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

cis-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\*\

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• 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

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*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

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EE H

t£ H K K

\B B I'm J K

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F F ^ n « G G d Jj

F F f

G G J

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-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.

From this study:

h) 'Redcrest' was rated lowest in overall fruit quality, probably

due to the cultivars' intense sourness, low pH and high titratable

acidity.

i) Two-dimensional partitioning (TDP) of sensory attributes showed

that the overall quality of strawberries was primarily dependent on

odor and sweetness level.

j) The cultivars differed in relative amounts of volatile

compounds, and canonical variate analysis classified the cultivars

according to the region in which they were bred.

FUTURE RESEARCH

a) Various polymeric films with varying gas permeability

characteristics, and different gas mixtures should be investigated

176

to increase the shelf life of strawberries under MAP.

b) To fully understand the volatile compounds causing the off-

odors, the mechanism of volatile synthesis in strawberry fruit

stored MAP should be investigated.

177

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