Control of Patulin in Fruit and Vegetable Beverage

Control of Patulin in Fruit and Vegetable Beverage

Processing using High Hydrostatic Pressure

By

Heying Hao

A Thesis

presented to

The University of Guelph

In partial fulfillment of requirements

for the degree of

Master of Science

in

Food Science

Guelph, Ontario, Canada

©Heying Hao, May, 2015

ABSTRACT

CONTROL OF PATULIN IN FRUIT AND VEGETABLE BEVERAGE PROCESSING USING HIGH HYDROSTATIC PRESSURE

Heying Hao Advisors: University of Guelph, 2015 Dr. Keith Warriner & Dr. Ting Zhou Patulin is recognized as hazard in apple based beverages. The thesis describes

research undertaken to control mycotoxins in apple based beverages. Specifically, an

on-site electrochemical biosensor was developed based on the reaction between

patulin and the conducting polymer precursor, pyrrole. The sensor was optimized with

respect to assay conditions and electrochemical signal processing method. By

studying the degradation of patulin in different apple based beverages it was found

that kinetics were dependent on the applied pressure, processing time and juice

constituents. From the results obtained it is proposed that the mechanism of patulin

degradation is through a direct and indirect oxidative attack on the lactone ring. The

byproducts of patulin degradation were not found to be toxic using a Drosophila

melanogaster toxicology model. The research represents advances in patulin detection

and degradation that can be applied in the apple beverage industry to decrease the risk

presented by the toxic mycotoxin.

III

Acknowledgements

I would like to express my sincere gratitude to my advisors, Dr. Keith Warriner and

Dr. Ting Zhou for their invaluable mentorship and guidance. I am so grateful to have

done my graduate studies under their supervision. I appreciate their insight, patience,

continuous encouragements and persistent support during the entire research and

writing process. My gratitude goes to my advisory committee members, Dr. Tatiana

Koutchma and Dr. Alexandra Smith for their kind help, constructive suggestions and

great support throughout my career as a food science student.

It's been a privilege to study and work at both the University of Guelph and Guelph

Food Research Centre-Argiculture and Agri-Food Canada (GFRC-AAFC). This

research could not be carried out without the assistance of all the staff and researchers

in the Department of Food Science and Guelph Food Research Centre. Many thanks

to Drs Rong Cao and Ronghua Liu for their friendly help and letting me use the

vacuum distillation in their lab. I also want to express my gratitude to Dr. Steve Cui

and Cathy Wang for letting me use the nitrogen evaporation in their lab and Philip

Strange with the help for the fruit fly work. Many thanks to Dr. Jacek Lipkowski in

the Department of Chemistry with the help for the electrochemistry work. And many

thanks to Dr. O. Brian Allen and Dr. Allan Willms in the Department of Mathematics

and Statistics for the help with statistical analysis and modelling development.

I would also like to acknowledge Dr. Suqin Shao, Dr. Xiu-Zhen Li, Dr. Yan Zhu, Dr.

IV

Azadeh Namvar, Fan Wu, Dr. Valquiria Ros Polski and all the other past and current

students and researchers for sharing their knowledge on patulin or expertise in their

field and making the lab an enjoyable place to work. I want to express my special

thanks to all my friends at University of Guelph for their kindness, support and

friendship. Moreover, I would like to express my great gratitude to my parents and

family for their patience, love, encouragement and understanding.

Last but not least, financial support provided by China Scholarship Council (CSC) program

and NSERC is also deeply appreciated.

V

TableofContentsChapter One .......................................................................................................... 1

Literature Review ................................................................................................... 1

1.1 Introduction .................................................................................................. 2

1.2 Control of Patulin in Apple Based Beverage Production ......................................... 4

1.3 Mycotoxin Producing Molds ............................................................................ 4

1.3.1 Economic impact of mycotoxins .................................................................. 8

1.3.2 Effect of mycotoxins on humans and animals ................................................. 9

1.3.3 Effects of patulin on animal and human health ............................................. 10

1.3.4 Synthesis of patulin by producing molds ..................................................... 11

1.3.5 Reactivity and stability of patulin .............................................................. 13

1.4 Analytical Methods for Quantification of Patulin ................................................ 18

1.5 Square Wave Voltammetry ............................................................................ 23

1.6 High Hydrostatic Pressure Processing .............................................................. 28

1.6.1 High hydrostatic pressure technique ........................................................... 28

1.6.2 Mode of microbial inactivation by high hydrostatic pressure ........................... 32

1.6.3 Variation in microbial inactivation by high hydrostatic pressure ...................... 34

1.6.4 Inactivation kinetics of different microbes (pressure inactivation of bacteria and

fungi) .......................................................................................................... 36

1.6.5 Inactivation of mycotoxins by high hydrostatic pressure ................................. 38

1.6.6 Chemical reactions under high hydrostatic pressure ....................................... 42

1.7 Fruit and Vegetable Juice Components ............................................................. 47

VI

1.7.1 Ascorbic acid content in fruits and vegetables .............................................. 47

1.7.2 Thiol group content in fruits and vegetables ................................................. 50

1.7.3 Nitrite content in fruits and vegetables ........................................................ 52

1.8 Fruit Flies (Drosophila melanogaster) and Toxicity Assay ................................... 53

Research Hypothesis and Objectives ..................................................................... 55

Research Hypothesis ....................................................................................... 55

Research Objectives ....................................................................................... 55

Chapter Two ........................................................................................................ 57

Electrochemical Based Sensor for Quantification of Patulin in Beverages ........................ 57

Abstract ........................................................................................................... 58

2.1 Introduction ................................................................................................ 58

2. 2 Materials and Methods ................................................................................. 60

2.2.1 Reagents ............................................................................................... 60

2.2.2 Screen printed electrode preparation and electrochemistry .............................. 60

2.2.3 Patulin assay .......................................................................................... 61

2.2.4 Extraction of patulin................................................................................ 61

2.2.5 HPLC-UV analysis of patulin ................................................................... 62

2.2.6 The Ellman assay of thiols in juice ............................................................. 62

2.2.7 Statistical analysis .................................................................................. 63

2.3 Results and Discussion .................................................................................. 63

2.3.1 The validation of electrode cards ............................................................... 63

VII

2.3.2 Optimization of patulin: pyrrole adduct formation ......................................... 64

2.3.3 Effect of supporting electrolyte pH on sensor response .................................. 64

2.3.4 Effect of the potential .............................................................................. 67

2.3.5 Effect of the S.W. frequency ..................................................................... 69

2.3.6 Dose response curve of the sensor towards patulin ........................................ 73

2.4. Conclusion ................................................................................................. 79

Chapter Three ...................................................................................................... 80

High Hydrostatic Pressure Assisted Degradation of Patulin in Fruit and Vegetable Beverages

......................................................................................................................... 80

Abstract ........................................................................................................... 81

3.1 Introduction ................................................................................................ 81

3.2 Materials and Methods .................................................................................. 83

3.2.1 Reagents ............................................................................................... 83

3.2.2 Model fruit and vegetable beverage preparation ............................................ 84

3.2.3 Juice characterization .............................................................................. 84

3.2.4 HHP processing treatment ........................................................................ 86

3.2.5 Extraction of patulin................................................................................ 89

3.2.6 HPLC-UV analysis of patulin ................................................................... 90

3.2.7 Patulin degradation kinetic in sulfhydryl protein, hydrogen peroxide or nitrite

buffer solution ............................................................................................... 90

3.2.8 Data analysis ......................................................................................... 91

3.3 Results ....................................................................................................... 92

VIII

3.3.1 Juice characterization by the determination of ascorbic acid, SH group and nitrite

content ......................................................................................................... 92

3.3.2 High hydrostatic pressure assisted degradation of patulin in different juices ....... 92

3.3.3 Correlation of HHP assisted patulin degradation with juice constituents ............ 98

3.3.4 Interactions between patulin and thiol proteins, ascorbic acid, hydrogen peroxide or

nitrite during HHP treatment .......................................................................... 101

3.3.5 Modelling the HHP assisted degradation of patulin in different juice matrices .. 103

3.4 Discussion ................................................................................................ 118

3.5 Conclusions .............................................................................................. 122

Chapter Four ...................................................................................................... 124

Potential Toxic Effects of Patulin Degradation Products Assessed using Fruit Fly (Drosophila

melanogaster) Toxicology Model .......................................................................... 124

Abstract ......................................................................................................... 125

4.1 Introduction .............................................................................................. 126

4.2 Materials and Methods ................................................................................ 128

4.2.1 Reagents ............................................................................................. 128

4.2.2. Sample preparation .............................................................................. 128

4.2.3 Apple juice agar and Sokolowski lab fly food ............................................ 129

4.2.4 HHP processing treatment and sample preparation for toxicity assay using D.

melanogaster model system ........................................................................... 130

4.2.5 Collection and inoculation of fruit fly eggs ................................................ 133

4.2.6 Data analysis ....................................................................................... 134

IX

4.3 Results ..................................................................................................... 135

4.3.1 Patulin sensitivity evaluation in D. melanogaster model system ..................... 135

4.3.2 HHP-detoxification evaluation in D. melanogaster model system .................. 141

4.4 Discussion ................................................................................................ 156

4.5 Conclusions .............................................................................................. 157

Chapter Five ...................................................................................................... 158

Conclusions and Recommendations........................................................................ 158

5.1 Conclusions .............................................................................................. 159

5.2 Recommendations ...................................................................................... 160

References ........................................................................................................ 162

X

List of Tables

Table 1. 1- Patulin contamination incidences in several countries ..................................... 4

Table 1. 2- Specific mycotoxins of significance in managing food safety produced by

different genera of fungi ........................................................................................... 7

Table 1. 3- D and Z values for the high hydrostatic pressure inactivation of different microbes

......................................................................................................................... 37

Table 1. 4- Effect of HHP processing on enzymes in different fruit and vegetable matrices . 43

Table 1. 5- HHP processing on bioactive components in fruit and vegetable juices ............ 46

Table 1. 6- Natural ascorbic acid (AA) content in cloudy apple juices from different apple

varieties in three years ........................................................................................... 48

Table 1. 7- Summary of patulin degradation in apple juice in previous studies. ................. 49

Table 1. 8-Summary of the significant thiols present in various fruits and vegetables ......... 51

Table 1. 9- Nitrate content in the selected vegetables during different seasons .................. 53

Table 2. 1- Determination of patulin concentration using HPLC and the developed

electrochemical sensor ........................................................................................... 76

Table 2. 2- The current (μA) of the decrease in oxidation peak relative to controls (1000 ppb

pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) using

square wave voltammetry ....................................................................................... 77

Table 3. 1- Models selected for patulin reduction kinetic screening ................................. 91

Table 3. 2- pH, Brix, ascorbic acid, sulfhydryl group and nitrite content in the juices before

HHP treatment: AS (Apple and spinach juice), PAM (Apple, pineapple and mint juice), CAB

(Apple, carrot, beet, lemon and ginger juice), GJ (Apple, romaine, celery, cucumber, spinach,

kale, parsley and lemon juice) ................................................................................. 92

XI

Table 3. 3- The degradation rates of the four kinds of juices at different pressures ............. 96

Table 3. 4-Performance of patulin degradation (ppb) in four kinds of beverages at 600 MPa

after preheat treatment (50 °C for 180 s). AS (Apple and spinach juice), CAB (Apple, carrot,

beet, lemon and ginger juice), PAM (Apple, pineapple and mint juice), GJ (Apple, romaine,

celery, cucumber, spinach, kale, parsley and lemon juice). The juices were spiked with 200

ppb of patulin ....................................................................................................... 97

Table 3. 5- Weibull model parameters for patulin decrease following a range of pressure-pH-

BSA concentration (mg/ml) combinations in the BSA model systems under HHP processing

....................................................................................................................... 105

Table 3. 6- Variance analysis of regression models for k the degradation kinetic (ANOVA for

Response Surface 2FI (two-factor interaction) Model) in the BSA model solution system

under HHP processing ......................................................................................... 105

Table 3. 7- Variance analysis of regression models of a the shape constant (ANOVA for

Response Surface Quadratic Model) in the BSA model solution system under HHP processing

....................................................................................................................... 107


hydrogen peroxide concentration combinations in the hydrogen peroxide model systems


Table 3. 9- Variance analysis of regression models for k the degradation kinetic (ANOVA for

Response Surface 2FI (two-factor interaction) Model) in the hydrogen peroxide model

solution system under HHP processing ................................................................... 110


Response Surface Quadratic Model) in the hydrogen peroxide model solution system under

HHP processing .................................................................................................. 112

XII


nitrite concentration (mg/L) combinations in the nitrite model systems under HHP processing

....................................................................................................................... 115

Table 3. 12- Variance analysis of regression models for k the degradation kinetic (ANOVA

for Response Surface Quadratic Model) in the nitrite model solution system under HHP

processing ......................................................................................................... 115


Response Surface Quadratic Model) in the nitrite model solution system under HHP

processing ......................................................................................................... 117

Table 4. 1-Hatching rate of larva, development rate of pupa and development rate of adult fly

when patulin concentration ranged from 0 to 500 ppm (0, 0.5, 1, 20, 50, 100, 200 and 500

ppm) in the lab fly food in the 12-well plate ............................................................. 136

Table 4. 2- Length of larva, pupa and adult fly at day 6, 10 and 15 (mm) in patulin containing

lab fly food ........................................................................................................ 137

Table 4. 3- Patulin concentration in the five sets of samples (HHP-B, HHP-C, PAT-C, HHP-T

and PAT-S samples) in the BSA modified juice for D. melanogaster model system ......... 141


and PAT-S samples) in the H2O2 modified juice for D. melanogaster model system ........ 142


and PAT-S samples) in the nitrite modified juice for D. melanogaster model system ....... 142

Table 4. 6- Hatching rate and development rate of pupa and development rate of adult fly at

Day 6, 10 and 15 for the patulin toxicity assay for BSA added apple and spinach juice ..... 147

Table 4. 7-Hatching rate and development rate of pupa and development rate of adult fly at

Day 6, 10 and 15 for the patulin toxicity assay for hydrogen peroxide added apple and spinach

juice ................................................................................................................. 151

XIII

Table 4. 8- Hatching rate and development rate of pupa and development rate of adult fly at

Day 6, 10 and 15 for the patulin toxicity assay for nitrite added apple and spinach juice ... 155

XIV

List of Figures

Figure 1. 1- The structure of patulin and photograph of spoiled apple fruit supporting growth

of Penicillium ........................................................................................................ 3

Figure 1. 2- Examples of the main mycotoxins encountered in foods and feed .................... 8

Figure 1. 3- Schematic diagram of patulin biosynthetic pathways ................................... 12

Figure 1. 4- The formation of PAT/CYS P1 adduct when patulin reacts with free cysteine .. 14

Figure 1. 5- Mechanism of metal-catalysed oxidation of ascorbic acid ............................. 15

Figure 1. 6- Reaction of patulin with glutathione ......................................................... 16

Figure 1. 7- Stability of patulin in buffered solutions poised at different pH values ............ 17

Figure 1. 8- The mode of action of patulin reacting with pyrrole .................................... 22

Figure 1. 9- Typical cyclic voltammogram of the peak catholic and anodic current

respectively for a reversible reaction ......................................................................... 25

Figure 1. 10- EC epsilon-modern equipment for electrochemical research ........................ 25

Figure 1. 11- Potential wave form for cyclic voltammetry ............................................. 26

Figure 1. 12- Change parameters dialog box for cyclic voltammetry ............................... 26

Figure 1. 13- Potential wave form for square wave voltammetry .................................... 27

Figure 1. 14- Change parameters dialog box for square wave voltammetry ....................... 27

Figure 1. 15- Schematic graph of high hydrostatic pressure equipment ............................ 30

Figure 1. 16- Application of HHP in different food sectors (Hyperbaric, 2010) ................. 31

Figure 1. 17- Pressure induced damage to microbes ..................................................... 34

Figure 1. 18- Relationship between temperature and pressure on the requirements to achieve a

5 log cfu reduction of model microbes ...................................................................... 38

Figure 1. 19- HHP effects on citrinin degradation at 250 MPa/35± 1 °C for 5 minutes ........ 39

Figure 1. 20- Patulin reduction in apple juice and apple concentrate at 20 °C .................... 41

Figure 1. 21- Vitamin C loss by high hydrostatic pressure processing .............................. 44

XV

Figure 1. 22- The life cycle of fruit flies (Drosophila melanogaster) ............................... 55

Figure 2. 1- Cyclic voltammetry of screen printed electrode cards in 2 mM potassium

ferricyanide with 1 M potassium nitrate in distilled water at the scan rate of 100 mV/s after

sonication treatment .............................................................................................. 63

Figure 2. 2- The effect of incubation time on the current of the decrease in oxidation peak to

control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin

mixture) .............................................................................................................. 65

Figure 2. 3- The effect of pH on the position (A) and current (B) of the decrease in oxidation

peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb

patulin mixture) .................................................................................................... 66

Figure 2. 4- The effect of pH on the position and the current of the decrease in oxidation peak

to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb

patulin mixture) .................................................................................................... 67

Figure 2. 5- The effect of the potential applied on the position (A) and current (B) of the

decrease in oxidation peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000

ppb pyrrole and 0 ppb patulin mixture) ..................................................................... 69

Figure 2. 6-The effect of the S.W. frequency on the current of the decrease in oxidation peak

relative to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0

ppb patulin mixture) .............................................................................................. 71

Figure 2. 7-The effect of the S.W. frequency on the current of the decrease in oxidation peak

relative to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0

ppb patulin mixture) .............................................................................................. 72

Figure 2. 8- Correlation relationship between patulin concentration and the current of the

decrease in oxidation peak relative to control (1000 ppb pyrrole and 0 ppb patulin mixture)

using square wave voltammetry ............................................................................... 75

XVI

Figure 2. 9- The current of the decrease in oxidation peak relative to control (1000 ppb

pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) ......... 78

Figure 3. 1- The schematic diagram of the interaction between the aforementioned

components and patulin ......................................................................................... 83

Figure 3. 2- High Pressure Processing unit, 51 L, Hyperbaric ........................................ 86

Figure 3. 3- Experimental design used for the identification of the presence of interaction

between patulin and thiol protein, ascorbic acid, hydrogen peroxide or nitrite during High

Pressure Processing ............................................................................................... 88

Figure 3. 4- Experimental design used for analysing patulin degradation kinetic in sulfhydryl

protein, oxidizing agent or nitrite model solution (acetate buffer model solution at pH 3.5, 4

and 4.5) after the pressure of 400 MPa, 500 MPa and 600 MPa for the treatment time (0 to

300 s, 30 s as the interval) ...................................................................................... 89

Figure 3. 5- Patulin degradation in AS juice (A: Apple and spinach juice), PAM juice (B:

Apple, pineapple and mint juice), CAB juice (C: Apple, carrot, beet, lemon and ginger juice)

and GJ juice (D: Apple, romaine, celery, cucumber, spinach, kale, parsley and lemon juice).

......................................................................................................................... 95

Figure 3. 6- The correlation between patulin decrease in the AS juice and the decrease of

ascorbic acid content after HHP treatment at 600 MPa (0, 60, 180 and 300 s) ................... 99

Figure 3. 7- The correlation between patulin decrease in the AS juice and the decrease of thiol

content after HHP treatment at 600 MPa (0, 60, 180 and 300 s) ..................................... 99

Figure 3. 8- The correlation between patulin decrease in the AS juice and the decrease of

nitrite content after HHP treatment at 600 MPa (0, 60, 180 and 300 s) with 50 °C for 180 s

preheat treatment ................................................................................................ 100

Figure 3. 9- Determination of patulin decrease and thiol group decrease after HHP processing

....................................................................................................................... 102

XVII

Figure 3. 10- Relationship between patulin degradation in apple juice and hydrogen peroxide

content under HHP treatment at 600 MPa for 300 s ................................................... 102

Figure 3. 11- Determination of patulin amount and nitrite content after HHP processing ... 103

Figure 3. 12- Response surface contour plots showing effects of pressure and pH on the

patulin degradation rate constant k in the BSA model solution system under HHP processing

....................................................................................................................... 106

Figure 3. 13- Response surface contour plots showing effects of pressure and BSA

concentration on the patulin degradation rate constant k in the BSA model solution system


Figure 3. 14- Response surface contour plots showing effects of pH and BSA concentration

on the patulin degradation rate constant k in the BSA model solution system under HHP

processing ......................................................................................................... 107


patulin degradation rate constant k in the hydrogen peroxide model solution system under

HHP processing .................................................................................................. 111

Figure 3. 16- Response surface contour plots showing effects of pressure and hydrogen

peroxide concentration on the patulin degradation rate constant k in the hydrogen peroxide

model solution system under HHP processing .......................................................... 111

Figure 3. 17- Response surface contour plots showing effects of pH and hydrogen peroxide

concentration on the patulin degradation rate constant k in the hydrogen peroxide model

solution system under HHP processing ................................................................... 112


patulin degradation rate constant k in the nitrite model solution system under HHP processing

....................................................................................................................... 116

XVIII

Figure 3. 19- Response surface contour plots showing effects of pressure and nitrite

concentration on the patulin degradation rate constant k in the nitrite model solution system


Figure 3. 20- Response surface contour plots showing effects of pH and nitrite concentration

on the patulin degradation rate constant k in the nitrite model solution system under HHP

processing ......................................................................................................... 117

Figure 4. 1- The HHP-detoxification assay using D. melanogaster model system for the

hydrogen peroxide added juice .............................................................................. 132

Figure 4. 2- The preparation for the HHP-T samples and HHP-C samples for the nitrite added

juice ................................................................................................................. 133

Figure 4. 3- Sokolowski lab fly food in 12-well plates ................................................ 133

Figure 4. 4- Pictures of larva at day 6 ...................................................................... 138

Figure 4. 5- Pictures of pupa at day 10 .................................................................... 139

Figure 4. 6- Pictures of adult fly at day 15 ............................................................... 140

Figure 4. 7- The comparison of hatching rates of fly eggs for the toxicity assay for BSA added

apple and spinach juice ........................................................................................ 145

Figure 4. 8- The comparison of pupation rates for the toxicity assay for BSA added apple and

spinach juice ...................................................................................................... 145

Figure 4. 9- The comparison of the development rates of adult flies for the toxicity assay for

BSA added apple and spinach juice ........................................................................ 146

Figure 4. 10- The comparison of hatching rates for the toxicity assay for hydrogen peroxide

added apple and spinach juice ............................................................................... 149

Figure 4. 11- The comparison of pupation rates for the toxicity assay for hydrogen peroxide

added apple and spinach juice ............................................................................... 149

XIX

Figure 4. 12- The comparison of the development rates of adult fly for the toxicity assay for

hydrogen peroxide added apple and spinach juice ..................................................... 150

Figure 4. 13- The comparison of hatching rates for the toxicity assay for nitrite added apple

and spinach juice ................................................................................................ 153

Figure 4. 14- The comparison of pupation rates for the toxicity assay for nitrite added apple

and spinach juice ................................................................................................ 154

Figure 4. 15- The comparison of the development rates of adult flies for the toxicity assay for

nitrite added apple and spinach juice....................................................................... 154

1

Chapter One Literature Review

2

1.1 Introduction

Patulin [4-hydroxy-4-H-furo(3,2-c)pyran-2(6H)-one] is a secondary metabolite

produced by moulds within the genera of Penicillium, Byssochylamys and Aspergillus

(Figure 1.1). In vivo animal studies have demonstrated that patulin can induce acute

symptoms such as ulceration and inflammation of the gastrointestinal tract (McKinley,

Carlton, & Boon, 1982) but is more commonly linked to chronic conditions such as

cancer (Mayer & Legator, 1969; Pfeiffer, Diwald, & Metzler, 2005; Pfeiffer, Gross, &

Metzler, 1998; Wichmann, Herbarth, & Lehmann, 2002). The hemiacetal functional

group, the C-6 and C-2 of the unsaturated heterocyclic lactone of patulin has been

proposed to react with sulfhydryl groups of proteins, enzymes and other components

of cells thereby eliciting toxicity (Fliege & Metzler, 2000b; Mahfoud, Maresca,

Garmy, & Fantini, 2002; Riley & Showker, 1991). Patulin also reacts with amine

groups, hydroxyl radicals and stable radicals such as diphenyl-1-picrylhydrazyl

(DPPH) (Drusch, Kopka, & Kaeding, 2007; Fliege & Metzler, 1999, 2000a; Lee &

Roschenthaler, 1986). Due to health concerns, the regulatory limit imposed by the

FDA for patulin in fruit and vegetable beverages is 50 ppb and 25 ppb in Europe (EC,

2006a; WHO, 1995).

3

Figure 1. 1- The structure of patulin and photograph of spoiled apple fruit supporting growth of Penicillium Source: Puel, Galtier, and Oswald (2010) The occurrence of patulin in fruits or vegetables is dependent on the growth of

mycotoxin producing mold. It follows that the highest patulin levels are encountered

in damaged fruit that has been held under warm and humid conditions (Baert,

Devlieghere, Flyps, Oosterlinck, Ahmed, Rajkovic, et al., 2007; Jackson, Beacham-

Bowden, Keller, Adhikari, Taylor, Chirtel, et al., 2003; Sydenham, Vismer, Marasas,

Brown, Schlechter, & Rheeder, 1997). It should be noted that although spoiled fruits

are commonly associated with patulin contamination, hazardous levels can also be

encountered in visibly sound fruit with no obvious spoilage symptoms (Jackson,

2003). Within Canada and US, the prevalence of patulin in apple juice is relatively

low compared to China and South Africa although it remains a concern (Table 1.1).

4

Table 1. 1- Patulin contamination incidences in several countries Country reported Patulin contamination level

in apple-based juice Reference

Canada 12 % > 50 ppb in 2012 OMAFRA website US 11.3 %>50 ppb exceptionally

up to 2700 ppb Harris et al. 2009

South Africa Up to 1650 ppb Shephard et al. 2010 China 16 % > 50 ppb Yuan et al. 2010 Tunisia 18 % > 50 ppb Zaied et.al. 2013

1.2 Control of Patulin in Apple Based Beverage Production

The most effective approach to control patulin in apple-based beverages is to prevent

contamination by producing moulds. Yet, given the open nature of fruit production

along with the economic incentives for using fallen fruit, the total prevention of

patulin in juice can be challenging (Drusch & Ragab, 2003; Harris, Bobe, & Bourquin,

2009; Iha & Sabino, 2008). In the following sections the range of control measures

that can be used to minimize or degrade patulin in vegetable and fruit beverages will

be described.

1.3 Mycotoxin Producing Molds

Moulds are a taxonomically diverse number of microorganism species with a diversity

only second to that insects (DeLong & Pace, 2001; Gonzalez Pereyra, Chiacchiera,

Rosa, Sager, Dalcero, & Cavaglieri, 2011; Yiannikouris & Jouany, 2002). One of the

underlying features of moulds is related to metabolic diversity and ability to inhabit

niches where bacterial growth is restricted such as in acidic fruit (Araujo, Marcon,

Maccheroni, van Elsas, van Vuurde, & Azevedo, 2002). The metabolic diversity of

moulds is underlined by the synthesis of complex structures such as mycotoxins. The

specific role of mycotoxins in nature is unclear although likely represents a means for

5

moulds to protect their niche against invasion from other microbes such as bacteria

given that many mycotoxins have bactericidal activity.

Mycotoxins are an example of a secondary metabolite which is synthesised in the

stationary phase of growth although is catabolically repressed in the presence of

glucose (Filtenborg, Frisvad, & Thrane, 1996; Hitokoto, Morozumi, Wauke, Sakai, &

Kurata, 1980; Logrieco, Bottalico, Mule, Moretti, & Perrone, 2003). The health risks

of mycotoxins were observed in early civilizations by the detrimental effects on

domestic animals and humans consuming contaminated grains or fruit spoiled by

producing moulds (Diekman & Green, 1992; Minervini, Giannoccaro, Cavallini, &

Visconti, 2005; Yiannikouris & Jouany, 2002). Fleming may not have been the first to

discover the antimicrobial effects of fungal secondary metabolites but certainly was a

pioneer with respect to identifying the potential of the compound penicillin to treat

infections (Demain & Sanchez, 2009). Of course Fleming identified a Penicillin-

producing mould that could inhibit the growth of Staphylococcus aureus (Demain &

Sanchez, 2009). Over the next several decades after Fleming’s discovery and isolation

of Penicillum spp, a number of other antimicrobial secondary metabolites were

isolated but were found to have detrimental side effect on humans and animals

(Hussein & Brasel, 2001). Subsequently, the fungal secondary metabolites that

exhibited cytotoxic effects were collectively termed as mycotoxins (Bennett & Klich,

2003).

Although there is little doubt that fungal toxins have detrimental effects on human and

animal health throughout history it was not until 1960’s that the significance of the

toxic secondary metabolites was evident (Bennett, 1987). For example, in 1962 an

unusual veterinary crisis occurred in England where approximately 100, 000 turkeys

6

died from being fed Brazilian peanut (groundnut) meal contaminated with aflatoxins

produced by Aspergillus flavus (Creppy, 2002; Hussein & Brasel, 2001). The incident

raised the profile of mycotoxins and through various studies over 400 types were

identified with the primary classes being aflatoxins, zearalenone, trichothecenes,

fumonisins, ochratoxin A and ergot alkaloids (Peraica, Radic, Lucic, & Pavlovic,

1999). The most significant mycotoxins appeared in food and feed are listed in Table

1.2 and Figure 1.2. As described above, any foods that can support the growth of

moulds are susceptible in being contaminated with mycotoxins.

7

Table 1. 2- Specific mycotoxins of significance in managing food safety produced by different genera of fungi Aspergillus Penicillium Fusarium Claviceps Aflatoxin B1, B2

Patulin Fumonisins Ergot Alkaloids

Aflatoxin M1 Critinin Trichothecenes (deoxynivalenol and T-2)

Aflatoxin G1, G2

Ochratoxin A Zearalenone

Ochratoxin A Peniterm A Cyclopiazonic acid

Penicillin acid

Roquefortine Isoflumigaclavines

A, B

Cyclopiazonic acid

(Brown, Yu, Kelkar, Fernandes, Nesbitt, Keller, et al., 1996; Geiser, Pitt, & Taylor, 1998; Kuiper-Goodman & Scott, 1989)

(Kuiper-Goodman & Scott, 1989; Sweeney & Dobson, 1998)

(Hussein & Brasel, 2001; Kuipergoodman, Scott, & Watanabe, 1987; Parry, Jenkinson, & McLeod, 1995)

(Diekman & Green, 1992; Panaccione, 2005)

8

Figure 1. 2- Examples of the main mycotoxins encountered in foods and feed Note: alfatoxin B1 (1), patulin (2), citrinin (3), ochratoxin A (4), fumonisin B1 (5), deoxynivalenol (6), T-2 toxin (7) and zearalenone (8). Source: Bennett and Klich (2003); Cigic and Prosen (2009)

1.3.1 Economic impact of mycotoxins

As previously mentioned, mycotoxins have adverse effects on animals and humans

(Bennett & Klich, 2003; Hussein & Brasel, 2001). The actual economic loss of

mycotoxins is difficult to predict because the losses can be direct through the spoilage

of the crop before harvest or rejection of contaminated crops such as cereal grains and

7 8

1 2

6 5

3 4

9

animal feeds at post-harvest (Jelinek, Pohland, & Wood, 1989; Placinta, D'Mello, &

Macdonald, 1999). It is estimated that mycotoxins cost American agriculture between

$630 million and $2.5 billion annually, mainly because of market rejection of

contaminated batches when high level of toxic mycotoxins detected (Miller,

Schaafsma, Bhatnagar, Bondy, Carbone, Harris, et al., 2014; Richard, Payne,

Desjardins, Maragos, Norred, Pestka, et al., 2003; Wu, 2004). Indirect losses can

occur through low harvest of cereal grains or fruits, poor animal development or

mortality that is linked to animal consumption of contaminated feeds, in addition to

the acute and chronic health risks that are due to human consumption of contaminated

foods.

1.3.2 Effect of mycotoxins on humans and animals

The indirect economic impact resulting from the introduction of mycotoxins within

the food chain is due to poor animal development, in addition to acute and chronic

effects in humans (Creppy, 2002; Hussein & Brasel, 2001). Mycotoxins exhibit a

range of toxicity (LD50 values) that primarily relate to the reactivity towards vital cell

functions, such as protein synthesis or immune system effectiveness, in addition to

affecting the bodies detoxification pathways (Richard, et al., 2003).

Because of the diversity of chemical structures and differing physical properties,

mycotoxins exhibit a wide array of biological effects on mammalian systems with

toxins being categorized based on genotoxic, mutagenic, carcinogenic, embryotoxic,

teratogenic or oestrogenic (Richard, et al., 2003). Mycotoxins cause damage to the

immune system, in addition to leading to organ failure especially with respect to the

kidneys, liver (heptatoxic) and gastrointestinal tract (Hussein & Brasel, 2001; Wild &

10

Gong, 2010; Wild & Turner, 2002). Some mycotoxins can cause cancers in a variety

of animal species and humans. The relatively short life span of most intensively

reared animals reduces the significance of cancer development and so is more

significant in humans (Richard, et al., 2003).

1.3.3 Effects of patulin on animal and human health

In the 1960’s there was renewed interest in patulin as a drug to cure arthritis and it

was during these trials that the toxic effects of patulin were finally identified.

Specifically, in animal trials the administration of patulin was found to induce

ulceration which was thought to be through a combination of irritating the mucosal

layer, in addition to disrupting the gastrointestinal tract by displacing Gram-positive

bacteria thereby permitting the proliferation of Gram-negative pathogens. However,

there is little evidence of patulin being carcinogenic (Jelinek, Pohland, & Wood, 1989;

Yiannikouris & Jouany, 2002).

The main mode by which patulin elicits toxicity is through interaction with sulfhydryl

groups associated with proteins thereby leading to impaired functionality such as

enzyme inhibition (Barhoumi & Burghardt, 1996). In acute intoxication, likely

experienced by those exposed to patulin in the clinical trials, the symptoms are

convulsions, dyspnea, pulmonary congestion, edema and agitation, in addition to

ulceration (Bullerman, 1979; Escoula, More, & Baradat, 1977; Mahfoud, Maresca,

Garmy, & Fantini, 2002). Chronic exposure with sub-acute levels of patulin was

demonstrated to induce weight loss, ulceration and renal failure in rat models.

Additional symptoms of constant exposure are tremors, impaired immune response

and neural motor function. Patulin is also considered to disrupt fetal development in

rodents and on occasion reabsorption (Bullerman, 1979; Osswald, Frank, Komitowski,

11

& Winter, 1978; Pfeiffer, Gross, & Metzler, 1998; Schuetze, Lehmann, Boenisch,

Simon, & Polte, 2010; Ueno, Kubota, Ito, & Nakamura, 1978; Yiannikouris & Jouany,

2002). All symptoms are thought to reside either directly or indirectly as a result of

enzyme inhibition caused by disruption of disulfide groups on proteins.

1.3.4 Synthesis of patulin by producing molds

Patulin is produced by a selection of moulds belonging to the genera of Penicillium,

Aspergillus and Byssochlamys. Although not exclusive, the mould of major concern is

P. expansum that is primarily recovered in fruits and vegetables. The synthesis of

patulin is affected by environmental factors such as incubation time, temperature, pH,

and nutrient source (McCallum, Tsao, & Zhou, 2002). The biosynthetic pathway of

patulin synthesis still needs to be fully elucidated although is known to involve at

least 10 steps (Figure 1.3).

12

Figure 1. 3- Schematic diagram of patulin biosynthetic pathways Source: Moake, Padilla-Zakour, and Worobo (2005).

The initial building blocks for patulin are derived from acetyl-CoA and malonyl-CoA

both derived from fatty acid metabolism by a 760 kDa 6-MSA synthetase (Gaucher,

1975). The 6-methylsalicylic acid is then transformed to m-cresol by 6-MSA

decarboxylase via several enzymic steps with several intermediates (isoepoxydon,

phyllostine, neopatulin, and E-ascladiol) being identified that form the functional

patulin (Sekiguchi, 1983; Sekiguchi & Gaucher, 1978, 1979; Sekiguchi, Gaucher, &

Yamada, 1979; Sekiguchi, Shimamoto, Yamada, & Gaucher, 1983). Patulin is formed

by the oxidation of E-ascladiol. There are several branches off the patulin pathways

and hence the mycotoxin can be considered one of several metabolic products. The

regulation of patulin biosynthesis is considered to be located on a gene cluster with

the level of nitrogen playing a key role in controlling expression (Dombrink-

Kurtzman, 2007; Keller, Turner, & Bennett, 2005; White, O'Callaghan, & Dobson,

13

2006). Maximal patulin production is induced when nitrogen is high and inoculum

level is low. Glucose can also stimulate patulin production provided nitrogen is absent

(i.e. to prevent growth) (R. E. Scott, Jones, & Gaucher, 1986). Manganese is an

essential mineral for patulin synthesis along with aeration and pH optima of 5 (Scott,

Jones, Lam, & Gaucher, 1986).

1.3.5 Reactivity and stability of patulin

In the course of toxicity studies, it was noted that the toxic effects of patulin could be

significantly reduced if reacted with cysteine (Barhoumi & Burghardt, 1996; Ciegler,

Beckwith, & Jackson, 1976; Mahfoud, Maresca, Garmy, & Fantini, 2002). The

formation of the cysteine adduct subsequently led to the discovery that patulin reacts

with sulphur groups associated with enzymes and other proteins (Figure1.4). The

reactivity of patulin is primarily through the reduction and opening of the lactone

group (Fliege & Metzler, 2000b). Antioxidants other than cysteine have also been

found to form adducts thereby rendering the mycotoxin neutralized (Brackett & Marth,

1979a; Riley & Showker, 1991). Relevant to the current thesis, ascorbic acid in apple

juice can become oxidized to dehydroascorbic acid which subsequently reacts with

patulin in a process catalyzed by oxygen along with Fe2+ (Figure 1.5 ) (Brackett &

Marth, 1979a; Drusch, Kopka, & Kaeding, 2007). The addition of ascorbic acid at 500

ppm to apple juice can reduce patulin levels by up to 70 % in the storage of 34 days

but in practical terms this mode of inactivating the mycotoxin is limited by the

exclusion of oxygen to minimize non-enzymic browning.

From mechanistic studies, the interaction of patulin with 4-bromothiophenol (BTP)

has been demonstrated to produce a diverse range of products all of which involved

opening the lactone ring and reaction of the thiol group of BTP. Glutathione is an

anti

Inte

hav

This

com

FigucystSou

ioxidant tha

erestingly th

e stronger o

s would su

mpared to th

ure 1. 4- Tteine

urce: Fliege

at further r

hese adduct

oxidizing p

uggest that

he original m

The formati

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reacts with

ts, formed b

ower than t

glutathione

mycotoxin.

on of PAT

er (2000b)

14

patulin to

by the react

the original

e-patulin ad

T/CYS P1 a

form vari

tion betwee

l reactants (

dducts can

adduct whe

ious adduct

en patulin a

(Fliege & M

be potentia

en patulin r

ts (Figure

and glutathi

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ally more t

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1.6).

ione,

00b).

toxic

free

Sou

Figurce: Martelgure 1. 5- M

l (1973) Mechanism oof metal-cat

O2 presence

15

talysed oxid

e

dation of asccorbic acid

FiguThefolloSou

ure 1. 6- Ree thiol grouowed by ad

urce: Fliege

eaction of paup of gluta

dditional reaand Metzle

atulin with athione reaactions to foer (2000a)

16

glutathionects with th

orm differenhe Carbon-2nt adducts.

2 or Carbo

on-6 of pattulin

17

The stability of patulin is highest under acidic conditions but becomes reactive and

unstable above pH 5.5 (Figure 1.7). It has also been reported that patulin is unstable at

alkaline pH in other studies (Brackett & Marth, 1979b; Stott & Bullerman, 1976).

Figure 1. 7- Stability of patulin in buffered solutions poised at different pH values Source: Drusch, Kopka, and Kaeding (2007) Kadakal and Nas (2003) found that thermal treatments at 90 °C or 100 °C for 20

minutes caused 19 % and 26 % patulin reductions respectively (220 ppb of patulin

spiked). However, thermal treatments can lead to juice caramelization thereby

changes in sensory characteristics. Patulin can also be degraded by illumination with

ultraviolet C (UV-C) light with the highest rate of reduction being observed at 222 nm

but also occurring at the germicidal wavelength, 254 nm (Yan, Koutchma, Warriner,

Suqin, & Ting, 2013). Although both thermal treatment and UV can be applied to

reduce patulin levels in apple juice there are limitations. Specifically, the thermal

treatments required to inactivate patulin from an initial level of 200 ppb to below

regulatory limits would result in unacceptable sensory changes in apple juice quality

(Kadakal & Nas, 2003). In a similar manner, UV-C results in the generation of photo-

0

20

40

60

80

100

0 10 20 30 40

pH 2.5

pH 4

pH 5.5

pH 7

Patulin

content (%

)

Storages(Days)

18

products resulting in odor and color changes in apple juice (Guerrero-Beltran &

Barbosa-Canovas, 2004). As a consequence, thermal and UV treatments are not

designed to degrade patulin and limited to ensuring a 5 log cfu reduction of

Escherichia coli O157:H7 (Wright, Sumner, Hackney, Pierson, & Zoecklein, 2000;

Yan, Koutchma, Warriner, & Ting, 2014). In this regard, the key interventions to

control patulin in apple juice are largely based on Good Agricultural Practice (GAP)

that minimized the use of spoiled fruit in apple juice production and undertake

extensive testing to prevent contaminated batches of juice concentrate entering the

food chain (Beretta, Gaiaschi, Galli, & Restani, 2000; Kabak, Dobson, & Var, 2006;

Yiannikouris & Jouany, 2002). Given the limitations of testing, there it is a need to

introduce interventions that can degrade patulin in an overall risk management

program. To this end the current research assessed the efficacy of high hydrostatic

pressure to degrade patulin.

1.4 Analytical Methods for Quantification of Patulin

There are several AOAC approved methods for quantifying the concentration of

patulin in apple juice. In the official method for patulin analysis, the first step is to

extract the mycotoxin with ethyl acetate followed by liquid-liquid extraction with a

1.5 % sodium carbonate solution to remove a proportion of interferents (Li et al.,

2007). The ethyl acetate fraction is evaporated to dryness and residual patulin

suspended in acidified (<pH 4) water. The sample is then passed through a C18

reversed-phase HPLC column and detected by monitoring the change in absorbance at

276 nm. More recent advances in patulin quantification include the application of

liquid chromatography/mass spectroscopy (LC/MS) that is less prone to interference

and more precise compared to HPLC/UV based methods (Rychlik & Schieberle, 1999;

19

Shephard & Leggott, 2000; Takino, Daishima, & Nakahara, 2003). Quantitative

GC/MS determinations of silyl or acetyl derivatized patulin has also been reported

(Cunha, Faria, & Fernandes, 2009; Moukas, Panagiotopoulou, & Markaki, 2008;

Sforza, Dall'Asta, & Marchelli, 2006).

Although sensitive, current commercial methods of patulin analysis are laboratory

based, labor intensive and expensive. As a consequence, there has been significant

interest in developing a low cost test that can be applied outside of the laboratory

environment for screening batches of apple juice concentrate, for example, prior to

acceptance. For other mycotoxins there are a range of immuno-based assays for

biosensor devices although this is not possible for patulin given that no antibodies

against the toxin are currently available (McElroy and Weiss 1993, Mhadhbi et al.,

2005). The lack of success in raising antibodies to patulin is due to the low molecular

weight of the mycotoxin (Mw 154) and also the reactivity towards proteins (Arafat,

Kern, & Dirheimer, 1985; Ashoor & Chu, 1973; Fliege & Metzler, 1999). Here, the

patulin would react with the thiol containing amino acids of the antibody as opposed

to binding (Barhoumi & Burghardt, 1996; Wheeler, Harrison, & Koehler, 1987). It

has been proposed that adducts formed between patulin and thiol species (cysteine

and glutathione) could be used as antigen targets in raising antibodies (Moake et al.,

2005). Although such antibodies would be useful for clinical actions to detect the

reaction products of patulin, it would have limited use in foods where the mycotoxin

would be in its free form.

A chemiluminescence sensor for patulin has been described by Liu, Gao, Niu, Li, and

Song (2008). The sensor is based on the enhanced luminescence of luminol when

reacted with hydrogen peroxide in the presence of patulin in alkali carrier solution.

20

The mode of action of the sensor is the generation of free radicals from the interaction

of patulin with hydrogen peroxide that subsequently activates the luminol to generate

luminescence (Liu, Gao, Niu, Li, & Song, 2008). Although the sensor was rapid there

is still the need to extract and concentrate the patulin from apple juice prior to analysis

that would ultimately limit its application for on-site testing.

A further patulin assay has been described based on the inhibition of bioluminescence

in Vibrio fisheri (Sarter & Zakhia, 2004). Bioluminescence in V. fisheri is generated

by the enzyme luciferase using ATP and FADH2 as co-factors. When cells are

exposed to toxic agents, the metabolism of the cell is negatively affected thereby

reducing the generation of ATP and reducing equivalents required to sustain the

luciferase reaction. Cells exposed to 7.5 mg/L of patulin decreased the

bioluminescence of V. fisheri culture by 50 % within 15 min. Although relatively

rapid the need for viable cultures and low sensitivity are clear limitations (Sarter &

Zakhia, 2004).

In the current study, a patulin assay has been developed based on the interaction of the

mycotoxin with pyrrole. The assay was initially developed by Namvar (2010) and

essentially based on the formation of a pyrrole: patulin adduct. The adduct formation

can be monitored through FTIR or more conveniently through electrochemical

detection. With respect to the latter, the formation of the patulin-pyrrole adduct forms

a termination unit at the end of the elongating conductive polypyrrole chain (Figure

1.8). This is visualized through a decrease in oxidative peaks when pyrrole, along

with the formed adduct, are co-electropolymerized onto carbon electrode surfaces. A

range of electrochemical methods can be used to probe the electro-polymerization

process with cyclic voltammetry being one. Here, the sample containing the patulin is

21

reacted with pyrrole and then the mixture is placed on the surface of a carbon

electrode. A potential scan is applied from -0.3 V to 1.9 V vs. Ag/AgCl which

oxidizes pyrrole, but with chain elongation terminating by the addition of the adduct.

Therefore, the decrease in oxidative peak is proportional to adduct levels which in

turn are proportional to the original patulin concentration in the sample.

22

Figure 1. 8- The mode of action of patulin reacting with pyrrole Source: Namvar (2010)

: Pyrrole

: Patulin

23

1.5 Square Wave Voltammetry

Cyclic voltammetry (CV) is one of the most commonly used electrochemical

techniques and is based on scanning the potential between two points in which an

oxidation or reduction event occurs (Allemand, Koch, Wudl, Rubin, Diederich,

Alvarez, et al., 1991; Janietz, Bradley, Grell, Giebeler, Inbasekaran, & Woo, 1998;

Nicholso, 1965; Richardson & Taube, 1981; Wang, Li, Shi, Li, & Gu, 2002). The

oxidation reaction results in an increase in the current whereas a reduction causes a

decrease in the recorded current. The kinetics of the electrochemical process is

defined by the diffusion rate of the redox species to the electrode surface which in

turn is partly governed by the potential scan rate. In the course of a potential scan, the

redox species diffuse to the electrode surface and undertake electron transfer. At high

scan rates the electroactive species become depleted. This is observed as a peak

current (Figure 1.9) using a BASi EC epsilon potentiostat (Figure 1.10) which applied

potential wave form (Figure 1.11) and the cyclic voltammetry parameters (Figure

1.12). In reversible reactions the reduced species on the surface donates electrons that

decrease the current in a diffusion limited reaction. Therefore, the magnitude of the

peak currents is dependent on the diffusion rate which in turn depends on substrate

concentration along with the scan rate. Based on this theory, it would be logical to

assume that the sensitivity of detecting electro-active species could be increased by

simply using high scan rates. However, as the scan rate increases the capacitive

currents increases to the point that can be higher than the faradic current. The net

result is that the peak is obscured and cannot be identified in a cyclic voltamogram.

This effect is especially observed with conducting polymer modified electrodes which

naturally have high capacitance. With systems such as conducting polymers there is a

24

need to reduce the contribution of capacitive currents thereby enabling the

visualization of the faradic current signal. This is achieved by subtracting the

capacitive background current using a technique referred to a differential pulse

voltammetry. Another technique is to apply a potential ramp but delay measuring the

current for a time period thereby allowing the capacitive currents to decrease. There

are several techniques based on this principle with Square Wave Voltammetry being

the most widely applied.

Square wave voltammetry (SWV) is an improvement on staircase voltammetry which

is itself a derivative of linear sweep voltammetry (Erdogdu, 2006; Schirmer, Keding,

& Russel, 2004). In square wave voltammetry, the potential wave form consists of a

square wave of constant amplitude superimposed on a staircase wave form. The

current is measured at the end of each half-cycle, and the current measured on the

reverse half-cycle (ir) is subtracted from the current measured on the forward half-

cycle (if). This current (if - ir) is displayed as a function of the applied potential (Figure

1.13) when the square wave voltammetry parameters were applied (Figure 1.14).

Oxidation or reduction of species is shown as a peak or trough in the current signal at

the potential at which the species begins to be oxidized or reduced. The current is

measured at the end of each potential change, right before the next, so that the

contribution to the current signal from the capacitive charging current is minimized.

Because of the lesser influence of capacitive charging current, the detection limits for

SWV are on the order of nanomolar concentrations.

25

Figure 1. 9- Typical cyclic voltammogram of the peak catholic and anodic current respectively for a reversible reaction Source: Bard and Faulkner (2001)

Figure 1. 10- EC epsilon-modern equipment for electrochemical research

26

Figure 1. 11- Potential wave form for cyclic voltammetry Source: Bard and Faulkner (2001)

Figure 1. 12- Change parameters dialog box for cyclic voltammetry

27

Figure 1. 13- Potential wave form for square wave voltammetry Source: Bard and Faulkner (2001)

Figure 1. 14- Change parameters dialog box for square wave voltammetry

28

1.6 High Hydrostatic Pressure Processing

1.6.1 High hydrostatic pressure technique

High hydrostatic pressure (HHP) has been one of a number of non-thermal processing

technologies that has transitioned from an academic research laboratory to

mainstream food manufacturing (Cheftel, 1995; Patterson, 2005). The application of

high pressure as a food preservation technique can be traced to the late 19th century

although it was more a curiosity than a practical process (Manas & Pagan, 2005;

Rastogi, Raghavarao, Balasubramaniam, Niranjan, & Knorr, 2007). The early systems

were inherently unstable and likely only generated pressure in the order of 100-200

MPa and had capacities of less than 1 litre. At this time thermal processing was

regarded as a more practical approach to food preservation and as a consequence high

pressure processing was primarily devoted to undertaking novel chemistry of

ceramics and polymers (McKenzie, Sarr, Mayura, Bailey, Miller, Rogers, et al., 1997;

Smelt, 1998). Apart from advancing material science, the technical advances also

developed HHP units with sufficient volume and operating pressures to be of practical

use in the food sector (Figure 1.15). In the 1990’s the first commercial products to be

HHP processed were low risk foods such as jams for shelf-life extension then later for

preserving avocado-based products (Hendrickx, Ludikhuyze, Van den Broeck, &

Weemaes, 1998; Horie, Kimura, Ida, Yosida, & Ohki, 1991; Watanabe, Arai, Kumeno,

& Honma, 1991). The main motivation for implementing HHP was the ability to

retain the qualities of products for which consumer demand remains. From 2000

onwards there was an increasing use of HHP in North America as a pathogen

reduction step to comply with regulations being introduced by the FDA and USDA to

29

enhance food safety of juices and deli meats amongst other products (Cheftel &

Culioli, 1997; Crawford, Murano, Olson, & Shenoy, 1996; Jung, Ghoul, & de

Lamballerie-Anton, 2003; Myers, Montoya, Cannon, Dickson, & Sebranek, 2013;

Patterson, Quinn, Simpson, & Gilmour, 1995; Yuste, Mor-Mur, Capellas, Guamis, &

Pla, 1998).

High pressure processing, also referred to as ultra-pressure processing or high

hydrostatic pressure processing is a batch process using chambers ranging from 1 litre

to 400 litres. The foods to be processed are typically vacuum packed but products

processed under modified atmosphere packaging have also been described (Rastogi,

Raghavarao, Balasubramaniam, Niranjan, & Knorr, 2007). The chamber is filled with

a non-compressible liquid which is commonly water or water: oil mix. A high

pressure intensifier builds up the pressure in the unit transmitting the force through the

water phase to the product being treated (Figure 1.15). A degree of compression takes

place that increases the temperature by 3 °C per 100 MPa. The pressure is released

upon completion of the treatment and the packs are removed in preparation for the

next run (Patazca, Koutchma, & Balasubramaniam, 2007).

30

Figure 1. 15- Schematic graph of high hydrostatic pressure equipment Source: Koutchma, Guo, Patazca, and Parisi (2005); Patazca, Koutchma, and Balasubramaniam (2007)

Figu In t

prod

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31

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32

number of processors use HHP in place of additives such as diacetate: lactate to

inhibit potential outgrowth although this may compromise shelf-life stability (Brul &

Coote, 1999; Patterson, 2005; Smelt, 1998; Styles, Hoover, & Farkas, 1991). The

seafood industry has a relatively long history of using HHP for shell removal but the

process is considered a significant intervention to reduce Vibrio vulnificus (Berlin,

Herson, Hicks, & Hoover, 1999; Bermudez-Aguirre & Barbosa-Canovas, 2011; Calci,

Meade, Tezloff, & Kingsley, 2005; Cook, 2003; Kural & Chen, 2008).

High acid juices represent the largest growing sectors in the HHP market with a broad

range of beverages commercially available (Jordan, Pascual, Bracey, & Mackey, 2001;

Patterson, 2005; Porretta, Birzi, Ghizzoni, & Vicini, 1995). The high acidity is

compatible with HHP given the enhanced microbial inactivation coupled with shelf-

life stability (Butz, FernandezGarcia, Lindauer, Dieterich, Bognar, & Tauscher, 2003;

Polydera, Stoforos, & Taoukis, 2003; Porretta, Birzi, Ghizzoni, & Vicini, 1995).

1.6.2 Mode of microbial inactivation by high hydrostatic pressure

The precise mode of inactivation of microbes by HPP remains to be fully elucidated

although evidence to date indicates that a combination of cellular targets is affected

(Figure 1.17). The nature of cellular damage is dependent on the applied pressure.

Specifically, at low pressure (50 MPa) the ribosomal function is inhibited with protein

denaturation and membrane damage occurring at 300 MPa. Beyond 300 MPa the

damage is irreversible leading to cell death (Abe, 2007; Rastogi, Raghavarao,

Balasubramaniam, Niranjan, & Knorr, 2007; Yaldagard, Mortazavi, & Tabatabaie,

2008). In this respect the loss of cell membrane functionality and integrity are

considered the key lethal effects caused by HHP. Supporting evidence for role of

pressure on membranes are based on the loss of nutrient transport and energy

33

generating (ATPase) proteins/enzymes from pressure treated cells (Malone, Chung, &

Yousef, 2006; Mentre & Hoa, 2001; Tholozan, Ritz, Jugiau, Federighi, & Tissier,

2000; Yayanos & Pollard, 1969). With respect to enzymes, irreversible damage is

caused by denaturation through disruption of non-covalent bonding thereby disrupting

metabolic, synthetic pathways and those required for cellular hemostasis such as pH

(Mozhaev, Heremans, Frank, Masson, & Balny, 1996; Silva, Foguel, & Royer, 2001;

Simpson & Gilmour, 1997). Nucleic acids such as DNA are not denatured by HPP but

become more compact thereby rendering the cell unable to replicate (Mohamed,

Diono, & Yousef, 2012; Robey, Benito, Hutson, Pascual, Park, & Mackey, 2001;

Wemekamp-Kamphuis, Karatzas, Wouters, & Abee, 2002).

In terms of practical significance, the mode of action by HPP explains why post-

treatment recovery of microbes can potentially occur through the repair of cellular

constituents. Furthermore, given that the stress response of microbes is primarily to

protect the protein biosynthetic machinery it can be anticipated that the history of the

microbe will affect the efficacy of HPP. Specifically, cells exposed to stress (water

activity and cold shock but to a lesser extent acid) will have enhanced tolerance to

pressure inactivation (Hormann, Scheyhing, Behr, Pavlovic, Ehrmann, & Vogel, 2006;

Lado & Yousef, 2002; Wemekamp-Kamphuis, Wouters, de Leeuw, Hain,

Chakraborty, & Abee, 2004). To date there have been no specific HHP response

genes identified which in turn the likelihood of generating barotolerant mutations is

low (Bartlett, Kato, & Horikoshi, 1995; Black, Koziol-Dube, Guan, Wei, Setlow,

Cortezzo, et al., 2005; Fernandes, Domitrovic, Kao, & Kurtenbach, 2004; Huang,

Lung, Yang, & Wang, 2014; Wemekamp-Kamphuis, Wouters, de Leeuw, Hain,

Chakraborty, & Abee, 2004).

FiguSou

1.6.

In g

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Gar

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3 Variation

general term

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Pressure induand Yousef

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Bertucco, 20

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bial inactiv

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34

ge to microb

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91). Cocci h

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have a tende

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008).

fatty

35

acids within their membranes exhibit higher tolerance to pressure than mesophiles or

psychrophiles (Bartlett, 2002; Daryaei, Coventry, Versteeg, & Sherkat, 2010;

Jaenicke, Bernhardt, Luedemann, & Stetter, 1988). In terms of specific bacteria,

Vibrio has been reported to be most the pressure sensitive with a 4 log reduction being

achieved at pressure in the order of 293 MPa for 120 s (Berlin, Herson, Hicks, &

Hoover, 1999; Koo, Jahncke, Reno, Hu, & Mallikarjunan, 2006; Kural & Chen, 2008;

Ma & Su, 2011; Murchie, Cruz-Romero, Kerry, Linton, Patterson, Smiddy, et al.,

2005). Yet, the relative resistance of different microbes is dependent on several

factors that include strain selection, propagation methods and intrinsic properties of

the product matrix. Specifically, cells in the stationary phase exhibit higher pressure

resistance to those undergoing exponential growth (Alpas, Kalchayanand, Bozoglu,

Sikes, Dunne, & Ray, 1999; Benito, Ventoura, Casadei, Robinson, & Mackey, 1999;

Mackey, Forestiere, & Isaacs, 1995; Manas & Mackey, 2004; Patterson, 2005;

Rendueles, Omer, Alvseike, Alonso-Calleja, Capita, & Prieto, 2011). This makes

sense given that growing cells have the need to express proteins and generate ATP. In

contrast, stationary cells have low metabolic rates and frequently express stress

proteins to further enhance pressure resistance (Doona, Feeherry, Ross, & Kustin,

2012; Griffin, Kish, Steele, & Hemley, 2011; Robey, Benito, Hutson, Pascual, Park,

& Mackey, 2001; Shearer, Neetoo, & Chen, 2010).

It is widely accepted that the lethality of HHP is enhanced by low pH. However, less

well investigated is the effect of food components on the enhancing or reducing

barotolerance (Balny & Masson, 1993; Cheftel, 1995; Roberts & Hoover, 1996). For

example, protein, sugars, and lipids can provide a protective effect towards high

pressure (Butz, FernandezGarcia, Lindauer, Dieterich, Bognar, & Tauscher, 2003;

36

Mackey, Forestiere, & Isaacs, 1995; Vervoort, Van der Plancken, Grauwet, Verlinde,

Matser, Hendrickx, et al., 2012). For example, milk proteins can enhance the bar

tolerance of S aureus compared to when simple buffer solutions are applied or the

bacteria are suspended in meat slurries (Shigehisa, Ohmori, Saito, Taji, & Hayashi,

1991; Smiddy, Sleator, Patterson, Hill, & Kelly, 2004).

1.6.4 Inactivation kinetics of different microbes (pressure inactivation of bacteria

and fungi)

Grouping of microbial types with respect to pressure tolerance is difficult given the

influence on strain type, supporting matrix, processing conditions and cultivation

conditions to recover survivors. Yet, through comparisons of inactivation data the

general trend is that bacterial endospores exhibit the highest bartolerance with yeasts

being most sensitive (Cheftel, 1995; Margosch, Ehrmann, Buckow, Heinz, Vogel, &

Gaenzle, 2006; Shimada, Andou, Naito, Yamada, Osumi, & Hayashi, 1993; Torres &

Velazquez, 2005; Wuytack, Boven, & Michiels, 1998). Vegetative bacterial cells have

intermediate pressure resistances although exceptions exist. For example, Vibro is

commonly found to be pressure sensitive relative to other bacterial types (Table 1.3).

E coli can exhibit high bar tolerance although is strongly strain dependent with no

differentiation between pathogenic and non-pathogenic types. Yet, there is a tendency

of Gram positives being more resistant compared to Gram negatives although this

depends on the food matrix, in addition to processing parameters (Brul & Coote, 1999;

Masschalck, Van Houdt, Van Haver, & Michiels, 2001; Patterson, 2005). Moulds

have intermediate pressure tolerance being inactivated between 300 – 600 MPa

although, given that the foods are vacuum packed, the risk of outgrowth is minimal

(Smelt, 1998).

37

Table 1. 3- D and Z values for the high hydrostatic pressure inactivation of different microbes Microbe Pref (MPa) Tref (°C) Log Dp (s) Zp (MPa) ZT (°C) Bacillus spores 400 100 0.27 614.7 45.2 Bacillus anthracis 400 NA 2.33 876.4 NA Clostridium spp 400 100 0.85 616.3 20.4 Clostridium sporogenes

400 100 0.70 1088.6 67.2

Cronobacter 400 NA 0.19 368.2 NA Escherichia coli 400 30 0.88 385.6 97.5 Listeria spp 400 30 0.56 298.9 38.6 Vibrio spp 400 30 0.058 206.9 18.4 Zygosaccharomyces bailii

400 30 0.84 91 141.7

Dp = decimal reduction time Zp = change in pressure to Dp by 1 log unit Zt = change in temperature to change Dp by 1 log unit. Source: Farakos and Zwietering (2011) Applied pressure is one parameter that defines the inactivation kinetics of microbes by

HHP. In general, growing cells are more pressure sensitive to those in the stationary

phase due to the expression of stress responses in the latter (Cheftel, 1995; Norton &

Sun, 2008). However, HHP processing temperature is one of the key parameters that

affect inactivation kinetics. The highest bar tolerance within microbes of interest

exists between 20-40 °C with increased efficacy of HHP at colder or higher

temperatures (Figure 1.18). The only exception is observed with L. lactis that

increases in bar-tolerance with temperature up to the point of thermal inactivation

(Sonoike, Setoyama, Kuma, & Kobayashi, 1992). The underlying mechanisms for the

relation of temperature and pressure on microbial inactivation is considered to be due

to the increased compressibility of water and cell cytoplasm with decreasing

temperature thereby enhancing transmission of pressure (mechanical) energy (Benito,

Ventoura, Casadei, Robinson, & Mackey, 1999; Hugas, Garriga, & Monfort, 2002;

Lor

Kilp

FiguachiSou

1.6.The

that

that

trea

Boz

i, Buckow,

patrick, 199

ure 1. 18- Rieve a 5 log

urce: Heinz

5 Inactivate fate of my

t the proces

t citrinin in

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zoglu, 2010)

, Knorr, H

98).

Relationshipg cfu reductiand Buckow

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).

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cotoxins by during HHP

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f 250 MPa

38

ehmacheri,

temperatureel microbes

high hydroP has not be

crobial redu

n be degrad

a for 5 min

2007; Patt

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ostatic preseen studied

uction step.

ded by 1.3-1

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ure on the r

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requiremen

eat extent g

s been repo

gure 1.19) u

soglu, Alpa

n &

nts to

given

orted

using

s, &

39

Figure 1. 19- HHP effects on citrinin degradation at 250 MPa/35± 1 °C for 5 minutes Source: Tokusoglu, Alpas, and Bozoglu (2010) Note: 1: 1 ppb, 2: 1.25 ppb, 3: 2.5 ppb, 4: 10 ppb, 5: 25 ppb and 6: 100 ppb spiked

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6

56 %

37 %25 %

1.3 %

98 %100 %

Citrinin degradation (%)

40

Relevant to the current thesis, patulin degradation by HHP has also been reported. In a

study, Bruna (1997) reported that HHP treatment of 300 MPa, 500 MPa, and 800 MPa

at 20 °C for 60 min in a 1 L HHP chamber led to a degradation of original patulin

content (155 µg/L) by 16, 20, and 23 % in apple concentrate (Figure 1.20). Higher

patulin degradation was observed when the same pressure regime was applied to

apple juice inoculated with patulin. Here, up to 62 % patulin reduction was reported

using 800 MPa for 60 min (Bruna, 1997). Furthermore, the authors went onto report

that increased patulin degradation by HHP could be achieved when combined with

temperature treatment (50 °C). Merkulow and Ludwig (2002) reported that by

applying HHP treatments in the range of 400-500 MPa can reduce patulin levels in

apple juice by 20-80 % through reactivity of the mycotoxin with cysteine within the

product. However, the process is highly variable and hence unpredictable (Bruna,

1997; Merkulow & Ludwig, 2002).

Studies to date on the degradation of patulin by HHP have been observational in

nature with no in depth mechanistic studies or factors that both enhance or reduce

process efficacy.

41

Figure 1. 20- Patulin reduction in apple juice and apple concentrate at 20 °C Source: Bruna (1997)

0

10

20

30

40

50

60

70

0 200 400 600 800 1000

Apple conc(56 Brix)

Apple juice(12 Brix)

Pressure level (MPa)

Patulin

red

uction (%)

42

1.6.6 Chemical reactions under high hydrostatic pressure

The chemistry and physics of matter change depending on the applied pressure. The

La Chatelier-Braun principle states “under equilibrium conditions, chemical reactions,

phase transitions or conformational changes involving a volume reduction will be

favoured by pressure” (Smelt, 1998). Therefore, by applying pressure, reactants are

brought together and volume changes occur in macromolecules that result in

deformation (Smelt, 1998). As a consequence, the internal structures of cells are

disrupted and enzymes are irreversibly damaged in some cases. It should be noted that

while ionic bonding is disrupted no breakage of chemical bonds occurs. Therefore,

pressure sensitive enzymes such as polyphenol oxidase, are inactivated by pressure

through the loss of tertiary and quaternary structure that is typically stabilized by ionic

bonding (Table 1.4). For example, HHP provides an advantage when processing apple

where the activity of polyphenol oxidase would ordinarily result in rapid spoilage

(Guerrero-Beltran, Barbosa-Canovas, & Swanson, 2005; Lopez-Malo, Palou,

Barbosa-Canovas, Welti-Chanes, & Swanson, 1998; Weemaes, Ludikhuyze, Van den

Broeck, & Hendrickx, 1998). However, other enzymes remain unaltered or increase in

activity following high pressure treatment (Table 1.4). With regards the latter, it is

thought that the increase in enzyme activity can be attributed to re-orientation of the

protein structure or through release from damaged cells (Ashie & Simpson, 1996; Farr,

1990; Hendrickx, Ludikhuyze, Van den Broeck, & Weemaes, 1998; Huppertz, Kelly,

& Fox, 2002; Terefe, Buckow, & Versteeg, 2014).

43

Table 1. 4- Effect of HHP processing on enzymes in different fruit and vegetable matrices

Enzyme Source HHP conditions Response Source Poly methyl esterase

Apple 200-600 MPa, 15-65 °C, 0.5-10 min

Increased activity with pressure up to 40% Increased activity with pressure up to 40 °C

(Baron, Denes, & Durier, 2006)

Polyphenol oxidase

Apple Up to 900 MPa Inactivation >600 MPa

(Weemaes, Ludikhuyze, Van den Broeck, & Hendrickx, 1998)

Peroxidase Apple 600 MPa, 20 °C, 15 min

Two-fold increase

(Prestamo, Arabas, Fonberg-Broczek, & Arroyo, 2001)

Carrot 500 MPa, 20 °C, 1 min

70 % increase (Anese, Nicoli, Dallaglio, & Lerici, 1995)

Orange 400 MPa, 32 °C,15 min

50 % inactivation (Cano, Hernandez, & DeAncos, 1997)

Lipoxygenase Avocado 689 MPa, 20 min 95 % inactivation (Palou, Lopez-Malo, Barbosa-Canovas, & Welti-Chanes, 2000)

Similar to macromolecules, the effect of pressure on low molecular weight

constituents is variable (Oey, Van der Plancken, Van Loey, & Hendrickx, 2008;

Ramirez, Saraiva, Perez Lamela, & Torres, 2009; Sancho, Lambert, Demazeau,

Largeteau, Bouvier, & Narbonne, 1999; Smelt, 1998). The significance to the effect of

food constituents is of interest due to the need to preserve nutrients such as vitamins

and functional compounds such as polyphenols whilst reducing the formation of toxic

byproducts (Escobedo-Avellaneda, Pateiro-Moure, Chotyakul, Antonio Torres, Welti-

Chanes, & Perez-Lamela, 2011; Tadapaneni, Daryaei, Krishnamurthy, Edirisinghe, &

Bur

biom

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hav

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45

A common feature of studies investigating the effect of HHP on vitamin C content is

that food systems were used as the matrix as opposed to more defined conditions. This

is the likely reason for the high variability in the HHP degradation percentages

reported for vitamin C (de Ancos, Sgroppo, Plaza, & Cano, 2002; Polydera, Stoforos,

& Taoukis, 2003). For example, reports state that no vitamin C loss occurs in orange

juice treated with HHP at 600 MPa (Table 1.5). Yet in grape juice the losses due to

HHP have been reported to be as high as 82 %. Some of the variability in the

degradation rates of vitamin C can be attributed to processing temperature which

becomes significant when HHP is applied at >40 °C. Other theories to describe the

variability are the residual enzyme activity that can contribute to degradation rates of

vitamin C during storage. The interaction of vitamin C with oxidative constituents

with foods is a further factor responsible for the variability encountered in HHP

degradation.

46

Table 1. 5- HHP processing on bioactive components in fruit and vegetable juices Product Treatment conditions Major findings Reference Orange juice 400-600

MPa/20 °C/15 min, 7 week storage at 4 and

10 °C

Vit C losses less than 6 % after HP. First order degradation kinetics for Vit C.

( Torres, Tiwari, Patras, Cullen, Brunton, & O'Donnell, 2011)

500-600 MPa/35-40 °C/3-4 min

Vit C degradation rates lower than pasteurized juice immediately after HP and during subsequent storage. Lower TAC loss of HP samples during storage.

(Polydera, Stoforos, & Taoukis, 2003, 2005a, 2005b)

100-800 MPa/30-100 °C/0-90 min

Pressure induced folic acid degradation. TAC decreased as a function of time.

(Nguyen, Indrawati, & Hendrickx, 2003)

Strawberry beverage

200-600 MPa/20 °C/30 min

Vit C losses lower than 12 % after HP.

(Sancho, Lambert, Demazeau, Largeteau, Bouvier, & Narbonne, 1999)

Vegetable beverage

100-400 MPa/20-42 °C/2-9 min

Vit C losses lower than 9 % and 16 to 48 % losses in TC after HP. TAC decreased as treatment pressure increased.

(Barba, Esteve, & Frigola, 2010)

Blueberry juice

200-600 MPa/20-42 °C/5-15 min

Vit C losses lower than 9 %.

(Barba, Esteve, & Frigola, 2013)

Vegetable soup

150-350 MPa/60 °C/15 min

Decrease in carotene concentration as treatment pressure increased.

(Plaza, Sanchez-Moreno, De Ancos, & Cano, 2006)

Carrot juice 100-800 MPa/30-100 °C/0-90 min

5-methyltetrahydrofolic acid is rather unstable at pressures exceeding 500 MPa.

(Indrawati, Verlinde, Ottoy, Van Loey, & Hendrickx, 2004)

47

1.7 Fruit and Vegetable Juice Components

1.7.1 Ascorbic acid content in fruits and vegetables

Ascorbic acid (AA) is a natural antioxidant and provides a protective function against

oxidative stress in cells. Although ascorbic acid and vitamin C are used

interchangeably, it must be noted that the latter term encompasses the more reactive

oxidized form, dehydroascorbic acid. Fruit and vegetables have long been regarded as

a key source of vitamin C in the daily diet (Cao, Russell, Lischner, & Prior, 1998;

Chebrolu, Jayaprakasha, Yoo, Jifon, & Patil, 2012). The content of ascorbic acid in

cloudy apple juices was ranging from 8.5 to 46.6 mg/100 ml (Table 1.6). The

variation of vitamin C in apple juices has been attributed to apple variety, harvest

season, post-harvest storage, fruit grinding and addition of exogenous ascorbic acid to

minimize non-enzymic browning (Kolniak-Ostek, Oszmianski, & Wojdylo, 2013).

As previously described, ascorbic acid or more correctly dehydroascorbic acid, can

degrade patulin in the presence of oxygen and ferric ions (Table 1.7) (Aytac & Acar,

1994; Brackett & Marth, 1979a; Drusch, Kopka, & Kaeding, 2007). Drusch, Kopka,

and Kaeding (2007) found that after 34 days, patulin was reduced by 70 % of its

initial concentration in the presence of ascorbic acid compared to 29-32 % in samples

with the absence of ascorbic acid. The degradation of patulin via ascorbic acid is

higher at neutral pH with greater stability under acidic environments. How high

hydrostatic pressure affects the reactivity of dehydroascorbic acid with patulin is

currently unknown.

48

Table 1. 6- Natural ascorbic acid (AA) content in cloudy apple juices from different apple varieties in three years Apple type Arlet Idared Jonafree Shampion Ozard

gold Topaz

Ascorbic acid(mg/100 ml)

10.5±4.5 8.5±4.8 10.8±3.8 46.6±51.7 8.3±3.7 12.5±11.3

Source: Kolniak-Ostek, Oszmianski, and Wojdylo (2013)

49

Table 1. 7- Summary of patulin degradation in apple juice in previous studies. Type of sample Patulin

conc. (ppb)

Ascorbic acid addition (mg/l)

Storage(days)

Degradation(%)

Reference

Aqueous buffer solution, pH 3.5

5000 0 8 20 (Brackett & Marth, 1979a)

Canned apple juice

4000 0 21 20-25 (P. M. Scott & Somers, 1968)

Apple juice, cloudy

82 103 14 45 (Steiner, Werner, & Washuettl, 1999)

81 501 14 35 81 999 14 64

Source: Drusch, Kopka, and Kaeding (2007)

50

1.7.2 Thiol group content in fruits and vegetables

Thiols present in a variety of vegetables and fruits that function as natural antioxidants.

Examples of thiols encountered include L-γ-glutamyl-L-cysteinylglycine (reduced

glutathione, or GSH), cysteine (CYS), homocysteine (HCYS), captopril (CAP), and

N-acetyl-L-cysteine (NAC) (Table 1.8) (Demirkol, Adams, & Ercal, 2004; Manda,

Adams, & Ercal, 2010). Two of the widely studied thiols are glutathione (GSH) and

cysteine (CYS). GSH is a natural antioxidant and acts to sequester free radicals by

reversible conversion to GSSG (glutathione disulfide). Cysteine and homocysteine are

further thiol groups containing compounds that are generated by biosynthetic

pathways that contribute to protein synthesis but also act as anti-oxidizing agents.

51

Table 1. 8-Summary of the significant thiols present in various fruits and vegetables

Source: Zhimin, Demirkol, Ercal, and Adams (2005)

52

1.7.3 Nitrite content in fruits and vegetables

Nitrite can be converted to the unstable nitric oxide under suitable conditions. A

major concern regarding nitrite is the formation of carcinogenic N-nitroso compounds

by reaction of nitrite with various amines and amides in foods (Mirvish, 1975;

Mirvish, Cardesa, Wallcave, & Shubik, 1975). Leafy green vegetables are a rich

source of nitrate (Table 1.9) with spinach, lettuce, cabbage and celery representing

significant sources (Chung, Kim, Kim, Hong, Lee, Kim, et al., 2003). The nitrate can

be converted to nitrite by processing or as a result of microbial activity after

production or during short term storage (Meah, Harrison, & Davies, 1994). The nitrite

content ranged from 0.1 to 110 mg/L for raw juices before storage, storage at 4 °C for

24 hours and storage at 20 °C for 24 hours in different kinds of juices such as carrot

juice, cabbage juice and red beetroot juice (Tamme, Reinik, Puessa, Roasto,

Meremaee, & Kiis, 2010). Given that nitrite forms nitric oxide at acidic pH with the

presence of reducing agent such as ferrous ions, it is possible to contribute to the

degradation of patulin via HHP although no studies have been performed to date.

53

Table 1. 9- Nitrate content in the selected vegetables during different seasons Vegetables Winter (November-March)

(mg/kg) Summer (April-October)

(mg/kg) Mean Range Mean Range

Chinese cabbage 1291 131-3249 2009 208-5490 Radish 1494 789-2643 2108 766-4570 Lettuce 1933 247-3283 2728 884-4488 Spinach 3334 427-7439 4814 195-7793 Cucumber 267 83-580 180 1-649 Carrot 373 6-971 282 1-1158 Cabbage 730 29-1498 722 1-1788 Source: Chung, et al. (2003)

1.8 Fruit Flies (Drosophila melanogaster) and Toxicity Assay

The degradation of patulin is commonly detected by HPLC analysis (He, Li, & Zhou,

2009). In the course of degradation it is possible that the byproducts formed could be

equal to or greater in toxicity than patulin which may not be detected using techniques

such as HPLC. To assess the toxicity of compounds, it is common to determine the

fate of a viable organism when exposed to the agent. For example, historically the

Ames test using a histamine mutant of Salmonella Typhimurium has been used to

evaluate carcinogenic properties of toxicants (Ames, 1979; McCann, Choi, Yamasaki,

& Ames, 1975). Here, a carcinogen would result in a reverse mutation in the His gene

resulting in the loss of histidine auto tropism. Although relatively easy, the Ames test

is limited to testing carcinogens and may not represent the toxicity that would occur in

higher organisms (Abid-Essefi, Ouanes, Hassen, Baudrimont, Creppy, & Bacha, 2004;

Schaaf, Nijmeijer, Maas, Roestenberg, de Groene, & Fink-Gremmels, 2002). In this

regard the opposite side of the scale is to use human or more likely primate trials

which obviously have ethical implications (Eriksen & Pettersson, 2004; Galtier,

Alvinerie, & Charpenteau, 1981; McKinley, Carlton, & Boon, 1982; Sorenson,

Simpson, & Castranova, 1985).

54

The current study will assess the toxicity of the byproducts of high pressure degraded

patulin using a fruit fly model (Naranjo, Busto, Sellers, Sandor, Ruiz, Roberts, et al.,

1981; Tice, Agurell, Anderson, Burlinson, Hartmann, Kobayashi, et al., 2000). The

fruit fly has been widely used for biological research in studies of genetics,

physiology, microbial pathogenesis toxicity analysis and life history evolution (Bilen

& Bonini, 2005; Karamanlidou, Lambropoulos, Koliais, Manousis, Ellar, & Kastritsis,

1991; Krishna, Goel, & Krishna, 2014).

Fruit flies (Drosophila melanogaster) have been used as an animal model for the

acute toxicity analysis of mycotoxin and its degraded product in a number of studies

(Han, Geller, Moniz, Das, Chippindale, & Walker, 2014a; Llewellyn & Chinnici,

1978; Panigrahi, 1993; Siddique, 2014). Drosophila melanogaster have a complete

metamorphosis, including the stages of egg, larvae, pupae and adult fly as shown in

Figure 1.22 (Christenson & Foote, 1960). The toxicity of several mycotoxins

including citrinin, AFB1 and patulin on Drosophila melanogaster have ever been

evaluated in terms of larva survival and mutation frequency (Belitsky, Khovanova,

Budunova, & Sharuptis, 1985). Small but significant increase in the mutation level at

3.2x10-3 mol/L (492.8 ppm) of patulin was reported previously (Belitsky, Khovanova,

Budunova, & Sharuptis, 1985).

55

Figure 1. 22- The life cycle of fruit flies (Drosophila melanogaster)

Research Hypothesis and Objectives

Research Hypothesis

Patulin can be degraded or sequestered by high hydrostatic pressure through

interaction with fruit or vegetable constituents which in turn is dependent on the

intrinsic and extrinsic factors associated with the matrix.

Research Objectives

The overall objective of the thesis is to investigate the mechanisms and factors

affecting the HHP assisted degradation of patulin in model systems.

Objective 1: Develop an electrochemical sensor for patulin detection to facilitate

quantification of the mycotoxin.

Objective 2: Determine factors that affect the rate and extent of high pressure assisted

patulin degradation in model fruit and vegetable beverages.

56

Objective 3: Determine the contribution of ascorbic acid, thiol protein, oxidizing

agent and nitrite on the pressure assisted degradation of patulin.

Objective 4: Assess the toxicity of patulin degradation products using a fruit fly model.

57

Chapter Two

Electrochemical Based Sensor for

Quantification of Patulin in Beverages

58

Abstract

The mycotoxin patulin remains a significant food safety issue associated with apple

based beverages. Patulin is relatively stable to pasteurization processes and as a

consequence the main risk management step is through testing. Traditional

diagnostics for patulin detection are costly and laboratory based. Therefore, the first

objective of the study was to develop a rapid test for patulin to facilitate detection of

the mycotoxin during high hydrostatic pressure trials. It was anticipated that the

sensor could also form the basis for a diagnostic test that could be applied for field

testing fruit and vegetable juices. The sensing approach was based on the formation of

a patulin: pyrrole adducts that could be quantified using carbon strip electrodes used

in combination with Square Wave Voltammetry (SWV). The sensor was optimized

with respect to adduct formation and electrochemical detection. The optimized sensor

configuration had a detection range for patulin of 80 – 800 ppb. Although the sensor

response exhibited a strong correlation (r2 = 0.99) to patulin concentration, the

sensitivity of the device was insufficient to detect the mycotoxin when present at the

maximal allowable limit of 50 ppb.

2.1 Introduction

Conventional patulin detection is based on thin-layer chromatography (TLC) or high

performance liquid chromatography (HPLC) (Gokmen & Acar, 1999). The official

method includes a solid phase extraction (SPE) step to concentrate the patulin target

and remove potential interference. The extracted sample is then quantified using

HPLC, LC/MS or GC (Gilbert & Anklam, 2002). Although sensitive, current methods

59

for patulin are expensive, require technical expertise and are time consuming. As a

consequence there is demand for sensors that can be used to detect patulin with

minimal user input and without the need for complex analytical techniques (Maragos

& Busman, 2010). Sensors based on chemiluminescence and fluorescence assays have

been described that provide sensitive detection although prone to interference from

sample constituents (Liu, Gao, Niu, Li, & Song, 2008; Tsao & Zhou, 2000). In the

following an electrochemical patulin sensor based on using screen printed electrodes

(The electrode pattern includes a carbon working electrode, a carbon counter

electrode, and a silver/silver chloride reference electrode) was developed. Screen

printed electrodes have become an established approach for developing disposable,

low cost, sensor devices (Wang, 2002).

The sensing approach is based on the unique reaction between patulin and pyrrole.

Patulin has strong electrophilic properties that form the basis for the mycotoxin potent

action on thiol groups associated with proteins. The same characteristics also enable

patulin to form adducts with pyrrole. The patulin: pyrrole monomer can terminate the

formation of polypyrrole during electropolymerization leading to a decrease in

oxidation peak. The oxidation peak during polypyrrole formation can be measured

using amperometric or cyclic voltammetry although both methods suffer from high

background current due to the high capacitance of the conducting polymer. The high

capacitance reduces the sensitivity of the sensing approach and hence techniques such

as differential pulse or square wave voltammetry are preferred to decrease the

contribution of background current (Namvar, 2010). In previous work, Namvar (2010)

demonstrated that provided patulin was at a limiting concentration the decrease in

oxidative peak could be correlated to patulin concentration in the pyrrole mixture

60

during the electropolymerization process. In the following study the work was

extended by adapting the patulin assay to a screen printed electrode format. Screen

printed electrodes are preferred for sensor development due to low cost, consistency

and compatibility with single use devices.

2. 2 Materials and Methods

2.2.1 Reagents

Pyrrole, dimethyl sulfoxide (DMSO), patulin, acetic acid, malic acid, 5-

(Hydroxymethyl) furfural (5-HMF) and cysteine were purchased from Sigma-Aldrich.

Phosphate buffer solution was prepared by mixing suitable amounts of Na2HPO4,

KH2PO4, KCl and NaCl. pH was adjusted using 0.1 M HCl or 0.1 M NaOH. Pyrrole

was vacuum distilled and the electrolyte was degassed using nitrogen prior to SWV.

Patulin was dissolved in 0.1 % acetic acid distilled water. Apple juice of 12 Brix

diluted from apple juice concentrate (Sun Rich Company, Toronto, ON) was used.

2.2.2 Screen printed electrode preparation and electrochemistry

Cyclic voltammetry (CV) and square wave voltammetry (SWV) were conducted

using a BASi EC epsilon potentiostat (West Lafayette, Indiana, USA) in conjunction

with Epsilon EC-2000-XP software. Screen printed electrodes were sourced from Pine

Research Instrumentation (Durham, NC, USA) and consisted of a carbon working

electrode (5x4 mm carbon rectangle recessed in insulating layer), carbon counter

electrode (1x12 mm) and Ag/AgCl reference electrode. Prior to use the screen printed

electrode area was cleaned by an initial sonication step for 1 min in 50 % v/v ethanol

solution followed by potential cycling (4 cycles) between -1.2 to 1.2 V vs Ag/AgCl in

0.1 M HCl to remove any passivating layer from the working electrode.

61

The consistency of the screen printed electrodes was verified by generating a cyclic

voltammogram for ferricyanide (2 mM ferricyanide in 1 M potassium nitrate) by

scanning the potential between -1.2 and 1.2 V vs. Ag/AgCl at a rate of 100 mV/s.

Electrodes were considered acceptable if the oxidative and reductive peaks were

within a 10 % tolerance limit.

2.2.3 Patulin assay

Test patulin concentrations were prepared in 0.1 % v/v acetic acid. 100 µl of patulin

acetic acid solution was dispensed into 1 ml amber tubes containing 100 µl of 1 ppm

freshly distilled pyrrole in DMSO. The mixture was held to test time at room

temperature (23 °C) in the dark to prevent photo-oxidation reactions. Aliquots (2 µl)

of the mixture were then dispensed onto the working electrode surface and allowed to

dry for 10 minutes before performing square wave voltammetry (SWV). The screen

printed electrode was placed into an electrochemical cell containing 0.1 M phosphate

buffer adjusted to the test pH as supporting electrolyte. The potential range of SWV

was 800 to 1900 mV with potential step of 4 mV, square wave amplitude of 25 mV

and frequency from 15 to 100 Hz. The oxidation peak was recorded using Epsilon

EC-2000-XP software.

2.2.4 Extraction of patulin

Aliquots of 150 µl pectinase enzyme solutions (3800 units/mL) were added to 20 ml

juices samples that were subsequently incubated for 2 h at 40 °C and then centrifuged

at 4500 × g for 5 min. The patulin was extracted from the supernatant of the

centrifuged juice using SPE method (Eisele & Gibson, 2003). The SPE cartridge

(Oasis HLB extraction cartridge, Waters Corp., Milford, MA) was conditioned by

62

passing 2 x 3 ml of methanol through the column which was then equilibrated with 2

x 3 ml of water before loading 2.5 ml of the juice sample. The cartridge was then

washed using 2 x 3 ml of 1 % acetic acid solution. Patulin was eluted with 1 ml ethyl

acetate and then evaporated to dryness under a stream of nitrogen at 40 °C. The dried

extract was suspended in 1 mL of 0.1 % acetic acid solution.

2.2.5 HPLC-UV analysis of patulin

The concentration of patulin in prepared standards was determined using RP-HPLC

(Agilent Technologies 1200 Series, Palo Alto, CA) in combination with a UV detector

operating at 276 nm. A Phenomenex Phenosphere C18 column with 3µm particle size

(150×4.6 mm) with a C18 guard column (Torrance, CA, USA) was used as the

separation column. The mobile phase consisted of 5% v/v acetonitrile and 0.05 % v/v

acetic acid in distilled water at a flow rate of 1 mL/min with run time of 20 min.

2.2.6 The Ellman assay of thiols in juice

In order to determine the amount of the interfering component, the sulfhydryl content

of the samples was determined spectrophotometrically in a UV–Vis plate reader (EL

340, Bio-Tek Instruments Inc., Winooski, VT, USA) at 420 nm by monitoring the

absorbance of the yellow product, 5-thio-2-nitrobenzoic acid (NTB) reducing from

5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) by the sulfhydryl group, according to a

described procedure of Riener, Kada, and Gruber (2002) with some modifications.

Briefly, 150 µl working solution (mixing 8 ml of 100 mM potassium phosphate buffer,

pH 7.0 and 228 µl of DTNB Stock Solution (1.5 mg/ml) in DMSO) was mixed with

10 µl sample or a bovine serum albumin (BSA) standard solution in a 96 well plate.

The reaction was conducted at room temperature for 5 min at which time the

absorbance was stabilized. All samples were tested in triplicate.

63

2.2.7 Statistical analysis

All the experiments were performed with three replicates. The results were expressed

as mean values and standard deviation (SD). The results were analyzed using one-way

analysis of variance (ANOVA) followed by Tukey’s HSD test with α=0.05. The

analysis was carried out using SPSS statistics 17.0 (IBM Corporation, Armonk, New

York, U.S.A.).

2.3 Results and Discussion

2.3.1 The validation of electrode cards

The cleaned screen printed electrodes were found to have consistent performance

based on the cyclic voltammetry of ferricyanide. The peak separation of the oxidation

reduction peaks was 177 mV which is expected from a catalytic electrode surface

(Figure 2.1). From the voltammogram the working surface area of the electrode was

10.38 mm2.

Figure 2. 1- Cyclic voltammetry of screen printed electrode cards in 2 mM potassium ferricyanide with 1 M potassium nitrate in distilled water at the scan rate of 100 mV/s after sonication treatment

64

2.3.2 Optimization of patulin: pyrrole adduct formation

Patulin (0 - 500 ppb) in 0.1 % acetic acid was mixed with 1000 ppb pyrrole in DMSO

and the mixtures were incubated in the dark for 10 - 80 min prior to performing SWV.

The decrease in oxidation peak was found to be dependent on the reaction time for

forming the pyrrole: patulin adduct (Figure 2.2). The peak currents decreased from

48.86±2.08 μA to 36.55±2.12 μA (500 ppb of initial patulin concentration in the

mixture) with a 30 min reaction time which was significantly different (P<0.05)

compared to controls containing 0 ppb patulin in the reaction mix. Longer incubation

times of 80 min resulted in a further significant (P<0.05) reduction in oxidation peak

current from 48.86±2.08 μA to 28.14±1.94 μA. The decrease in oxidation peak was

caused by the generation of patulin: pyrrole adduct that caused termination of polymer

formation via electropolymerization of the free pyrrole monomer units. The results are

in agreement with Namvar (2010) who also reported a time dependent effect on

adduct formation. It is also possible that additional parameters such as temperature

could have affected the rate of adduct formation. Yet, given that acceptable peak

reductions were observed using the tested reaction conditions a 60 min incubation

period was selected for subsequent trials (Figure 2.2).

2.3.3 Effect of supporting electrolyte pH on sensor response

The effect of supporting electrolyte pH on the changes in oxidative peak was

determined using phosphate as the buffering salt (Figure 2.3A and 2.3B). It was found

that the oxidation peak shifted to positive potentials as the pH of the supporting

electrolyte became acidic (Figure 2.3A). This was to be expected given that the

polymerization of pyrrole is known to be enhanced in acidic solutions due to the

presence of protons to facilitate the electro-oxidation reaction (Diaz, Kanazawa, &

65

0

5

10

15

20

25

0 20 40 60 80 100

Time (minute)

Curren

t (μA)

Gardini, 1979; Gospodinova & Terlemezyan, 1998). In terms of the oxidation peak

current, the highest response (i.e. difference between control and reaction mix

containing adduct) was observed at pH 5 with decreased response either side of the

optima (Figure 2.4). The results can be explained by the higher rate of pyrrole

polymerization at acidic pH and it is possible that branching to the elongating

polypyrrole occurred due to the termination of linear chains by reaction with patulin:

pyrrole adducts. At neutral pH the electropolymerization of pyrrole monomers can be

hindered through dimerization that effectively inhibits electropolymerization at alkali

pH values. In the current case it could be that at pH 5 the reactivity of polypyrrole and

pyrrole: patulin adduct would be sufficient to observe the termination step of polymer

elongation relative to controls.

Figure 2. 2- The effect of incubation time on the current of the decrease in oxidation peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 0.1 M phosphate buffer of pH 4, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The step E was 4 mV. S.W. amplitude was 25 mV and the S.W. frequency was 20 Hz.

66

Figure 2. 3- The effect of pH on the position (A) and current (B) of the decrease in oxidation peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 0.1 M phosphate buffer, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The step E was 4 mV. S.W. amplitude was 25 mV and the S.W. frequency was 20 Hz.

‐60

‐40

‐20

0

20

40

60

80

100

3 3.5 4 4.5 5 5.5 6 6.5

pH

potential(m

V)

A

0

5

10

15

20

25

30

3 3.5 4 4.5 5 5.5 6 6.5

pH

Curren

t(μA)

B

67

Figure 2. 4- The effect of pH on the position and the current of the decrease in oxidation peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 0.1 M phosphate buffer, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The step E was 4 mV. S.W. amplitude was 25 mV and the S.W. frequency was 20 Hz.

2.3.4 Effect of the potential

The effects of the potential (the difference between the initial potential and final

potential applied) on the current and position of the decrease in oxidation peak to

control were investigated ranging from 0.8 V to 1.9 V. The initial potential was from

400 mV to 1500 mV and the final potential was -400 mV. The results were as shown

in Figure 2.5A and 2.5B.

In terms of peak position, by shifting the potential to more positive values, the peak

position potential decreased from 76 mV to 28 mV, a little shift towards negative

value as shown in Figure 2.5A. However, the difference current increased from 5.26

pH5.5

pH3

pH3.5

pH5

pH4

pH6

68

μA to 21.27 μA as the potential applied increased from 0.8 V to 1.6 V and decreased

from 21.27 μA to 16.00 μA as the potential applied increased from 1.6 V to 1.9 V

(Figure 2.5B). The observations indicate that the position and current of the decrease

in oxidation peak to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000

ppb pyrrole and 0 ppb patulin mixture) are related to the potential applied. Among the

applied potentials investigated, the potential of 1.6 V could lead to the highest

difference current and was selected as the potential applied for the following studies.

Figuthe mixNotwas 2.3.

The

of th

of c

shor

ure 2. 5- Thdecrease in

xture to 1000te: 0.1 M phs 4 mV, S.W

5 Effect of

e principle o

he pulse tim

current mea

rter duration

0

10

20

30

40

50

60

70

80

90

0

potential(m

V)

he effect of n oxidation0 ppb pyrro

hosphate buW. amplitude

f the S.W. fr

of SWV is t

me. The low

asurement w

n and hence

.7 0.9

f the potentin peak to cole and 0 ppuffer of pH 5e was 25 mV

frequency

o apply a po

wer the frequ

will be. Wh

e likely incl

1.1

69

ial applied ocontrol (100pb patulin m5, screen priV and the S

otential step

uency, the l

hen high fre

ludes a prop

1.3 1.5

Potential

on the posit00 ppb pyr

mixture) inted electro

S.W. frequen

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equencies a

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5 1.7

tion (A) andrrole and 5

ode cards. Tncy of 20 H

frequency be

pulse durati

are applied

apacitive cu

1.9 2

A

B

d current (B500 ppb pat

The step chaHz.

eing the inv

on and the

the pulse i

urrent. From

2.1

B) of tulin

ange

verse

time

is of

m the

70

results it was found that the peak current difference (i.e. decrease in oxidative peak)

increased with frequency up to 75 Hz then plateaued (Figure 2.6 and Figure 2.7). The

dependency of peak oxidation current as a function of the frequency indicates the

contribution of capacitive and faradic current response from the elongating

polypyrrole but also illustrates that the reaction was dependent on the diffusion of

reactants (i.e. monomer) to the electrode surface as opposed to being limited by the

electron transfer reaction.

71

Figure 2. 6-The effect of the S.W. frequency on the current of the decrease in oxidation peak relative to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 1: the S.W. frequency of 100 Hz, 2: 95 Hz, 3: 85 Hz, 4: 75 Hz, 5: 65 Hz 6: 55 Hz, 7: 45 Hz, 8: 35 Hz, 9: 25 Hz and 10: 15 Hz. 0.1 M phosphate buffer of pH 5, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The step E was 4 mV. S.W. amplitude was 25 mV.

72

Figure 2. 7-The effect of the S.W. frequency on the current of the decrease in oxidation peak relative to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 0.1 M phosphate buffer of pH 5, screen printed electrode cards the initial potential was 1200 mV and the final potential was -400 mV. The step E was 4 mV. S.W. amplitude was 25 mV.

y = 0.3455x + 16.485R² = 0.9916

0

5

10

15

20

25

30

35

40

45

50

0 20 40 60 80

S.W. frequency(Hz)

Curren

t(μA)

73

2.3.6 Dose response curve of the sensor towards patulin

A dose response curve was generated by inclusion of different levels of patulin in the

reaction mix to form the patulin: pyrrole adduct. The decrease in oxidation peak when

reacting pyrrole with patulin to form the adduct was significantly (r2 = 0.99)

correlated to the concentration of the mycotoxin within the range of 80 – 800 ppb

(Figure 2.8) and were in agreement with the standard HPLC based method of analysis

(Table 2.1). The limit of detection (LOD) was 14 ppb, calculated based on a three

times signal to noise ratio and the limit of quantification (LOQ) was 45 ppb,

calculated based on a ten times signal to noise ratio (Armbruster, Tillman, & Hubbs,

1994; Murillo-Arbizu, Gonzalez-Penas, Hansen, Amezqueta, & Ostergaard, 2008; Wu,

Dang, Niu, & Hu, 2008). The sensor response was reproducible with a relative

standard deviation (RSD) of 1.2 %.

Trials were performed to determine the sensor performance using apple juice spiked

with patulin. Here the apple juice replaced the 0.1 % v/v acetic acid when forming the

pyrrole: patulin adducts. It was found that apple juice alone inhibited the oxidation of

pyrrole thereby resulting in the failure of the monomer to polymerize and lack of an

oxidative peak.

In order to determine the inhibitor within apple juice, further trials were performed

using constituents in buffered solution. Malic acid constitutes the main acid associated

with apple juice (Mattick & Moyer, 1983). In the current study, the addition of malic

acid up to 10 ppm did not have a positive or negative effect on reaction between

patulin and pyrrole through the electropolymerization process (Table 2.2 and Figure

2.9)

Hydroxymethyl furfural (5-HMF) is commonly found in thermally processed apple

74

juice and interferes with detection of patulin by HPLC ((Rupp & Turnipseed, 2000).

In the current study, 5-HMF did not have a negative effect on the patulin: pyrrole

adducts or electropolymerization process when applied at levels in the order of 2000

ppb (Table 2.2 and Figure 2.9). However, the adduct formation and the

electropolymerization reaction were negatively affected by the inclusion of cysteine

(3-6 ppm) in the reaction mix. As an antioxidant it is likely that the cysteine

sequestered the patulin to prevent adduct formation. The concentration of thiol groups

within apple juice was determined using the Ellman Assay. From sampling retail store

brought apple juice the average thiol content was found to be 3.21±0.33 μM which

would be higher than would be expected patulin concentration if present. Therefore,

in the current case the inhibition of the sensor response when patulin was introduced

via apple juice was caused by the reactivity of the mycotoxin with thiol containing

compounds.

75

Figure 2. 8- Correlation relationship between patulin concentration and the current of the decrease in oxidation peak relative to control (1000 ppb pyrrole and 0 ppb patulin mixture) using square wave voltammetry Note: The incubation time was 60 minutes. 0.1 M phosphate buffer of pH 5, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The S.W. frequency was 75 Hz. The step E was 4 mV and the S.W. amplitude was 25 mV.

y = 9.6194x + 29.884R² = 0.9916

0

100

200

300

400

500

600

700

800

900

0 20 40 60 80 100

Current (μA)

patulin(ppb)

76

Table 2. 1- Determination of patulin concentration using HPLC and the developed electrochemical sensor

Values are means ± standard deviations (n = 3) for all analyses.

Sample number HPLC detected(ppb) Electrochemical sensor detected (ppb)

1 134.38±1.12 135.16±1.622 248.15±1.46 246.96±1.283 198.36±1.37 197.75±1.844 423.96±1.54 425.18±1.265 362.17±1.68 362.84±1.38

77

Table 2. 2- The current (μA) of the decrease in oxidation peak relative to controls (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) using square wave voltammetry Samples Current of oxidation peak

decrease Patulin acetic acid solution 42.17±3.21 Patulin acetic acid solution(10 ppm malic acid) 43.25±2.89 Patulin acetic acid solution(2 ppm 5-HMF) 42.11±2.58 Values are means ± standard deviations (n = 3) for all analyses. Note: The incubation time was 60 minutes. 0.1 M phosphate buffer of pH 5, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The S.W. frequency was 75 Hz. The step E is 4 mV and the S.W. amplitude was 25 mV.

78

Figure 2. 9- The current of the decrease in oxidation peak relative to control (1000 ppb pyrrole and 500 ppb patulin mixture to 1000 ppb pyrrole and 0 ppb patulin mixture) Note: 1: Patulin acetic acid solution, 2: Patulin acetic acid solution (10 ppm malic acid), 3: Patulin acetic acid solution (2 ppm 5-HMF). 0.1 M phosphate buffer of pH 5, screen printed electrode cards, the initial potential was 1200 mV and the final potential was -400 mV. The S.W. frequency was 75 Hz. The step E is 4 mV. S.W. amplitude was 25 mV.

79

2.4. Conclusion

The study demonstrated proof-of-principle that the formation of adduct between

patulin and pyrrole can form the basis of a sensor for quantification of the mycotoxin.

The adduct formation was optimized along with the Square Wave Voltammetry

parameters. Although the sensor response was in agreement with the HPLC method

there was significant interference when attempting to detect patulin in apple juice. As

a consequence the patulin would require extraction prior to analysis and hence would

not provide significant advantages of the HPLC analytical method.

80

Chapter Three High Hydrostatic Pressure Assisted Degradation of Patulin in Fruit and Vegetable Beverages

81

Abstract

Patulin is a recognized biohazard in apple based beverages and there is a need for

interventions to reduce levels of the mycotoxin. In the following study the degradation of

patulin introduced into different juices then treated using high hydrostatic pressure (HHP) was

evaluated. The apple based juices tested were AS (apple and spinach), PAM (Pineapple,

Apple and Mint), CAB (Apple, Carrot, Beet, Lemon and Ginger) and GJ (Romaine, Celery,

Cucumber, Apple, Spinach, Kale, Parsley and lemon) juices. The extent of patulin

degradation was found to be dependent on applied pressure, time of processing and the

intrinsic characteristics of the juice. GJ juice supported the highest degradation in patulin with

degradations in the order of 30 % (60 ppb) with a treatment time of 300 s at 600 MPa. In

comparison, the same processing conditions resulted in 33 ppb in PAM juice. When the

compositions of juices were compared it was noted that GJ that supported the highest

degradation of patulin, contained the highest levels of thiol groups and nitrite relative to the

other juice types tested. From using buffered patulin containing solutions it was demonstrated

that the thiol content of the juice was the dominating factor that supported the high pressure

assisted degradation of patulin. In contrast, ascorbic acid had a negligible role in high pressure

degradation of patulin. Supplementing beverages with hydrogen peroxide or nitrite were

found to enhance the reduction of patulin in juices with HHP treatment. From the results it

can be concluded that pressure does not directly degrade patulin but enhances nucleophilic

attack on the lactone ring. The study has illustrated that high pressure processing can be

considered as a further tool in the risk management of patulin in apple based beverages.

3.1 Introduction

High hydrostatic pressure (HHP) has become increasingly popular for the non-thermal

pasteurization of raw juices (Buzrul, Alpas, Largeteau, & Demazeau, 2008; Erkmen & Dogan,

2004). As a non-thermal pasteurization method, HHP supports pathogen reduction whilst

82

retaining the raw sensory quality of the product (Linton, McClements, & Patterson, 1999;

Patterson & Kilpatrick, 1998). The majority of studies to date have focused on pathogen

inactivation by HHP with relatively little directed towards determining the fate of mycotoxins.

The mycotoxin, citrinin, was reduced by 1.3 % to 100 % by HHP processing of 250 MPa

(Tokusoglu, Alpas, & Bozoglu, 2010). Bruna (1997) reported that HHP treatments led to a

patulin reduction by up to 62 % in apple juice. The authors reported that patulin degradation

was enhanced by mild heat (50 °C) and HHP combined treatment. However, it can be

predicted that by using high temperatures during HHP would result in loss of raw sensory

characteristics, active enzymes and nutrients which are considered quality indicators of raw

juice products (Hendrickx, Ludikhuyze, Van den Broeck, & Weemaes, 1998; Oey, Lille, Van

Loey, & Hendrickx, 2008; Polydera, Stoforos, & Taoukis, 2003; Sancho, Lambert, Demazeau,

Largeteau, Bouvier, & Narbonne, 1999; Tewari, Jayas, & Holley, 1999).

The contribution of ascorbic acid, thiol groups and nitrite on the high pressure assisted

degradation of patulin is not further explored. From previous work it is theorized that the

hemiacetal group and the lactone ring of patulin are susceptible to attack from nucleophilic

groups such as thiol, nitrite and peroxide (Figure 3.1) (Fliege & Metzler, 1998, 1999, 2000a,

2000b; Karaca & Velioglu, 2009). Fliege and Metzler (2000b) reported that initial SH-

addition at C-2 and C-6 of patulin was identified during the interaction with N-acetylcysteine

and glutathione. The aim of this part of the work is to probe further into the mechanisms of

HHP patulin degradation and identify the dependent factors that facilitate the reaction.

FigucomSou

3.2

3.2.

Patu

5,5'-

acid

Asco

Thio

Hydpero

Nitri

ure 3. 1- Tmponents anurce: Fliege

Material

1 Reagents

ulin, aceton

-dithiobis-(

d, hydrogen

orbic acid

ol

drogen oxide

ite

The schematnd patulin

and Metzle

ls and Me

s

nitrile (ACN

2-nitrobenz

n peroxide

tic diagram

er (1999, 20

ethods

N), methano

zoic acid) (D

solution (3

83

m of the int

00b); Karac

l, ethyl acet

DTNB), bo

0 % v/v in

P

eraction be

ca and Velio

tate, acetic

ovine serum

n H2O), iro

Patulin

etween the

oglu (2009)

acid, metap

m albumin (

n(II) chlori

aforementio

)

phosphoric a

(BSA), asco

ide and sod

oned

acid,

orbic

dium

84

nitrite were purchased from Sigma-Aldrich (St. Louis., MO, USA). Griess reagent for

nitrite assay kit colorimetric was provided by Abcam Inc (Cambridge, MA, USA).

3.2.2 Model fruit and vegetable beverage preparation

Fresh spinach (200 g) was obtained from a local supermarket and suspended in 500

ml of distilled water then blended to form a homogenate. After blending, the spinach

juice was centrifuged at 5000 × g for 10 min to remove large particulates. The

supernatant juice was diluted in distilled water to a ratio 1 part homogenate to 2 parts

water to form spinach juice.

Apple juice concentrate (71 °Brix) was diluted with distilled water to a final brix of

12 and then diluted using the spinach juice (1:1) with the pH being adjusted to 3.5

using lemon juice (subsequently referred to as AS). The other juices tested were

supplied by Blue Print Cleanse (NY, USA). PAM (Pineapple, Apple and Mint), CAB

(Apple, Carrot, Beet, Lemon and Ginger), and GJ (Romaine, Celery, Cucumber,

Apple, Spinach, Kale, Parsley and Lemon) juices were supplied by BluePrint Cleanse.

The acetate buffer system consisted of 0.2 M acetic acid solution and 0.2 M sodium

acetate solution then adjusted to the appropriate pH.

3.2.3 Juice characterization

The pH values of the different juices were measured using a pH meter (model 868,

Thermo Orion, MA, USA). The ascorbic acid content was determined according to

the method described by Patil et al. (2004). Briefly, the sample was homogenized

with extraction solution (final concentration of 3 % metaphosphoric acid and 2 %

acetic acid). The resulting mixture was centrifuged and the supernatant was filtered

through a 0.45 µm membrane filter and analyzed by HPLC at 254 nm (Agilent

85

Technologies 1200 Series, Palo Alto, CA). A Phenomenex Phenosphere C18 column

with 3µm particle size (150×4.6 mm) with a C18 guard column (Torrance, CA, USA)

was used as the separation column. The entire chromatographic separation was

performed at an isocratic mobile phase of 0.1 % metaphosphoric acid at 1 ml/min and

the run time was 10 min. All samples were prepared in triplicate in HPLC with a 10 µl

injection volume.

The sulfhydryl content of the samples was determined spectrophotometrically in a

UV–Vis plate reader by EL 340, Bio-Tek Instruments Inc. (Winooski, VT, USA) at

420 nm as described in the Section 2.2.5. Sulfhydryl content was measured by

monitoring the absorbance of the yellow product, 5-thio-2-nitrobenzoic acid (NTB)

reducing from 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) by sulfhydryl group,

according to a described procedure of Riener, Kada, and Gruber (2002) with some

modifications. Briefly, 150 µl working solution(mixing 8 ml of 100 mM potassium

phosphate buffer, pH 7.0 and 228 µl of DTNB stock solution (1.5 mg/ml) in DMSO)

was mixed with 10 µl sample or bovine serum albumin (BSA) standard solution in a

96 well plate. The reaction was conducted at room temperature for 5 min at which

time the absorbance was stabilized. All samples were tested in triplicate.

Nitrite concentration was determined by Griess reagent for nitrite assay kit

colorimetric by Abcam Inc. (Cambridge, MA, USA) at 540 nm. For nitrite

determination, 80 μl sample solution and 20 μl buffer solution was mixed in the 96-

well plate along with 50 μl of Griess Reagent A. After 5 minutes, 50 μl of Griess

Reagent B was added to each well, and mixed. The mixture was incubated for 10

minutes at room temperature, and the absorbance was measured at 540 nm with a

microplate reader.

86

3.2.4 HHP processing treatment

The juices were dispensed in 25 ml aliquots into pouches and subsequently spiked

with the appropriate concentration of patulin. The pouches were vacuum sealed to

exclude air and transported in a cold box to the HHP processing facility. The HHP

unit was a Hyperbaric 51 L capacity chamber that could apply pressures up to 600

MPa (Figure 3.2). All treatments were undertaken at 11 °C unless otherwise stated.

Figure 3. 2- High Pressure Processing unit, 51 L, Hyperbaric

Vacuum packed juices or buffer solutions of 25 ml (prepared as in Figure 3.3 and

Figure 3.4) were pressurized in a HHP unit (51 L; Gridpath Solutions Inc., Stoney

Creek, ON, Canada) at pressures ranging from 400 MPa to 600 MPa for different

holding times (0 to 300 s) at 11 °C respectively.

87

Acetic acid buffer system, pH 4

(BSA 0 and 30 mg/ml, 20 ppm patulin)

Patulin and

sulfhydryl group

determination

600 MPa, 300 s

Figure 3. 3- Experimental design used for the identification of the presence of interaction between patulin and thiol protein, ascorbic acid, hydrogen peroxide or nitrite during High Pressure Processing


(Aa 0 and1000 ppm, 200ppb patulin)

AS juice

(Aa 0 and1000 ppm added, 200 ppb patulin)

Patulin analysis 600 MPa, 300 s

Apple juice

(200 ppb patulin,

different concentration of

H2O2)

Patulin analysis

600 MPa, 300 s

Ascorbic acid (Aa) and patulin

Hydrogen peroxide and patulin

Thiol and patulin

88

Figure 3. 4- Experimental design used for the identification of the presence of interaction between patulin and thiol protein, ascorbic acid, hydrogen peroxide or nitrite during High Pressure Processing

Patulin analysis

AS juice

(200 ppb patulin)

Preheat 50 oC, 180 s

AS juice

(200 ppb patulin)

Preheat 50 oC, 180 s

600 MPa, 180 s

AS juice

(200 ppb patulin)

600 MPa, 180 s

AS juice

(20 ppm patulin) Patulin and nitrite analysis

Preheat 50oC, 180 s

600 MPa, 180 s

Nitrite and patulin

89

Figure 3. 5- Experimental design used for analysing patulin degradation kinetic in sulfhydryl protein, oxidizing agent or nitrite model solution (acetate buffer model solution at pH 3.5, 4 and 4.5) after the pressure of 400 MPa, 500 MPa and 600 MPa for the treatment time (0 to 300 s, 30 s as the interval) Note: The nitrite model system was preheated at 50 °C for 180 s before the HHP treatment.

3.2.5 Extraction of patulin

Aliquots of 150 µl pectinase enzyme solutions (3800 units/ml) were added to 20 ml

juices samples that were subsequently incubated for 2 h at 40 °C and then centrifuged

at 4500 × g for 5 min. The patulin was extracted from the supernatant of the

centrifuged juice using SPE method (Eisele & Gibson, 2003). The SPE cartridge

(Oasis HLB extraction cartridge, Waters Corp., Milford, MA) was conditioned by

passing 2 x 3 ml of methanol through the column and then equilibrated with 2 x 3 ml

of water before loading 2.5 ml of the juice sample. The cartridge was then washed

Sulfhydryl protein model system

(1, 2 and 3 mg/ml BSA acetate buffer)

Oxidizing agent model system

(0.3 %, 0.5 % and 0.7 % H2O

2 +1 mM/L ferrous ions)

Nitrite model system

(5.7, 11.4 and 17.1 mg/L nitrite +1 mM/L ferrous ions)

200 ppb

patulin spiked

Vacuum

sealed

HHP HPLC

90

using 2 x 3 ml of 1 % acetic acid solution. Patulin was eluted with 1 ml ethyl acetate

and then evaporated to dryness under a stream of nitrogen at 40 °C. The dried extract

was suspended in 1 ml of 0.1 % acetic acid solution.

3.2.6 HPLC-UV analysis of patulin

Patulin was quantified using RP-HPLC (Agilent Technologies 1200 Series, Palo Alto,

CA) equipped with a quaternary pump, an online degasser and a wavelength set at 276

nm. The method was the same as described in the section of 2.2.4. A Phenomenex

Phenosphere C18 column with 3 µm particle size (150×4.6 mm) with a C18 guard

column (Torrance, CA, USA) was used as the separation column. The mobile phase

consisted of 5 % v/v acetonitrile and 0.05 % v/v acetic acid in distilled water at a flow

rate of 1 ml/min with run time for 20 min.

3.2.7 Patulin degradation kinetic in sulfhydryl protein, hydrogen peroxide or

nitrite buffer solution

Acetate buffered solutions (pH 3.5, pH 4 and pH 4.5) were prepared containing 1, 2,

and 3 mg/ml of BSA or 0.3 %, 0.5 % and 0.7 % of H2O2 and 1 mM/L ferrous ions or

5.7, 11.4 and 17.1 mg/L of nitrite and 1 mM/L ferrous ions (Figure 3.4). Patulin was

added to each solution to give a final concentration of 200 ppb. Residual patulin

following HHP processing was quantified by HPLC-UV. The data were fitted using

biphasic model, Weibull model or first order model as appropriate using Matlab

software (Table 3.1).

91

Table 3. 1- Models selected for patulin reduction kinetic screening

Note: Ct is the concentration at the treatment time = t, C0 is the concentration at time=0, f in the biphasic model is the fraction parameter, k1 is the kinetic parameter in the first phase, k2 is the kinetic parameter in the second phase. k in the first order model is the kinetic rate parameter. k in the Weibull model is the kinetic rate parameter and a is shape parameter (dimensionless).

3.2.8 Data analysisAll the experiments were performed with three replicates. The results were expressed

as mean values and standard deviations (SD). The results were analyzed using one-

way analysis of variance (ANOVA) followed by Tukey's HSD test with α=0.05. The

analysis was carried out using SPSS Statistics 17.0 (IBM Corporation, Armonk, New

York, USA). The screening of models and the estimation for model parameters were

conducted using Matlab R2011a (Math Works Inc., Natick, Massachusetts, USA).

The surface response analysis was carried out using Design Expert 7.0 (Stat-Ease, Inc.,

Minneapolis, Minnesota, USA).

92

3.3 Results

3.3.1 Juice characterization by the determination of ascorbic acid, SH group and

nitrite content

The ascorbic acid concentration of the different juices varied between 1.34 – 1.57 mg/100 ml

with PAM (Pineapple, apple and mint) having the highest and GJ (Romaine, celery, cucumber,

apple, spinach, kale, parsley and lemon) the lowest (Table 3.2). The concentration of thiol

groups in the different juices varied from 3.93 – 9.67 μM. The highest levels of thiol were

present in GJ juice with PAM containing the lowest concentration (Table 3.2). With respect to

the nitrite concentration, GJ juice contained the highest levels (24 ppm) with CAB (Apple,

carrot, beet, lemon and ginger juice) having the lowest concentration (Table 3.2).

Table 3. 2- pH, Brix, ascorbic acid, sulfhydryl group and nitrite content in the juices before HHP treatment: AS (Apple and spinach juice), PAM (Apple, pineapple and mint juice), CAB (Apple, carrot, beet, lemon and ginger juice), GJ (Apple, romaine, celery, cucumber, spinach, kale, parsley and lemon juice) Juice types

pH Brix Ascorbic acid (mg/100ml)

Sulfhydryl group (µM/L)

Nitrite (mg/L)

AS 3.55±0.08a 6.6±0.1b 1.42±0.03b 6.13±0.35b 17.83±0.24c PAM 3.71±0.02b 10.9±0.1d 1.57±0.02c 3.93±0.31a 5.07±0.47b CAB 3.83±0.02c 8.3±0.1c 1.49±0.02b 6.90±0.36c 2.14±0.34a GJ 4.22±0.04d 3.8±0.1a 1.34±0.03a 9.67±0.50d 23.64±0.31d Values are means ± standard deviations (n = 3) for all analyses.

3.3.2 High hydrostatic pressure assisted degradation of patulin in different juices

The test juices were spiked with 200 ppb patulin and then subjected to different HHP

regimes. The extent of patulin degradation was dependent on the applied pressure and

duration of treatment. With the apple spinach combination (AS juice) the highest level

of patulin degradation (43 ppb) was recorded for treatments at 600 MPa for 300 s

(Figure 3.5A). HHP treated PAM juice achieved a decrease of 33.3 ppb with samples

treated for 300 s at 600 MPa (Figure 3.5B).

93

The highest decrease in patulin in CAB juice was 45 ppb using 600 MPa for 300 s

(Figure 3.5C). The highest level of patulin degradation was observed in GJ juice with

a decrease of 60 ppb (Figure 3.5D). The kinetics of patulin degradation in GJ juice

followed diphasic behaviour with an initial rapid degradation followed by a slower

rate at extended treatment times. The degradation rates for the four kinds of juices

were as shown in Table 3.3.

The extent of patulin degradation by HHP processing was enhanced by applying an

initial heat treatment at 50 °C for 180 s in the four kinds of juices spiked with 200 ppb

patulin (Table 3.4). It was found that patulin decreased by 174 ppb, 112 ppb, 84 ppb,

and 177 ppb in AS, PAM, CAB, and GJ juice respectively as shown in Table 3.4.

94

Figure 3. 6- Patulin degradation in AS juice (A: Apple and spinach juice), PAM juice (B: Apple, pineapple and mint juice), CAB juice (C: Apple, carrot, beet, lemon and ginger juice) and GJ juice (D: Apple, romaine, celery, cucumber, spinach, kale, parsley and lemon juice).

0

10

20

30

40

50

60

70

0 60 120 180 240 300

600MPa

500MPa

400MPa

Time (s)

Patulin

reduction (ppb)

AS Juice A

0

10

20

30

40

50

60

70

0 60 120 180 240 300

600MPa

500MPa

400MPaPatulin

reduction (ppb)

Time(s)

PAM JuiceB

Figu(B: gingpars

ure 3. 7- PaApple, pin

ger juice) asley and lem

0

10

20

30

40

50

60

70

0

Patulin

reduction (ppb)

atulin degradeapple and and GJ jui

mon juice).

60

dation in Amint juice)

ice (D: Ap

120 18

Tim

CAB

95

AS juice (A: ), CAB juic

pple, romain

80 240

me(s)

Juice

Apple and ce (C: Applne, celery,

300

spinach juile, carrot, bcucumber,

600MPa

500MPa

400MPa

C

D

ice), PAM jbeet, lemon spinach, k

juice and kale,

96

Table 3. 3- The degradation rates of the four kinds of juices at different pressures Juice type Degradation rate (ppb/min)

400 500 600 AS 2.70 2.70 6.41 6.41 8.72 8.72PAM 2.63 2.63 4.40 4.40 6.65 6.65CAB 2.58 2.58 6.39 6.39 11.50 7.27GJ 8.02 4.34 10.28 4.81 15.65 7.79

97

Table 3. 4-Performance of patulin degradation (ppb) in four kinds of beverages at 600 MPa after preheat treatment (50 °C for 180 s). AS (Apple and spinach juice), CAB (Apple, carrot, beet, lemon and ginger juice), PAM (Apple, pineapple and mint juice), GJ (Apple, romaine, celery, cucumber, spinach, kale, parsley and lemon juice). The juices were spiked with 200 ppb of patulin Pressure/time Patulin degradation (ppb) AS CAB PAM GJ

600MPa/60s 72.73±1.62 23.51±0.61 38.42±0.92

91.38±0.71

600MPa/180s 172.29±0.56 55.38±1.09 87.41±1.08

171.12±1.34

600MPa/300s 174.29±0.62 83.87±1.01 111.64±1.22

177.40±1.02

Values are means ± standard deviations (n = 3) for all analyses. Note: The extraction rate of patulin in AS, CAB, PAM and GJ juices is 90.94 %, 95.51 %, 90.57 % and 88.41 %, respectively.

98

3.3.3 Correlation of HHP assisted patulin degradation with juice constituents

The decrease of ascorbic acid, thiol content and nitrite was measured in AS juice

spiked with 200 ppb of patulin after HHP treatment of 600 MPa (0, 60, 180 and 300 s).

The extent of patulin degradation in AS juice could be significantly (P>0.05)

correlated with the disappearance of ascorbic acid following HHP treatments at 600

MPa (Figure 3.6). Patulin decrease in the AS juice was also significantly correlated

(p<0.05) with the decrease of thiol content after 600 MPa (0, 60, 180 and 300 s)

(Figure 3.7). The result would suggest that the reaction of thiol and ascorbic acid with

patulin was enhanced during high pressure treatment.

Nitrite content of 17.8 ppm was not significantly changed (p>0.05) after treatment at

600 MPa (0, 60, 180 and 300 s at 11 °C) when the patulin decreased by 43.11 ppb.

This would suggest negligible interaction of nitrite with patulin during HHP treatment.

However, nitrite content did decrease from 17.8 ppm to 15.57 ppm after the AS juice

was preheated at 50 °C for 180 s prior to HHP processing of 600 MPa (Figure 3.8). In

this event it was evident that pre-heating step activated either the patulin or nitrite

given both were decreased when subsequently subjected to high hydrostatic pressure.

99

Figure 3. 8- The correlation between patulin decrease in the AS juice and the decrease of ascorbic acid content after HHP treatment at 600 MPa (0, 60, 180 and 300 s)

Figure 3. 9- The correlation between patulin decrease in the AS juice and the decrease of thiol content after HHP treatment at 600 MPa (0, 60, 180 and 300 s)

y = 320.9x + 1.1646R² = 0.9531

0

5

10

15

20

25

30

35

40

45

50

0 0.05 0.1 0.15

Ascorbic acid (mg/100ml)

Pat

ulin

(pp

b)

y = 67.172x + 3.1704R² = 0.9546

0

5

10

15

20

25

30

35

40

45

50

0 0.2 0.4 0.6 0.8

Thiol content(uM/L)

Pat

ulin

(pp

b)

100

Figure 3. 10- The correlation between patulin decrease in the AS juice and the decrease of nitrite content after HHP treatment at 600 MPa (0, 60, 180 and 300 s) with 50 °C for 180 s preheat treatment

y = 81.493x ‐ 0.5687R² = 0.9888

0

20

40

60

80

100

120

140

160

180

200

0 0.5 1 1.5 2 2.5

Nitrite content(mg/L)

Pat

ulin

(ppb

)

101

3.3.4 Interactions between patulin and thiol proteins, ascorbic acid, hydrogen

peroxide or nitrite during HHP treatment

Patulin in acetate buffer (pH 4) supplemented with BSA (30 mg/ml) was decreased by

2.16 ppm (10.8 % of initial concentration) when subjected to 600 MPa for 300s. The

sulfhydryl group of BSA decreased by 17.31 μM suggesting that the thiol groups had

interacted with patulin (Figure 3.9). This was further supported by the fact that no

patulin degradation was observed when samples were HHP treated in the absence of

BSA.

When the BSA was substituted with ascorbic acid (1000 ppm) in acetate buffer

system (pH 4) no significant (P>0.05) decrease in patulin levels was observed after

HHP at 600 MPa for 300 s. No significant difference (P>0.05) in patulin levels was

recorded in apple and spinach juice spiked with patulin in the presence or absence of

ascorbic acid. Here, the patulin degradation by HHP treatment at 600 MPa for 300 s

was 44.18±2.16 ppb in AS juice supplemented with ascorbic acid that compares with

43.11±1.78 ppb in non-supplemented juice. The results would confirm that at pH 4,

ascorbic acid has negligible interactions with patulin during high pressure treatment.

Apple juice (pH 3.5, Brix 12.0) spiked with 200 ppb of patulin and different amounts

of hydrogen peroxide (up to 10 %) prior to treating at 600 MPa for 300 s. The extent

of patulin degradation by HHP could be correlated to hydrogen peroxide

concentration up to 1 % v/v (Figure 3.10). There was further HHP assisted

degradation of patulin in the presence of hydrogen peroxide up to 10 % v/v although

the rate was significantly lower compared to when <1 % was applied (Figure 3.10).

102

The AS juice spiked with 20 ppm of patulin and treated in a water bath set at 50 °C

for 180 s followed by 600 MPa for 180 s led to 7.6 ppm of patulin degradation.

Endogenous nitrite concentration was decreased by 5.14 mg/l in the same sample

suggesting heat activation had an effect on the degradation rate of patulin Figure 3.11.

Figure 3. 12- Relationship between patulin degradation in apple juice and hydrogen peroxide content under HHP treatment at 600 MPa for 300 s

0.0

20.0

40.0

60.0

80.0

0% 2% 4% 6% 8% 10% 12%

Pat

ulin

red

ucti

on (

%)

Hydrogen peroxide content (v/v)


(BSA 30 mg/ml, 20 ppm patulin)

Patulin degraded by

10.84 % and thiol

group by 17.3 μM/L


(BSA 0 mg/ml, 20 ppm patulin)

Patulin degraded by

0 %

600 MPa, 300s

Figure 3. 11- Determination of patulin decrease and thiol group decrease after HHPprocessing

103

3.3.5 Modelling the HHP assisted degradation of patulin in different juice

matrices

After screening the biphasic, Weibull and first order models using the Matlab

software, the Weibull model presented the best fit to the experimental data as the

highest r2 and lowest RMSE values suggested. In the Weibull model equation, Ct (ppb)

is the residual concentration of patulin at the time t. C0 (ppb) is the initial patulin

concentration. k is the patulin degradation kinetic constant(s-1). a is the shape constant

(dimensionless) determining the shape of degradation curve. The parameters (k and a)

in the BSA model solution system (Figure 3.4) were estimated using Matlab software

as shown in Table 3.5.

The relationship of k patulin degradation kinetic rate and pressure, pH and BSA

concentration were analyzed by the regression analysis method (Box-Behnken method)

using Design-Expert 7.0. The regression equation between response variable (Y=k)

and independent variables (X1= pressure, X2= pH and X3= BSA concentration) was

AS juice

(200 ppb patulin) 94.73 % patulin reduction

Preheat 50 o

C, 180 s

600 MPa, 180 s

AS juice

(200 ppb patulin) No patulin degradation

Preheat 50 o

C, 180 s

AS juice

(200 ppb patulin) 18.23 % patulin degradation

600 MPa, 180 s

AS juice

(20ppm patulin)

38.14 % patulin degradation

Nitrite degraded by 5.14 mg/L Preheat 50

o

C, 180 s

600 MPa, 180 s

Figure 3. 13- Determination of patulin amount and nitrite content after HHP processing

104

shown below.

Equation 1.

Y=5.27*10-3-1.09*10-5X1-1.20*10-3X2-1.90*10-3X3+2.33*10-6X1X2+3.72*10-6X1X3

+3.06*10-4 X2X3.

The model P value <0.0001 confirms that the regression can be used to predict the k

patulin degradation kinetic rate in relation to thiol group content (Table 3.6).

The surface response graphs illustrate the interaction of patulin HHP assisted

degradation via pressure with BSA concentration under different pH conditions

(Figures 3.12, 3.13 and 3.14). From the graph it was evident that the degree of patulin

degradation was a function of applied pressure, pH and BSA. The regression equation

of a (Y) the shape constant and pressure (X1), pH (X2) and BSA concentration (X3)

was as shown below by Box-Behnken design using Design-Expert 7.0.

Equation 2.

Y=0.83-1.27E-003X1+0.29X2-0.24X3+3.11E-004X1X2+2.78E-004X1X3+0.05X2X3-

7.96E-007X12-0.06X2

2-1.51E-003X32

The model P value<0.0001 (P<0.05) implies the model is significant and the

regression model is effective and can be used to predict a the shape constant

(R2=0.9912) (Table 3.7) in the BSA model solution system under HHP processing.

105

Table 3. 5- Weibull model parameters for patulin decrease following a range of pressure-pH-BSA concentration (mg/ml) combinations in the BSA model systems under HHP processing

Model system (pH-

pressure)

BSA conc. mg/ml

Patulin k 10-5/s

Shape (a) RMSE (10-

3) r2

pH 3.5-400 1 44.85±0.72 0.98±0.01 1.74 0.998 2 76.28±1.29 0.99±0.01 3.38 0.998 3 115.53±0.31 1.05±0.00 6.40 0.996

pH 3.5-500 1 47.83±0.35 0.90±0.00 1.48 0.999 2 93.05±1.02 0.95±0.01 4.85 0.997 3 146.43±0.35 1.03±0.00 6.55 0.997

pH 3.5-600 1 52.43±0.66 0.81±0.00 1.22 0.999 2 123.63±0.96 0.91±0.01 14.07 0.984 3 211.80±0.10 1.04±0.00 26.19 0.973

pH 4-400 1 58.17±0.99 0.97±0.01 2.75 0.998 2 95.87±0.43 1.03±0.00 3.56 0.998 3 134.90±1.21 1.08±0.00 6.32 0.997

pH 4-500 1 61.95±1.31 0.90±0.01 2.79 0.998 2 126.37±1.43 1.01±0.01 3.15 0.999 3 191.17±0.97 1.08±0.01 7.20 0.998

pH 4-600 1 69.65±2.16 0.84±0.01 3.60 0.998 2 163.57±0.55 0.96±0.00 7.24 0.997 3 270.77±0.21 1.08±0.00 13.04 0.995

pH 4.5-400 1 70.08±1.07 0.98±0.01 2.62 0.999 2 108.53±1.83 1.03±0.01 3.37 0.999 3 154.47±0.06 1.12±0.00 7.77 0.996 pH 4.5-500 1 76.87±2.03 0.93±0.02 2.26 0.999 2 152.97±0.31 1.03±0.00 3.19 0.999 3 234.93±0.55 1.13±0.00 7.85 0.998 pH 4.5-600 1 87.66±1.57 0.88±0.01 2.86 0.999 2 203.30±1.18 1.01±0.01 3.94 0.999 3 334.43±0.15 1.13±0.00 7.89 0.999 Table 3. 6- Variance analysis of regression models for k the degradation kinetic (ANOVA for Response Surface 2FI (two-factor interaction) Model) in the BSA model solution system under HHP processing Source df Sum of Squares Mean

Square F Value p-value

Model 6 6.009E-006 1.002E-006 472.03 < 0.0001 Residual 10 2.122E-008 2.122E-009 Cor Total 16 6.030E-006

R-Squared 0.9965

106

Figure 3. 14- Response surface contour plots showing effects of pressure and pH on the patulin degradation rate constant k in the BSA model solution system under HHP processing

Figure 3. 15- Response surface contour plots showing effects of pressure and BSA concentration on the patulin degradation rate constant k in the BSA model solution system under HHP processing

107

Figure 3. 16- Response surface contour plots showing effects of pH and BSA concentration on the patulin degradation rate constant k in the BSA model solution system under HHP processing Table 3. 7- Variance analysis of regression models of a the shape constant (ANOVA for Response Surface Quadratic Model) in the BSA model solution system under HHP processing Source df Sum of Squares Mean


Model 9 0.081 8.948E-003 87.25 < 0.0001 Residual 7 7.179E-004 1.026E-004 Cor Total 16 0.081

R-Squared 0.9912

108

The parameters (k and a) in the hydrogen peroxide model solution system (Figure 3.4)

were estimated using Matlab software (Table 3.8). The relationship of k patulin

degradation kinetic rate and pressure, pH and hydrogen peroxide concentration were

analyzed by the regression analysis method (Box-Behnken method) using Design-

Expert 7.0. The regression equation between response variable (Y=k) and independent

variables (X1= pressure, X2= pH and X3= hydrogen peroxide concentration) was as

shown below.

Equation 3.

Y =1.20E-003-5.58E-007 X1+2.90E-005 X2-7.99E-004 X3-9.00E-007X1X2+2.33E-

005 X1X3-8.53E-004 X2X3


regression model is effective and can be used to predict the k, patulin degradation

kinetic rate (R2=0.9835) (Table 3.9) in the hydrogen peroxide model solution system

under HHP processing. The surface response graphs showing the effects of pressure,

pH and hydrogen peroxide concentration (Figures 3.15, 3.16 and 3.17). The graphs

indicate the patulin degradation rate constant k increased as the pressure and hydrogen

peroxide concentration increased but decreased as the pH became less acidic.

The regression equation of a (Y) the shape constant and pressure (X1), pH (X2) and

hydrogen peroxide concentration (X3) was as shown below by Box-Behnken design

using Design-Expert 7.0 in the hydrogen peroxide model solution system under HHP

processing.

Equation 4.

Y=0.13-3.27E-004X1+0.38X2+0.98X3-9.31E-004X1X2+4.83E-

004X1X3+0.10X2X3+3.52E-006X12+8.10E-004X2

2-1.58X32

109


regression model is effective and can be used to predict a shape constant (R2=0.9893)

(Table 3.10) in the hydrogen peroxide model solution system under HHP processing.

110

Table 3. 8- Weibull model parameters for patulin decrease following a range of pressure-pH-hydrogen peroxide concentration combinations in the hydrogen peroxide model systems under HHP processing

Model system

H2O2 conc.

Patulin k (10-

5/s) Shape (a)

RMSE (10-

3) r2

pH 3.5-400 0.3 % 103.83±1.51 0.90±0.01 2.87 0.999 0.5 % 259.30±0.20 0.94±0.00 10.63 0.997 0.7 % 356.33±1.75 0.92±0.01 4.93 0.999

pH 3.5-500 0.3 % 184.43±1.46 0.87±0.01 14.10 0.992 0.5 % 349.87±0.21 0.92±0.00 3.28 0.999 0.7 % 477.17±0.95 0.86±0.00 8.05 0.999

pH 3.5-600 0.3 % 187.47±2.54 0.93±0.01 8.49 0.997 0.5 % 424.93±0.06 0.98±0.00 9.76 0.998 0.7 % 649.13±0.99 0.92±0.01 8.31 0.999

pH 4-400 0.3 % 99.43±1.59 0.92±0.01 1.87 0.999 0.5 % 208.86±0.45 0.98±0.00 5.14 0.999 0.7 % 325.90±2.26 0.91±0.01 4.94 0.999

pH 4-500 0.3 % 141.80±1.68 0.86±0.01 4.46 0.999 0.5 % 308.97±0.78 0.91±0.01 7.69 0.997 0.7 % 400.07±1.46 0.82±0.00 12.35 0.998

pH 4-600 0.3 % 148.17±1.04 0.83±0.01 3.56 0.999 0.5 % 371.60±1.81 0.88±0.01 5.13 0.997 0.7 % 561.07±2.00 0.87±0.00 7.83 0.999

pH 4.5-400 0.3 % 100.23±1.26 0.96±0.01 1.88 0.999 0.5 % 196.53±0.06 0.99±0.00 5.70 0.999 0.7 % 309.43±2.31 0.92±0.01 4.75 0.999 pH 4.5-500 0.3 % 104.93±2.40 0.82±0.01 3.79 0.999 0.5 % 286.07±0.12 0.93±0.00 2.41 0.999 0.7 % 360.60±0.75 0.84±0.01 10.97 0.999 pH 4.5-600 0.3 % 124.37±2.15 0.78±0.01 9.75 0.997 0.5 % 344.17±0.06 0.85±0.00 4.90 0.993 0.7 % 486.67±3.19 0.92±0.00 3.38 0.999 Table 3. 9- Variance analysis of regression models for k the degradation kinetic (ANOVA for Response Surface 2FI (two-factor interaction) Model) in the hydrogen peroxide model solution system under HHP processing Source df Sum of Squares Mean


Model 6 2.458E-005 4.096E-006 99.25 < 0.0001 Residual 10 4.127E-007 4.127E-008 Cor Total 16 2.499E-005

R-Squared 0.9835

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Figure 3. 17- Response surface contour plots showing effects of pressure and pH on the patulin degradation rate constant k in the hydrogen peroxide model solution system under HHP processing

Figure 3. 18- Response surface contour plots showing effects of pressure and hydrogen peroxide concentration on the patulin degradation rate constant k in the hydrogen peroxide model solution system under HHP processing

112

Figure 3. 19- Response surface contour plots showing effects of pH and hydrogen peroxide concentration on the patulin degradation rate constant k in the hydrogen peroxide model solution system under HHP processing Table 3. 10- Variance analysis of regression models of a the shape constant (ANOVA for Response Surface Quadratic Model) in the hydrogen peroxide model solution system under HHP processing Source df Sum of Squares Mean


Model 9 0.040 4.448E-003 71.85 < 0.0001 Residual 7 4.334E-004 6.191E-005 Cor Total 16 0.040

R-Squared 0.9893

113

The parameters (k and a) in the nitrite model solution system (Figure 3.4) were

estimated using Matlab software as shown in Table 3.11.

The relationship of patulin degradation kinetic rate (k) with pressure, pH and nitrite

concentration were analyzed by the regression analysis method (Box-Behnken method)

using Design-Expert 7.0. The regression equation between response variable (Y=k)

and independent variables (X1= pressure, X2= pH and X3= nitrite concentration) was

as shown below.

Equation 5.

Y=-0.13+3.81E-005X1+0.06X2+2.92E-004X3-7.43E-006X1X2+1.56E-006X1X3-

2.34E-004X2X3-1.10E-008X12-7.03E-003X2

2+7.86E-006X32

The model P value 0.0006 indicates the model is significant and the regression model

is effective and can be used to predict the k patulin degradation kinetic rate

(R2=0.9556) in the nitrite model solution system under HHP processing (Table 3.12).

The surface response graphs illustrate that k increased with applied pressure and

nitrite concentration. Interestingly there was an optimum pH of 3.75 with the k value

decreasing on either side of this value (Figures 3.18, 3.19 and 3.20). The patulin

degradation rate constant k can achieve the maximum when the pressure is 600 MPa,

the pH is 3.75 and the nitrite is 17.1 mg/L. The regression equation of (Y) the shape

constant and pressure (X1), pH (X2) and nitrite concentration (X3) was as shown below

by Box-Behnken design using Design-Expert 7.0 in the nitrite model solution system

under HHP processing.

Equation 6.

Y=-2.78+4.36E-003X1+1.23X2+0.02X3-8.60E-005X1X2-3.22E-005X1X3+1.20E-

003X2X3-3.31E-006X12-0.15X2

2-8.62E-006X32

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The model P value=0.006 implies the model is significant and the regression model is

effective and can be used to predict the shape constant (R2= 0.9103) (Table 3.13) in

the nitrite model solution system under HHP processing.

115

Table 3. 11- Weibull model parameters for patulin decrease following a range of pressure-pH-nitrite concentration (mg/L) combinations in the nitrite model systems under HHP processing

Model system

Nitrite

conc. Patulin k (10-5/s) Shape (a)

RMSE (10-

3) r2

pH 3.5-400 5.7 107.37±0.71 0.84±0.01 6.04 0.997 11.4 212.00±0.30 0.85±0.01 6.71 0.998 17.1 352.87±0.15 0.99±0.00 2.86 0.999

pH 3.5-500 5.7 179.20±2.12 0.93±0.01 4.28 0.999 11.4 386.47±1.10 0.95±0.01 4.84 0.999 17.1 613.10±0.30 0.98±0.01 12.82 0.998

pH 3.5-600 5.7 346.47±1.02 0.99±0.01 4.43 0.999 11.4 480.67±1.89 0.94±0.01 3.77 0.999 17.1 862.70±0.26 0.90±0.00 26.68 0.992

pH 4-400 5.7 133.57±5.21 0.83±0.02 6.94 0.997 11.4 274.43±0.35 0.92±0.01 3.98 0.999 17.1 379.67±0.51 0.98±0.00 6.43 0.999

pH 4-500 5.7 257.80±1.11 0.94±0.00 3.33 0.999 11.4 452.20±0.95 0.97±0.01 12.10 0.998 17.1 696.57±6.94 1.00±0.01 11.84 0.998

pH 4-600 5.7 374.77±0.35 0.93±0.01 5.44 0.999 11.4 611.03±2.08 0.99±0.01 12.52 0.998 17.1 959.80±6.65 0.99±0.00 17.64 0.997

pH 4.5-400 5.7 82.52±1.05 0.84±0.01 4.47 0.998 11.4 126.47±0.45 0.87±0.00 6.46 0.997 17.1 172.13±0.15 0.89±0.00 7.29 0.998 pH 4.5-500 5.7 123.57±0.12 0.89±0.00 7.16 0.996 11.4 188.03±1.31 0.92±0.01 3.23 0.999 17.1 289.90±0.10 0.94±0.00 11.75 0.997 pH 4.5-600 5.7 186.63±1.24 0.98±0.01 3.36 0.999 11.4 246.93±2.29 0.96±0.01 9.34 0.998 17.1 326.13±0.06 0.87±0.00 7.20 0.999 Table 3. 12- Variance analysis of regression models for k the degradation kinetic (ANOVA for Response Surface Quadratic Model) in the nitrite model solution system under HHP processing Source df Sum of Squares Mean


Model 9 6.920E-005 7.689E-006 16.73 0.0006 Residual 7 3.217E-006 4.596E-007 Cor Total 16 7.242E-005

R-Squared 0.9556

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Figure 3. 20- Response surface contour plots showing effects of pressure and pH on the patulin degradation rate constant k in the nitrite model solution system under HHP processing

Figure 3. 21- Response surface contour plots showing effects of pressure and nitrite concentration on the patulin degradation rate constant k in the nitrite model solution system under HHP processing

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Figure 3. 22- Response surface contour plots showing effects of pH and nitrite concentration on the patulin degradation rate constant k in the nitrite model solution system under HHP processing Table 3. 13- Variance analysis of regression models of a the shape constant (ANOVA for Response Surface Quadratic Model) in the nitrite model solution system under HHP processing Source df Sum of Squares Mean Square F Value p-value Model 9 0.032 3.581E-003 7.89 0.0063 Residual 7 3.176E-003 4.538E-004 Cor Total 16 0.035

R-Squared 0.9103

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3.4 Discussion

The model juices were selected to represent a spectrum of different characteristics.

Specifically, PAM was high in ascorbic acid whilst low in nitrites. In contrast GJ juice

was low in ascorbic acid, high in thiol containing proteins and nitrite. Irrespective of

the juice type, the extent of patulin reduction was dependent on the applied pressure

and duration of treatment.

In the current study it was evident that the extent of high pressure degradation of

patulin was also dependent on the constituents of the different juices. This would

support the hypothesis high pressure alone does not result in the degradation of

patulin but rather enhances the oxidative reactions that ultimately result in opening of

the lactone group on the mycotoxin.

In the study, it was found that the amount of patulin degradation was significantly

correlated with the decrease of ascorbic acid although was not an equimolar reaction.

Indeed, the extent as the ascorbic acid degradation was independent of the presence of

patulin. The result would suggest that under high pressure processing that ascorbic

acid and patulin are degraded independently with negligible interaction. Such a theory

is supported by the findings of the current study whereby PAM juice that had a high

ascorbic acid content did not correspond to increased degradation of patulin. In

addition, the losses of ascorbic acid due to HHP have been reported to be as high as

82 % in grape juice suggesting independent reaction mechanisms (Del Pozo-Insfran,

Del Follo-Martinez, Talcott, & Brenes, 2007).

Nitrite is regarded as a stable oxidizing agent that elicits effect through conversion to

the more reactive nitric oxide. In the current study it was demonstrated that nitrite did

neither undergo such a conversion nor significantly affect the stability of patulin

119

beyond that cause by the pressure treatment. However, by applying a heating step at

50 ºC prior to high pressure treatment, the efficacy of patulin degradation by HHP

was enhanced. It is well established that thermal treatments enhance the conversion of

nitrites to nitric oxide that likely interacted with patulin (Gangolli, Vandenbrandt,

Feron, Janzowsky, Koeman, Speijers, et al., 1994; Hou, Janczuk, & Wang, 1999; Ray,

Chakraborti, & Gulati, 2007; Tamme, Reinik, Puessa, Roasto, Meremaee, & Kiis,

2010). It follows that high pressure further enhanced the oxidative decomposition of

patulin leading to lower levels of the mycotoxin compared to applying pressure alone.

This hypothesis was supported by the fact AS and GJ juices both of which were high

in nitrites thereby supporting >170 ppb degradation of patulin when the combined

thermal and pressure treatments were applied.

The highest pressure assisted degradation of patulin was observed in the presence of

thiol groups such as those on protein. Therefore, it was not unexpected to find that the

highest degradation of patulin levels by high pressure was supported by GJ juice that

contained the highest concentration of thiol. Similar to ascorbic acid, the decrease in

thiol group concentration was not equal to that of patulin that would suggest there was

no equimolar reaction. The thiol encountered in vegetable and fruit juice include

glutathione (GSH), cysteine (CYS), homocysteine (HCYS), captopril (CAP), and N-

acetyl-L-cysteine (NAC) (Demirkol, Adams, & Ercal, 2004; Qiang, Demirkol, Ercal,

& Adams, 2005). The reaction of patulin with cysteine was equimolar reported by

Fliege and Metzler (2000b). However, patulin reacted with glutathione or N-

acetylcysteine by the ratio of 1:2 was studied by Fliege and Metzler (2000b).

Fliege and Metzler (2000b) reported that patulin forms adducts with the thiol group

containing compounds such as N-acetylcysteine, glutathione, and cysteine. A

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common feature of adduct formation is the SH addition adduct at C-6 and C-2 (Fliege

& Metzler, 2000b). Therefore, it is likely that the thiol groups contained within the

beverages formed similar adducts with patulin in a process assisted by high pressure.

The results are in agreement with Ludwig (2002) who reported pressure assisted

formation of adducts when patulin was high pressure processed in the presence of

thiol containing compounds (Ludwig, 2002). Morgavi, Boudra, Jouany, and Graviou

(2003) reported that the adduct formed from the interaction of patulin with sulfhydryl

containing cysteine and glutathione prevented the negative effects of patulin infection

on rumen fermentation, while non-sulfhydryl–containing ascorbic acid and ferulic

acid did not protect against patulin toxicity.

The patulin degradation increased from 43.91 % to 100 % in the CAB, PAM, AS and

GJ juices when the juice was preheated at 50 °C for 180 s then HHP treated at 600

MPa for 300 s immediately. The patulin contamination level in AS and GJ juice was

decreased to lower than 50 ppb after preheating and HHP combined treatment, which

is the maximum level regulated by the FDA, Health Canada and European

Commission in USA, Canada and Europe. The increased patulin degradation in juices

by HHP could be achieved by performing HHP treatment at 50 °C (Bruna, 1997).

When pressure treatment was performed in acetate buffered solutions containing

hydrogen peroxide there was a high reduction in patulin levels. The reaction between

hydrogen peroxide and patulin has been previously reported (Drusch, Kopka, &

Kaeding, 2007; Karaca & Velioglu, 2009; Liu, Gao, Niu, Li, & Song, 2008). The free

radicals generated by the breakdown of hydrogen peroxide directly oxidized the

patulin in a process enhanced by the application of pressure. It was noted that with

excess hydrogen peroxide (>1 % v/v) resulted in slower patulin degradation rates.

121

This may have been caused by the generation of excess free radicals that neutralized

via termination reactions. A similar observation for the lower oxidative capacity of

hydrogen peroxide has been previously reported thereby supporting the hypothesis

(Dahl & Pallesen, 2003; Okuda, Nishiyama, Saito, & Katsuki, 1996).

In addition to the presence of thiol and other reactive groups, the rate of patulin

degradation was dependent on pH. At acidic pH values, patulin appeared less reactive

under applied pressure compared to when the supporting solution was at neutral pH. It

is well documented that the stability of patulin is stable under acidic pH but less so

under neutral or alkali conditions (Collin, Bodart, Badot, Bouseta, & Nizet, 2008;

Drusch, Kopka, & Kaeding, 2007).

The high pressure degradation of patulin in the presence of nitrite illustrated a pH

optimum of 3.75. The underlying mechanism to explain the pH optima is unclear but

could be associated with the ionic state of constituents that reacts with patulin.

The biphasic model has been used to model high pressure assisted

degradation/inactivation of chemical, microbial and enzymes (Igual, Sampedro,

Martinez-Navarrete, & Fan, 2013; Zimmermann, Schaffner, & Aragao, 2013). The

non-linear models are frequently applied to pressure assisted processes (Indrawati,

Van Loey, & Hendrickx, 2005; Nguyen, Indrawati, Van Loey, & Hendrickx, 2005;

Rawson, Brunton, & Tuohy, 2012). For example, Rawson, Brunton, and Tuohy (2012)

modelled the high pressure degradation of falcarinol (FaOH), falcarindiol (FaDOH)

and falcarindiol-3-acetate (FaDOAc) in carrots using the Weibull model. The biphasic

model is commonly used to describe situations with the presence of two distinct

subpopulations. The first portion of the kinetic curve is assumed to represent the

sensitive portion of the reaction and the second portion is assumed to represent the

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portion more resistant (Igual, Sampedro, Martinez-Navarrete, & Fan, 2013). The two

distinct subpopulations of the biphasic model may be caused by the diffusion of the

reactants during the reaction (Luo & Anderson, 2008; Murgia, Pisani, Shukla, & Scott,

2003).When the reaction rate is dependent on the concentration of the reactant, the

degradation of chemicals is non-linear. The Weibull model has the shape parameter (a)

which can reflect the change of the reaction rate (Pocas, Oliveira, Brandsch, & Hogg,

2012; Rawson, Brunton, & Tuohy, 2012).

The products of the patulin degradation by HHP processing are still unknown. The

thiol compound such as thiol containing protein, glutathione, cysteine, and

thioglycolate are believed by many to produce biologically inactive products when

reacted with patulin (Ciegler, Beckwith, & Jackson, 1976; Lindroth & Von Wright,

1990; Morgavi, Boudra, Jouany, & Graviou, 2003). In the previous study, treatment

of patulin solution of 32 µM with 10 % ozone reduced patulin to undetectable level

and produced no identifiable reaction products (McKenzie, et al., 1997).

3.5 Conclusions

For the first time, the factors affecting the high pressure assisted degradation of

patulin have been studied. From comparing the extent of patulin degradation with

juice constituents it was evident that thiol groups associated with sulphur containing

amino acids, amongst others, contributed to reduce levels of the mycotoxin. Nitrites,

however, contributed to enhancing the effect of HHP on patulin provided a pre-

heating step was applied which presumably resulted in the generation of nitric oxide.

A further strong oxidizing agent, hydrogen peroxide, could also increase the kinetics

of pressure degradation of patulin. Although the byproducts of pressure degradation

were not identified the results would suggest that the reactivity of patulin with

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oxidative species resulted in adduct formation or breakdown of the lactone ring.

Regardless of this fact, the results highlight that juices likely to contain patulin can be

remediated by supplementing thiol or other oxidative species into the product formula.

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Chapter Four

Potential Toxic Effects of Patulin Degradation

Products Assessed using Fruit Fly (Drosophila

melanogaster) Toxicology Model

125

Abstract

Patulin is a recognized biohazard in apple based beverages. In the following study,

potential toxic effects of patulin degradation products were assessed using a fruit fly

(Drosophila melanogaster) toxicology model. In the patulin sensitivity evaluations

towards fruit fly (Drosophila melanogaster), it was found that the concentration of

patulin (500 ppm) inhibited the growth of pupa and adult fruit flies completely. 500

ppm was selected as the patulin concentration to conduct the acute toxicity evaluation

of the patulin degradation products after the patulin sensitivity test. For the patulin

detoxification test, HHP treated samples were compared to patulin spiked samples and

blank samples. The results of hatching and development rate supported no additional

toxicity contributed by the HHP-degraded products of patulin and other HHP sensitive

compounds in the apple and spinach juice with added bovine serum albumin (BSA),

hydrogen peroxide or nitrite.

126

4.1 Introduction

Patulin was initially considered to be a broad range antibiotic that had the potential for

curing the common cold (Braese, Encinas, Keck, & Nising, 2009; McKenzie, et al.,

1997). However, subsequent studies revealed the toxic effects of patulin and

consequently the mould secondary metabolite was reclassified as a mycotoxin

(Bullerman, 1979; Mahfoud, Maresca, Garmy, & Fantini, 2002; Stott & Bullerman,

1975). Patulin was mutagenic, immunosuppressive, neurotoxic, teratogenic and to a

limited extent, carcinogenic (Mayer & Legator, 1969; Pfeiffer, Diwald, & Metzler,

2005; Pfeiffer, Gross, & Metzler, 1998; Wichmann, Herbarth, & Lehmann, 2002).

The current study has illustrated that the HHP can promote the degradation of patulin

through direct or indirect oxidation by juice constituents. However, the disappearance

of patulin is monitored through HPLC with UV detection and it is possible that

adducts formed can have equal or greater toxicity. For example, patulin: ascorbic acid

adducts have low UV absorbance but exhibit comparable toxic effects to patulin

(Morgavi, Boudra, Jouany, & Graviou, 2003).

The actual byproducts of the high pressure assisted degradation remain unknown but

likely are diverse if the same mechanism occurs as observed in UV treatment or

during interaction with glutathione (Assatarakul, Churey, Manns, & Worobo, 2012;

Funes, Gomez, Resnik, & Alzamora, 2013; McKenzie et al., 1997; San Martin,

Barbosa-Canovas, & Swanson, 2002; Yan, Koutchma, Warriner, Shao, & Zhou, 2013;

Yun et al., 2008).

127

Fruit flies (Drosophila melanogaster) have been used as an alternative to the use of

higher animals for toxicity assessment (Han, Geller, Moniz, Das, Chippindale, &

Walker, 2014b; Kazemi-Esfarjani & Benzer, 2000). Drosophila melanogaster have a

complete metamorphosis, including the stages of egg, larva, pupa and adult fly. The

toxicity of several mycotoxins including citrinin, AFB1 and patulin on Drosophila

melanogaster have ever been evaluated in terms of genotoxic activity (Belitsky,

Khovanova, Budunova, & Sharuptis, 1985) using the induction of somatic

mutagenesis (total sum of somatic recombination, point mutations and elimination of

one X-chromosome) in the cells of Drosophila melanogaster larva as activity

indicator. It was found that patulin elevated the level of somatic mutations in D.

melanogaster at the concentration of 3.2x10-3 M. In the final part of the study the

potential toxicity of the degradation products of patulin treated with high pressure was

assessed.

128

4.2 Materials and Methods

4.2.1 Reagents

Patulin, acetonitrile (ACN), methanol, ethyl acetate, acetic acid, bovine serum

albumin (BSA), hydrogen peroxide, sodium nitrite, sucrose, agar, 4-methyl-

hydroxybenzoate, potassium phosphate, potassium phosphate tartrate, sodium

chloride, calcium chloride, magnesium chloride, iron (III) sulphate, dry yeast and

propionic acid were purchased from Sigma-Aldrich (St. Louis., MO, USA). Apple

juice (pH = 2.92) was purchased from a local supermarket.

4.2.2. Sample preparation

The apple and spinach homogenate (AS) was prepared as described in section 3.2.2.

Spinach (200 g) was obtained from a local supermarket and suspended in 500 ml of

distilled water then blended to form a homogenate. After blending, the spinach juice

was centrifuged at 5000 × g for 10 min to remove large particulate. The supernatant

juice was diluted in distilled water to a ratio 1 part homogenate to 2 parts water to

form spinach juice. Apple juice concentrate (71 °Brix) was diluted with distilled water

to a final °Brix of 12 and then diluted using the spinach juice (1:1) (subsequently

referred to as AS). The AS juice was supplemented with BSA to make BSA modified

AS juice (3 g/100 ml final concentration of BSA in juice). The AS juice was added

with hydrogen peroxide to make hydrogen peroxide modified AS juice (10 % final

concentration of hydrogen peroxide in juice). The AS juice was supplemented with

nitrite to make nitrite modified AS juice (1000 ppm final concentration of nitrite in

juice). The modified juices were adjusted to the final pH 3.5 using lemon juice. The

129

modified AS juice samples were spiked with patulin at the appropriate test

concentration.

4.2.3 Apple juice agar and Sokolowski lab fly food

The preparation of apple juice agar and Sokolowski fly food were modified from

Sokolowski’s method (Sokolowski, Hansell, & Rotin, 1983). Apple juice agar was

used to promote egg production by fruit fly (Drosophila melanogaster). Briefly, 5 g

sucrose, 4.5 g agar, 0.3 g 4-methyl-hydroxybenzoate and 150 ml of distilled water

were heated to a boil. Then 125 ml of low acidity apple juice was added and the

solution was heated to boil again. After cooling to about 70 ºC, the solution was

dispensed to the petri dishes (100 mm in diameter) as apple juice agar (Sokolowski

lab, University of Toronto, Canada).

Sokolowski lab fly food was used in the D. melanogaster growth experiments. Fly

food base (400 ml of distilled water, 50 g sucrose, 14.5 g agar, 0.5 g potassium

phosphate, 4 g potassium sodium tartrate, 0.25 g sodium chloride, 0.25 g calcium

chloride, 0.25 g magnesium chloride and 0.25 g iron (III) sulphate in 1 L flask) and

yeast medium (100 ml distilled water, 25 g dry yeast) were prepared and autoclaved

(121 ºC, 30 min) separately. After autoclaving, the yeast medium was transferred into

the fly food base and 2.5 ml of propionic acid was added to the solution prior to

dispensing 40 ml of solution into bottles or 1 ml of solution into the well of 12-well

plate.

130

4.2.4 HHP processing treatment and sample preparation for toxicity assay using

D. melanogaster model system

Vacuum packed modified AS juices were pressurized in a HHP unit at 600 MPa for

300 s as described in section 3.2.4. The juices spiked with the appropriate

concentration of patulin were dispensed in 25 ml aliquots into pouches. The pouches

were vacuum sealed to exclude air and transported in a cold box to the HHP

processing facility. The HHP unit was a Hyperbaric 51 litre capacity chamber that

could apply pressures up to 600 MPa. All treatments were undertaken at 11 °C unless

otherwise stated.

The experimental design for toxicity assay using the D. melanogaster model system

included D. melanogaster sensitivity evaluation to patulin and the HHP-detoxification

experiment. In the D. melanogaster sensitivity evaluation to patulin, acidified water

solutions (acetate buffer system consisted of 0.2 M acetic acid solution and 0.2 M

sodium acetate solution adjusted to the final pH 4) with various concentrations of

patulin were prepared and then mixed with the Sokolowski lab fly food (50 ºC) in a

ratio 1 part patulin solution to 9 parts Sokolowski lab fly food to form a patulin

containing lab fly food for test. The final patulin concentrations of the lab fly food

ranged from 0.5 to 500 ppm with acidified water replacing the mycotoxin in the

control. The mixtures (1 ml) were immediately distributed into each well of 12-well

plates and dried overnight at 20 ºC.

Five sets of samples of AS juice was supplemented with BSA, nitrite or hydrogen

peroxide, respectively. For example, the experimental design was as shown in Figure

4.1A and 4.1B when the AS juice was supplemented with hydrogen peroxide. The

five sets of samples were HHP-B, HHP-C, HHP-T, and PAT-C and PAT-S samples

131

(Figure 4.1). When the AS juice was supplemented with BSA (3 g/100 ml BSA), the

experimental design was the same as that for the hydrogen peroxide added juice

except that the BSA addition replaced the hydrogen peroxide addition. When the AS

juice was supplemented with nitrite (1000 ppm), the experimental design was the

same as that for the hydrogen peroxide added juice except that the nitrite addition

replaced the hydrogen peroxide addition and the nitrite added juice was preheated at

50 °C for 3 minutes prior to HHP processing (Figure 4.2). The treated samples (HHP-

T) were high pressure processed at 600 MPa for 300 s with patulin being determined

using HPLC.

The five sets of samples (HHP-B, HHP-C, HHP-T, PAT-C and PAT-S samples) were

mixed with the Sokolowski lab fly food at 50 ºC in 1:9 ratio, respectively. Lots (1ml)

of the patulin containing feed were then transferred to a 12-well plate allowed to dry

overnight at 20 ºC (Figure 4.3).

Figuthe NothydppmsamB: Tand hydtrea500HHPwith(HHtrea

B

A

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132

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133

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134

German). The inoculated fly eggs were incubated at room temperature (approximately

21 ºC) under a relative humidity of 32 % with the development of fly eggs being

monitored daily. The number and the morphology of larva, pupa and adult flies were

recorded with the hatching rate, development rate of pupa and development rate of

adult flies calculated by following equations (Equation 4.1, 4.2 and 4.3).

% /

4.1

% /

4.2

/

4.3

The length of larva, pupa and adult fly was measured from images taken from a stereo

microscope (Carl Zeiss Microscope GmbH, Jena, German) by comparing the image

with one of a ruler taken under the same conditions.

4.2.6 Data analysis

In the patulin sensitivity evaluation, experiments were evaluated six times (n = 6)

using the D. melanogaster model system using a completely randomized design. In

the HHP-detoxification experiments, treatments were performed with three replicates

using a completely randomized design. For each replication, six replicate samples

were conducted (n = 18) using the D. melanogaster model system. The data obtained

for hatching rate, development rate of pupa and development rate of adult fly were

expressed as mean values and standard deviation (SD). The results were analyzed

135

using one-way analysis of variance (ANOVA) followed by Tukey's HSD test with

p=0.05 using SPSS Statistics 17.0 (IBM Corporation, Armonk, New York, U.S.A.).

4.3 Results

4.3.1 Patulin sensitivity evaluation in D. melanogaster model system

Baseline studies assessed the sensitivity of fruit flies to different levels of patulin

supplemented into the lab fly food during the incubation of fruit fly D. melanogaster.

The life cycle of D. melanogaster was observed as larva (day 1~6), pupae (day 7~12)

and adult flies (day 13~16). It was found that the highest concentration of patulin (500

mg/L) had a significant effect on the extent and rate of hatching along with the

subsequent larva development (Table 4.1). There were no significant differences (P >

0.05) in terms of hatching rate, development rate of pupa and development rate of

adult fly and the length of larva, pupa and adult fly when patulin doses of 200 ppm

were applied (Table 4.1 and Table 4.2). The images of larva, pupa and adult flies at

day 6, 10 and 15 are as shown in Figures 4.4, 4.5 and 4.6. Surviving larva lost

viability by day 11 in the 500 ppm patulin supplemented fly food. The results

indicated that the minimum concentration of patulin that resulted in a larvicidal effect

on D. melanogaster was between 200 and 500 ppm. Therefore, 500 ppm was selected

as the patulin concentration used in subsequent experiments to assess the toxic effects

of byproducts derived from high pressure treated samples.

136

Table 4. 1-Hatching rate of larva, development rate of pupa and development rate of adult fly when patulin concentration ranged from 0 to 500 ppm (0, 0.5, 1, 20, 50, 100, 200 and 500 ppm) in the lab fly food in the 12-well plate Concentration of patulin (mg·L-1)

Hatching rate at Day 6 (%) a

Development rate of pupa at Day 10 (%) a

Development rate of adult at Day 15 (%) a

0 61.8 ± 12.5 A 63.4 ± 15.7 A 60.5 ± 12.7 A 0.5 62.3 ± 13.0 A 62.3 ± 13.0 A 57.4 ± 12.0 A 1 64.4 ± 12.6 A 66.1 ± 15.2 A 60.7 ± 16.3 A 20 62.5 ± 12.6 A 63.4 ± 13.1 A 60.8 ± 14.1 A 50 62.7 ± 10.9 A 65.4 ± 11.4 A 61.4 ± 8.1 A 100 57.2 ± 4.7 A 57.2 ± 4.7 A 56.5 ± 4.5 A 200 62.2 ± 7.5 A 62.8 ± 6.6 A 59.3 ± 8.2 A 500 28.1 ± 8.6 B 0 ± 0 B 0 ± 0 B a Values are averages ± standard deviations (n = 6). A different letter (A, B) indicates significant differences (P < 0.05) in mean values were observed.

137

Table 4. 2- Length of larva, pupa and adult fly at day 6, 10 and 15 (mm) in patulin containing lab fly food Patulin concentration Day 6 (mm)a Day 10 (mm)a Day 15 (mm)a 0 ppm 3.3±0.2A 3.2±0.2A 2.4±0.1A 0.5 ppm 3.3±0.1A 3.2±0.1A 2.3±0.2A 1 ppm 3.4±0.2A 3.1±0.2A 2.4±0.2A 20 ppm 3.4±0.1A 3.2±0.2A 2.4±0.1A 50 ppm 3.3±0.2A 3.2±0.1A 2.3±0.2A 100 ppm 3.4±0.1A 3.1±0.2A 2.3±0.1A 200 ppm 3.4±0.1A 3.2±0.2A 2.4±0.1A 500 ppm 1.4±0.2B - - a Values are averages ± standard deviations (n = 6). A different letter (A, B) indicates significant differences (P < 0.05) in mean values were observed.

138

Figure 4. 4- Pictures of larva at day 6

A

A: 0 ppm of patulin B: 0.5 ppm of patulin C: 1 ppm of patulin D: 20 ppm of patulin E: 50 ppm of patulin F: 100 ppm of patulin G: 200 ppm of patulin H: 500 ppm of patulin

B

C D

E F

G H

139

Figure 4. 5- Pictures of pupa at day 10


A B

C D

E F

G H

140

Figure 4. 6- Pictures of adult fly at day 15


A B

C D

E F

G H

141

4.3.2 HHP-detoxification evaluation in D. melanogaster model system

Level of patulin degradation in juice following HHP processing

The patulin concentration in apple and spinach juice containing BSA samples was

reduced from 5000 ppm to 2770 ppm (HHP-T) following HHP treatment. The patulin

level in the control BSA added juice samples (PAT-C) detected by HPLC was 5000

ppm. The PAT-S samples of BSA added AS juice contained 2770 ppm of patulin

without HHP treatment (Table 4.3). The HHP-treated H2O2 added AS juice samples

which initially contained 5000 ppm, contained 2140 ppm (HHP-T) of patulin after

HHP treatment of 600 MPa for 300 s. The patulin level in the control hydrogen

peroxide added juice samples (PAT-C) detected by HPLC was 5000 ppm. The PAT-

S samples of hydrogen peroxide added AS juice contained 2140 ppm of patulin

without HHP treatment (Table 4.4). The preheat-HHP treated samples of the nitrite

added apple and spinach juice which initially contained 5000 ppm of patulin,

contained 1320 ppm (HHP-T) of patulin after preheat treatment at 180 °C for 3 min

and HHP treatment of 600 MPa for 300 s. The patulin level in the control nitrite added

juice samples (PAT-C) detected by HPLC was 5000 ppm. The PAT-S samples of

nitrite added AS juice contained 1320 ppm of patulin without preheat and HHP

treatment (Table 4.5).

Table 4. 3- Patulin concentration in the five sets of samples (HHP-B, HHP-C, PAT-C, HHP-T and PAT-S samples) in the BSA modified juice for D. melanogaster model system

Samples Spiked patulin conc. in BSA modified AS juice (ppm)

HHP treatment Final patulin conc. in juice (ppm)

HHP-B 0 No 0 HHP-C 0 Yes 0 PAT-C 5000 No 5000 HHP-T 5000 Yes 2770 PAT-S 2770 No 2770

142

Table 4. 4- Patulin concentration in the five sets of samples (HHP-B, HHP-C, PAT-C, HHP-T and PAT-S samples) in the H2O2 modified juice for D. melanogaster model system

Samples Spiked patulin conc. in H2O2 modified AS juice (ppm)



Table 4. 5- Patulin concentration in the five sets of samples (HHP-B, HHP-C, PAT-C, HHP-T and PAT-S samples) in the nitrite modified juice for D. melanogaster model system

Samples Spiked patulin conc. in nitrite modified AS juice (ppm)



Larva, pupa and fly development on feed supplemented with feed containing no

patulin

The results showed that the survival rates at different development stages among

HHP-B and HHP-C (without patulin) were not significantly different for the BSA

added AS juice (Figure 4.7, 4.8 and 4.9), hydrogen peroxide added AS juice (Figure

4.10, 4.11 and 4.12) or nitrite added AS juice (Figure 4.13, 4.14 and 4.15),

respectively.

Larva, pupa and fly development on feed supplemented with patulin containing

juice subjected to HHP

The results showed that the survival rates at different development stages among

143

HHP-T and PAT-S samples (277 ppm of patulin supplemented in fly food) were not

significantly different for the BSA added AS juice (Table 4.6), whereas only the larval

stage in the PAT-C samples (500 ppm of patulin supplemented in fly food) for the

BSA added AS juice showed significant difference (Table 4.6).

The results for the hydrogen peroxide added AS juice showed that the survival rates at

different development stages among HHP-T and PAT-S samples (214 ppm of patulin

supplemented in fly food) were not significantly different (Table 4.7), whereas only

larval stage in the PAT-C samples (500 ppm of patulin supplemented in fly food) for

the hydrogen peroxide added AS juice showed significant difference (Table 4.7).

The results for the nitrite added AS juice showed that the survival rates at different

development stages among HHP-T and PAT-S samples (132 ppm of patulin

supplemented in fly food) were not significantly different (Table 4.8), whereas only

larval stage in the PAT-C samples (500ppm of patulin supplemented in fly food) for

the nitrite added AS juice demonstrated no additional toxicity contributed by the

HHP-degraded products of patulin (Table 4.8).

None of the larva illustrated toxic effects when provided fly food that had been

supplemented with BSA and patulin containing juice then treated with high pressure

(Figure 4.7). In contrast, the same BSA and patulin containing feed that had not been

high pressure processed resulted in loss of viability in a proportion of the eggs.

The hatching rate (56.8 %) of fly eggs incubated on the lab fly food containing HHP

treated BSA and patulin AS juice emerged as larva that compares to 5.7 % of fly eggs

incubated on the non-HHP feed control (Table 4.6). The result indicates that patulin

that had been subjected to HHP was less toxic compared to native mycotoxin.

The control samples (PAT-C) containing lab fly food (500 ppm of patulin

144

concentration in the lab fly food) completely inhibited the pupation rate, as the larva

was feeding on the toxic patulin containing fly food (500 ppm in the fly food). In

contrast, the pupa developed to a greater extent on HHP treated samples although only

62 % of those eggs fully developed to pupa (Table 4.6).

The control (PAT-C) containing lab fly food (500 ppm patulin in the lab fly food)

affected the growth and development of adult fly significantly compared to the growth

and development of adult fly feeding on the HHP treated sample (Table 4.6). The

control (PAT-C) containing lab fly food (500 ppm patulin in the lab fly food)

completely inhibited the growth and development of adult fly (Table 4.6). In contrast,

those flies feeding on HHP treated feed were not significantly different (P>0.05) to

controls that had no mycotoxin addition (Table 4.6).

145

0

10

20

30

40

50

60

0 2 4 6 8

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Egg hatching(%)

Figure 4. 7- The comparison of hatching rates of fly eggs for the toxicity assay for BSA added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 277 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin= 277 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

Figure 4. 8- The comparison of pupation rates for the toxicity assay for BSA added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 277 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin= 277 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

0

10

20

30

40

50

60

70

0 5 10 15

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Pupationrate(%

)

146

Figure 4. 9- The comparison of the development rates of adult flies for the toxicity assay for BSA added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 277 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin= 277 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

0

10

20

30

40

50

60

70

80

0 5 10 15 20

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Developmen

t rate of adult fly (%)

Day

147

Table 4. 6- Hatching rate and development rate of pupa and development rate of adult fly at Day 6, 10 and 15 for the patulin toxicity assay for BSA added apple and spinach juice Samples Hatching rate at

Day 6 (%) a Development rate of pupa at Day 10 (%) a


HHP-B 52.4 ± 12.5 A 59.3 ± 16.0 A 55.9 ± 16.1 A PAT-S 52.4 ± 9.0 A 59.5 ± 5.5 A 61.9 ± 14.1 A PAT-C 5.7 ± 2.9 B 0± 0 B 0 ±0 B HHP-T 56.8 ± 14.9 A 61.7 ± 5.4 A 58.0 ± 15.4 A HHP-C 53.4 ± 13.5 A 59.9 ± 5.5 A 68.0 ± 9.7 A a Values are averages ± standard deviations (n = 18). A different letter (A, B) indicates significant differences (P < 0.05) in mean values were observed. Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 277 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin= 277 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

148

For the H2O2 added AS juice, the survival curves of larva, pupa and adult fly among

the blank (HHP-B), HHP control (HHP-C), patulin treated (HHP-T), patulin spiked

(PAT-S) and patulin control (PAT-C) samples are shown in Figures 4.10, 4.11 and

4.12. The results showed that the survival rates at different development stages among

the blank(HHP-B), HHP control (HHP-C), patulin treated(HHP-T) and patulin

spiked(PAT-S) samples were not significantly different, whereas only larval stage in

the lab fly food containing patulin control (PAT-C) samples (500 ppm of patulin in

the lab fly food). For the H2O2 added AS juice, at day 6, the hatching rates of fly eggs

in the lab fly food containing blank (HHP-B) juice, spiked (PAT-S) juice, HHP

control (HHP-C) juice and treated (HHP-T) juice were 51.7 %, 56.0 %, 52.7 % and

53.6 % as shown in Table 4.7, respectively. While the egg hatching rate in the fly

food containing the control (PAT-C) sample was 11.2 % (Table 4.7). The control

(PAT-C) sample containing lab fly food completely inhibited the development of

pupa. The spiked (PAT-S) and treated (HHP-T) had 59.6 % and 58.3 % of pupa

survival at day 10, respectively as shown in Table 4.7. The control (PAT-C) samples

(500 ppm of patulin in the lab fly food ) affected the growth and development of adult

fly significantly compared to the growth and development of adult fly in the lab fly

food containing spiked (PAT-S) and treated (HHP-T) samples, at day 15. The

hatching rate, development rate of pupa and development rate of adult fly of fly eggs

in the HHP-B (patulin = 0 ppm without HHP treatment) and HHP-C (patulin = 0 ppm

with HHP treatment) containing lab fly food were not significantly different compared

to those of fly eggs in the PAT-S and HHP-T containing lab fly food (214 ppm of

patulin concentration in the lab fly food) as shown in Table 4.7.

149

Figure 4. 10- The comparison of hatching rates for the toxicity assay for hydrogen peroxide added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 214 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin = 214 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

Figure 4. 11- The comparison of pupation rates for the toxicity assay for hydrogen peroxide added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 214 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin= 214 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

0

10

20

30

40

50

60

0 2 4 6 8

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Egg hatching(%)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 5 10 15

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Pupation rate(%)

150

Figure 4. 12- The comparison of the development rates of adult fly for the toxicity assay for hydrogen peroxide added apple and spinach juice Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 214 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin = 214 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

0

10

20

30

40

50

60

0 5 10 15 20

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Developmen


151

Table 4. 7-Hatching rate and development rate of pupa and development rate of adult fly at Day 6, 10 and 15 for the patulin toxicity assay for hydrogen peroxide added apple and spinach juice Samples Hatching rate at



HHP-B 51.7 ± 9.8 A 56.3 ± 12.3 A 54.1 ± 14.7 A PAT-S 56.0 ± 8.0 A 59.6 ± 8.1 A 56.1 ± 11.5 A PAT-C 11.2 ± 2.3 B 0± 0 B 0 ±0 B HHP-T 53.6 ± 2.0 A 58.3± 3.1 A 53.7 ± 4.7 A HHP-C 52.7 ± 12.8 A 57.3 ± 15.3 A 54.7 ± 6.7 A a Values are averages ± standard deviations (n = 18). A different letter (A, B) indicates significant differences (P < 0.05) in mean values were observed. Note: HHP-B (patulin = 0 ppm without HHP treatment), PAT-S (patulin = 214 ppm without HHP treatment), PAT-C (patulin = 500 ppm without HHP treatment), HHP-T (patulin = 214 ppm with HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

152

For the preheated and HHP-treated samples of the nitrite added apple and spinach

juice, the survival curves of larva, pupa and adult flies among the blank (HHP-B),

HHP control (HHP-C), patulin treated (HHP-T), patulin spiked (PAT-S) and patulin

control (PAT-C) samples are shown in Figures 4.13, 4.14 and 4.15. The results

showed that the survival rates at different development stages among the blank (HHP-

B), HHP control (HHP-C), patulin treated (HHP-T) and patulin spiked (PAT-S)

samples were not significantly different (Table 4.8), whereas only larval stage in the

patulin control (PAT-C) samples. For the nitrite added apple and spinach juice, at day

6, the hatching rates of fly eggs in the lab fly food containing blank (HHP-B) juice,

HHP control (HHP-C), spiked (PAT-S) juice and treated (HHP-T) juice were 56.9 %,

54.3 %, 49.8 % and 49.2 %(Table 4.8), respectively. While the egg hatching rate in

the fly food containing the control (PAT-C) sample was 10.7 % (Table 4.8). In Table

4.8, it is shown that the control (PAT-C) samples completely inhibited the

development of pupa. The spiked (PAT-S) and treated (HHP-T) had 55.6 % and 54.6 %

pupa survival at day 10 (Table 4.8), respectively. The control (PAT-C) samples (500

ppm of patulin in lab fly food containing PAT-C juice) affected the growth and

development of adult fly significantly compared to the growth and development of

adult fly in spiked (PAT-S) and treated (HHP-T) samples, at day 15. The adult fly

survival rates were 53.4 % and 50.3 %, respectively as shown in Table 4.8. While the

control (PAT-C) containing lab fly food (500 ppm patulin in the lab fly food)

inhibited the growth and development of adult fly completely with the development

rate of adult fly of 0 % as shown in Table 4.8. The hatching rate, development rate of

pupa and development rate of adult fly from fly eggs in the HHP-B (patulin = 0 ppm

without HHP treatment) and HHP-C (patulin = 0 ppm with HHP treatment)

153

containing lab fly food were not significantly different compared to those of fly eggs

in the PAT-S and HHP-T containing lab fly food (132 ppm of patulin concentration in

the lab fly food) as shown in Table 4.8.

Figure 4. 13- The comparison of hatching rates for the toxicity assay for nitrite added apple and spinach juice Note: HHP-B (patulin = 0 ppm without preheat and HHP treatment), PAT-S (patulin = 132 ppm without preheat and HHP treatment), PAT-C (patulin = 500 ppm without preheat and HHP treatment), HHP-T (patulin= 132 ppm with preheat and HHP treatment) and HHP-C (patulin = 0 ppm with preheat and HHP treatment)

0

10

20

30

40

50

60

0 2 4 6 8

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Egg hatching(%)

154

Figure 4. 14- The comparison of pupation rates for the toxicity assay for nitrite added apple and spinach juice Note: HHP-B (patulin = 0 ppm without preheat and HHP treatment), PAT-S (patulin = 132 ppm without preheat and HHP treatment), PAT-C (patulin = 500 ppm without preheat and HHP treatment), HHP-T (patulin= 132 ppm with preheat and HHP treatment) and HHP-C (patulin = 0 ppm with preheat and HHP treatment)

Figure 4. 15- The comparison of the development rates of adult flies for the toxicity assay for nitrite added apple and spinach juice Note: HHP-B (patulin = 0 ppm without preheat and HHP treatment), PAT-S (patulin = 132 ppm without preheat and HHP treatment), PAT-C (patulin = 500 ppm without preheat and HHP treatment), HHP-T (patulin= 132 ppm with preheat and HHP treatment) and HHP-C (patulin = 0 ppm with preheat and HHP treatment)

0

10

20

30

40

50

60

70

0 5 10 15

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Pupationrate(%)

0

10

20

30

40

50

60

70

0 5 10 15 20

HHP‐B

PAT‐S

PAT‐C

HHP‐T

HHP‐C

Day

Developmen


155

Table 4. 8- Hatching rate and development rate of pupa and development rate of adult fly at Day 6, 10 and 15 for the patulin toxicity assay for nitrite added apple and spinach juice Samples Hatching rate at



HHP-B 56.9 ± 8.1 A 63.4 ± 15.7 A 67.1 ± 17.5 A PAT-S 49.8 ± 4.2 A 55.6 ± 4.9 A 53.4 ± 3.0 A PAT-C 10.7 ± 1.7 B 0± 0 B 0 ±0 B HHP-T 49.2 ± 5.9 A 54.6 ± 5.8 A 50.3 ± 6.9 A HHP-C 54.3 ± 13.1 A 58.9 ± 6.0 A 54.7 ± 7.5 A a Values are averages ± standard deviations (n = 18). A different letter (A, B) indicates significant differences (P < 0.05) in mean values were observed. Note: HHP-B (patulin = 0 ppm without preheat and HHP treatment), PAT-S (patulin = 132 ppm without preheat and HHP treatment), PAT-C (patulin = 500 ppm without preheat and HHP treatment), HHP-T (patulin= 132 ppm with preheat and HHP treatment) and HHP-C (patulin = 0 ppm with preheat and HHP treatment)

156

4.4 Discussion

The D. melanogaster model system was applied to assess if the byproducts of HHP

assisted patulin degradation elicited the same toxicity as the native mycotoxin. It was

found that patulin had a significant effect on egg, larva, pupa and fly development.

The results are in agreement with others using the same model to illustrate the toxic

effects of patulin (Belitsky, Khovanova, Budunova, & Sharuptis, 1985; Cole &

Rolinson, 1972; Paterson, Simmonds, & Blaney, 1987). In the aforementioned studies,

it was found that patulin was required to be > 200 ppm before negative effects on fly

development were observed. The current study found the same result given that

patulin provided at 500 ppm resulted in a notable imparement of egg, larva, pupa or

fly development. However, if the patulin was subjected to HHP prior to incorporating

into the fly food the development of flies through their life cycle was not different

compared to feed containing no mycotoxin. The results suggest that the degradation

products of patulin HHP processed in juice were non-toxic.

In a previous study it was found that patulin-cysteine adduct mixtures had been shown

to reduce the bactericidal effects of patulin by more than 100 fold (Lieu & Bullerman,

1978). In another study, treatment with thiol compounds such as cysteine and

glutathione prevented the negative effects of patulin infection on rumen fermentation

(Morgavi, Boudra, Jouany, & Graviou, 2003).

In the interaction of patulin with oxidizing agent such as hydrogen peroxide or nitrite,

the electrophilic properties of patulin were probably inhibited after the interaction.

Therefore, the toxicity of patulin was decreased due to the loss of activity. One

mechanism of patulin toxicity was to cause toxic effects when reacting with thiol

157

groups associated with enzymes due to the electrophilic properties of patulin

(Barhoumi & Burghardt, 1996). In the current study, it was found that HHP

processing decreased the toxicity of patulin contaminated juice through

supplementing the juice with BSA, hydrogen peroxide or nitrite.

The toxicity assay using the fruit fly (D. melanogaster) model preliminarily

confirmed HHP processing can be safely applied in the degradation of patulin in fruit

and vegetable beverage. However, the model still has limitations such as the inability

to determine the concentration of byproducts and also the need for patulin

concentration in excess of what would be typically encountered. The model can only

evaluate the toxicity of patulin byproducts in terms of acute toxicity in the current

study.

4.5 Conclusions

In summary, by using the metamorphosis insect (D. melanogaster) model, compared

to the spiked (PAT-S), HHP-C and HHP-B samples, not significantly different results

of hatching and development rate of fruit fly (D. Melanogaster) for HHP-T samples

supported no additional toxicity contributed by the HHP-degraded products of patulin

and other HHP sensitive compounds in apple and spinach juice were produced.

Compared to PAT-C samples, significantly different results of hatching and

development rate of fruit fly (D. Melanogaster) for HHP-T samples supported that the

toxicity of patulin was decreased by the degradation effects of HHP processing on

patulin.

158

Chapter Five

Conclusions and Recommendations

159

5.1 Conclusions

The study investigated the electrochemical based sensor for quantification of patulin

in beverages and degradation of patulin in different juices by high hydrostatic

pressure processing and the toxicity of the HHP-degraded adduct, aimed at

establishing the fundamental understanding needed to further explore the solution of

patulin contamination in beverage products.

In the first section of the study, the quantification of patulin in beverages using an

electrochemical based sensor was investigated. The electrochemical device was

effective to detect patulin. Moreover, the electrochemical behavior and the selectivity

of the sensor were studied as well to explore their relation with the sensor response.

The sensor response was found to be affected by the pH of the supporting electrolyte,

the applied potential and the square wave frequency. Moreover, the sensor sensitivity

was not interfered by the malic acid or 5-HMF but was interfered by thiol constituents

since the components of apple juice were so complex. When patulin concentration

ranged from 80 ppb to 800 ppb in the pyrrole mixture, the patulin concentration and

the decrease in oxidation current relative to controls was correlated with the

correlation coefficient of 0.99.

In the second part of the study the behavior of patulin degradation in different juices

as affected by the pressure level and time of high hydrostatic pressure processing was

investigated. The patulin degradation rate was affected by both pressure level and

time. High pressure treated juice was found to cause significantly higher patulin

degradation rate as compared to low pressure treated juice. As expected, patulin

degradation was depending on the juice substrate .Therefore, the intrinsic property

such as the content of ascorbic acid, thiol and nitrite was studied in order to explore

160

their relationship with patulin degradation. Patulin degradation in juice containing

high level of thiol and nitrite was significantly faster than juice containing low levels

of these components. Therefore, the patulin removal technique should take the

pressure level, time, juice substrate components like thiol and nitrite into

consideration.

As the major components that can interact with patulin in juice, ascorbic acid, thiol-

containing protein, oxidizing agent and nitrite were investigated as the factors

influencing patulin degradation during HHP processing in Chapter 3. It was found that

ascorbic acid did not enhance patulin removal during the HHP processing but thiol-

containing BSA, hydrogen peroxide, nitrite could enhance patulin degradation during

HHP technique. Moreover, the patulin reduction kinetic in the solution system was

screened for different mathematical models and can be further analysed using the

Weibull model. The above conclusion leads to a further study of the toxicity

evaluation of HHP-degraded adduct of patulin in Chapter 4 by exposing it to the fruit

flies (Drosophila melanogaster). It was found that no additional toxicity contributed

by the HHP-degraded products of patulin and other HHP sensitive compounds in

apple and spinach juice was produced.

5.2 Recommendations

Overall, this thesis research has established some fundamental understanding of how

patulin is detected using the electrochemical based sensor and degraded by high

hydrostatic pressure processing, which may serve as a foundation for future research.

Based on the results gathered and the phenomena observed during the course of this

research, the following recommendations can be made for future studies:

161

(1) The chemistry characterization of the adduct formed through patulin and pyrrole

incubation. The exact chemical structure of the formed adduct by patulin and

pyrrole during incubation is unknown yet. The chemistry characterization of the

adduct may help to improve the performance of the electrochemical based sensor

by adjusting the influencing factors.

(2) Effects of pressure level and time on patulin degradation in vegetable juice.

Vegetable juice has different chemical compositions such as high thiol and nitrite

content and low acid than fruit juices, which may result in different patulin

degradation behavior.

(3) Model of patulin degradation during HHP considering pressure level, pH,

temperature and principal composition chemicals. A fully developed model can be

applied to predict patulin degradation extent to achieve regulated patulin level for

contaminated juice using the novel food processing technique-high hydrostatic

pressure processing.

(4) The toxicity evaluation of the HHP-degraded adduct from patulin using animal

trial. Animal trial can be applied to further study the toxicity of the HHP-degraded

adduct from patulin. The observed results can further evaluate the toxicity

compared to the fruit flies (Drosophila melanogaster).

162

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Control of Patulin in Fruit and Vegetable Beverage