fruit and other horticultural products (Leahy and Reineccius, 1984; Nunez, et al., 1984). These methods include liquid-liquid or solvent extraction (Hirvi, 1983; Idstein et al. 1984; Douillard and Guichard, 1989), steam/distillation extraction at atmospheric pressure or under vacuum (Pino, 1982; Bartely and Schwede, 1987; Ohta, et al., 1987) and headspace volatile extraction (Schaefer, 1981; Liardon et al. 1984) . The objective of the study generally governs the method of choice and this in turn affects the type and amounts of volatiles obtained (Parliment, 1986). Yabumoto and Jennings (1977) used direct headspace sampling, entrapment of headspace gas on Porapak Q adsorbent and steam distillation-extraction (SDE) of volatiles of cantaloupe. Direct headspace sampling resulted in low boiling volatiles while Porapak Q trapping was less efficient at trapping ethylene, methyl acetate, ethyl acetate and ethanol. SDE resulted in extraction of high boiling compounds. Of the three methods Nunez et al. (1984) used in their grapefruit studies, SDE gave the best results as compared to distillation-solvent extraction. However, Bartley and Schwede (1987) found that the concentrations of mango volatiles were markedly decreased when the volatiles were isolated by SDE as compared to a headspace vapor concentration procedure. The variation in the type and amounts of volatiles obtained can be attributed to the fact that each isolation procedure alters to some extent the overall aroma composition of the product extracted. Honaken and Hirvi (1990) attributed this fact to formation of new compounds and artifacts during the 26 extraction procedure. Jennings and Filsoof (1977), after studying a number of preparation and extraction methods, concluded no single sampling procedure is entirely satisfactory, but that one procedure may be superior depending on the sample composition and the compounds of interest. 2.6.1 Liquid-liquid and steam distillation procedures. The liquid-liquid (solvent) method for extraction of volatiles is the easiest among all extraction procedures and involves simply mixing the liquid sample with a solvent to extract the volatiles. Mixtures of different solvents such as diethyl ether, pentane and dichloromethane have been found to be efficient in the extraction of volatiles. Flath and Forrey (1970), using isopentane, extracted 45 volatiles from 'Smooth Cayenne' pineapple. Schreier et al. (1980) used liquid-liquid extraction, adsorption chromatography on silica gel and coupled gas chromatography-mass spectrometry (GC-MS) to study the aroma compound composition of ten Burgundy Pinot noir wines. Hirvi (1983) extracted volatiles from a number of strawberry varieties by mixing the pressed juice with a mixture of pentane-diethyl ether (1:2). Douillard and Guichard (1989) identified and quantified 61 volatiles from fourteen frozen strawberry varieties after direct extraction with dichloromethane. Leahy and Reineccius (1984) reported that solvent extraction is limited to the analysis of foods that contain little or no lipids. They also noted that this method is labor intensive, and results in poor extraction of low boiling compounds. Tressl et al. (1977) 27 extracted 100 aroma components from cooked white asparagus using a liquid-liquid procedure. However, they required 18 L of sample and 24 hr to extract the volatiles. Distillation extraction involves removal of volatiles by the application of heat. Dix and Fritz (1987) found distillation extraction to be a simple, fast and effective isolation procedure with excellent recoveries of a number of organic compounds with boiling points ranging from 77 to 238°C. Distillation under normal atmospheric pressure usually involves high extraction temperatures (Nunez, et al. , 1984; Ohta, et al. , 1987). This generally results in formation of artifacts by thermal degradation or hydrolysis (Leahy and Reineccius, 1984). Vacuum distillation is used to limit the thermal degradation of volatiles and formation of artifacts. Pino (1982) and Pino et al. (1986 a,b) used a vacuum rotary evaporator to extract volatiles from orange and grapefruit juices with diethyl ether being used to separate the volatiles from the distillate vapor. Guichard and Souty (1988) extracted 82 compounds from six cultivars of fresh apricots using vacuum distillation and fractionation on a silica gel column. Takeoka et al. , (1986) extracted volatiles from Kiwi fruit concentrate by vacuum distillation, followed by continuous liquid-liquid extraction. Variation of direct steam distillation led to simultaneous steam distillation-extraction (SDE). Likens and Nickerson (1964) designed the Likens-Nickerson apparatus for the simultaneous steam distillation-extraction (SDE) of volatiles from liquid samples. Hayase et al. (1984) extracted volatiles from mangoes using 28 simultaneous SDE. They identified 114 to 13 0 compounds which included hexanal and fcraris-2-hexenal. Spencer et al. (1978) extracted esters, monoterpernes and lactones from fresh and canned peaches using SDE. The advantage of this extraction apparatus is the concentration of dilute sample solution with small amounts of solvent. The use of a vacuum minimizes artifact formation due to use of low temperature. Ohta et al. (1987) extracted and identified a high-boiling, unstable compound, 2,5-dimethyl-4-hydroxy-2,3-dihydro-3-furanone from pineapple fruit using this procedure. 2.6.2 Headspace analysis of volatiles. Isolation of volatiles from the headspace vapor of food phase as a means of extracting volatiles has become very common in recent years (MacLeod and /Ames, 1986) . Direct headspace analysis of food volatiles in the vapor phase is one of the simplest procedures in analyzing equilibrium headspace vapor (Jennings and Filsoof, 1977). This method also gives more meaningful results than solvent or distillation procedures because of minimal introduction of artifacts (Bartely and Schwede, 1987) . Leahy and Reineccius (1984) reported that headspace methods are simple and rapid, and more importantly, measure the odorous compounds in the proportions typically presented to the human nose. Improvements to direct headspace volatile analysis have included the concentration of volatiles on solid adsorbents by purging the headspace vapor. The solid adsorption headspace 29 procedure involves purging a gas, generally nitrogen, over the headspace of the sample and through an outlet coupled to a tube packed with an adsorbent. The common solid adsorbents that have been used include Tenax GC (Bartley and Schwede, 1989), Porapaks (Jennings et al. , 1972; Tassan and Russel, 1974; Yabumoto and Jennings, 1977) and Chromosorbs (Chairote et al., 1981) which are all synthetic porous polymers. Activated charcoal has also been used as a volatile adsorbent (Dart and Nursten, 1984). The choice of the adsorbent depends on the properties and concentration of compounds and their purity. Schaefer (1981) evaluated five adsorbents during the study of carrot volatiles. Although Porapak Q and Ambersorb were found to be the best adsorbents, Porapak Q produced a number of blank peaks while large volumes of solvent were required to desorb the volatiles from Ambersorb. Tenax GC was found to have a low trapping efficiency while activated carbon was unable to trap some aldehydes. MacLeod and Ames (1986) compared Tenax GC and Tenax TA and obtained superior blank gas chromatograms from Tenax TA. Tenax GC was highly stable at a very high temperature, had relatively low background levels and was capable of extracting high-boiling compounds. Headspace vapor analysis with adsorbents has been used to adsorb volatiles from beverages (Jennings et al. 1972), onions (Mazza et al. , 1980), sourdough (Hansen and Lund, 1987), oysters (Josephson et al. 1985) and tomatoes (Buttery et al. 1988). Desorption of volatiles from the trap either involves thermal desorption (Tassan and Russel, 1974; MacLeod and Ames, 1986; Bartley and Schwede, 1989) or solvent 30 extraction (Hansen and Lund, 1987; Buttery et al. 1988). The headspace analysis procedures are best suited for the most volatile, low boiling compounds. 2.7 Relationship between sensory and volatile compound data. Sensory quality of food is an important aspect in the success of a 'new' storage technique. Sensory panel evaluation of food products has become a standard quality assurance practice. To measure sensory quality, a set of sensory quality criteria that describes the largest, most relevant and most reliable variations for a given product is required (Piggot, 1986). Therefore, it is important that descriptors be examined first to determine whether they are truly critical to the evaluation of the product. Because of the many quality variables that can be used, statistical approaches can be utilized to evaluate sensory descriptors, performance of judges and product under study (Kwan and Kowalski, 1980) . Sensory evaluation by itself, however, is inadequate to describe all the quality changes in food products. Thus, sensory evaluation has been used in conjunction with instrumental analysis to offer a better explanation of quality changes in food products (Liardon et al. 1984). The presence of trace amounts of volatiles are responsible for the odor that gives much of a product character (Yahia et al., 1990). More than 150 compounds were identified in strawberry fruit (McFadden et al., 1965). Therefore, correlation of sensory data with instrumental analysis of volatile compounds to 31 assess the aroma quality of fruit is important. Min (1981) obtained good correlations between sensory evaluation and GC data of edible oil subjected to various levels of oxidation. Pino (1982) and Pino et al. (1986a,b) applied linear regression to sensory and volatile compound data for orange and grapefruit juices. Such compounds as myrcene, 2-hexanol, linalool in orange juice and methyl butanoate, ethyl butanoate, limonene, nootkatone in grapefruit juice were found to contribute significantly to juice aroma. Spencer et al. (1978) applied stepwise multiple regression to determine the relationship of sensory and volatile data from fresh and canned peaches. Description of odor of gas chromatographic eluates can provide valuable information as well (Tassan and Russel, 1974). Chairote et al. (1981) trapped apricot headspace volatiles on chromosorb adsorbent and subjected the traps to a sniff test. Their results indicated that the aroma of apricot was due to the presence of compounds such as benzaldehyde, linalool, 4-terpineol and 2-phenylethanol which are responsible for the floral and fruity notes of the aroma. Hayase et al. (1984) characterized the changes in odors of tomato fruit during ripening by using the GC-sniff method. They found that hexenal, trans-2-hexenal, 2-iso-butylthioazole, 2-methyl-2-hepten-6-one, geranylacetone and farnesylacetine increased with natural and artificial ripening. It is thus possible to obtain valuable information concerning the character and the strength of odorous components (Honkanen and Hirvi, 1990). Hall and Anderson (1985) reported that the importance of any volatile 32 compound to food odor and flavor is generally determined by relating the actual concentration of the compound to an odor or flavor threshold value. They used multiple regression analysis to obtain predictive equations, some of which had high correlations with flavor descriptors. Although strawberry fruit has been described as having no 'character impact compound', some of the compounds identified in the berries have been correlated with sensory data. Honkanen and Hirvi (1990) reported that correlations have been obtained between the sensory character of odor of fresh strawberries with concentrations of volatile compounds such as ethyl butanoate, ethyl hexanoate, trans-hexen-2-enal, 2 , 5-dimethyl-4-methoxy-2ff-furan-3 -one and linalool. Guichard and Souty (1988) compared the relative quantities of aroma compounds in six cultivars of fresh apricots. They found that 'Moniqui' had a flowery aroma due to the presence of terpenic ketones. However, 'Polonais', which contained many C6-compounds, had herbaceous notes. 2.8 Multivariate analysis of sensory and flavor/aroma data. Because large amounts of data are collected during volatile compound analysis, appropriate methods for data handling and analysis are required. McFadden et al. (1965) isolated 150 volatile compounds from strawberry fruit; however no statistical analysis was carried out. Multivariate statistical analysis (MVA) methods are now being commonly used in food science studies especially those related to flavor volatile analysis. Aishima (1979 a,b) and 33 Aishima et al. (1979) applied MVA to GC volatiles extracted from soy sauce samples. The techniques used by those researchers included multiple regression, principal component analysis (PCA) and discriminant analysis. They concluded that: a) eight brands of soy sauce could be discriminated and classified by use of those MVA techniques; b) the GC data could be related to sensory scores; and c) large sets of data could be reduced in dimension. Schreier and Reiner (1979) carried out discriminant analysis on GC data from German and French brandies and French cognacs. Statistically highly significant separations between the samples were obtained and volatile esters were found to contribute to the separation and classification of individual groups. Liardon and Ott (1984) and Liardon et al. (1984) first applied stepwise discriminant analysis (SDA) to select, from the bulk of coffee headspace components, the most significant volatiles for discriminating the different profiles. The subsets obtained were analyzed by canonical (CA) and discriminant (DA) analysis. They found that 55 profiles could be classified into 15 coffee categories with a 90% success rate. MVA has also been applied in the characterization of white wine (Cabezudo et al., 1985) and frozen peas (Martens, 1986). 34 3.0 MATERIALS AND METHODS. 3.1 Strawberry samples and preparation. 3.1.1 Strawberry samples. 'Chandler' strawberries, imported from California and purchased from local wholesalers in Vancouver, British Columbia, were used in these experiments. Soon after purchase, the strawberries were selected on the basis of uniform red color, moderate size, touch-firmness and lack of physical damage. The selected berries were weighed into samples of 3 00 grams each. 3.1.2 Modified atmosphere packaging of strawberry samples. Each 300 gram strawberry sample was packed into pouches made from high barrier polyolefin plastic film (CL 804, Dupont Canada, Windsor, ON). The gas transmission rates of the film were 0.31, 1.55 and 4.65 cm3/m2/24 hr/atm at 23°C for nitrogen, oxygen and carbon dioxide, respectively (Dupont Canada, Windsor, ON) . The moisture vapor transmission rate was 4.65 g/m2/24 hr at 95% RH at 23°C. Each pouch measured 2 0 cm by 2 0 cm with a surface area to sample weight ratio of 1.33 cm2/g. Each pouch with 3 00 grams of fruit sample was flushed with the intended gas or gas mixture and quickly heat sealed. Samples for sensory evaluation and chemical analysis were packaged in duplicate while samples for gas and volatile compound analyses were packaged in triplicate. Unpackaged strawberry samples (control) were placed in open flat cardboard boxes which were wrapped with low barrier plastic film to prevent excessive moisture loss and dehydration of fruit. 35 3.1.3 Gas treatment and storage of strawberry samples. The gases used to flush the packaged fruit were carbon dioxide (100% C02) , mixed gas (11% C02 + 11% 02 + 78% N2) and air (Linde Specialty Gas Co., Vancouver, BC & Edmonton, AB) . All fruit samples were stored at 1°C for up to 10 days. The whole experiment was repeated five times during the study period (August 1989 -preliminary; March 1990, April 1990, July 1990 - experimental data collection; and October 1990 - data for comparison between headspace volatile compounds desorbed by solvent and thermal desorptions). 3.1.4 Sampling procedure and analyses of MAP strawberry samples. Modified atmosphere packaged fruit for each gas treatment and unpackaged fruit was removed from storage at days 3, 6 and 10, and analyzed for desired parameters. The strawberries were also analyzed at day 0 prior to storage. At each sampling time, the strawberries from each treatment were subjected to sensory evaluation, volatile compound determination and gas analysis. Chemical analyses of ethanol, glucose and fructose as well as the determination of soluble solids, pH, titratable acidity were carried out. 3.2 Sensory evaluation. Quantitative descriptive analysis (Stone et al. , 1974) was used to evaluate sensory attributes of strawberry fruit stored under modified atmosphere (MA) conditions. This procedure involved 36 extensive training of judges, as well as the judges establishing descriptive terms to characterize the product under investigation and also being able to quantitatively estimate the intensity of each attribute (Kwan and Kowalski, 1980; McTigue et al., 1989). 3.2.1 Training of judges. Nine judges, aged between 25-40 years (5 females and 4 males), with sensory evaluation experience were trained in descriptive evaluation of strawberry fruit. All judges were associated with the Food Science Department (UBC) and were selected on the basis of interest and availability. Due to the small number of judges, all were retained through the study with continued training. The strawberries used during the training sessions had been subjected to various treatments such as storage at 0, 5, 10 and 2 0°C with and without packaging in different gas mixtures and different film pouches for 2 to 5 days. A two-week training period involving four sessions was used to familiarize the judges with characteristics of strawberries and to establish terms to describe the quality attributes of strawberry fruit stored under different gas conditions (MAP) at 1°C. Further, standardization of the judges on the varying intensities of sensory (flavor) characteristics was essential. During the training sessions, a number of descriptors from the literature (Noble and Shannon, 1987) and suggestions from the judges were used. The terms retained were those that the majority of judges agreed upon as the ones that would discriminate and differentiate the fruit (Table 1). A sensory score sheet with 37 Table 1. Sensory attributes used to describe characteristics of strawberry fruit stored under modified atmosphere packaging. Sensory attribute Definition Odor by mouth 1. Strawberry odor 2. 3. 4. 5. Off-odor Fermented odor Musty odor Earthy odor Taste 6. 7. 8. Sweet Sour Bitter Typical strawberry odor with fruity, estery aroma Undesirable odor indicating spoilage Odor characterized by alcoholic and fermented product Odor associated with moldy, musty character Odor associated with earth or soil Natural sweetness Natural sourness Natural bitterness Others 9. Texture 10. Overall fruit quality Firmness of fruit Acceptance of fruit taking into consideration of all the above attributes 38 10 cm unstructured scale lines, each with anchored terms at both ends such as 'none' and 'very strong', 'not unacceptable' and 'very acceptable' was used (Table 2). The judges indicated the intensity of each attribute by placing a vertical line on the unstructured line. Numerical data were obtained by measuring the distance from the left side (zero) to the vertical line made on the scale. 3.2.2 Sample preparation for sensory evaluation. At each sampling time, the strawberries from each treatment were removed from storage 1 1/2 hr prior to sensory evaluation to equilibrate to room temperature. The strawberries from each treatment were sliced into small pieces (1/8), mixed for homogeneity and subjected to sensory evaluation in replicate. The room was air-conditioned and illuminated with a red light. The coded samples (3 digit) were presented one at a time in a random order to the judges who sat in a round table set-up and made independent evaluations. The judges obtained their servings for each treatment from one main plate and there was a 3-5 min interval between each serving. Water and unsalted crackers were provided to the judges and used between each each serving. After the first set of replicate samples were evaluated, a short break (5 min) was taken at which time a discussion was initiated to ensure all judges were in agreement in their evaluation of sensory attributes, and as a means of continuous training. Replicate samples were evaluated at each session. At the end of each evaluation session, the judges 39 Table 3. Sensory score sheet used to quantitaively evaluate strawberry fruit SENSORY SCORE SHEET NAME DATE . .SAMPLE. Please evaluate the flavor/odor by mouth of these samples of strawberry. Make a vertical line on each horizontal line to indicate the intensity of each attribute. none Strawberry odor + very strong + Off-odor none + very strong + Fermented (alcoholic) Musty (Old/stale) none + none + very strong + very strong + Earthy/soil none + very strong + Texture not firm + very firm + Sweet none + very sweet + Sour none + very sour + Bitterness none + very bitter + not acceptable Overall quality + (acceptance) very acceptable + Comments: 40 were formally asked if they thought any of the samples were totally unacceptable and such samples were eliminated in the next evaluation session. 3.3 Chemical analyses. For the measurement of soluble solids, pH, titratable acidity, glucose, fructose and ethanol, 50 to 100 gram samples were used. Each strawberry sample was weighed, blended at a high speed at room temperature in a Waring blender for 3 min without the addition of water, followed by centrifugation at 10,000xg for 10 min at 1°C. The supernatant was filtered through a Whatman No. 4 filter paper and the filtrate was used for analysis. Soluble solids content of a sample was measured by placing a few drops of the filtrate on the prism surface of an Abbe Mark II Refractometer (Cambridge Instrument, Buffalo, NY) at 2 0°C. The pH of the strawberry filtrate was measured by a Fisher Accumet pH meter Model 62 0 (Fisher Scientific Co., Ottawa, ON). Titratable acidity was assessed by titrating the diluted filtrate (1:10) with 0.IN NaOH to pH 8.1 and was calculated as citric acid (g/lOOg sample). Glucose, fructose and ethanol were analyzed using enzymatic assay kits (Boehringer Mannheim, Laval, PQ). All measurements were carried out in duplicate. In the ethanol analysis, ethanol is oxidized to acetaldehyde in the presence of the enzyme alcohol dehydrogenase (ADH) by nicotinamide-adenine dinucleotide (NAD). Ethanol + NAD+ < > Acetaldehyde + NADH + H+ (1) 41 Under alkaline conditions, the trapped acetaldehyde is oxidized in the presence of aldehyde dehydrogenase (Al-DH) to acetic acid. The NADH formed is then determined by means of absorbance at 340 nm. Acetaldehyde + NAD+ + H20 > Acetic acid + NADH + H+ (2) In glucose and fructose determinations, D-glucose and D-fructose are phosphorylated by the enzyme hexokinase (HK) and adenosine-5'-triphosphate (ATP) to glucose-6-phosphate (G-6-P) and fructose-6-phosphate (F-6-P) with the simultaneous formation of adenosine-5'-diphosphate (ADP). D-glucose + ATP > G-6-P + ADP (3) D-fructose + ATP > F-6-P + ADP (4) In the presence glucose-6-phosphate dehydrogenase (G6P-DH), G-6-P is oxidized by nicotinamide-adenine dinucleotide phosphate (NADP) to gluconate-6-phosphate with the formation of reduced nicotinamide-adenine dinucleotide phosphate (NADPH). G-6-P + NADP+ > Gluconate-6-phosphate + NADPH + H+ (5) At the end of this reaction, F-6-P is then converted to G-6-P by added phosphoglucose isomerase (PGI) to form G-6-P. The G-6-P subsequently reacts with NADP forming gluconate-6-phosphate and NADPH. In each case, the NADPH formed is stoichiometric with the amount of glucose and fructose. The amount of NADPH was determined from the absorption values at 340 nm (Boehringer Mannheim manual, 1989) . 42 3.4 Extraction and analysis of volatiles from strawberries. 3.4.1 Solvent extraction of volatile compounds. One hundred grams of each strawberry fruit sample were blended with 100 mL of deionized water in a Waring blender for 3 min at room temperature and the slurry was extracted twice, each time with 100 mL of distilled dichloromethane or a mixture of diethyl ether and pentane (2:1) after vigorous shaking and standing for 2 hours at room temperature (Douillard and Guichard, 1990) . All high grade solvents were obtained from BDH Chemicals, Toronto, ON. The solvent extracts were dried over anhydrous Na2S04 (BDH Chemicals, Toronto, ON), and then were concentrated by holding the flask in a water bath maintained at 40°C. Finally the extract was concentrated further to approximately 200 (XL by a gentle stream of N2 over the surface. The concentrated extracts (1 (XL) were injected into the GC for isolation and analysis. 3.4.2 Distillation extraction of volatile compounds. Direct and vacuum steam/distillation were also used to extract volatile compounds from strawberry fruit (Schreier, 1980) . A 100-gram sample of fruit was blended with 100 mL of deionized water in a blender as described in section 3.4.1. The blended mixture was subjected to distillation without and with a vacuum at 650 Pa using a Buchi Rotavapor apparatus unit (Glasapparatefabrik, Flawil, Switzerland) or to a modified Likens-Nickerson apparatus for simultaneous steam distillation extraction (Aishima, 1983). With distillation extraction in the Rotavapor apparatus, the temperature 43 was maintained at 80-90°C without vacuum and 45-50°C with vacuum using a Buchler Thermolift (Buchler Instruments, Inc., Fort Lee, NJ) water bath. When the Likens-Nickerson apparatus was used, the blended fruit in flasks were heated to a temperature of 40-50°C with the aid of a heating jacket. The volatile compounds were collected by condensing them on traps cooled to -1°C with water containing anti-freeze. The extraction was carried out for 2 hr and the condensed volatile compounds were separated by liquid-liquid or solvent extraction using dichloromethane or a mixture of diethyl ether and pentane (2:1) at room temperature. The extracts obtained were concentrated to approximately 200 |LlL as described in section 3.4.1 and analyzed by GC. 3.4.3 Headspace volatile extraction procedures. Strawberries taken from storage were extracted by a dynamic headspace technique and analyzed by gas chromatography (GC), and the volatile compounds identified with gas chromatography-mass spectrometry (GC-MS). 3.4.3.1 Headspace volatile extraction with solvent desorption from Tenax GC. Strawberry samples were enclosed in flasks and the volatile compounds extracted by purging the headspace gas with N2 and trapping the volatile compounds onto a porous polymer - Tenax GC (Dirinck et al. , 1977; Hirvi and Honkanen, 1982; Olafsdottir et al. , 1985) . Three hundred grams of a strawberry sample from each 44 treatment were sliced into quarters and placed into 2 L three-neck round bottomed flasks held at 40°C (Figure 2). An inlet tubing delivered high grade prepurified UHP (ultra-high purity) N2 (Linde Specialty Gas Co., Vancouver, BC) flowing at 30 mL/min. Gas from the flask flowed through outlet glass tubing and passed through an adsorbent trap containing Tenax GC (p-2,6-diphenyl-p-phenylene oxide; 60-80 mesh, Alltech Co., Deerfield, IL). Approximately 120 mg of Tenax GC was packed into each glass tubing and secured at both ends with deactivated glass wool. The glass wool and the glass tubings were deactivated with SYLON™-CT (5% dimethyl-dichlorosilane) (Sulpelco Inc., Toronto, ON) prior to use. The glass tubings measured 11.5 cm in length, 6 mm outer diameter and 4 mm internal diameter. The Tenax GC adsorbent was conditioned before use with N2 which passed through the traps at 2 0 0°C for 4 or more hr at a flow rate of 30 mL/min (Jennings and Filsoof, 1977) . During volatile compound extraction, the flasks containing the fruit slices were held in a water bath at 40°C for 3 0 min and then purged with prepurified N2 at 3 0 mL/min for 2 hr. The volatile compounds trapped onto the Tenax GC were eluted with 2 mL of double distilled diethyl ether (BDH Chemicals, Toronto, ON). The ether extract was concentrated by a gentle stream of N2 on the surface to approximately 200 (J.L and 1 |LlL was injected into the GC and GC-MS for separation and identification of the volatile compounds. To quantify the compounds, 2-nonanone (PolyScience Corp., Niles, IL) was added to the flasks as the internal standard before purging the volatile compounds. This internal standard was dissolved in 45 Tenax GC Nitrogen inlet i—. _Glass stopper Strawberries Water bath Figure 2. Set-up for the apparatus used to collect the headspace volatiles by trapping on the adsorbent Tenax GC. 46 diethyl ether in the ratio of 1:10 and 0.5 mL was added to the flask. Quantitation was performed by taking the ratio of each peak to that of the internal standard as relative amounts of volatile compounds. 3.4.3.1.1 GC analysis of volatile compounds desorbed by solvent. Volatile compounds desorbed by solvent from the Tenax GC adsorbent were separated and analyzed on a Varian 3700 GC (Varian Associates, Inc., Palo Alto, CA) equipped with a flame ionization detector (FID) and connected to a fused SPB-1 non-polar capillary column (30 m, 0.20 mm i.d., 0.25 (im film thickness - Supelco Inc., Toronto, ON) . The temperature was held at 3 0°C for 5 min and then programmed to 2 00°C at 5°C/min. Injector port and detector temperatures were set at 250°C, and the flow rates for hydrogen and air were 30 and 300 mL/min, respectively. Helium carrier gas flow was set at 3 0 mL/min and into the column at 1 mL/min. The split ratio was 100:1. Peak areas were integrated and recorded on a Hewlet-Packard 3390A integrator (Hewlet-Packard, Avondale, PA). 3.4.3.2 Headspace volatile extraction with thermal desorption from Tenax GC. Volatile compounds were extracted from strawberries and trapped in a similar manner as described in section 3.4.3.1. This was followed by thermal desorption-gas chromatography/mass spectrometry analysis - TDGC/MS (Hirvi and Honkanen, 1982). The trapped volatiles from each strawberry sample were thermally desorbed from 47 the Tenax GC with a Dynatherm Thermal Desorption Unit (TDU) Model 850 (Hewlet-Packard, Avondale, PA) . The TDU was operated at a desorption temperature of 2 5 0°C for 5 min. The TDU valve compartment was held at 150°C with the heated transfer line at 165°C. The TDU was coupled to a Hewlett-Packard 5988A GC/MS (Hewlet-Packard, Avondale, PA). The desorbed volatile compounds were cryo-focused at 10°C using liquid carbon dioxide. The GC/MS was connected to a non-polar, thick, capillary column (60 m, 0.32 mm i.d., 1.0 |Llm film thickness) phase bonded with 5% diphenyl:94% dimethyl:1% vinyl polysiloxane phases (SPB-5, Sulpelco, Inc., Toronto, ON). The analytical column was held at 10°C for 5 min, ramped to 160°C at 5°C/min, then programmed at 8°C/min to a final temperature of 250°C and held at this temperature for 4 min. The column was directly interfaced to the mass spectrometer (MS) source through a 250°C transfer line. The MS was operated with an ion source temperature of 200°C, ionization voltage of 70 eV and electron multiplier at 2200 V. The data were stored on a hard disk and held for processing. 3.4.4 Volatile compound extraction from model system. Available known volatile compounds were added to diethyl ether for model studies. These standard compounds were obtained from Aldrich Co., Milwaukee, WI and PolyScience Corp., Niles, IL. Each standard was added to diethyl ether in the ratio of 1:10 and directly injected into the GC to determine the retention times, the 48 response of the volatile compounds and performance of the GC with repeated injection. The standards were also extracted using the headspace extraction procedure described above as a measure of recovery of volatile compounds after extraction. 3.4.5 Identification of volatile compounds by GC/MS. At UBC, GC-MS analyses were performed with a Hewlett-Packard 5985 mass spectrometer (Hewlet-Packard, Avondale, PA) directly coupled to a gas chromatograph using the same column and injection conditions with same temperature programme conditions described in section 3.4.3.1.1. Electron impact mass spectra were recorded at 70 eV (ion source energy), and the ion source and interface temperature were set at 200°C and 285°C, respectively. At BC Research, a Hewlett-Packard 5988A GC/MS (Hewlet-Packard, Avondale, PA) was used to acquire mass spectras. The column conditions for the GC are described in section 3.4.3.2. Available standard volatile compounds were analyzed on the same GC/MS systems. The mass spectral patterns of the volatile compounds were first matched with the standard spectra from the National Bureau of Standards (NBS) Library on the Data System. Confirmation of volatile compounds was made by using retention time data and the spectral data from analysis of available authentic volatile compounds. 3.5 Gas monitoring in packages with strawberry fruit The gas composition of the atmosphere within each pouch was 49 monitored during the storage period. C02 and 02 were analyzed by sampling 0.5 mL of headspace gas using a 1 mL gas-tight syringe fitted with a stainless steel needle and injecting the gas into the Shimadzu Gas chromatograph 14A (Shimadzu Scientific Instruments, Inc., Kyoto, Japan) equipped with a thermal conductivity detector (TCD) . Sampling of gases from the pouches was made through a clear GE Silicone seal (GE Canada, Mississauga, ON) adhered to each pouch by 3M Scotch™ magic tape. The GC was fitted with dual stainless steel columns (1.8 m and 3.2 mm i.d.) packed with Porapak N (80-100 mesh, Sulpelco Inc., Toronto, ON) for separating C02 and Molecular Sieve 5A (60-80 mesh, Sulpelco Inc., Toronto, ON) for 02. The flow rate for helium, the carrier gas, was 3 0 mL/min. Oven temperature was set at 80°C and injector port and detector temperatures were 150°C. A standard gas (Linde Specialty Gas, Co., Edmonton, AB) containing 14.0% C02, 4.49% 02, 0.50% C2H2, and the balance being N2 was used to standardize the GC prior to gas sample analysis. Peak areas for the gases were integrated and directly converted to percentage gas by a Shimadzu CR501 Chromatopac integrator (Shimadzu Scientific Instruments, Inc., Kyoto, Japan). For each treatment, triplicate injections were made at each sampling time. Gas sampling commenced 1-2 hr after packaging and placing in storage and thereafter was measured at each sampling time. Air contains 0.93% argon (Ar) (Weast, 1984). Since 02 and Ar coeluted in the column system employed for in-package gas analysis, the Ar content was subtracted from the 02 content. 50 3.7 Statistical analyses. 3.7.1 Analysis of variance and correlations. The sensory data obtained were subjected to analysis of variance (ANOVA) using General Linear Models (GLM) and means were separated by least significant difference (LSD) (Greig and Bjerring, 1980; SAS, 1985). The experimental design for sensory measurements was a randomized incomplete block design over time and in repeated measurement (Gomez and Gomez, 1984; Nakhasi et al. , 1991). The main effects used in the analysis of sensory data in the three-way ANOVA were gas treatments (carbon dioxide, mixed gas, air, as well as unpackaged), storage times (0, 3, 6 and 10 days) and judges (block). Sensory data collected during the experimentation were combined (March, April and July). Fisher's (protected) least significance differences (lsd) were computed for the treatments and storage times to determine the significant difference among these effects (SAS, 1985). Simple correlation coefficients were computed for all sensory variables with chemical parameters and with gas chromatographic data (SAS, 1985) . 3.7.2 Multivariate statistical analysis. Multivariate analysis using principal component, multiple regression and discriminant analysis were applied to the collected sensory and volatile data (BMDP, 1985; SAS 1985; SYSTAT/SYGRAPH, 1989). These techniques were applied to reduce the dimension of data and to identify subsets of variables of sensory attributes and volatile compounds that would best explain the important changes in 51 the fruit stored under MAP conditions. Multivariate analysis of variance (MANOVA) was used to examine all the sensory attributes at once to reveal their influence on treatments over storage time, and multiple discriminant analysis was used to classifying samples based on gas chromatographic data into different treatment and/or quality level (Noble et al. 1984; SAS, 1985). Three types of multivariate analyses were performed by BMDP (1985), SAS (1985) and SYSTAT/SYGRAPH (1989) computer packages. (1) Principal component analysis (PCA) Principal component analysis is a statistical technique that involves transformation of the original set of p variables (Xa/ X2, . . . , Xp) obtained from n observations into smaller sets of linear combinations that account for most of the variance of the original set of variables (Dillon and Goldstein, 1984) . Principal components (PCk) are calculated from equation 6. PCk = auX! + a12X2 + a13X3 + ... + akiXk (6) where aki represents the eigen vector with the sum of squares being one. The variance in PCk is maximized among all principal components with PCk and PCk+1 being uncorrelated (Aishima, 1979a) . (2) Discriminant analysis Multiple discriminant analysis (canonical variate analysis) was also used to obtain a more detailed analysis of volatile compounds and interpret the flavor changes in the fruit as well as classifying the fruit into various treatments and/or quality levels. The main objective of multiple discriminant analysis is to classify a number of observations (n) into previously defined 52 groups (k) based on several measurements (Xx, X2, . . . , Xp) taken on predictor variables (Dillon and Goldstein, 1984). Using the independent variables, the technique derives linear combinations which are used to calculate discriminant scores or functions which aid in classification of individual observations. The discriminant function is expressed as: Zi = ailXl + ai2X2 + • • • + ^ipXp (V) where Z{ is the discriminant score, aip is the discriminant weight and Xp is the independent variable. The linear combination derived (Zt) is calculated in such a way as to maximize the ratio of between-group variation to within-group variation. The generalized distance calculated from discriminant functions are called Mahalanobis (D2) distance and canonical variables are calculated in order to discriminate samples on the basis of two dimensional space (Aishima, 1979b). The resultant canonical variables form a new co-ordinate system in which the samples can be plotted. Stepwise discriminant analysis can also be used to select subsets of independent variables that best discriminate among the samples. (3) Multiple regression analysis Regression analysis estimates or predicts the mean value of the dependent variable Y on the basis of the known or fixed values of one or more explanatory (independent) variables Xi (Dillon and Goldstein, 1984) . A multiple regression model is generally expressed as: Y = B0 + BaXi + B2X2 + BiXi + . . . + BmXm + e (8) where Y and Xi represent dependent and independent variables, 53 respectively. B0 and Bi represent a constant and partial regression which are calculated by a linear least square method while e is the error term. A correlation coefficient between Y and scores estimated from calculated multiple regression model is called a multiple correlation coefficient (R) . R2, called a multiple determination coefficient, expresses the explained ratio of variation in Y from the multiple regression model (Aishima, 1979b). 54 4.0 RESULTS AND DISCUSSION 4.1 Part 1. Sensory evaluation of strawberries stored under MAP. The objectives of Part one of this study were to: a) use quantitative descriptive analysis (QDA) to assess the changes in sensory quality attributes of strawberries during storage under modified atmosphere packaging (MAP) conditions at 1°C; b) study the influence of MAP on some chemical changes (pH, soluble solids, glucose and fructose, titratable acidity and ethanol), and relate them to sensory quality changes, and c) apply multivariate statistical analysis to relate fruit quality changes due to the effects of MAP. 4.2 Sensory quality attributes of strawberries kept in storage. 4.2.1 General sensory evaluation. The changes in sensory quality of strawberries packaged in different gases or gas mixtures and stored at 1°C for 10 days were determined by quantitative descriptive analysis (QDA). The sensory descriptive terms were obtained during the training sessions. The odor descriptors were strawberry odor, off-odors, fermented, musty and earthy odors. The taste attributes included sweetness, sourness and bitterness. Texture (firmness) of fruit was evaluated by the chewing action of panelists. The judges evaluated the overall quality of strawberries in terms of flavor acceptance (scores rated on a 10 cm scale line) with consideration of all attributes evaluated. A value of less than 3 for overall quality for the strawberries evaluated was considered unacceptable and 55 rejected. A value of 3 was the average rating for samples the judges indicated were unacceptable or were not to be included in the next sensory evaluation session. 4.2.2 Reliability of judges in sensory evaluation. Sensory score results for strawberries evaluated at day zero were subjected to statistical analysis to assess the performance of judges with repeated evaluation of the same samples (replication). Combined data from the three experimental periods (March, April and July) for all the sensory attributes from each of the nine judges was used. A two-way analysis of variance in a randomized complete block design with judges (block) and replication as the main effects was carried out on the sensory attributes. There were no significant differences among replications and also no differences from the judges by replication interaction (Table 3) . This indicates that the judges were consistent and repeatable in their evaluation of replicated samples. However, judges were found to be the major source of variation for seven of the sensory attributes. The seven attributes were strawberry odor, off-odor, earthy odor, texture, sweetness, sourness and overall fruit quality, with the terms fermented odor, musty odor and bitterness found to be non-significant among the judges. Statistically significant results among the judges may be due to inconsistent use of sensory terms. Hall and Lingnert (1984) reported that the inconsistent use of terms is a well known phenomenon in sensory analysis of foods and should be taken into consideration. They also suggested that this 56 Table 3. Influence of judges and replications on evaluation of sensory attributes of strawberries evaluated on day 0 (data from nine judges). Sensory attributes Strawberry odor Off-odor Fermented odor Musty odor Earthy odor Texture Sweetness Sourness Bitterness Overall quality Jz 5.76***y 2.35* 1.35 1.89 4.54*** 2.80* 11.23*** 3.56** 1.90 5.98*** F ratio R 0.84 1.77 0.65 0.63 0.77 1.05 0.40 0.60 0.81 0.34 JXR 0.15 1.59 0.66 0.54 0.78 0.44 0.59 0.52 0.33 0.37 Mean square erroi 4.41 1.19 0.35 0.72 1.51 0.43 4.22 6.48 0.18 5.26 ZJ=judges; R=replications; JR=judgeXreplication. y**^**^* significantly different at the 0.1, 1 and 5% level, respectively. 57 was an indication that the judges were not only using different levels on the rating scale but also judged the magnitudes of the differences between the samples to be different. 4.2.3 Examination of the performance of judges with PCA. The combined results of nine judges for all the sensory attributes of strawberry fruit evaluated at day 0 were subjected to principal component analysis (PCA) to identify outliers and inconsistent judges. The strawberry samples (replicates) evaluated by each judge were treated as 'objects' and the ten sensory attributes as 'features' (variables) which formed a 'data vector' describing the object (Kwan and Kowalski, 1980) . From the analysis, four principal components (PC) were obtained with eigenvalues greater than 0.90 and these PC accounted for 79% of the variance. From the plot of the first two PC's, most of the judges' scores were clustered closely together indicating agreement in their evaluation of the same sample, except for scores of judges C and D (Figure 3). Therefore, sensory scores from these judges (C and D) were eliminated from further analyses and all subsequent analyzed data based on the results of the seven remaining judges. 4.2.4 Analysis of variance (univariate) for sensory data. Data for the seven judges retained after PCA were analyzed by three-way analysis of variance (ANOVA) in a randomized incomplete block design (SAS, 1985; Steel and Torrie, 1980; O'Mahony, 1985; Piggot, 1986;). The main factors used were the different 58 GO CM c CD C o Q. E o o a. o i _ D_ 0 -1 " -2 --3 --5 I B C - C C C l I I I EcE B H H D D -B E ^ BC c b F B A^§R E A 0 E f l B F F ^ ^ F fr _ A A F D G P A E C B C D " D I I I D -3 •1 0 1 Principal component 1 (31%) Figure 3. Principal component plot of the scores of nine judges who evaluated strawberries at day 0 (letters represent each judge). 59 treatments, storage time and judges (as block). The analysis was aimed at determining whether or not differences existed between the different treatments with respect to each storage time and at different storage times. The results of the ANOVA for sensory attribute ratings across the treatments and storage time are summarized in Table 4. Nearly all attributes were influenced by the treatment and storage time. There were highly significant differences among the treatments and between the various storage times for all sensory attributes of strawberries stored under MAP conditions except the attributes of earthy odor and sourness. Although inconsistent judges were eliminated prior to analysis of variance, the judges were still a highly significant source of variation in all attributes studied except the term earthy odor. Heymann and Noble (1987) eliminated inconsistent judges in their study but they also failed to produce consistent results among the remaining judges. 4.2.5 Multivariate analysis of variance of sensory attributes. The individual analysis of variance (ANOVA) for each attribute was followed with multivariate analysis of variance (MANOVA). In ANOVA, the F test enables one to test for significant sample differences over one attribute, while in MANOVA, the Bartlet or approximate F test using Wilk's lambda (or other statistics), enables the inspection of the data as a whole (Noble et al., 1984) . Powers and Ware (1986) reported that MANOVA involves joint examination of the measurement values to learn whether treatments 60 Table 4. Influence of gas treatment, storage time and judges on sensory attributes of strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C (data from seven judges). Sensory attributes Strawberry odor Off-odor Fermented odor Musty odor Earthy odor Texture Sweetness Sourness Bitterness Overall quality Treatment 29.06***2 72.14*** 27.66*** 52.15*** 1.05 20.17*** 6.76*** 0.73 15.48*** 61.24*** F ratio Time 18.02*** 28.71*** 11.71*** 26.03*** 0.76 11.20*** 15.99*** 2.70 4.30*** 38.17*** Judges 12.87*** 6.19*** 7.69*** 9.61*** 1.17 19.67*** 18.52*** 13.63*** 12.99*** 9.15*** Table 4 (cont.). Influence of gas treatment, storage time and judges on sensory attribute of strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C (data from seven judges) . Sensory attribute Strawberry odor Off-odor Fermented odor Musty odor Earthy odor Texture Sweetness Sourness Bitterness Overall quality Treat7 X Time 1.33 3.10*** 2.64* 9.61*** 0.62 2.05 1.21 0.81 2.04 3.60** F ratio Treat X Judges 1.28 1.84** 1.94*** 2.89* 0.76 0.84 1.52 3.88*** 1.36 0.81 Time X Judges 3.89** 4.87*** 2.19* 2.36*** 0.21 2.18* 3.38*** 4.75*** 0.96 3.09*** Treat X Time X Judges 0.56 0.98 0.93 3.39*** 0.70 0.60 0.55 0.68 1.15 0.84 Mean square error 3.50 5.24 3.94 0.87 20.12 4.41 4.64 3.23 3.11 5.06 z***,**,* Significantly different at 0.1, 1 and 5% levels, respectively. YTreat=gas treatment; Time=storage time (evaluation at days 0, 3, 6 and 10). 61 have affected significant differences in a product. Table 5 shows the summary of the MANOVA for all the sensory attributes of MAP strawberries. Analysis of the sensory attributes across the treatments and all sampling times for the seven judges showed highly significant differences among treatments, storage time, judges and, their interactions. Piggot and Jardine (1979) indicated that significance among samples results from large dispersion among the different samples. They concluded that such results from sensory data indicate agreement in the use of the terms, and the attributes are effective overall as product discriminators. Therefore, the judges were effective in discriminating among the different treatments at the same storage time and at different storage times. 4.2.6 Differences among treatments over storage time. At each sensory evaluation session, the judges were presented with stored unpackaged strawberry samples and stored strawberries packaged in air, mixed gas or carbon dioxide. The intensity of each attribute was evaluated on a 10 cm unstructured scale line. The intensity scores of most sensory attributes changed during storage of strawberries and among the different gas treatments. Tables 6, 7 and 8 shows the calculated means of perceived intensities for the different sensory attributes for each treatment at each storage time. During the 10-day storage period, the judges were able to detect changes in the sensory attributes among the different 62 Table 5. Multivariate analysis of variance on all sensory attributes of strawberries stored for 10 days under modified atmosphere packaging conditions at 1°C (evaluation of samples at days 0, 3, 6 and 10). Sources of variation Approximate F ratio Treatment Judges Storage time Treatment X Judges Treatment X Storage time Judges X Storage time 5.83**z 16.43** 2.98** 2.07** 1.54** 1.97** z** Significantly different at the 1% level. 63 Table 6. Mean2 score rating of odor attributes for strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C. Sample treatment Unpackaged Packaged Air Mixed gas C02 LSD Days in storage 0 3 6 10 0 3 6 10 0 3 6 10 0 3 6 SODy 6.4a 5.7ab 5.5bc 4.4cd 6.4a 5.3cb 4.1de 4.2de 6.4a 4.6cd 3.If 3.5ef 6.4a 3.3ef 1.8g 0.9 Odor sens OFD 0.5g 1.2fg 1.8f 1.7f 0.5g 1.9f 3.2de 3.9cd 0.5g 2.3ef 4.8bc 5.4b 0.5g 5.9b 8.0a 1.1 ory attribute FMT 0.2f 0.5ef 0.2f 0.5ef 0.2f 1.2de 1.7cd 2. 6bc 0.2f 1.2de 2.7abc 3.2ab 0.2f 2.9abc 3. 6a 1.0 MST 0.5f 1.2ef 1.2ef 1.9e 0.5f 1.7e 3.3d 3. 6cd 0.5f 2.0e 4.6bc 4.8b 0.5f 5.2b 7.0a 1.1 EAR 0.9 1.1 0.9 2.6 0.9 0.7 0.4 0.6 0.9 1.1 0.4 0.4 0.9 0.9 0.2 *Means separated by least significant difference (LSD) at the 5% level. ySOD=strawberry odor; OFD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy odor. 64 Table 7. Mean2 score rating of taste attributes for strawberry fruit stored under modified atmosphere packaging for 10 days at 1°C. Sample Days in treatment storage Taste sensory attribute Sweet Sour Bitter Unpackaged Packaged Air Mixed gas CO, 0 3 6 10 0 3 6 10 0 3 6 10 0 3 6 5.4a 5.3ab 4.6abc 4.lbcd 5.4a 5. 3ab 4.3bcd 4.2bcd 5.4a 5.5a 3.2de 3.8cd 5.4a 3.7cde 2.7e 3.4 3.2 3.0 2.9 3.4 3.2 2.2 2.6 3.4 2.9 2.4 3.0 3.4 2.8 2.5 0.2e 0.8cde 0.4de 0.8cde 0.2e 0.8cde 0.4de 1.3bc 0.2e l.lcd 1.4bc 2.0b 0.2e 2.0b 3.0a LSD 1.1 0.9 zMeans separated by least significant difference (LSD) at the 5% level. Table 8. Mean2 score rating for texture and overall rating of strawberry fruit stored under modified atmosphere packaging for 10 days at 1° Sample Days in storage Texture Overall qualityy Unpackaged Packaged Air Mixed gas C02 0 3 6 10 0 3 6 10 0 3 6 10 0 3 6 7.4a 6.7ab 5.6cdef 6.6abc 7.4a 6.Obcde 5.lefgh 5.4defg 7.4a 6.3bcd 5.0fgh 4.3hi 7.4a 4.4gh 3.4i LSD 1.0 7.5a 6.4b 6.2bc 5 .2c 7.5a 5.7bc 4.0d 3.5d 7, 5. 3. 1. 5a 6bc Ode 9f 7.5a 2.2ef 0.6g 1.1 zMeans separated by least significant difference (LSD) at the 5% level. yOverall quality in terms of overall flavor acceptance (score of less than 3 indicates unacceptable sample). 66 treatments and at different storage times. Strawberries from different gas treatments subsequently received lower scores in desirable attributes of strawberry odor, sweetness and texture (lost their firm texture) but progressively received higher scores of undesirable attributes of off-odor as well as fermented and musty odors during the storage period. The high score ratings at day 0 for strawberry odor, texture, sweetness and overall quality of 6.4, 7.4, 5.4 and 7.5, respectively, dropped to 1.8, 3.4, 2.7 and 0.6, respectively, after 6-10 days of storage of MAP strawberries among the different treatments. The low score rating for off-odor, fermented and musty odors of MAP strawberries at day 0 of 0.5, 0.2 and 0.5 increased to 8.0, 3.6 and 7.0 after 6-10 days among the different treatments, respectively. The differences in rating of the strawberries can be attributed to both the treatments and time in storage. Figures 4a, b, c and d show quantitative descriptive polygons illustrating the sensory attributes evaluated in the strawberry fruit stored under MAP at 1°C. Each treatment was compared with samples evaluated at day 0. The relative intensity for each sensory attribute is depicted by the length of the line from the center and represents the mean of each attribute. The least change in sensory attribute rating among the different treatments during storage was between the unpackaged strawberries (Figure 4a) . Significant changes in the unpackaged strawberries were observed after 10 days from the stand point of strawberry odor, off-odor and overall fruit quality. Ratings of some of the different attributes 67 MST FMT Figure 4a. Flavor profiles (quantitative descriptive polygons) of strawberries evaluated at day 0 (F) and unpackaged strawberries (U) stored for 10 days at 1°C (numbers stand for days in storage; SOD=strawberry odor; 0FD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy; TEX=texture; SWT=sweet; SOU=sour; BIT=bitter; OVQ=overall quality). MST FMT 68 SOU SWT Figure 4b. Flavor profiles (quantitative descriptive polygons) of strawberries evaluated at day 0 (F), and strawberries packaged in air (A) and stored for 10 days at 1°C (numbers stand for days in storage; SOD=strawberry odor; 0FD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy odor; TEX=texture; SWT=sweet; S0U=sour; BIT=bitter; OVQ=overall quality). 69 Figure 4c. Flavor profiles (quantitative descriptive polygons) of strawberries evaluated at day 0 (F), and strawberries packaged in mixed gas (M) and stored for 10 days at 1°C (numbers stand for days in storage; SOD=strawberry odor; 0FD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy odor; TEX=texture; SWT=sweet; S0U=sour; BIT=bitter; OVQ=overall quality). 70 MST FMT Figure 4d. Flavor profiles (quantitative descriptive polygons) of strawberries evaluated at day 0 (F), and strawberries packaged in carbon dioxide (C) and stored for 10 days at 1°C (numbers stand for days in storage; SOD=strawberry odor; 0FD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy odor; TEX=texture; SWT=sweet; S0U=sour; BIT=bitter; OVQ=overall quality). 71 changed between day 0 to the end of the storage time (10 days) from 6.4 to 4.4 for strawberry odor, 0.5 to 1.7 for off-odor, and 7.5 to 5.2 for overall quality. Fruit packaged in air showed significant deviations from day 0 samples in strawberry odor, off-odor, fermented odor, musty odor, texture, sweetness and overall fruit quality after 10 days in storage (Figure 4b) . Some of these attributes showed rating changes from 6.4 to 4.2 for strawberry odor, 0.5 to 3.9 for off-odor, 0.2 to 2.6 for fermented odor, 0.5 to 3.6 for musty odor, 7.4 to 5.4 for texture and 7.5 to 3.5 for overall quality. Compared to MAP strawberries packaged in air, MAP strawberries packaged in mixed gas (11% C02 + 11% 02) had significantly lower ratings after 6 days in storage for strawberry odor, texture, sweetness, overall quality and a high rating of undesirable attributes of off-odor, fermented odor and musty odor (Figure 4c). The ratings for strawberry odor, off-odor, fermented odor, musty odor, texture and overall quality changed from 6.4 to 3.1, 0.5 to 4.8, 0.2 to 2.7, 0.5 to 4.6, 7.4 to 5.0 and 7.5 to 3.0, respectively after 6 days in storage. The changes in the ratings of attributes for strawberries kept in air and mixed gas may be related to changes in 02 and C02 levels in the packages. With an increase in storage time of MAP strawberries, 02 decreased and C02 increased in the microatmosphere surrounding the strawberries in the package systems (Table 9). After 3 days of storage, 02 levels in the microatmospheres of MAP strawberries were 9.8% and 2.2% while the C02 levels were 10.1% and 18.9% for input air and mixed gas, respectively, in package 72 Table 9. Changes in carbon dioxide and oxygen levels in MA packages containing strawberries flushed with air, mixed gas and carbon dioxide and stored for 10 days at 1°C. Days stor, 0Z 3 6 10 in age Air C02 l.ly 10.1 19.4 22.3 02 20.1 9.8 4.1 3.8 Gas composition (%) Mixed C02 10.0 18.9 25.9 26.8 gas 02 10.2 2.2 2.0 2.0 Carbon C02 95.9 97.3 92.9 95.2 dioxide 02 0.3 0.1 0.1 0.2 zGas measurements started two hours after MAP packaged strawberries were placed in storage at 1°C. yGas sampling made from three separate packages. 73 systems. Bretch (1980), Kader (1980) and Kader et al. (1989) reported that strawberries can tolerate 02 levels as low as 2% and C02 levels as high as 2 0%. These levels were exceeded in MAP samples treated with the mixed gas after 6 days of storage and air treated MAP samples after 10 days of storage. Such levels of 02 and C02 could cause anaerobic respiration and development of undesirable attributes (Carlin et al. 1990) . Off-flavors formed by anaerobic reactions due to very low 02 (less than 1%) have been noted in a number of fruits including bananas, apples, avocados and strawberries (Brecht, 1980). Burton (1982) reported that strawberries develop off-flavors in atmospheres containing 3% 02 while El-Kazzaz et al. (1983) detected off-flavors in strawberries treated with air + 15% C02. The changes in sensory attributes were more pronounced and striking in fruit stored in packages initially flushed with carbon dioxide (100% C02 treated samples). Within 3 days of storage, fruit in the C02 flushed packages had a significantly low rating of the desirable attributes of strawberry odor, texture, and sweetness as well as high ratings for the undesirable attributes of off-odor and musty odor (Figure 4d). There was also a very low rating for the overall quality of the fruit. These changes may be as a result of anaerobic respiration caused by the high carbon dioxide levels. The carbon dioxide levels in the microatmospheres were greater than 90% throughout the 10-day storage period in the MAP packages of strawberries treated with carbon dioxide (Table 9). The sweetness rating of strawberries generally declined for all 74 treatments but significant changes and the lowest rating were observed with strawberries stored in carbon dioxide (Table 7) . Changes in the attributes of bitterness, sourness and earthy odor of strawberries showed inconsistent changes. 4.2.7 Relationship between sensory attributes. 4.2.7.1 Correlation coefficients among sensory attributes. Some of the sensory attributes used in this study are associated with the high quality factors of strawberries while others are associated with low quality factors of the fruit. To study the relationship between sensory attributes, simple pairwise correlations between all attributes were computed. Correlations between the different sensory attributes of strawberries are shown in Table 10. Strawberry odor, was highly correlated to overall fruit quality (r=0.69) but negatively correlated with the undesirable attributes of off-odor (r=-0.62), fermented odor (r=-0.45) and musty odor (r=-0.57). All of the undesirable attributes of strawberries were positively correlated with each other but negatively correlated with overall fruit quality. Texture, sweetness and overall fruit quality were positively correlated with each other. The attributes of earthy odor and sourness of the fruit showed non-significant correlations with other attributes. Guinard and Cliff (1987) reported that in descriptive analysis, a significant correlation between two terms suggests that they may have been used to describe the same attribute. This may have been true in cases where attributes were Table 10. Simple correlation coefficients between sensory attributes of strawberry fruit stored under modified atmosphere packaging for 10 days (used all the data collected). Sen. attr SOD OFD FMT MST TEX SWT SOU BIT OVQ Z SODy 1.00 -0.62***x -0.45*** -0.57*** 0.41*** 0.48*** -0.08 -0.24*** 0.69*** OFD 1.00 0.60*** 0.79*** -0.49*** -0.32*** 0.01 0.51*** -0.77*** Correlation coefficient FMT 1.00 0.44*** -0.38*** -0.22*** 0.09 0.34*** -0.55*** MST 1.00 -0.53*** -0.42*** 0.01 0.43*** -0.69*** TEX 1.00 0.50*** -0.12* -0.28*** -0.53*** s 1 -0 -0 0 (r) SWT .00 ^ 27*** .21*** m47*** SOU 1.00 0.18** a.02 BIT 1.00 -0.40*** zSen. attr.=sensory attributes ySOD=strawberry odor; OFD=off-odor; FMT=fermented; MST=musty; TEX=texture; SWT=sweet; SOU=sour; BIT=bitter; OVQ=overall fruit quality, x**^**^* significantly different at the 0.1, 1 and 5% levels, respectively, en 76 used to describe related sensory attributes such as off-odor, fermented odor and musty odor. The judges were trained, however, to use the terms for the desired attributes, although some of the attributes may have been describing related terms. Schutz and Darmell (1974) suggested that significant relationships between sensory characteristics could be due to the fact that the characteristics covary in the sample, and are measuring the same property and are measures of properties opposite of one another. The negative correlation between strawberry odor, texture, sweetness and overall fruit quality with off-odor, fermented and musty odor during storage indicates that as the undesirable attributes of strawberries developed with storage time under MAP, the desirable attributes diminished in magnitude. 4.2.8 Multivariate statistical analysis of sensory data. To measure the sensory quality of fruit held under MAP at 1°C, a set of sensory attributes which described the largest, most relevant and most reliable variations were used. Because of the many variables involved, multivariate techniques are required for the examination of the total sensory variation of the product under study (Piggot, 1986) . 4.2.8.1 Principal component analysis of sensory data. Principal component analysis (PCA) on the correlation matrix, generated from the sensory ratings for each gas treatment at each storage time, across all the attributes, was carried out. PCA was 77 performed to reduce the number of variables, and to illustrate the relationships among all sensory attributes (variables) with regards to different treatments as well as storage time. The first two principal components (PC) obtained after PCA accounted for 80% and 12% of the variance, respectively. These two PC had eigenvalues greater than 1. In the scree test (Guinard and Cliff, 1987; Heymann and Noble, 1987, 1989), the scree plot showed a break at the second eigenvalue. Therefore, these two PC were thought of as the most 'important' and thus interpretation of data will be limited to these 2 PC. Principal component analysis reduced the ten sensory attributes to two principal components. In Figure 5, the factor loadings of the ten sensory attributes from data collected during the storage periods are plotted on the first two PC and the sensory attributes (variables) are plotted as vectors. The sensory attributes of strawberry fruit stored under modified atmosphere packaging at 1°C were mainly a contrast of the desirable attributes (strawberry odor, firm texture and sweetness) against the undesirable attributes (off-odor, fermented odor, musty odor and bitterness) . The 180° orientation of the vectors of the contrasting attributes indicates that they were inversely correlated (Rogers et al. , 1986) . Overall quality of the fruit was associated with the desirable attributes. The desirable and undesirable attributes were highly correlated amongst each other as demonstrated by the small angle between their vectors. Also, they were highly correlated with the first PC as indicated by their close alignment to this axis. All the attributes of importance had 78 1.0 CM CM c CD c o Q. E o o "co Q. o 0.5 0.0 --0.5 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 Principal component 1 (80%) Figure 5. Principal component loadings of sensory attributes of strawberries evaluated from different treatments and different storage times (sensory attributes plotted as vectors; SOD=strawberry odor; 0FD=off-odor; FMT=fermented odor; MST=musty odor; EAR=earthy; TEX=texture; SWT=sweet; S0U=sour; BIT=bitter; OVQ=overall quality). 79 vectors of equal length, an indication that they were all important in explaining the differences in the samples. The right angle between sourness and earthy odor attributes with all other attributes indicates there was no correlation and that these attributes were associated more with the second PC. In Figure 6, the scores of samples from the different treatments and different storage times were plotted on the first two PC. The samples, depending on quality due to treatment and storage time, were separated along the first PC according to desirable attributes found in high quality strawberries or undesirable attributes that developed in storage under MAP (anaerobic conditions) (Figures 5 and 6). The unpackaged strawberries evaluated at day 0, and unpackaged samples that had been held in storage for 3, 6 and 10 days, the MAP strawberries with input air stored for 3 and 6 days, and the MAP strawberries with input mixed gas (11% C02 + 11% 02) stored for 3 days were all characterized by high ratings of desirable attributes. The attributes associated with these samples included strawberry odor, firm texture, sweetness as well as overall quality of the fruit. All these samples were located on the righthand side of the plot (Figure 6) and received high positive scores on PC 1. Examination of sensory data (Table 6, 7, 8) shows that ratings of desirable attributes in strawberries was high early in storage and in samples not subjected to 100% C02 gas treatment (abusive treatment). At the same time, the undesirable attributes received low scores. The C02 levels were less than 19% and the 02 more than 2% in the 80 4 r 2 -1 ~ 0 --2 <= -10 -5 0 Principal component 1 (80%) Figure 6. Principal component scores of samples from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated at different storage times (numbers stand for days in storage). 81 packaged strawberries (Table 9). Although the unpackaged strawberries were still associated with desirable attributes for up to 10 days, many of the berries had fungal growth. Growth of fungus on strawberries leading to decay is the major cause of loss of strawberries during storage (El-Kazzaz, et al., 1983) . The strawberries packaged in air and stored up to 10 days at 1°C, and the strawberries packaged in mixed gas (11% C02 + 11% 02) and stored for 6 and 10 days, possessed undesirable attributes of off-odors, fermented odor, musty odor and bitterness (Figure 5 and 6). These samples received lower scores on PC 1 and the intensity scores of undesirable attributes were high while those of desirable attributes were low (Table 6, 7, 8). The strawberries packaged in carbon dioxide (100% C02) were found to be associated with the undesirable attributes within three days of storage and received lower values on PC 1. All these samples were located on the lefthand side of the plot (Figure 6). It is clear that strawberries packaged in 100% C02 quickly developed undesirable sensory attributes that are common in deteriorated, low quality fruit. Strawberries packaged in low C02 and high 02 levels were initially associated with attributes of high quality but developed the undesirable attributes with increasing storage time. Strawberries packaged in mixed gas (11% C02 + 11% 02), quickly accumulated C02 and depleted 02 within the package atmosphere and developed undesirable attributes earlier than the strawberries packaged with air atmosphere. This may be attributed to the rapid build-up of C02 and depletion of 02 in these 82 packages (Table 9). Regardless of the treatment, with extended storage and high C02 levels greater than 2 0% and 02 levels less than 3%, all the fruit developed undesirable attributes. The development of undesirable attributes with storage time under MAP can be attributed to changes in the gas composition. 4.2.9 Changes in chemical parameters of strawberries. Changes in chemical composition of strawberries stored under MAP at 1°C are shown in Table 11. The pH of strawberries subjected to various treatments sampled at different storage times varied between 3.47 to 3.85. Although there were fluctuations in pH measurements, there was no trend in pH changes among the treatments. pH changes may be attributed in part to dissolved carbon dioxide in the tissues as carbonic acid or from organic acids produced under anaerobic respiration. Under our conditions of study, the increase in organic acids may not have significantly affected the pH changes due to the buffering capacity of the tissues (Day et al., 1990). Soluble solids varied between 6.3 and 8.4; however, the changes were not consistent among the treatments (Table 11). Inconsistent results for soluble solids contents in fruits stored under CA or MAP have been reported by other researchers (El-Kazzaz et al. , 19 83; Day et al. , 19 90) . This could be due to the dynamic equilibrium of anabolism and catabolism of carbohydrates. Titratable acidity, glucose and fructose measured for strawberries from the different treatments at different storage 83 Table 11. Soluble solids, pH, titratable acidity, sugar and ethanol in strawberry fruit stored under modified atmosphere packaging at 1°C. Sample treatment Unpackaged Air Mixed gas Days in storage Carbon dioxide 0 3 6 10 0 3 6 10 0 3 6 10 0 3 6 Soluble solids (%) 7.9W 7.9 7.1 7.4 7.9 7.9 7.2 7.0 7.9 8.4 7.1 6.9 7.9 7.4 6.3 PH 3.70 3.60 3.47 3.54 3.70 3.63 3.57 3.61 3.70 3.85 3.76 3.59 3.70 3.75 3.64 TAZ 1.06 0.92 1.12 1.12 1.06 1.23 1.01 1.11 1.06 1.00 0.98 0.99 1.06 0.98 0.84 Glue* 3.75 3.74 3.57 3.75 3.75 4.13 3.60 3.44 3.75 4.42 3.79 3.48 3.75 4.05 3.24 Fruc" 4.10 4.00 3.91 3.93 4.10 4.53 3.95 3.72 4.10 4.95 4.11 3.76 4.10 4.33 3.45 Ethanol (g/100g) 0.20 0.20 0.20 0.20 0.20 0.25 1.24 2.32 0.20 1.17 1.85 2.73 0.20 1.03 1.07 zTA=titratable acidity (g/lOOg) yGluc=glucose (g/lOOg). xFruc=fructose (g/lOOg). "Duplicate measurements. 84 times did not show any consistent trend (Table 11) . This may be an indication of the dynamic metabolic state of the strawberries in storage under various conditions. Unpackaged strawberries did not accumulate ethanol during the 10-day storage period. However, there was accumulation of ethanol in gas-treated strawberries, with the highest accumulation in fruit packaged in mixed gas (Table 11) . Accumulation of ethanol in fruit treated with carbon dioxide did not change much after 3 days in storage. In the absence of 02 or in the presence of high C02 levels, anaerobic respiration takes place with the resultant accumulation of ethanol and acetaldehyde (Thomas, 1929; Li and Kader, 1989; Ke et al. 1991). 4.2.9.1 Relationship between sensory and chemical parameters. Table 12 shows the simple pairwise relationship between sensory attributes studied with chemical parameters of soluble solids, glucose, fructose, pH, titratable acidity and ethanol. There were no significant relationships between pH and titratable acidity with any of the sensory attributes. Except for the significant relationship between glucose and fructose with sweetness, all other sensory attributes did not show a significant correlation with these two chemical parameters. Strawberry odor, texture, sweetness, sourness and overall fruit quality had a positive relationship with soluble solids but negative with ethanol content. The undesirable attributes of off-odor, fermented odor, musty odor and bitterness had a negative relationship with soluble solids but positive with ethanol content. Ethanol is known to accumulate 85 Table 12. Correlation coefficients between sensory attributes of strawberries and chemical parameters (used means). Sensory Chemical parameter Attribute SODz OFD FMT MST EAR TEX SWT SOUR BIT OVQ Soluble solids 0.77**y -0.74** -0.68* -0.76** 0.16 0.78** 0.91*** 0.66* -0.53 0.78** Glucose 0.41 -0.41 -0.37 -0.43 -0.02 0.46 0.62* 0.50 -0.20 0.44 Fructose 0.42 -0.41 -0.37 -0.45 -0.11 0.46 0.66* 0.50 -0.23 0.46 PH -0.15 -0.20 0.21 0.17 -0.40 -0.04 0.11 0.15 0.30 -0.13 Titratable acidity 0.51 -0.55 -0.47 -0.55 0.21 0.43 0.43 0.20 -0.46 0.48 Ethano -0.66* 0.64* 0.77** 0.62* -0.38 -0.72** -0.60* -0.51 0.72** -0.72** zSOD=strawberry odor; OFD=off-odor; FMT=fermented; MST=musty; EAR=earthy; TEX=texture; SWT=sweet; SOU=sour; BIT=bitter; OVQ=Overall fruit quality. y***f**t* significantly different at 0.1, 1 and 5% level, respectively. 86 under high C02 levels and reduced 02 levels and has been attributed to off-odor development. Li and Kader (1989) found that atmospheres of 1% 02 + 15% C02 and 0.5% 02 + 2 0% C02 led to accumulation of ethanol in strawberries. Ke et al. (1991) found that off-flavors in strawberries correlated very well with ethanol, ethyl acetate and acetaldehyde. 4.2.10 Changes in gas composition of fruit stored under MAP. In general, there was a decline in 02 levels and an increase in C02 levels in packages initially flushed with air and mixed gas (Table 9). Similar changes in gas composition of produce packaged in films were reported by Forney et al. (1989) and Nakhasi et al. (1991) . Changes in the headspace gas composition could be attributed primarily to the result of fruit respiration since the film used was a high barrier type. Day et al. (1990) reported that the low 02 permeability of high barrier packaging film restricts 02 diffusion into the packages from atmospheric air, so that oxygen consumed in the aerobic respiration process cannot be replenished. These changes in the gas compositions may have led to reduced respiration rate. Forney et al. (1989) attributed this respiration rate to lowering of 02 levels and simultaneous increase in C02 levels in the storage atmosphere. The accumulation of C02 was more rapid in packages flushed with mixed gas than with air. The 02 concentrations decreased to lower levels in packages flushed with mixed gas earlier than in packages flushed with air. The C02 levels in microatmosphere of packages of strawberries treated with 87 carbon dioxide remained at more than 90% throughout the entire storage period. 4.2.11 Storage potential of strawberries kept under MAP. In terms of overall fruit quality, unpackaged strawberries were acceptable with a rating value of greater than 3 up to 10 days in storage (Figure 7). With 6 days of storage, the unpackaged strawberries started to develop surface fungal growth and by the tenth day of storage, most of the berries were covered with mycelium. Fruit in packages flushed with air prior to sealing was of good quality for 10 days with a final overall quality rating of 3.5. Strawberries packaged in mixed gas received a rating of 3 after 6 days in storage but were unacceptable after 10 days with a final rating of 1.9. Although strawberries packaged with air as the initial microatmosphere and with mixed gas had a good fresh tissue appearance with a green calyx and no fungal growth after 10 days of storage, they had developed undesirable odors (Table 6, 7, 8) . The absence of fungal growth in packaged fruit may be attributed to the presence of high C02 and low 02 levels. Day et al. (1990) found that yeast and mold populations in blueberries packaged in high barrier film (0.232, 0.775 and 4.65 cm3/m2/24 h/atm for N2, 02 and C02, respectively) were much lower compared to blueberries packaged in intermediate barrier films (341, 1287 and 6512 cm3/m2/24 h/atm for N2, 02 and C02, respectively) . Yeasts and molds are known to be sensitive to high carbon dioxide and low oxygen levels (Follstad, 1966; Wells and Uota, 1970; Svircev et 0 3 6 Days in storage 10 - > Carbon dioxide Mixed gas i Air Unpackaged Unacceptable Figure 7. The overall quality rating of strawberries from different MAP treatments kept in storage for 10 days at 1°C. 89 al., 1984). Strawberries packaged in carbon dioxide were unacceptable within 3 days of storage. It appears that air with an initial 02 content of about 21% (with no C02) may be valuable as an input gas for extending the storage life of MAP strawberries under the conditions of the present study. Of the three gas treatments, carbon dioxide treated strawberries samples were the worst in terms of overall quality. With air and mixed gas treated strawberries, the fruit quality was maintained for a moderate storage period. The deterioration of the packaged strawberries occurred earlier with mixed gas as the flush as compared with the air flush. This occurrence may be related to the rapid accumulation of C02 and depletion of 02 in the package systems with the mixed gas flush (Table 9). Unpackaged samples developed visible mold within six days of storage. 4.3 CONCLUSIONS Quantitative descriptive analysis was used to study the sensory quality changes of strawberries stored under modified atmosphere conditions. Strawberries were stored at 1°C for 10 days under MAP conditions in high barrier film pouches flushed with carbon dioxide (100% C02), mixed gas (11% C02 + 11% 02 + 78% N2) , or air. Sensory score differences between samples were statistically significant for various treatments at different storage time. During the 10-day storage period, sensory scores for desirable attributes decreased in all gas-treated strawberries while the scores of undesirable attributes increased. Air-treated samples had higher 90 overall quality ratings than the rating for the mixed gas- or carbon dioxide-treated samples at each storage time. Although unpackaged samples scored highest in overall quality at all storage times, fungal growth became apparent after 6 days in storage at 1°C. Principal component analysis (PCA) was used to examine the changes in sensory quality of MAP strawberries during the storage period for all gas treatments. The plot of the first two principal components, which accounted for 92% of variance, indicated that the changes in sensory quality of strawberries under MAP were mainly a contrast of desirable against undesirable attributes. Fresh strawberries at the beginning of the experimentation were considered to have desirable attributes. As the storage time progressed, undesirable attributes of the strawberries were noted by the panel members. PCA was successful in separating out strawberry samples on the basis of gas treatment and/or sensory quality by using scores of several sensory attributes. Changes in pH, soluble solids, titratable acidity, glucose and fructose contents for MAP strawberries stored for various times were not related to the different gas treatments. The ethanol content increased in gas treated samples, with mixed gas-treated samples showing the highest ethanol content. Desirable attributes were positively correlated to soluble solids but negatively correlated to ethanol content. The undesirable attributes were negatively correlated with soluble solids but positively with ethanol content. 91 4.4 Part 2. Flavor volatile analysis of strawberries stored under MAP. The objectives of Part 2 of this research were to: a) extract and identify the types and relative amounts of volatile compounds of strawberries stored under MAP conditions; b) study the influence of MAP on volatile profiles of strawberries and their influence on quality; and c) predict the treatment category and quality of strawberries stored under MAP from the data for volatile compounds by applying multivariate statistical analyses, and also relate sensory to GC data. 4.5 Volatile compound extraction from strawberries. A number of methods have been used to extract volatile compounds from strawberry fruit (McFadden et al., 1965; Schreier, 1980; Honkanen and Hirvi, 1990). Preliminary studies were conducted to evaluate: a) direct solvent extraction using dichloromethane, diethyl ether and pentane, either separately or as a mixture of diethyl ether and pentane in a 2:1 proportion (Hirvi, 1983; Pino et al. , 1986b); b) volatilization techniques. The volatilization techniques included direct distillation using a Rotavapor unit, simultaneous steam distillation extraction (SDE) with and without vacuum (Nunez et al. 1984; Takeoka et al., 1986), dynamic purge-and-trap of volatiles onto Tenax GC adsorbent followed by either diethyl ether desorption (Olafsdottir et al. , 1985; Hansen and Lund, 1987) or thermal desorption (Hirvi and Honkanen, 1982; Jeltema et al. 1984). A charcoal adsorbent, ORBO™ 92 was also used and the adsorbed volatiles were eluted from the trap with dichloromethane (Schreier, 1980). 4.5.1 Direct solvent and simultaneous distillation extraction. Figure 8 shows chromatograms of unstored, fresh strawberry volatile compounds obtained by direct solvent extraction, and simultaneous distillation extraction (SDE) without and with vacuum applied. With a direct solvent extraction method, which involved mixing a strawberry fruit sample (blended sample or filtrate from the blended sample) with dichloromethane in equal volumes (1:1), many volatile compounds were extracted (Figure 8A) . Similar results with minor variation in volatile compounds were obtained with other solvents (pentane and diethyl ether). Although this solvent extraction method has been used by other researchers for a variety of foods, it requires large amounts of sample and a large solvent volume to sample volume ratio as well as numerous repeated extractions (Tressl et al., 1977; Barron and Etievant, 1990). By using the SDE method without application of vacuum, more volatile compounds were extracted than with the solvent extraction method but much higher temperatures of 70-100°C were necessary for extraction (Figure 8B). To minimize any undesirable heat effects on the strawberry volatile compounds, steam distillation with a vacuum (650 Pa) was used with extraction temperatures of 40-50°C. The gas chromatograms shown in Figure 8C indicated that a greater number and amount of volatile compounds were extracted by this method compared to the number and amount of volatiles obtained with 93 B «-&VM Figure 8. Comparison of strawberry flavor profiles prepared by: direct solvent extraction (A); steam distillation (B) and vacuum steam distillation extraction (C) (volatile compounds extracted from fresh strawberries). 94 either the direct solvent extraction or steam distillation used without vacuum. Because of the possibility of the formation of artifacts during the high temperature extraction process as well as the requirement of a large sample size and high solvent volume to sample volume ratio (Ohta et al. , 1987), these above mentioned methods were not used further in this study. 4.5.2 Volatile extraction by dynamic headspace procedure. The dynamic headspace evaluation of strawberries stored under modified atmosphere packaging at 1°C was aimed at the identification of volatile compounds that may contribute to the unpleasant off-flavors/odors. The selection of the dynamic headspace method was based on the supposition that only naturally-occurring volatile compounds in strawberry fruit would be extracted. Headspace purge-and-trap of volatile compounds on an adsorbent such as Tenax GC or powdered charcoal, followed by either solvent desorption or thermal desorption of the volatile compounds are commonly used in the dynamic headspace extraction procedures. The headspace method is known to introduce the least number of artifacts of any of extraction methods (Schreier, 1980; Bartley and Schwede, 1987) . Figure 9 shows, the chromatograms for adsorbed strawberry volatile compounds from charcoal traps which were extracted with dichloromethane, from Tenax GC traps extracted by diethyl ether, and from heated Tenax GC traps. Although the three chromatograms have similar patterns, some volatile compound profile differences 95 B ii idf UUJIUJ \ii V! u L**1 P nAiWdM* 1« IS ~i T T r WJ y^juLiM T T T 1 1* IS Figure 9. Chromatograms obtained from strawberry volatiles extracted by headspace technique A) charcoal adsorbent and B) Tenax GC eluted with solvent; and C) thermally desorbed from Tenax GC (volatile compounds extracted from fresh strawberries). 96 were evident. After desorption of the volatile compounds from the charcoal trap, 37 volatile peaks were obtained on the chromatogram (Figure 9A), but this value was lower than the number of volatile compounds peaks from the Tenax trap (Figure 9B and C). Charcoal adsorbents are known to strongly adsorb some volatile compounds which would explain the failure to desorb all trapped volatile compounds (Schaefer, 1981). Adsorption of volatile compounds on Tenax GC adsorbent followed by solvent (diethyl ether) desorption resulted in 58 chromatographic peaks (Figure 9B) . Mazza et al. (1980) and Olafsadottir et al. (1985) found the Tenax procedure was suitable for concentrating headspace volatile compounds. Thermal desorption of strawberry volatile compounds from Tenax GC resulted in 55 peaks being resolved (Figure 9C). Volatile compounds that may have been strongly adsorbed to the Tenax may have been desorbed at elevated temperatures during thermal desorption. Aishima (1983) isolated ethylguaiacol, a high boiling compound from soy sauce, by thermal desorption. However, the high temperature desorption may possibly introduce artifacts. Although a number of similar volatile compounds were extracted with the various extraction procedures, variations especially with the thermal desorption procedure were obtained. Desorption of volatile compounds by solvent extraction of Tenax GC brings about the release of low molecular and less polar compounds, while the thermal desorption method has the effect of releasing both low and high molecular weight compounds from the Tenax GC, and may also result in formation of artifacts (Honanken and Hirvi, 1990). For 97 the major part of the research on GC profiling of volatile compounds from MAP strawberries, the dynamic headspace procedure involving trapping of volatile compounds on the Tenax GC followed by solvent desorption was used. 4.6 Evaluation of volatile extraction from a model system. A model system with known volatile compounds including six esters and three ketones diluted with diethyl ether in various concentrations was used to determine the degree of compound separation by direct injections onto the GC column. The reproducibility of peaks with repeated injections was good with coefficients of variation of 3.9 to 5.5% for the esters and ketones (Table 13) . The model system of known compounds was added to water and used to study the reproducibility of recovering the compounds by headspace purge-and-trap of volatiles on the Tenax GC adsorbent and elution of volatiles with diethyl ether. Coefficients of variation for the various compounds ranged between 3 to 16.3% (Table 14). 4.7 Evaluation of strawberry volatile compound extraction by dynamic headspace technique. A study was initiated to assess the reproducibility of GC profiles of volatile compounds in a fresh strawberry extract derived by the dynamic headspace technique. Table 15 shows the means, standard deviations and coefficients of variation for the 25 selected volatile compounds for an assessment of the 98 Table 13. Reproducibility of peak areas for known volatile compounds in a model system. The same volatile compound mixture was injected four times into GC. Peak Compound Peak areas of volatile compounds No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 3-Pentanone Methyl butanoate Ethyl butanoate Hexyl butanaote Ethyl hexanoate 2-Nonanone Ethyl heptanoate 3-Heptanone Ethyl octanoate Mean2 34649.5 30890.8 37351.0 33161.5 39720.5 45692.3 42565.8 45432.3 44149.0 SDy 1421.2 1202.3 1711.3 1672.3 1565.0 2324.1 2324.1 2490.0 2449.8 %CVX 4.1 3.9 4.6 5.0 3.9 5.5 5.5 5.5 5.5 'mean of 4 injections into GC. ySD=standard deviation. xCV=coefficient of variation (%CV=standard deviation/mean*100) . Table 14. Reproducibility of GC peak areas for known volatile compounds extracted from an aqueous solution by the dynamic headspace technique. Peak Compound Peak areas of volatile compounds No. 1. 2. 3. 4. 5. 6. 7. 8. 9. 3-Pentanone Methyl butanoate Ethyl butanoate Hexyl butanaote Ethyl hexanoate 2-Nonanone Ethyl heptanoate 3-Heptanone Ethyl octanoate Mean2 4074.0 7901.4 13708.3 15661.2 97582.0 67493.3 88918.7 68363.3 60393.7 SDy 380.1 1094.5 408.6 2559.7 5848.0 4739.7 5976.5 6266.4 6689.1 %CVX 9.3 13.9 3.0 16.3 6.0 7.0 6.7 9.2 11.1 2Mean of 4 replicate extracts by dynamic headspace technique. ySD=standard deviation. xCV=coefficient of variation (%CV=standard deviation/mean*100) . 99 Table 15. Means, standard deviations and coefficients of variation for specific volatile compounds extracted from strawberry fruit by the dynamic headspace technique (volatile compounds extracted from fresh strawberries). Peak No.z 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Volatile compound Ethyl propionate Methyl butanoate Ethyl butanoate Butyl acetate 1-Methylethyl butanoate 2-Methylethyl butanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-Octanone Methyl hexanaote Butyl butanoate Ethyl hexanoate 1-Hexenyl acetate 2-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl 1,6-octadien-3-Ethyl heptanoate Hexyl butanoate Ethyl octanoate Octyl acetate s-Octyl acetate Hexyl hexanoate Octyl propanoate Unkwown MeanY 3.3 45.5 176.7 37.2 9.2 5.4 4.3 4.0 1.8 48.7 19.8 259.5 17.2 116.8 3.1 0.5 -ol 0.8 1.8 9.1 2.2 10.6 2.3 1.8 7.1 0.6 SDX 0.5 7.1 32.3 6.5 1.9 0.8 0.9 0.7 0.2 8.1 3.9 41.1 2.4 20.7 0.5 0.1 0.1 0.3 1.4 0.4 1.2 0.2 0.3 0.8 0.1 %CVW 15.1 15.6 18.3 17.5 20.4 14.4 20.1 18.4 11.4 16.6 19.6 15.8 13.7 17.7 16.3 19.3 15.5 17.6 15.3 16.1 11.8 8.0 18.4 11.8 18.5 zpeaks were renumbered to represent only selected volatile compounds from strawberry extract. yMean of 4 replicate extracts by dynamic headspace technique. Relative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard (X10~2) . xSD=standard deviation. wCV=coefficient of variation (%CV=standard deviation/mean*100) . 100 reproducibility of GC peak areas for the strawberry volatile compounds extracted by the dynamic headspace technique. Volatile compounds from four strawberry samples were independently extracted and injected into the GC. The coefficients of variation for the four extracts were between 8-21% with an average of 16.2%. Although the strawberries were sorted for uniformity based on color, size and touch-firmness, variability of up to 21% among replicated samples extracted by the headspace procedure were obtained. Kallio and Lapvetelainen (1984) and Douillard and Guichard (1989) reported coefficients of variation of up to 49% with the solvent extraction procedure, and they attributed this variability to the different stages of maturity of the berries. Aishima (1983) used the headspace procedure to study volatile compounds of soy sauce samples and reported variability of up to 27%. The influence of strawberry tissue disruption prior to the dynamic headspace extraction was studied. The disrupted strawberry tissue samples included: 1) tissue macerated by Waring blender at full speed for 3 min at room temperature; 2) strawberries sliced in half; 3) strawberries sliced in quarters and 4) decapped whole strawberries. Table 16 shows the influence of preparation methods for the strawberry samples on the peak areas of selected volatile compounds extracted by the dynamic headspace technique. In general, more volatiles were extracted from sliced strawberries than from the whole fruit, with more volatile compounds being recovered from quartered strawberries than with the sliced halved 101 Table 16. Influence of strawberry preparation on the peak areas of volatile compounds extracted by dynamic headspace technique2 (volatile compounds extracted from fresh strawberries). Vol at :ile compound Ethyl propionate Ethyl butanoate Ethyl hexanoate 2-Hexenyl acetate Total Relative Mascerated tissue 5. 59. 56. 20. 143. . 9 X .4 .9 .8 .0 amounts Sample Whole fruit 11.8 142.8 64.3 98.3 317.2 of pn volatilesY sparations Half sliced fruit 7.5 216.3 126.2 163.6 513.6 (xl0"2) Quarter sliced fruit 13. 401. 237. 312. 964. .4 .3 .0 .8 .5 ZA flow rate of 30 mL/min and incubation temperature of 40° were used. yRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. xMean of three samples extracted separately. 102 fruit. Maceration of the fruit resulted in lower amounts of volatile compounds being extracted than with other preparation methods. For further studies, strawberries were sliced into quarters and used for volatile compound extraction. This slicing was intended to simulate somewhat the disintegration of strawberry tissue during the first few bites in the mouth with the release of volatile compounds. The effects of N2 flow rate, incubation time and incubation temperature on the extraction of volatile compounds were studied. A N2 flow rate of 45 mL/min was found to be better for the extraction of most of the volatile compounds compared to the flow rates of 15 and 3 0 mL/min (Table 17). However, a high flow rate would result in loss of volatile compounds due to bleeding through the adsorbent (Schaefer, 1981). As the incubation time increased for collection of volatile compounds, more volatiles were adsorbed on the Tenax GC (Table 18). With 3 hr and 4 hr collection times, the amount of strawberry volatile compounds collected was much higher than for the 1 hr and 2 hr periods. But longer incubation times are known to result in large variation of volatile compounds being collected (Olafsdottir et al., 1985). As shown in Table 19, the most suitable temperature for the extraction of selected volatile compounds from strawberries was 40°C. In this study, the strawberries were sliced into quarters, a N2 flow rate of 30 mL/min., a purge-and-trap time of 2 hr and incubation temperature of 40°C were used. 103 Table 17. Effect of nitrogen flow rate on the peak areas of volatile compounds extracted from strawberries using the headspace technique2 (volatile compounds extracted from fresh strawberries). Volatile compounds Relative amounts of volatilesy(xlO 2) Nitrogen flow rate (mL/min) 15 30 45 Ethyl propionate Ethyl butanoate Methyl hexanoate Ethyl hexanoate 2-Hexenyl acetate Total 140.lx 204.3 52.0 65.6 109.2 571.2 99.7 196.9 52.4 83.0 105.5 537.5 98.4 242.6 80.9 187.9 126.2 736.0 zPurge-and-trap time was 2 hr and incubation temperature 40°C. yRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. xMean of three samples extracted separately. Table 18. Effect of purge-and-trap time (hr) on the peak areas of volatile compounds extracted from strawberries using the dynamic headspace technique2 Volatile compounds Relative amounts of volatilesy(xlO ) Purge-and-trap time (hr) Ethyl propionate Ethyl butanoate Methyl hexanoate Ethyl hexanoate 2-Hexenyl acetate 95.2X 102.7 35.1 24.6 61.4 99.7 196.9 52.4 83.0 105.5 72.8 333.9 83.8 307.3 139.4 42.6 251.9 64.6 342.8 124.3 Total 319.0 537.5 937.2 826.2 z Flow rate of 30 mL/min and incubation temperature of 40°. yRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. xMean of three samples extracted separately. 104 Table 19. Effect of incubation temperature on the peak areas of volatile compounds extracted from strawberries using the dynamic headsapce technique2 (volatile compounds extracted from fresh strawberries) . Volatile compound Relative amounts of volatilesY(xlO ) Incubation temperature (°C) 40 60 80 Ethyl propionate Ethyl butanoate Methyl hexanoate Ethyl hexanoate 2-Hexenyl acetate 9 9 . 7 X 1 9 6 . 9 5 2 . 4 8 3 . 0 1 0 5 . 5 6 8 . 4 1 0 4 . 5 4 7 . 6 1 2 7 . 6 8 6 . 5 1 0 0 . 0 4 9 . 2 2 9 . 8 2 1 . 1 4 6 . 2 Total 537.5 434.6 246.3 ZA flow rate of 30 mL/min and purge-and-trap time of 2 hr were used. YRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. xMean of three samples extracted separately. 105 4.8 Identification of strawberry volatile compounds. Volatile compounds from quartered strawberries held at 40°C v/ere trapped on Tenax GC after purging the headspace of a flask with N2 gas. The retention time and mass spectrum obtained for each strawberry volatile compound were matched with known mass spectra in a computer data library. Figure 10 shows the match of a library mass spectrum of methyl butanoate with the mass spectrum of a strawberry volatile compound. Table 2 0 indicates the identified volatile compounds present in the strawberry volatile fraction trapped on Tenax GC, and Figure 11 shows a representative GC chromatogram for the strawberry volatile extract eluted from Tenax GC with diethyl ether. The chromatogram was re-numbered to represent selected peaks, and numbering was in order of elution time. Up to 50 volatile compounds were identified as components of the strawberry volatile extract, and they included 40 esters, 2 alcohols, 6 carbonyls and 2 sulphides (Table 20) . Among the esters were ethyl acetate, ethyl propionate, methyl and ethyl butanoates, methyl and ethyl hexanoates, 3-hexenyl acetate, 2-hexenyl acetate, methyl and ethyl heptanoates, and hexyl butanoate. The alcohols included 3,7-dimethyl-1,6-octadien-3-ol (linalool), and ethanol which eluted together with the solvent, diethyl ether. Table 21 presents identified strawberry volatile compounds thermally desorbed from the Tenax GC traps. The 40 compounds identified by GC-MS methodology included 25 esters, 10 carbonyl compounds, 3 alcohols, 2 acids and 1 sulphide compound. Ester compounds included ethyl acetate, methyl butanoate, ethyl 2-106 1 Sc an 1 1 O O O O — j 1 KJUJILtlCJ J 1 1 1 fl«O0H 1 3 i ^ 1 bwwen ! ^ i /oop»J 1 3 38 I ? 0 G . G H \ ( _ ^ M i a i *" i ° 1 c t c ! 0 0 0 0 T i o 4 ICE fifiAPH i i 1 . i 6 0 0 0 1 i-> J 4 1 , . / i 4»4ujen/ 1 4 j 2 0 8 0 K i < j e* • i • ' • • 8 / 8 43 1 1 1 1 i l i ( I / . / 1 8 m in J o f LIHIHI 71 l\ 1 <. C O J O \ i i i i i t Bulo.no i c AC i d , m e t h y l I r. 1 j l ( i 1 i I i .1 l l Hi i • i • 1 90 40 • 7 1 4 I J \ * \ 59 N \ i i 1. ! i « 4 • i • • • • i • • • • , . 50 60 70 Iu4_ _ _ ,f^l e s • i • 80 : / U I U Z 4 . 67 / i 1 U i02 \ y 4-\ r^T \ t e r u t i ) m u ; / 1 1 1 90 4 r\*\ \ \ • 1 !00 — 1 curxntn :8000 ; :5000 :4880 :2000 : 1000G ; f l00 f l 6 0 0 0 ;4000 ' 1 8utanoic acid, methvl ester <9CI) flol. Ut. : 102.067 Figure 10. Mass spectrum of methyl butanoate from strawberry extract and its' match from the library spectra (volatile compound extracted from fresh strawberries). 107 Table 20. Tentatively identified2 strawberry volatile compounds which were desorbed from Tenax GC adsorbent by diethyl ether (volatile compounds extracted from fresh strawberries). Peak Volatile compound Retention time No. (min) l.y 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. Acetaldehyde Ethanol Acetone 2-Methylpentane Ethyl acetate Acetic acid Ethyl propionate Ethyl-2-methyl acetate Propionic acid Propyl acetate Methyl butanoate Dimethyl disulphide Propyl-2-methyl acetate Ethyl butanoate Butyl acetate Ethyl 1-methylbutanaote Ethyl 2-methylbutanoate Ethyl 3-methylbutanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-Methyl acetyl-1-butanoate 2-Octanone Propyl butanoate Ethyl pentanoate Methyl hexanoate 3-Acetyldihydro 2 (3)-furanone Methyl heptanoate Dimethyl trisulphide Butyl butanoate 1-methylpropyl butanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate Hexyl acetate 1-Methylethyl hexanoate 2-Nonanone (internal standard) Pentyl methyl acetate 3,7-Dimethyl-l,6-octadien-3-ol Ethyl heptanoate 6-Ethyl-2-methyl octane Methyl nonanoate 5.14 5.87* 6.01 6.30* 6.50 6.80 7.29 7.83* 7.85 7.90 8.76* 9.14 10.70 10.80 11.08 11.80 11.90 12.20 12.77* 13.18* 13.20* 13.31* 13.57 13.67* 14.20 15.78* 16.22 16.44* 16.56 16.97 17.15 17.77 19.53* 19.74 20.06 20.13* 20.49 21.02 108 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. Phenylmethyl acetate 2-Ethylhexyl acetate 2-Methylpropyl hexanoate Hexyl butanoate Ethyl octanoate 1-Dodecane Octyl acetate sec-Octyl acetate 2-Methylbutyl hexanoate Octyl propionate Hexyl hexanoate Octyl 2-propionate Unknown 3 Unkown 4 21.50 21.59 22.05 22.85* 23.01* 23.01 23.44 24.29 25.28 27.40 28.51 28.68 29.03 29.16 zVolatile compounds identified by GC/MS. yPeaks 1 to 3 eluted with the solvent peak "Reference (authetic) compound used to confirm identified strawberry volatile compound. 1 0 9 H<iOMl->r :OM(io 70000 5MW) *vub (J-X 1 1 — ] 1 1 1 29 8 JO 35 10 IS SO T 10 Figure 11. Typical GC chromatogram of strawberry volatiles eluted from Tenax GC with diethyl ether (peaks re-numbered to show GC peaks of interest; IS=2-nonanone used as internal standard; volatile compounds extracted from fresh strawberries). 110 Table 21. Tentatively identified2 strawberry volatile compounds which were thermally desorbed from Tenax GC adsorbent (volatile compounds extracted from fresh strawberries). Peak Volatile compound name Retention time No. 1. 2. 3. 4. 5. 6. 7. 6. 8. 9. 10. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 2-Propane Ethyl ether Dichloromethane Hexane Ethyl acetate Trichloromethane 3-Buten-l-ol or Ethyl-3-butenoate Unknown 2,2,3-Trimethylpentane Ethyl propionate Methyl butanoate Ethyl 2-methylpropionate Methyl benzene Methyl 3-methylbutanoate Isocyanato-ethane Ethyl butanoate Unknown Ethyl 1-Methylbutanoate Unknown Ethyl 2-methylbutanoate 1,4-Dioxane 2-Hexenal 3-Methyl-l-butyl acetate 4-Methyl-2-hexanone Propyl butanoate Ethyl pentanoate Phenyl butanedioc acid Pentyl acetate Methyl hexanoate Ethyl-3-methyl-2-butenoate Dimethyl trisulfide Ethyl hexanoate 4-Hexenyl acetate 3-Methyl-l,3-pentadiene 1-Hexene 2,5,6-trimethyl octane 2-Octen-4-ol 2-Methylbutyl 2-methylpropionate 2,2,2-Trimethylhexane 4-Ethyl-2,2,6,6-tetramethylheptane 2,8-Dimethyl undecane 2-Nonanone (min) 7.69 8.11 9.13 12.00 12.42*y 12.84 13.19 14.79 15.95 17.95* 17.72* 19.44 20.10 20.30 21.30 21.62* 22.00 23.21 23.42 23.59 23.79 23.79 24.74 25.42 25.61* 25.71* 25.80 26.24 26.77* 27.43 29.45 29.72* 29.97 30.11 30.30 30.89 31.53 31.92 32.24 32.37 32.92 33.33* I l l 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 3,7-Dimethyl-l,6-octadien-3-ol 2-Methyl hexanoate Phenylmethyl acetate Ethyl benzoate Hexyl butanoate Ethyl octanoate Octyl acetate 2,3-Dimethyl-3-hexanol Phenylmethyl butanoate 1-Methyloctyl butanoate 33.72 34.23 35.80 36.09 36.19 36.32* 36.67 37.29 40.27 41.06 z V o l a t i l e compounds i d e n t i f i e d by GC/MS. YReference ( a u t h e t i c ) compound used t o conf i rm i d e n t i f i e d s t r a w b e r r y v o l a t i l e compound. 112 methylpropionate, methyl 3-methyl butanoate, propyl butanoate, ethyl pentanoate, methyl hexanoate, ethyl-3-methyl-2-butenoate, ethyl hexanoate, phenylmethyl acetate and ethyl octanoate. The carbonyl compounds were 2-hexenal, 1-hexene, 3-methyl-1,3-pentadiene and 4-ethyl-2,2,6,6-tetramethylheptane. Thermal desorption produced alkenes such as 3-methyl-1,3-pentadiene which were not eluted from the Tenax GC with diethyl ether. Ethanol was not detected and this may be due to the bleeding of the low molecular weight compound through Tenax GC trap (Schaefer, 1981) . Most of the strawberry volatile compounds identified in this study have been reported to be present in fresh strawberries by other researchers (McFadden et al., 1965; Schreier, 1980; Dirinck et al. , 1981; Hirvi and Honkanen, 1982; Douillard and Guichard, 1990). The variation in the types and amounts of the strawberry volatile compounds apparently depends on the method of volatile compound extraction and fruit maturity. Of the many strawberry volatile compounds tentatively identified in this research study, the most frequently appearing ones in the GC chromatograms under all the conditions are presented in Table 22. Volatile compounds that have been reported to contribute to typical strawberry aroma include methyl butanoate, ethyl butanoate, methyl hexanoate, ethyl hexanoate, trans-2-hexyl acetate, trans-2-hexenal, trans-2-hexen-l-ol and 2,5-dimethyl-4-methoxy-3(2H)-furanone (furanoel) (Schreier, 1980; Hirvi and Honkanen, 1982; Douillard and Guichard, 1990) . Some of these volatiles, such as the hexanoates, heptanoates and the hexenyl acetates, were Table 22. Strawberry volatile compounds selected for statistical analysis (peaks re-numbered). Peak No. 4 5 14 15 16 17 19 20 22 25 29 30 31 32 33 36 37 38 44 45 47 48 50 51 54 Renumbered Peaksy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Labelz a b c d e f g h i J k 1 m n o P q r s t u V w X Y RTX 5.18 5.49 8.57 9.07 10.72 10.80 11.70 11.79 12.88 13.51 16.22 16.44 16.56 16.88 17.77 19.86 19.99 20.09 22.80 22.96 23.39 24.24 28.48 28.59 29.14 Volatile compound Ethyl propionate Methyl butanoate Ethyl butanoate Butyl acetate Ethyl 1-methylbutanoate Ethyl 2-methylbutanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-Octanone Methyl hexanaote Butyl butanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl-l,6-octadien-3-ol Ethyl heptanoate Hexyl butanoate Ethyl octanoate Octyl acetate sec-Octyl acetate Hexyl hexanoate Octyl propionate Unknown zLabel=peak name, used in canonical plots (Figures 23, 26, 29) yRe-numbered peaks selected for statistical analysis. xRT=retention time in minutes. 114 tentatively identified as indicated in Tables 20, 21 and 22. 4.9 Volatile compounds of strawberries stored under MAP. Strawberry volatile compounds were extracted on days 3, 6 and 10 from unpackaged strawberries and from MAP strawberries with input gases as air, mixed gas (11% C02 + 11% 02) or carbon dioxide (100% C02) . Volatile compounds were also extracted from fresh strawberries at day 0 (prior to storage) . The GC analyses of strawberry extracts were carried out on the same day as the extraction to obviate any chemical changes of the volatile compounds during the storage of the ether extract from the Tenax GC traps. Figure 12 shows typical GC chromatograms obtained from unpackaged strawberries and from MAP strawberries with input gases as air, mixed gas or carbon dioxide after 6 days of storage. These chromatograms possessed more than 60 peaks, 50 of which were tentatively identified (Table 20). The profiles of the chromatograms were similar with the most noticeable differences being the peak heights. The ratio of each sample peak area to the peak area of an internal standard (2-nonanone) was used to express the relative amounts of strawberry volatile compounds. The relative amounts of volatile compounds varied depending on the type of volatile compound, treatment and storage time (Tables 23, 24 and 25). The variation in the relative amounts of volatile compounds for the different treatments and storage times presumably was related to changes in the perceived flavor/odor of strawberries B S 5 ill lj mJk. LiJ_ 51 IS tl ' T -IS I! iiliil J&1 t <f £ .-MjJ*t^.A»_MM_ i) IS St IS It IS It it Figures 12. Flavor volatile profiles of unpackaged strawberries (A) and MAP strawberries packaged in air (B), mixed gas (C) or carbon dioxide (D) after 6 days of storage at 1°C. Table 23. Relative amounts2 of selected volatiles from strawberry fruit evaluated at day 0 and at day 3 of storage at 1°C for unpackaged and MAP samples with input gases as air, mixed gas or carbon dioxide. Labely Volatile compound Relative amounts (xlO"2) Day 0 Unpack" Air Mixed Carbon gas dioxide a b c d e f g h i J k 1 m n o P q r s t u V w X y Total Ethyl propionate Methyl butanoate Ethyl butanoate Butyl acetate Ethyl 1-methylbutanoate Ethyl 2-methylbutanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-0ctanone Methyl hexanoate Butyl butanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl-l,6-octadien-3-Ethyl heptanoate Hexyl butanoate Ethyl octanoate Octyl acetate sec-Octyl acetate Hexyl hexanoate Octyl propionate Unknown 3.7 45.8 179.4 37.2 9.9 6.3 4.2 3.7 1.6 50.2 19.6 260.6 20.1 116.8 3.0 0.5 -ol 1.0 1.8 9.6 2.4 8.9 2.7 1.7 6.1 0.7 797.5 3.3 38.0 247.7 47.0 22.1 7.7 5.6 3.5 1.9 38.4 15.0 292.5 11.7 109.0 3.0 0.7 0.8 1.4 9.1 2.8 13.9 1.9 1.9 8.8 0.7 888.4 10.6 30.4 190.2 20.8 25.9 10.5 12.0 5.9 1.2 32.1 4.6 174.5 15.7 135.7 1.3 2.2 0.8 2.9 6.5 3.1 6.3 3.0 1.7 2.7 1.1 701.7 6.7 6.5 146.1 13.1 63.5 12.1 10.6 4.9 1.1 8.8 1.1 161.0 9.9 54.3 2.3 1.8 0.7 1.6 1.8 3.7 6.4 1.7 1.0 0.5 1.4 522.6 5.7 7.0 168.2 35.2 22.5 7.6 10.4 7.2 2.3 18.4 0.8 313.3 6.6 104.7 4.9 0.4 3.7 13.1 0.7 3.6 16.7 3.5 0.6 1.0 1.7 759.8 zRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. yLabel=peak name, used in canonical plots (Figures 23, 26, 29). "Unpackaged strawberries. Table 24. Relative amounts2 of selected volatiles of strawberry fruit evaluated at day 0 and at day 6 of storage at 1°C for unpackaged and MAP samples with input gas as air, mixed gas or carbon dioxide. Labely Volatile compound Relative amounts (xl0~2) Day 0 Unpack" Air Mixed Carbon gas dioxide a Ethyl propionate b Methyl butanoate c Ethyl butanoate d Butyl acetate e Ethyl 1-methylbutanoate f Ethyl 2-methylbutanoate g Pentyl acetate h 2-Methyl-l-butyl acetate i 2-0ctanone j Methyl hexanaote k Butyl butanoate 1 Ethyl hexanoate m 3-Hexenyl acetate n 2-Hexenyl acetate o 1-Methylethyl hexanoate p Methyl heptanoate q 3,7-Dimethyl-l,6-octadien-3-ol r Ethyl heptanoate s Hexyl butanoate t Ethyl octanoate u Octyl acetate v sec-Octyl acetate w Hexyl hexanoate x Octyl propionate y Unknown Total 797.5 1071.5 699.9 456.7 995.7 zRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. yLabel=peak name, used in canonical plots (Figures 23, 26, 29) . "Unpad aged strawberries. 3 . 7 4 5 . 8 1 7 9 . 4 3 7 . 2 9 . 9 6 . 3 4 . 2 3 . 7 1 .6 5 0 . 2 1 9 . 6 2 6 0 . 6 2 0 . 1 1 1 6 . 8 3 . 0 0 . 5 1 .0 1 .8 9 . 6 2 . 4 8 . 9 2 . 7 1.7 6 . 1 0 . 7 5 . 7 9 . 8 3 5 5 . 2 3 4 . 6 9 9 . 3 1 6 . 0 1 7 . 9 5 . 6 3 . 1 8 . 7 1 .5 3 9 4 . 4 1 0 . 3 7 7 . 7 2 . 1 0 . 6 0 . 6 1 .2 0 . 6 3 . 9 1 8 . 2 1 .4 1 .1 1.2 1 .0 9 . 5 3 3 . 0 1 2 1 . 7 2 6 . 6 6 . 4 6 . 4 3 . 2 2 . 8 1 .2 4 5 . 9 1 6 . 2 2 2 2 . 6 1 5 . 7 1 4 3 . 8 1 .9 1 .9 1.0 2 . 0 1 2 . 1 4 . 0 7 . 9 3 . 5 2 . 3 6 . 3 2 . 1 9 . 1 9 . 3 1 2 0 . 6 9 . 3 5 1 . 4 1 7 . 6 1 6 . 1 4 . 3 1 .1 1 1 . 3 1.0 1 4 2 . 5 1 0 . 4 2 8 . 1 1 .9 2 . 3 1.0 1 .9 2 . 7 4 . 4 5 . 5 1 .7 0 . 7 1.0 1 .5 7 . 0 6 . 4 2 2 7 . 1 4 4 . 2 3 2 . 3 9 . 0 1 7 . 0 7 . 2 3 . 2 1 4 . 7 0 . 8 4 5 0 . 3 4 . 0 1 1 2 . 2 8 . 3 0 . 5 3 . 8 1 5 . 5 0 . 0 3 . 4 2 4 . 0 1 .3 0 . 1 1.2 2 . 2 Table 25. Relative amounts2 of selected volatiles of strawberry fruit evaluated at day 0 and at day 10 of storage at 1°C for unpackaged and MAP samples with input gas as air, mixed gas or carbon dioxide. Labely Volatile compound Relative amounts (xl0~2) Day 0 Unpack0 Air Mixed Carbon gas dioxide a b c d e f g h i J k 1 m n 0 P q r s t u V w X y Ethyl propionate Methyl butanoate Ethyl butanoate Butyl acetate Ethyl 1-methylbutanoate Ethyl 2-methylbutanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-Octanone Methyl hexanaote Butyl butanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl-l,6-octadien-3-ol Ethyl heptanoate Hexyl butanoate Ethyl octanoate Octyl acetate sec-Octyl acetate Hexyl hexanoate Octyl propionate Unknown Total 3.7 45.8 179.4 37.2 9.9 6.3 4.2 3.7 1.6 50.2 19.6 260.6 20.1 116.8 3.0 0.5 1.0 1.8 9.6 2.4 8.9 2.7 1.7 6.1 0.7 797.5 6.7 8.2 350.7 34.8 103.3 18.8 14.5 5.6 3.3 12.8 1.9 520.7 13.5 92.6 2.8 0.7 1.0 1.5 1.0 4.7 17.5 2.4 0.9 1.3 1.1 1222.4 11.1 19.7 59.3 12.2 7.6 4.0 2.5 3.2 0.5 26.3 2.8 94.0 12.1 86.2 2.9 1.8 0.9 2.3 3.9 2.6 7.0 5.1 1.6 2.7 2.1 374.5 8.3 23.5 166.9 29.8 17.1 11.2 8.9 7.2 3.6 41.7 11.9 374.9 7.2 141.4 4.7 3.6 2.9 10.5 5.3 4.3 16.9 9.5 2.3 7.9 2.9 924.3 8.8 9.5 190.5 39.5 24.6 9.7 23.7 8.0 4.4 18.3 1.6 467.1 3.8 95.0 8.0 0.6 5.5 13.9 0.7 3.3 21.1 1.5 0.6 1.4 2.1 963.0 zRelative amounts of volatile compounds were calculated as the ratio between each sample peak area to the peak area of the internal standard. yLabel=peak name, used in canonical plots (Figures 23, 26, 29) . "Unpackaged strawberries. 119 stored under modified atmosphere packaging conditions. The total relative amount of volatile compounds, total relative amount of groups of various volatile compounds and relative amounts of individual volatile compounds extracted for each treatment at each storage time were examined. In general, the total amount of volatile compounds extracted from strawberries stored under MAP conditions was lower than that for unpackaged strawberries (Figure 13). There was no particular trend for relative amounts of individual and group volatile compounds from the strawberries held under different MAP conditions. However, the relative total amount of butanoates for strawberries kept under MAP conditions was lower than that for unpackaged strawberries (Figure 14). Other researchers including Guadagni et al. (1971), Lidster et al. (1983) and Willaert et al. (1983) found volatile compound synthesis to be diminished in apples stored under high C02 and low 02 levels. De Pooter et al. (1987) concluded that the reduced volatile synthesis in 'Golden Delicious' apples under CA storage could be attributed to the interference with the carboxylic acid metabolism and alcohol dehydrogenase activity. 4.10 Multivariate statistical analyses of sensory and volatile data. 4.10.1 Simple correlation of odor attributes with volatile data. Data from the different MAP treatments and storage time were combined and subjected to correlation and regression analyses. The correlation and regression analyses were applied to data on the 120 O > c 3 O E a « o •*^  V > a v 14.0O 1 1.60 9 . 2 0 6 .80 4 . 4 0 2 .00 H— Unpackaged 0 3 6 Days in s to rage p - - A - - Air — o — Mixed gas -•+•••• Carbon dioxide 10 Figures 13- Relative total amounts of volatile compounds extracted from strawberries stored under various MAP conditions for 10 days at 1°C. 03 a o c (0 • * -a .a c 3 o E a > 6 .00 4 . 8 0 •ft 3 . 60 -2.40 -1.20 0 .00 — i — Unpackaged - -A - - Air — o — Mixed gas ••••+•••• Carbon dioxide 0 3 6 Days in storage 10 Figures 14. Relative total amounts of butanoates extracted from strawberries stored under various MAP conditions for 10 days at 1°C. 121 sensory attributes of strawberry odor, off-odor, fermented odor and musty odor, overall fruit quality as well as relative amounts of volatile compounds. The other sensory attributes such as texture, sweetness, sourness and bitterness were omitted since they are related to nonvolatile constituents (Spencer et al. 1978). Correlation coefficient analysis was carried out in an attempt to reveal any volatile compounds that may have a strong contribution or correlation with desirable or undesirable odor attributes. Reasonably high significant correlations were obtained between some of the sensory attribute scores and the relative amounts of strawberry volatile compounds detected by GC. Table 2 6 shows that the relative amounts of some volatile compounds were positively correlated to desirable strawberry odor and overall quality for strawberries under MAP conditions. These compounds included methyl butanoate, butyl butanoate, 3-hexenyl acetate and hexyl butanoate. Further, these compounds were negatively correlated to the undesirable attributes. Compounds positively correlated to the undesirable attributes (off-odor, fermented odor and musty odor) but negatively to desirable attributes were 1-methylethyl hexanoate, methyl heptanoate, 3,7-dimethyl-1,6-octadien-3-ol, ethyl heptanoate, octyl acetate and the unknown. It appears that the presence of these compounds may have contributed to undesirable attributes detected by the judges among the different treatments. However, the chemical changes taking place in strawberries stored under MAP conditions may be due to more than one volatile compound (Powers, 1982). Therefore, a number of Table 26. Correlation coefficients (r) between sensory attributes and quantity of volatile peaks (relative amounts of volatile compounds, n=108) . Label2 Volatile compound b g h i k m 0 P q r s u V w X y Methyl butanoate Pentyl acetate 2-methyl-l-butyl acetate 2-octanone Butyl butanaoate 3-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl-l,6-octadien-3-ol Ethyl heptanoate Hexyl butanoate Octyl acetate sec-Octyl acetate Hexyl hexanoate Octyl propionate Unknown Correlation OVQy 0.31***x -0.13 -0.32*** -0.18 0.33*** 0.32*** -0.44*** -0.20* -0.57*** -0.57*** 0.23** -0.28* 0.27** 0.14 0.17 -0.47*** SOD 0.41*** -0.22* -0.34*** -0.19* 0.39*** 0.35*** -0.40*** -0.18 -0.54*** -0.54*** 0.35*** -0.31*** -0.19 0.20* 0.23* -0.47*** coefficients(r) OFD -0.40*** 0.21* 0.34*** 0.22* -0.35*** -0.38*** 0.49*** 0.49*** 0.64*** 0.64*** -0.36*** 0.33*** 0.16 -0.28** -0.23* 0.40*** FMT -0.31*** 0.12 0.24* 0.03 -0.29** -0.29** 0.43*** 0.43*** 0.53*** 0.55*** -0.22* 0.11 0.15 -0.20* -0.19* 0.40*** MST -0.36** 0.15 0.29** 0.21 -0.31** -0.36*** 0.43*** 0.43*** 0.62*** 0.59*** -0.30** 0.33** 0.20* -0.24* -0.18 0.40*** zLabel=peak name, used in canonical plots (Figures 23, 26, 29) . yOVQ=overall quality; SOD=strawberry odor; OFD=off-odor; FMT=fermented odor; MST=musty odor, x***^**^* significantly different at 0.1, 1 and 5% level 123 volatile compounds may have had a cumulative effect in the perception of desirable or undesirable attributes by the judges. 4.10.2 Multiple regression of odor attributes with volatile data. Multiple regression analysis was performed to: a) determine the relationship between sensory scores and relative amounts of volatile compounds obtained from strawberries stored under MAP and b) predict the sensory quality of strawberries from the data of relative amounts of volatile compounds. Regression could aid in reducing the data set and elucidating important quality-determining volatile compounds (Leland et al. 1987). Also, one can evaluate the contribution that each variable makes to the regression of the dependent variable on the independent variables (Pino, 1982; Powers, 19 82) . Multiple regression models were developed by regressing all the data on relative amounts of volatile compounds, and by the use of forward stepwise regression on the odor attributes to select variables of importance for the sensory attributes (SAS, 1985). Table 27 shows a summary of multiple regression of all 25 volatile compounds to predict odor scores as well as subsets obtained by stepwise regression. The R2 indicates that the volatile compounds could explain up to 70% of the variance of the sensory attributes, when all of the data for the volatile compounds were used in the regression for each sensory attribute. With different sensory attributes, forward stepwise regression selected between 6 to 9 volatiles and on average accounted for 65% of the variance. Higher Table 27. Summary of multiple regression of all volatile compounds and those selected by the stepwise procedure against each of the odor sensory attributes (n=108). Sensory attribute Strawberry odor Off-odor Fermented odor Musty odor Overall quality Method of regression General Stepwise General Stepwise General Stepwise General Stepwise General Stepwise Model All 7 peaks All 6 peaks All 8 peaks All 7 peaks All 9 peaks Rz 0.81 0.79 0.84 0.81 0.81 0.77 0.82 0.78 0.82 0.81 R2y 0.65 0.62 0.70 0.65 0.66 0.60 0.67 0.61 0.67 0.65 F value of regression 5.98***x 22.95*** 7.77*** 31.29*** 6.25*** 18.66*** 6.67*** 22.30*** 6.78*** 20.27*** zMultiple correlation coefficient (correlation between Y and score estimated from regression model). yMultiple determination coefficient (variance explained in Y from the regression model. **** Significantly different at the 0.1% level 125 variance was explained when all the variables were used in the regression. Therefore, for modelling and subsequent analysis, the 25 volatile compounds and some of the subsets from stepwise regression were used. Such information would be valuable in assessing the value of relative amounts of selected volatile compounds as indicators of quality changes of the strawberries stored under MAP. Table 2 8 shows the regression equations developed from data for selected volatile compounds by stepwise regression for predicting odor sensory attributes and overall quality. Figure 15 shows the observed and predicted values of overall fruit quality from volatile compounds selected by stepwise regression (based on the equation in Table 28) . Data from the following volatile compounds were included in the equation: ethyl butanoate; 1-methylpropyl butanoate; 1-hexenyl acetate; 3-methylethyl hexanoate; 3,7-dimethyl-l,6-octadien-3-ol; hexyl butanoate; sec-octyl acetate; octyl 2-propionate and the unknown. 4.10.3 Preliminary data analysis with principal component and discriminant analysis. All GC data collected at each storage time from each treatment were subjected to principal component analysis and discriminant analysis. The scores of the first two principal components and first two canonical variates were plotted, to aid in interpretation of data. It was impossible to develop a clear picture of the behavior of the different treatments at various storage times with changes in gas composition from Figures 16 and 17. Therefore, the 126 Table 28. Regression equations developed from data for volatile compounds selected by stepwise regression regressed against each of the odor attributes (n=108) . SODz= 4.328 + 0.002*cY + 0.085*k + 0.079*m - 0.393*q - 0.068*s - 0.127*t - 0.391*y OFD = 3.458 - 0.004*c - 0.079*k - 0.073*m + 0.598*q + 0.090*r + 0.464*y FMT = 2.011 - 0.003*c - 0.018*d - 0.073*k - 0.050*m + 0.145*o + 0.414*q + 0.102*s + 0.216*y MST = 3.034 - 0.004*c - 0.090*k - 0.100*m + 0.776*q + 0.085*s + 0.156*t - 0.255*y OVQ = 4.328 + 0.003*c + 0.137*k + 0.149*m - 0.190*0 - 0.450*q - 0.276*s - 0.230*v + 0.177*x - 0.354*y ESOD=strawberry odor; OFD=off-odor; FMT=fermented odor; MST=musty odor; OVQ=overall fruit quality. yVolatile compounds listed in Table 22. 127 0 1 2 3 4 5 6 7 8 Overall quality score Figure 15. Predicted and observed scores of overall quality of strawberry fruit stored under MAP for 10 days using nine volatile compounds selected by stepwise regression. 128 4 £ 0 -1 --2 -2 M M MC * B b K g 4 1 K K C H *k„ K M ^ | Ju^J M H^  Hff M H BJ M M I B A G %SL*\* F F F A B % B E F 0 1 4 Principal component 1 Figure 16. Principal component scores obtained from PCA of 25 volatile compounds from all strawberry samples evaluated from different treatments and storage times (A=samples evaluated at day 0; B, C, D=unpackaged samples; E, F, G=samples packaged in air; H, I, J=samples packaged in mixed gas, K, L, M=samples packaged in carbon dioxide and evaluated at days 3, 6 and 10, respectively). 129 6 F 4 -2 -•= 0 --2 --4 --6 L » « D \ ^bo D L L ^ M L M M M M K C K E H M K K EE H t£ H K K \B B I'm J K K F F ^ n « G G d Jj F F f  G J G -10 -5 0 10 Canonical varlate 1 Figure 17. Canonical variate scores obtained from CVA of 25 volatile compounds from all strawberry samples evaluated from different treatments and storage dates (A=samples evaluated at day 0; B, C, D=unpackaged samples; E, F, G=samples packaged in air; H, I, J=samples packaged in mixed gas, K, L, M=samples packaged in carbon dioxide and evaluated at days 3, 6 and 10, respectively). 130 data were divided into different groups based on storage time and re-analyzed by the same statistical procedures to indicate how relative amounts of selected volatile compounds could be used as indicators of the quality changes taking place in the strawberries stored under various MAP conditions. 4.10.4 Principal component analysis (PCA) of volatile data. Principal component analysis was first used to: a) examine the data for interpretable patterns; b) transform and reduce the amount of data; c) determine which volatile peaks correlated well with each other and d) determine the relationship of a volatile compound with overall fruit quality. The data from each treatment based on storage time at 1°C, were analyzed. At each storage time, five principal components (PC) with eigenvalues greater than 1.0 and % cumulative proportion (variance explained) of 84, 86 and 86% for day 3, 6 and 10 samples were obtained, respectively (Table 29) . Therefore, the information contained for the 25 volatile compounds (variables) was contracted (reduced) into five principal components (PC) with only 14-16% loss of information at each storage time. Figures 18, 19 and 2 0 show plots for the first two principal components for strawberries that had been in storage for 3, 6 and 10 days at 1°C. At all storage times, PCA failed to separate the data for different treatments into distinct groups or form some interpretable pattern in the distribution of data for the different samples. Although data for some samples from different treatments showed some groupings, interpretation was difficult. Headley and 131 Table 29. Principal component analysis of strawberry volatiles analyzed after 3, 6 and 10 days. Days in Principal Eigenvalue % Proportion % Cumulative storage component contribution proportion 3 1 7.1 28 28 2 6.2 25 53 3 3.9 16 69 4 2.4 9 78 5 1.5 6 84 1 8.7 35 35 2 5.4 21 56 3 3.4 14 70 4 2.3 9 79 5 1.6 6 86 10 1 8.0 32 32 2 6.2 25 57 3 3.6 15 72 4 2.2 9 81 5 1.3 4 86 132 C\j CM c Q) C O a E o o 13 CL O Q_ 2 -0 --1 --2 -2 •1 0 1 Principal component 1 (28%) Figure 18. Principal component scores of strawberry samples evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 3 days in storage at 1°C. 1 3 3 CTS CM -+-• c 0 c O Q. E o o Q. o c 0 h £ "1 *--2 •1 0 1 Principal component 1 (35%) Figure 19. Principal component scores of strawberry samples evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 6 days in storage at 1°C. 134 2 -1 -0 -2 1 0 1 2 Principal component 1 (32%) Figure 20. Principal component scores of strawberry samples evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 10 days in storage at 1°C. 135 Hardy (1989) successfully applied PCA in their classification of different whiskies varying in composition of 48 volatile compounds as a result of dilution, blending or contamination. Kwan and Kowalski (1980) applied PCA to determine the consistency of individual judges and uniformity among them during the evaluation of wines. However, Aishima (1979a,b) found that the scattergrams from PCA could not be used to discriminate 8 brands of soy sauce, but instead, successfully applied discriminant analysis on the principal components obtained from PCA. Heymann and Noble (1989) reported that PCA is not a very useful technique in classification of samples but is valuable in the initial examination of data and to detect data containing outliers. 4.10.5 Discriminant/Canonical variate analysis of volatile data. Because of the failure of PCA to classify or give some kind of interpretable pattern from the GC data, multiple discriminant analysis was applied. The GC data for 25 selected volatile compounds (Table 22) as well as volatile compound data subsets obtained after stepwise discriminant analysis (Table 30) were used in an attempt at classification. Multiple discriminant analysis was used to find the function which would be able to best separate samples into predetermined groups by maximizing intergroup distances while minimizing within group distance (Jeltema et al. 1984). Leland et al. (1987) used discriminant analysis to build and assess classification models of milk samples subjected to different oxidation levels. The objective of using discriminant 136 Table 30. Strawberry volatile compounds selected by stepwise discriminant analysis for inclusion into models to predict the treament and/or quality category. Days in Label3 Selected volatile compound F ratio a d k m P q t X b e f h J 1 m n P r X a e g m P Ethyl propionate Butyl acetate Butyl butanoate 3-Hexenyl acetate Methyl heptanoate 3,7 Dimethyl-1,6-octadien-3-ol Ethyl octanoate Octyl propionate Methyl butanoate Ethyl 1-methylbutanoate 2-Methylethyl butanoate 2-Methyl-l-butyl acetate Methyl hexanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate Methyl heptanoate Ethyl heptanoate Octyl acetate Ethyl propionate Ethyl 1-methylbutanoate Pentyl acetate 3-Hexenyl acetate Methyl heptanoate to enter 22.3***b 27.4*** 23.8*** 17.4*** 16.1*** 28.2*** 16.6*** 19.4*** 43.2*** 63.9*** 53.1*** 53.1*** 52.8*** 46.0*** 52.9*** 54.3*** 53.8*** 48.2*** 52.7*** 27.6*** 38.7*** 38.9*** 26.2*** 30.8*** z*** Significantly different at the 0.1% level YLabel=peak name, used in canonical plots (Figures 23, 26, 29) . 137 analysis in this research was to classify the chromatograms into groups corresponding to the different treatments and/or quality of strawberries stored under MAP. For all three storage times, the multivariate statistic of Wilk's lambda from canonical variate analysis (CVA) indicated highly significant differences between the treatments (Table 31). The strawberries from different MAP treatments for each storage time differed significantly, based on the relative amounts of all volatile compounds extracted from each sample. From these statistical tests, however, it was not possible to determine which sample treatments differed from one another nor was it possible to tell which volatile compounds were of importance. Therefore, results from canonical variate analysis (CVA) at each storage time were examined. For the three storage times, the first three canonical variates constructed from the 25 volatile compounds accounted for 95, 97 and 94% of the total variance for day 3, 6 and 10, respectively (Table 31) . In each case, all the canonical variates were highly significant with most of the variance being explained by the first three. Therefore, further discussion will be limited to these three variates. Figures 21 and 22 show the plots of the first two and first three canonical variates of individual observations from each sample treatment after 3 days in storage. Three distinct groups were formed with group 1 containing strawberries evaluated at day 0 (F) and unpackaged strawberries from day 3 of storage (U) . Group 138 Table 31. Canonical variate analysis of strawberry volatiles evaluated at days 3, 6 and 10 Days in Wilk's2 Canonical Canonical Eigen Signif.Y Variance storage lambda variate correlation value level explained (%) 10 1 2 3 1 2 3 1 2 3 0.984 0.961 0.939 0.998 0.995 0.980 0.984 0.968 0.958 30.9 11.9 7.5 204.2 91.0 24.9 30.1 15.0 11.2 * ** * ** *** *** *** ** * *** * * * *** 58 81 95 62 90 97 50 75 94 M u l t i v a r i a t e s t a t i s t i c . y***f**f* s i g n i f i c a n t l y d i f f e r e n t a t t h e 0 . 1 , 1 and 5% l e v e l , r e s p e c t i v e l y . x S i g n i f i c a n c e l e v e l . 139 10 I- c •5 0 -5 -10 o c -10 M M ^ MM A AA A A 0 BFiy u^¥ip F F FU 10 Canonical variate 1 (58%) Figure 21. Canonical plot of the first two canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 3 days in storage at 1°C. 140 Figure 22. Canonical plot of the first three canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 3 days in storage at 1°C. 141 2 contained strawberries packaged in air (A) and those in mixed gas (M) , while group 3, which was clearly separated, represented strawberries packaged in carbon dioxide (C). Examination of the Mahalanobis distances (probabilities) showed that all the sample centroids, except those of day 0 (F) and unpackaged strawberries after 3 days of storage were significantly different (Table 32). The first canonical variate separated the unpackaged and MAP packaged strawberry samples (Figure 21). The data for treatments of packaged strawberries with air (A) , mixed gas (M) and carbon dioxide (C) as input gases are located on the left-hand side of the plot. Data for the other two unpackaged samples evaluated at day 0 and after 3 days of storage are located on the right-hand side of the plot. The second canonical variate separated the data on strawberries packaged in carbon dioxide from the data for all other samples. This separation was based on quality ratings of strawberries after 3 days of storage at 1°C. All samples, except those treated with carbon dioxide, were still acceptable with an overall fruit quality rating greater than 3 (sensory data in Tables 6, 7, 8) . The failure of canonical variate 1 to separate the data for samples evaluated at day 0 (F) and data for unpackaged strawberries at day 3 of storage (U) could be attributed to the fact that few quality changes would have occurred in the unpackaged strawberries during that time interval. Sensory data for overall fruit quality shows that the scores for strawberries at day 0 and unpackaged strawberries evaluated at day 3 were close (Table 8). Although 142 Table 32. Mahalanobis2 distances between different strawberry treatments analyzed by canonical variate analysis using 25 volatile compounds. Days in StOTaye 3 6 10 F U A M C F U A M C F U A M C Cent F y 0 4.7 11.8***x 11.1*** 13.5*** 0 22.3*-** 14.8*** 20.8*** 39.0*** 0 12.2*** 10.6*** 12.5*** 15.7*** roids (means) o U 0 11.7*** 10.9*** 13.4*** 0 26.9*** 22.3*** 30.1*** 0 10.2*** 9.2*** 12.0*** if strawberry A 0 8.5*** 10.7*** 0 23.5*** 33.1*** 0 6.4* 12.2*** treatments M 0 g_ g*** 0 32.6*** 0 11.3*** C 0 0 0 Generalized distance calculated from discriminant function. yF=day 0 samples; U=unpackaged samples; A, M, C=MAP samples held in air, mixed gas and carbon dioxide, respectively. x***,**,* Significantly different at the 0.1, 1 and 5% level, respectively. 143 examination of Figure 21 shows that data for air and mixed gas treated samples were grouped together, inclusion of the third canonical variate in the plot (Figure 22) revealed that the data for these sample treatments were different. The plot confirms the significant difference as indicated by the Mahalanobis results (Table 32). However, the overall fruit quality ratings were not significantly different (Table 8) . Except for carbon dioxide treated samples, data for all other treatments were located in the lower part of the plot by the second canonical variate. The C02 and 02 levels in pouches with fruit treated with air and mixed gas were still within tolerance levels for strawberries (Table 9) . Brecht (1980) and Kader et al. (1989) reported that strawberries can tolerate 02 levels as low as 2% and C02 levels as high as 20%. These levels had not yet been reached in the microatmosphere of the air- and mixed gas-treated samples. The depletion of 02 and increase of C02 have been attributed to the deterioration in fruit quality under CA/MA storage (El-Kazzaz et al. 1983). The 100% C02 treatment which is highly abusive, must account for the rapid quality change of strawberries within 3 days of storage and clear separation by CVA of these treated strawberries. Smith (1963) reported that very high levels of C02 lead to death of cell tissues and thus poor fruit quality. The canonical loadings of the first two canonical variates were plotted in an effort to determine the volatile compounds that might relate to the quality ratings of strawberry samples from the different treatments. Figure 23 shows the projection of the 144 0.4 0.3 -0.2 -0.1 -.= o.o -a c o § -0.1 -0.2 --0.3 -0.3 -0.2 -0.1 0.0 0.1 0.2 Canonical variate 1 (58%) Figure 23. Projection of canonical loadings (correlations) of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 3 days in storage at 1°C. (lower case letters stand for volatile compounds in Table 23). 145 canonical configuration (canonical loadings) spanned by the first two canonical variates (axes) which contributed to 82% discrimination between the samples that had been in storage for 3 days. The centroid (mean) of sample scores of the different treatments are overlaid on the plot. It appears that separation of the sample treatments based on MA packaging with regards to the first canonical variate was by contrasting the volatile compounds pentyl acetate (g), 2-methyl-1-butyl acetate (h), and the unknown (y) for the day 0 (F) and unpackaged (U) strawberries, and the volatile compounds methyl butanoate (b) , methyl hexanoate (j), butyl butanoate (k) , and hexyl butanoate (s) for strawberries packaged with air (A) , mixed gas (M) and carbon dioxide (C) as input gas. Separation based on quality was achieved by the second canonical variate with the discriminating variables being contrasted between ethyl propionate (a), methyl heptanoate (p) and ethyl heptanoate (r) against butyl acetate (d) , ethyl hexanoate (1), 1-methylethyl hexanoate (o) , 3,7-dimethyl-l,6-octadien-3-ol (q) and octyl acetate (u) (Table 22). Figures 24 and 25 show the plots of the first two and first three canonical variates, respectively, of the different treatments after 6 days of storage at 1°C. More groups of the samples were formed and this may be due to different levels of deterioration. The Mahalanobis distance (their probabilities) shows that all the sample centroids were significantly different from each other (Table 32) . The first canonical variate separated the good and the worst samples (carbon dioxide-treated samples). After 6 days in 146 20 10 -0 -10 --20 -30 -20 -10 0 10 20 Canonical variate 1 (62%) Figure 24. Canonical plot of the first two canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 6 days in storage at 1°C. 147 Figure 25. Canonical plot of the first three canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 6 days in storage at 1°C. 148 storage, the samples held in a high carbon dioxide microatmosphere were deemed unacceptable (Table 8) while the other samples had deteriorated to various degrees compared to the samples evaluated at day 0. Except for the carbon dioxide treated samples, all others samples were acceptable with an overall quality rating of 3 or greater (Table 8). Thus the first canonical variate separated the unpackaged as well as air- and mixed gas-treated samples from the carbon dioxide-treated samples based on the extent of their level of deterioration. Overlaying the plot of canonical loadings over the centroid (mean) of sample scores shows the volatile compounds that were important in discriminating between the samples (Figure 26). Separation of good samples from the worst samples was a contrast between pentyl acetate (g) , 2-methyl-l-butyl acetate (h) , 1-methylethyl hexanoate (o) , 3,7-dimethyl-l,6-octadien-3-ol (q) and octyl acetate (u) for the good samples and methyl butanoate (b), methyl haxanoate (j), 3-hexenyl acetate (m) , hexyl butanoate (s) and hexyl hexanoate (w) for the worst samples. Canonical plots of samples after 10 days in storage are shown in Figures 27 and 28. Three distinct groups were formed by the first two canonical variates. Since fruit undergoes natural deterioration during storage, it is understandable that a clear separation and classification by the first canonical variable of samples evaluated at day 0 (F) and the unpackaged samples evaluated after 10 days (U) occurred. The samples treated with the different gases (air, mixed gas and carbon dioxide) were well separated from day 0 samples by the second canonical variate. Although it appears 149 1.0 oo £J CM (D v_ Ctf > o c o c o 0.5 -0.0 -0.5 -0.2 -0.1 0.0 0.1 0.2 Canonical variate 1 (62%) Figure 26. Projection of canonical loadings (correlations) of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) kept in storage for 6 days at 1°C (lower case letters stand for volatile compounds in Table 23). 150 10 5 -0 --5 •10 -15 -15 -10 0 10 Canonical variate 1 (50%) Figure 27. Canonical plot of the first two canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 10 days in storage at 1°C. 151 Figure 28. Canonical plot of the first three canonical variates for strawberries evaluated at day 0 (F) and from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) evaluated after 10 days in storage at 1°C. 152 that the packaged samples did not separate from each other, the Mahalanobis distance probabilities of the centroids are significantly different (Table 32) . The difference in grouping of strawberries stored under MAP and those unpackaged after 10 days of storage seem to indicate different forms of deterioration. The deterioration of unpackaged samples may be attributed to molds since the strawberries were almost entirely covered by fungal mycelia by the tenth day of storage (Sommer et al. , 1973; El-Kazzaz et al. , 1983; Day et al., 1990) . On the other hand, deterioration of MAP strawberries may have been due to anaerobic respiration reactions because of high C02 (greater than 20%) and low 02 (less than 2%) levels (Kader, 1980; Kader et al., 1989; Carlin et al., 1990) . High C02 and low 02 levels were determined in all of the microatmosphere of packaged strawberries after ten days of storage (Table 9) . All of the packaged fruit held for 10 days received low sensory ratings for desirable attributes and high ratings for undesirable attributes (Tables 6, 7, 8) . The overall quality ratings for the MAP packaged fruit were low (close to or less than 3) . Fruit packaged with air, mixed gas and carbon dioxide as input gases may have had similar types and amounts of volatile compounds. The relative amounts of volatile compounds were overlaid on the plot of canonical loadings to elucidate the volatile compounds aiding in discrimination (Figure 29). The day 0 samples (F) were mainly discriminated by 1-methylethyl butanoate (e), methyl heptaonate (p), hexyl hexanoate (w) and the unknown (y), and the 153 0.3 m CM CvJ (D -4-< cd > a c o c o 0.2 -0.1 -0.0 -0.1 --0.2 ^ -0.4 -0.3 -0.2 -0.1 0.0 0.1 0.2 Canonical varlate 1 (50%) 0.3 Figure 29. Projection of canonical loadings (correlations) of volatile data and centroid (mean) sample scores for strawberries evaluated at day 0 and strawberries from different treatments (unpackaged=U; air=A; mixed gas=M; carbon dioxide=C) kept in storage for 10 days at 1°C (lower case letters stand, for volatile compounds in Table 23). 154 other samples by methyl butanoate (b), butyl acetate (d), pentyl acetate (g) , 1-methylethyl-l-butyl acetate (o), 3,7-dimethyl-l,6-octadien-3-ol (q) and ethyl heptanoate (r). Using multiple discriminant/canonical variate analysis, it was possible to follow the changes in quality of strawberries held under different MAP conditions during storage at 1°C. The changes in C02 and 02 levels with storage time may have influenced the volatile profiles of MAP fruit with the consequence of deteriorated samples possessing similar volatile compounds. 4.11 CONCLUSIONS Liquid-liquid extraction, steam distillation extraction and dynamic headspace extraction were evaluated for the removal of volatile compounds from fresh strawberries. Headspace extraction of the volatile compounds by Tenax GC followed by solvent desorption was found to be most appropriate for removal of volatile compounds from strawberries. Most of the fifty volatiles extracted by the dynamic headspace technique onto the adsorbent Tenax GC were separated and identified by gas chromatography/mass spectrometry (GC/MS) as esters. The changes in amounts of volatile compounds in strawberries packaged in pouches flushed with different gases were found to depend on the treatment and storage time. Total relative amounts of volatile compounds and total amount of butanoates from strawberries stored under different MAP conditions were low compared to amounts for unpackaged strawberries. Simple pairwise correlations of volatile compounds and odor attributes indicated 155 that methyl butanoate, butyl butanoate, and hexyl hexanoate were positively correlated with strawberry odor and overall quality but negatively correlated with undesirable attributes. The undesirable attributes (off-odor, fermented odor and musty odor) were positively correlated with 2-methyl-1-butyl acetate, 1-methylethyl hexanoate, 3,7 dimethyl-1,6-octadien-3-ol, ethyl heptanoate, octyl acetate and an unknown. The volatile compounds listed above were negatively correlated with desirable attributes. Multiple regression of 25 selected volatile compounds with the odor attributes accounted for up to 70% of the variation, while stepwise regression selected between 6 and 9 variables with up to 65% of variance being explained. From the results of multiple discriminant/canonical variate analysis, it was possible to follow the changes in quality of strawberry fruit held under different gases during storage at 1°C. The data for 25 selected volatile compounds from untreated and gas-treated samples were subjected to discriminant/canonical variate analysis (CVA). At each storage time, CVA was used to classify the samples according to treatment and/or quality as evaluated by a sensory panel. Sensory data for MAP strawberries in air and mixed gas (3 days of storage), unpackaged fruit (3 days of storage) and fresh strawberries evaluated (day 0) were separated by canonical variate 2 from data for samples that had been held in carbon dioxide (100% C02) . After 10 days in storage, all MAP strawberries were classified in close proximity, with the indication that quality attribute scores of the strawberries were low. This loss 156 in quality can be attributed to elevated C02 and lower 02 levels in the microatmospheres of packaged strawberries. Canonical variate analysis of the data on the volatile compound contents in strawberry samples could be valuable in monitoring quality and supplementing the sensory evaluation of fruit stored under various conditions. Compared to principal component analysis (PCA), canonical variate analysis appeared to provide some clear classification of strawberry samples based on treatment and/or quality of the fruit stored under modified atmosphere conditions. 157 5.0 Part 3. Quality Attributes of Strawberry Cultivars Grown in British Columbia (B.C.) 5.1 INTRODUCTION Under British Columbia (B.C.) growing conditions, selected strawberry cultivars produce high quality fruit with attractive aroma, flavor, color and textural features (Daubeny, 1979). Generally, selection of acceptable strawberries is based on fruit yield, plant growth characteristics and fruit quality (Sistrunk and Moore, 1971) . Sensory attributes are important aspects of fruit quality. Sensory attributes, such as color, texture, odor and the balance between sweetness and sourness have been identified as important determinants of overall quality of strawberry fruit (Luby et al., 1987; Pritts et al. , 1987; Wang and Dale, 1990). Since many sensory attributes can be determinants of overall quality, it is desirable to identify those which are the most important. Regression analyses have been used to identify major attributes which contribute to fruit quality (Pino et al., 1986). Component analysis was considered as a possible statistical procedure for assessing attribute contributions to strawberry quality. Yield component analysis has been used to partition yield components and determine the proportion each measurable component contributes to the total yield (Swartz et al. , 1985; Baumann and Eaton, 1986). This method has not been used to determine differences among cultivars with regard to the relative importance of specific sensory attributes to the overall general quality assessment of the 158 fruit. Chemical factors such as pH, soluble solids, titratable acidity and volatile compounds have been shown to be related to overall quality assessment of fresh and frozen strawberry fruit (Hirvi and Honkanen, 1982; Hirvi, 1983; Guichard and Souty, 1988; Douillard and Guichard, 1990) . Cultivars vary in concentration of specific volatiles commonly found in strawberry fruit such as methyl butanoate, ethyl butanoate, methyl hexanoate and ethyl hexanoate, fcrans-2-hexen-l-ol, trans-2-hexenal and 2,5-dimethyl-4-methoxy-3 (2if) furanone (Schreier, 1980; Douillard and Guichard, 1989). Volatile compounds have been used to classify cultivars into different groups (Douillard and Guichard, 1989; 1990), and are also related to sensory data for strawberry cultivars (Hirvi, 1983) . The objectives of this study were to: a) evaluate sensory attributes of fruit quality and to determine their relative importance in strawberry fruit grown in B.C., and b) to evaluate the flavor volatile compounds of the cultivars for potential classification. 5.2 MATERIALS AND METHODS 5.2.1 Strawberry samples Five strawberry cultivars grown in B.C. were harvested at the ripe stage in 1989 and 1990. The cultivars were 'Rainier', 'Redcrest', 'Selva', 'Sumas' and 'Totem'. 'Mrak' was also included in 1990 for volatile compound analysis. 'Rainier' and 'Selva' are used primarily for fresh market while the others are usually 159 processed. 'Selva' and 'Mrak' are day neutral cultivars which were bred in California while the others are short day cultivars bred in B.C., Washington or Oregon (Pacific Northwest). All the cultivars were grown in hill rows and harvested on three dates within a 10 day period. Fruits from each cultivar were decapped and sorted for uniformity in terms of moderate size, red color and touch-firmness. 5.2.2 Sensory and chemical evaluation Quantitative descriptive analysis (QDA) was used for sensory evaluation (Noble et al. 1984; Guinard and Cliff, 1987; Heymann and Noble, 1987) . All analyses were carried out on the day of harvest. Six judges, aged between 20-30 years (6 females, all members of UBC Food Science Department), with sensory evaluation experience were trained in descriptive evaluation of strawberries. During the training sessions, the judges made suggestions and established descriptive terms to characterize the various strawberry cultivars. Replicated samples of each cultivar consisting of eight berries were evaluated at each date for color, texture, strawberry odor (in mouth), sweetness, sourness and overall fruit quality. Evaluations of the coded berry samples by the judges were made at a round table, under red lighting, with the judges making independent judgements. Color evaluations were made under normal lighting conditions. The judges used a 10 cm unstructured line scale with anchored terms at both ends and indicated the intensity of each attribute by placing a vertical line on the scale. Quantitation of the results was achieved by 160 measuring the distance from zero to the vertical line. Water and unsalted crackers were provided to the judges and used between tasting of samples. The fruit sample of 50-100 grams was blended in a Waring blender (at room temperature) at low speed for 3 min in preparation for determination of soluble solids, pH and titratable acidity. The macerate was centrifuged at 10,000xg for 10 min at 1°C to obtain a supernatant which was filtered thereafter with Whatman No. 4 filter paper. A few drops of the filtrate were placed on an Abbe Mark II Refractometer (Cambridge Instrument, Buffalo, NY) to measure the soluble solids. The pH was measured with a Fisher Accumet pH meter Model 620 (Fisher Scientific Co., Ottawa, ON) . Titratable acidity was measured by titrating diluted filtrate (1:10) with 0. IN NaOH to pH 8.1 and calculated as citric acid (g/lOOg sample). All measurements were made in duplicate. 5.2.3 Volatile compound analysis For each of the six cultivars, volatiles were extracted by purging the headspace gas of enclosed strawberries and trapping the volatile compounds onto a porous polymer - Tenax GC (Dirinck et al. , 1977; Olafsdorttir et al., 1985). Volatile compound analyses for each cultivar were carried out in triplicate. The volatile compound extraction procedure and analysis has been described in the materials and methods section 3.4.3 - 3.4.5. 161 5.2.4 Statistical analyses Data were analysed by analysis of variance of the date means, preliminary analyses having showed no main effects of dates and few interactions. Cultivar means were separated by • Fisher's (protected) lsd (Steel and Torrie, 1980). The contributions of several quality attributes to overall quality were assessed by two-dimensional partitioning (TDP) of the total variation in the overall quality assessment (Eaton et al., 1986). The quality attributes were determined by the judges in the following arbitrary sequence: color, texture, odor, sweetness, sourness and overall quality. Orthogonalization of the attributes was carried out in the same sequence. First, this sequence allowed the measurement of the contribution, R2, of each variable to total variation in overall quality after the contribution of preceding variables had been taken into account. Second, a separate analysis of variance was carried out on each of the orthogonal variates and the results expressed as a further subdivision of the R2 values. Canonical variate analysis (CVA) was applied to the selected 25 volatile compounds to differentiate and classify the six different cultivars grown in B.C. (SAS, 1985; Liardon, et al. 1984; SYSTAT/SYGRAPH, 1989) . Canonical variate analysis derives linear combinations from the independent variables measured and the discriminant functions obtained are used to classify samples to prior defined groups (Dillon and Goldstein, 1984) . 162 5.3 RESULTS AND DISCUSSION 5.3.1 Sensory evaluation of strawberry cultivars. Of the five cultivars, 'Totem' was evaluated by the judges as the deepest in red color and 'Selva' was the least red with the others intermediate in color (Table 33) . The deep red color of 'Totem', rated highest by the judges, makes it a popular and preferred cultivar by the processing industry. 'Redcrest' had the firmest texture whereas 'Ranier' and 'Sumas' had the softest texture. There were no significant differences in the intensity of the strawberry odor among the five cultivars. 'Sumas' cultivar was considered by the sensory panel to be the sweetest while 'Redcrest' was the least sweet (Table 33). Sensory panel results indicated that 'Redcrest' had the highest sourness, while 'Selva' and 'Sumas' were the least sour. Although 'Redcrest' was evaluated by the judges as the most sour, it had significantly higher soluble solids and a more favorable ratio of sugars to titatrable acidity (Hirvi, 1983) than all other cultivars (Table 34). However, 'Redcrest' also had the lowest pH and a high titratable acidity, which may have been responsible for the intense sourness detected by the panelists. 'Selva' and 'Sumas' had the lowest titratable acidity. 'Redcrest' was rated lowest in terms of overall quality perhaps because of its' high level of sourness and limited sweetness. Correlation coefficients among the sensory attributes were very low and several were very highly significant (Table 35). Sweetness was positively correlated with strawberry odor (r=0.50) but Table 33. Means of sensory attributes for strawberry fruit grown in British Columbia in 1989 and 1990. Cultivar Sensory attributes Ranier Redcrest Selva Sumas Totem LSD Color 6.1c 6.5bc 5.2d 6.9b 8.2a 0.7 Texture 4.6d 6. 6a 6.1b 4.6d 5.5c 0.7 Sody 4.7a 4.6a 4.2a 4.4a 4.7a 0.9 Sweet 4. lab 2.6c 4.0b 4.7a 4.2ab 0.9 Sour 5.0b 8.3a 3.8c 4.4c 5.0b 0.8 Overall quality 4.4a 3.1b 4.5a 4.8a 4.6a 0.9 zmeans in columns with different letters are significantly different at the 5% level. Means were seperated by LSD test. ySod=strawberry odor. 164 Table 34. Mean2 soluble solids, pH, titratable acidity and sugar to acid ratio of strawberry cultivars grown in B.C. Cultivar Ranier Redcrest Selva Sumas Totem LSD Soluble solids (%) 7.6c 9.7a 7.8bc 7.7bc 8.4b 0.9 Chemical measurements PH 3.32bc 3.18d 3.49a 3.24cd 3.35bc 0.10 Titratable acidity (g/100g) 1.07a 1.04a 0.92b 0.91b 1.07a 0.12 Ratio of so to luble solids titratable acidity 7.8b 9.1a 8.6ab 8.6ab 7.9ab 1.2 "means within columns with different letters are significantly different at the 5% level. Means separated by LSD test. Table 35. Sensory attributes Color Texture Odor Sweetness Sourness Ovq Correlation coeffients of sensory att strawberry fruit grown in BC in 1989 Correlat: Color Texture 1.00 0.04 0.19***y 0.11* 0.03 0.18*** 1.00 0.02 -0.20*** 0.31*** -0.06 Lon coefficients Sodz Sweet 1.00 0.50*** 1.00 -0.03 -0.35** 0.50*** 0.64*** ributes of and 1990. Sour Ovq 1.00 -0.28*** 1.00 zSod=strawberry odor; Ovq=overall quality. y***^*^* significantly different at the 0.1, 1 repectively. and 165 negatively to sourness (r=-0.35) . Overall quality of the fruit was positively correlated to strawberry odor (r=0.50) and sweetness (r=0.64) but negatively correlated to sourness (r=-28). 5.3.2 Overall quality. The overall quality of strawberry fruit was related to a number of sensory attributes studied (Table 36). All the attributes only accounted for 50% of the variation in overall quality. Odor accounted for 23.9% and sweetness 17.7% of the total variation in overall quality evaluations of the cultivars in the study. Color of the fruit accounted for 4.1% and sourness contributed 2.9% to the total sum of squares. There were significant cultivar effects upon overall quality of the fruit and upon all orthogonal variates except strawberry odor (Table 36). Therefore, differences among the cultivars could mainly be attributed to the differences in these orthogonal components of sensory attributes. Judges were a significant source of variation in all attributes except texture. It is not unusual for judges to be a major source of variation in sensory evaluation of products (Hall and Lingnert, 1984). Lack of agreement among judges has been attributed to inconsistent use of the sensory terms or use of different levels of the rating scale (Heymann and Noble, 1987) . 5.3.3 Strawberry volatile compound analysis. Selected volatile compounds identified in strawberry cultivars Table 36. Two-dimensional partitioning of the total sum of squares for overall quality (%) of five strawberry cultivars grown in B.C. Source df Independent Dependent variables variable Y J/Y R/J/Y C CY CJ/Y Error Total 1 10 12 4 4 40 48 119 Col2 0.5*y 0.7*** 0.1 1.4*** 0.6*** 0.4 0.5 4.1* Tex 0.1* 0.1 0.1** 0.3*** 0.1** 0.2 0.2 1.1 Sod 1.2 14.9*** 0.8 0.2 0.2 3.0 3.7 23.9*** Swt 0.1 8.2*** 1.0* 1.8** 0.4 4.3*** 1.8 17.7*** Sou 0.0 1.3*** 0.2* 0.3** 0.1 0.7*** 0.3 2.9 Res 2.6 11.3** 2.1 15.7*** 0.5 11.2 6.9 50.3 XX -3.7 -6.4 4.1 -18.6 1.0 8.0 15.7 0.0 Ovq 0.8 30.1** 8.2 1.1** 3.0* 27.7* 29.1 100.0 zCol=color; Tex=texture; Sod=strawberry odor/ Swt=sweetness; Sou=sourness; Ovq=overall fruit quality; Res=residual; XX=compensation (product terms); Y=years; J=judges; C=cultivars; R=replicates; /=within; df=degrees of freedom. y***,**,* Significant at the 0.1, 1 and 5% level, respectively. Significance in the rows refers to analysis of variance and in the total rows to regression analysis. 167 grown in B.C. are shown in Table 37. Most of the compounds identified were esters of acetates, butanoates and hexanoates. Similar volatiles have previously been identified in strawberrry fruit (Schreier, 1980; Hirvi, 1983; Douillard and Guichard, 1990; Honkanen and Hirvi, 1990). The relative amounts of each volatile compound varied among the different cultivars with 'Mrak' and 'Selva' containing the highest relative total amounts. The individual volatile compounds in relatively high amounts included methyl and ethyl butanoates, methyl and ethyl hexanoates, 2-hexenyl acetate, and ethyl heptanoate. Six of the compounds were quantified in relatively high amounts (Figure 30). 'Mrak' contained high relative amounts of methyl butanoate. Ethyl butanoate was highest in 'Mrak', 'Selva' and 'Totem'. 'Mrak', 'Selva' and 'Sumas' had considerably higher relative amounts of ethyl hexanoate than 'Sumas' and 'Totem'. All the six cultivars had high relative amounts of 2-hexenyl acetate, but 'Selva' had the highest relative amount. Although the judges' results on strawberry odor revealed non-significant differences among the cultivars, volatile compound data indicates variation in the relative amounts of the volatile compounds. Such differences could be used to explain differences in the overall fruit quality of the cultivars (Dirinck et al. 1981). Canonical variate analysis (CVA) was applied to the 25 volatile compounds to differentiate and classify the six different cultivars grown in B.C. (Dillon and Goldstein, 1984; Heymann and Noble, 1989) . The first four canonical variates (CV) obtained were highly Table 37. Relative amounts2 of selected volatile compounds of six strawberry cultivars grown in B.C. Label Volatile compound Relative amounts of volatiles (xlO 2) Mrak Ranier Redcrest Selva Sumas Totem ay b c d e f g h i J k 1 m n 0 P q r s t u v w X y Ethyl propionate Methyl butanoate Ethyl butanoate Butyl acetate Ethyl 1-methylbutanoate Ethyl 2-methylbutanoate Pentyl acetate 2-Methyl-l-butyl acetate 2-octanone Methyl hexanoate Butyl butanoate Ethyl hexanoate 3-Hexenyl acetate 2-Hexenyl acetate 1-Methylethyl hexanoate Methyl heptanoate 3,7-Dimethyl 1,6-octadien-3-ol Ethyl heptanoate Hexyl butanoate Ethyl octanoate Octyl acetate sec-Octyl acetate Hexyl hexanoate Octyl propionate Unknown Total 4.0 36.6 118.7 8.8 24.2 27.3 8.4 4.3 2.3 41.3 6.5 158.4 4.4 100.0 3.6 0.6 7.1 14.1 4.9 2.6 3.7 12.7 0.9 2.1 2.3 601.9 3.6 13.0 28.2 1.5 2.4 4.8 6.9 3.6 3.2 45.6 0.2 75.9 5.4 61.0 6.0 1.0 10.1 21.2 1.3 1.1 1.1 3.8 0.2 0.3 1.6 306.8 4.4 14.9 47.1 3.3 3.4 1.1 6.1 3.6 4.0 12.2 0.8 27.6 7.4 80.0 9.9 0.6 4.6 17.3 2.2 2.3 1.0 7.4 1.1 0.7 2.6 269.6 3.6 9.7 84.4 14.6 9.4 7.7 9.5 6.0 2.4 30.1 4.3 199.5 9.5 150.9 2.5 0.6 10.3 15.7 3.0 2.7 6.0 21.9 1.6 1.8 3.0 613.4 7.8 2.6 33.9 1.2 5.6 0.7 6.9 2.0 3.3 24.9 0.7 186.6 4.6 76.9 5.6 0.7 2.1 9.8 2.4 3.8 0.6 7.4 2.4 0.6 5.1 399.6 4.3 18.4 88.9 4.7 1.8 6.3 9.9 2.7 4.0 6.0 1.2 44.3 5.4 84.9 7.4 0.4 10.5 13.5 6.9 2.9 0.7 3.0 0.5 0.7 2.8 334.7 Calculated as the ratio between each peak to that of the internal standard. yLabel stands for identified volatile compound (used in Fig 32) . CO w -J < -J O > Uu 0 CO \-z D o < Hi > < _J LU DC 2.10 1.68 -1.26 -0.84 0.42 0.00 Ethyl propionate Ethyl butanoate • Methyl hexanoate Ethyl hexanoate 2-hexenyl aoetate Ethyl heptanaote MRA RAN RED SEL SUM TOT CULTIVARS Figure 30. Relative amounts of some volatiles in six cultivars grown in B.C. (Mra=Mrak, Ran=Ranier, Red=Redcrest, Sel=Selva, Sum=Sumas, Tot=Totem). IX) 170 significant and explained 97% of the variance, 85% of which was explained by the first two variates (75% and 10% by the first and second CV, respectively). The first canonical variate separated and classified the cultivars into two main groups (Figure 31). One group contained the cultivars 'Mrak' and 'Selva', both of which originated from the breeding program of the University of California, Davis. The second group contained the cultivars 'Rainier', 'Redcrest', 'Sumas' and 'Totem', all of which are Pacific Northwest cultivars. A plot of the canonical loadings of the flavor volatile compounds on the two variates (Figure 32) showed that the volatile compounds that correlated well with the first canonical variate and aided in separation of cultivars were a contrast of 2-octanone and methyl hexanoate against butyl acetate, ethyl 1-methylbutanoate, 2-methyl-l-butyl acetate, butyl butanoate, 2-hexenyl acetate, octyl acetate, sec-octyl acetate and octyl propionate. The cultivars from the California breeding program were dominated by the latter group of volatile compounds. Headspace flavor volatile evaluation and multivariate statistical analysis such as CVA could aid breeders in the selection of new cultivars that have desirable aroma during the varietal selection program. The simple headspace procedure used in this reasearch has the advatange of permiting determination of volatile compounds from any sample size (Hirvi and Honkanen, 1982). 5.4 CONCLUSIONS Cultivars grown in British Columbia differred significantly in 171 10 0 f--5 10 -15 -10 -5 0 10 Canonical variate 1 (75%) Figure 31. Canonical plot of six strawberry cultivars grown in B.C. based on 25 selected volatile compounds. Letters stand for each cultivar: M=Mrak, R=Ranier, X=Redcrest, S=Selva, U=Sumas, T=Totem. 172 20 10 -0 •10 --20 -30 t -40 -30 -20 10 0 10 Canonical varlate 1 (75%) Figure 32. Projection of canonical loadings (correlations) of volatile data and centroid scores for strawberry cultivars grown in B.C. ((M=Mrak, R=Ranier, X=Redcrest/ S=Selva, T=Totem; lower case letters stand for volatile compounds listed in Table 39). 173 all sensory attributes except strawberry odor. 'Redcrest' was lowest in overall fruit quality presumably, due to intense sourness as related to low pH and high titratable acidity. Two-dimensional partitioning (TDP), a statistical procedure originally used in yield component analysis, showed that odor and sweetness were major contributors to total variation of overall fruit quality. Cultivars, judges and the cultivar by judge interaction also contributed significantly to total variation. Although the judges did not detect significant differences in strawberry odor among cultivars, data showed that the cultivars differed in relative total volatile compounds with 'Mrak' and 'Selva' containing the highest amounts. The cultivars were classified into different groups with CVA. 174 6.0 GENERAL SUMMARY OF THESIS RESULTS Strawberries stored at 1°C for 10 days under modified atmosphere package conditions in high barrier film pouches flushed with either carbon dioxide (100 C02), mixed gas (11% C02 + 11% 02 + 78% N2) , or air were used to study changes in sensory attributes, chemical properties and gas chromatographic data as indicators of spoilage. The data collected was applied to multivariate statistical techniques to analyze the multidimensional set of data. From this study: a) nearly all sensory attributes studied significantly differed among the various treatments over storage time. b) principal component analysis (PCA) of sensory attributes indicated the changes among the various treatments over storage time were a contrast of desirable and undesirable attributes. c) packaged strawberries treated with air retained their desirable attributes for longer storage times than those treated with mixed gas or carbon dioxide. d) most volatile compounds extracted from strawberry fruit by dynamic headspace and identified by gas chromatography/mass spectrometry (GC/MS) were esters. e) some volatile compounds such as methyl butanoate, 1-methylethyl hexanaote, 3,7 dimethyl-1,6-octadien-3-ol and ethyl heptanoate correlated with odor attributes. Up to 70% of variation was accounted for between odor attributes and the 25 selected volatile compounds. f) based on 25 selected volatile compounds, canonical variate 175 analysis (CVA) separated and classified the strawberries at each storage time into different treatments and/or quality levels. Therefore, CVA of chromatographic data together with sensory data could be used to monitor quality changes in fruit stored under MAP. g) increases in C02 levels and decreases in 02 levels initiated development of undesirable attributes. Initial gas treatment with high 02 of 21% (no C02) may be valuable in extending shelf life of fruit stored under MAP. However, fungal growth may limit the storage period of the strawberries. In the last part of this research, strawberry cultivars from two breeding regions were compared for sensory attributes, chemical properties and gas chromatographic data. 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