1. health and fitness
2. disease

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
University of Guelph, 2015
Advisors:
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.
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.
III
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.
IV
TableofContents
Chapter 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 V
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 VI
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 VII
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 VIII
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 IX
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 X
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-pHBSA 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 Table 3. 8- Weibull model parameters for patulin decrease following a range of pressure-pHhydrogen peroxide concentration combinations in the hydrogen peroxide model systems
under HHP processing ......................................................................................... 110 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 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.................................................................................................. 112 XI
Table 3. 11- Weibull model parameters for patulin decrease following a range of pressure-pHnitrite 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 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 ......................................................................................................... 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 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 ........ 142 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 ....... 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 XII
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 XIII
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 XIV
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 XV
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 XVI
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
under HHP processing ......................................................................................... 106 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 Figure 3. 15- 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.................................................................................................. 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 Figure 3. 18- 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
....................................................................................................................... 116 XVII
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
under HHP processing ......................................................................................... 116 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 XVIII
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 XIX
Chapter One
Literature Review
1
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).
2
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, BeachamBowden, 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).
3
Table 1. 1- Patulin contamination incidences in several countries
Country reported
Patulin contamination level
Reference
in apple-based juice
Canada
12 % > 50 ppb in 2012
OMAFRA website
US
11.3 %>50 ppb exceptionally
Harris et al. 2009
up to 2700 ppb
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
4
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 Penicillinproducing 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
5
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.
6
Table 1. 2- Specific mycotoxins of significance in managing food safety produced by
different genera of fungi
Aspergillus
Penicillium
Fusarium
Claviceps
Aflatoxin B1,
Patulin
Fumonisins
Ergot
B2
Alkaloids
Aflatoxin M1
Critinin
Trichothecenes
(deoxynivalenol
and T-2)
Aflatoxin G1, Ochratoxin A
Zearalenone
G2
Ochratoxin A
Peniterm A
Cyclopiazonic Penicillin
acid
acid
Roquefortine
Isoflumigaclavines
A, B
Cyclopiazonic
acid
(Diekman &
(Kuiper-Goodman (Hussein &
(Brown, Yu,
Green, 1992;
& Scott, 1989;
Brasel, 2001;
Kelkar,
Sweeney &
Kuipergoodman, Panaccione,
Fernandes,
2005)
Dobson, 1998)
Scott, &
Nesbitt,
Watanabe,
Keller, et al.,
1987; Parry,
1996; Geiser,
Jenkinson, &
Pitt, & Taylor,
McLeod, 1995)
1998; KuiperGoodman &
Scott, 1989)
7
1
3
2
4
5
6
7
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
8
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 &
9
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,
10
& 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).
11
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 (DombrinkKurtzman, 2007; Keller, Turner, & Bennett, 2005; White, O'Callaghan, & Dobson,
12
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
13
antiioxidant thaat further reacts
r
with patulin to form variious adductts (Figure 1.6).
Inteerestingly thhese adductts, formed by
b the reacttion betweeen patulin and
a glutathiione,
have stronger oxidizing
o
power than the
t originall reactants (Fliege
(
& Metzler,
M
20000b).
Thiss would su
uggest that glutathionee-patulin addducts can be potentiaally more toxic
t
com
mpared to th
he original m
mycotoxin.
Figuure 1. 4- The
T formation of PAT
T/CYS P1 aadduct wheen patulin reacts
r
with free
cystteine
Souurce: Fliege and Metzleer (2000b)
14
O2 presencee Figgure 1. 5- Mechanism
M
of metal-cattalysed oxiddation of asccorbic acid
Souurce: Martell (1973)
15
Figuure 1. 6- Reeaction of paatulin with glutathione
Thee thiol grouup of glutaathione reacts with thhe Carbon-2
2 or Carbo
on-6 of pattulin
folloowed by ad
dditional reaactions to fo
orm differennt adducts.
Souurce: Fliege and Metzleer (2000a)
16
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).
Patulin content (%)
100
80
pH 2.5
pH 4
60
pH 5.5
40
pH 7
20
0
0
10
20
30
40
Storages(Days)
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 photo17
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;
18
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.
19
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
20
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.
21
: Pyrrole
: Patulin
Figure 1. 8- The mode of action of patulin reacting with pyrrole
Source: Namvar (2010)
22
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
23
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 halfcycle (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.
24
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
25
Figure 1. 11- Potential wave form for cyclic voltammetry
Source: Bard and Faulkner (2001)
Figure 1. 12- Change parameters dialog box for cyclic voltammetry
26
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
27
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
28
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).
29
Figure 1. 15- Schematic graph of high hydrostatic pressure equipment
Source: Koutchma, Guo, Patazca, and Parisi (2005); Patazca, Koutchma, and
Balasubramaniam (2007)
30
Figuure 1. 16- Application
A
of HHP in different
d
foood sectors (Hyperbaric
(
c, 2010)
In terms
t
of HHP
H
processsed foods, vegetabless and fruitss remain th
he predomiinant
prodduct processsed with avvocado and
d apple baseed productss being the main produucts,
althhough rice is also inccluded (Fig
gure 1.16). The mainn motivatioon for HHP
P of
vegetables/fruitts is to reeduce path
hogen and spoilage micro
m
floraa and enzzyme
inacctivation. Acidity
A
and/oor low wateer activity facilitates
f
shhelf-stabilitty although low
acidd starch prooducts can be prone to
o prematuree spoilage by spore foorming bacteria
(Rastogi, Ragh
havarao, Balasubramaaniam, Niraanjan, & Knorr,
K
2007
7; San Maartin,
Barbbosa-Canovvas, & Swannson, 2002)).
Meaat products, or more specifically
y ready-to-eeat (RTE) deli
d meats, and juicess are
incrreasingly siignificant products
p
forr HHP in recent
r
years. Within North
N
Ameerica,
HHP
P processinng is key ffor Listeriaa control and
a
reductioon of otherr pathogenss. A
31
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 shelflife 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
32
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 posttreatment 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).
33
Figuure 1. 17- Pressure
P
induuced damagge to microbbes
Souurce: Lado and
a Yousef (2002)
1.6.3 Variation
n in microb
bial inactiv
vation by hiigh hydrosttatic pressu
ure
In ggeneral term
ms it has been
b
found
d that prokaaryotes havve higher barotoleranc
b
ce to
presssure comppared to euukaryotes with
w
Gram positive bacteria
b
ex
xhibiting hiigher
resistance thann Gram negaative (Alpass, Kalchayaanand, Bozo
oglu, & Rayy, 2000; Huugas,
Garrriga, & Moonfort, 20022; Kalchayaanand, Sikess, Dunne, & Ray, 1998; Spilimbeergo,
Elvaassore, & Bertucco,
B
20002; Styles, Hoover, & Farkas, 199
91). Cocci have
h
a tendeency
to hhave higherr resistancee compared
d to rods w
with the highest barottolerance being
b
linkked to endoospores (Heeinz & Knorr, 1996; Jofre, Garrriga, & Ayymerich, 20008).
Althhough still to be confi
firmed, therrmophilic bacteria withh increased
d saturated fatty
34
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;
35
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).
36
Table 1. 3- D and Z
microbes
Microbe
Bacillus spores
Bacillus anthracis
Clostridium spp
Clostridium
sporogenes
Cronobacter
Escherichia coli
Listeria spp
Vibrio spp
Zygosaccharomyces
bailii
values for the high hydrostatic pressure inactivation of different
Pref (MPa)
400
400
400
400
Tref (°C)
100
NA
100
100
Log Dp (s)
0.27
2.33
0.85
0.70
Zp (MPa)
614.7
876.4
616.3
1088.6
ZT (°C)
45.2
NA
20.4
67.2
400
400
400
400
400
NA
30
30
30
30
0.19
0.88
0.56
0.058
0.84
368.2
385.6
298.9
206.9
91
NA
97.5
38.6
18.4
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;
37
Lori, Buckow,, Knorr, Heinz, & Leehmacheri, 2007; Pattterson, 2005; Patterson &
Kilppatrick, 19998).
Figuure 1. 18- Relationship
R
p between temperature
t
e and pressuure on the requiremen
r
nts to
achiieve a 5 logg cfu reductiion of modeel microbes
Souurce: Heinz and Buckow
w (2009)
1.6.5 Inactivattion of myccotoxins by high hydroostatic presssure
Thee fate of myycotoxins during
d
HHP
P has not beeen studied
d to any greeat extent given
g
thatt the processs is designned as a miccrobial reduuction step.. Yet, it hass been repoorted
thatt citrinin in black tablee olives cann be degradded by 1.3-1100 % (Figgure 1.19) using
u
treaatments in the
t order off 250 MPaa for 5 min at 35 ± 1 °C (Tokussoglu, Alpas, &
Bozzoglu, 2010)).
38
Citrinin degradation (%)
100
90
80
70
60
50
40
30
20
10
0
100 %
98 %
56 %
37 %
25 %
1.3 %
1
2
3
4
5
6
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
39
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.
40
Patulin reduction (%)
70
Apple conc(56 Brix)
60
Apple juice(12 Brix)
50
40
30
20
10
0
0
200
400
600
800
1000
Pressure level (MPa)
Figure 1. 20- Patulin reduction in apple juice and apple concentrate at 20 °C
Source: Bruna (1997)
41
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).
42
Table 1. 4- Effect of HHP processing on enzymes in different fruit and vegetable
matrices
Enzyme
Source
HHP conditions
Response
Source
Poly
methyl Apple
200-600
MPa, Increased activity (Baron, Denes,
Durier,
esterase
15-65 °C, 0.5-10 with pressure up &
to 40% Increased 2006)
min
activity
with
pressure up to
40 °C
Polyphenol
Apple
Up to 900 MPa
Inactivation >600 (Weemaes,
oxidase
MPa
Ludikhuyze,
Van
den
Broeck,
&
Hendrickx,
1998)
Peroxidase
Apple
600 MPa, 20 °C, Two-fold
(Prestamo,
15 min
increase
Arabas,
FonbergBroczek,
&
Arroyo, 2001)
Carrot
500 MPa, 20 °C, 70 % increase
(Anese, Nicoli,
1 min
Dallaglio,
&
Lerici, 1995)
Orange
400
MPa, 50 % inactivation (Cano,
32 °C,15 min
Hernandez, &
DeAncos,
1997)
Lipoxygenase
Avocado 689 MPa, 20 min 95 % inactivation (Palou, LopezMalo, BarbosaCanovas,
&
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, WeltiChanes, & Perez-Lamela, 2011; Tadapaneni, Daryaei, Krishnamurthy, Edirisinghe, &
43
Burrton-Freemaan, 2014). One of the key advaantages of HHP is th
he retentionn of
biom
molecules whilst
w
ensurring inactiv
vation of miicrobes andd spoilage enzymes.
e
Inn the
conttext of the current thessis it may appear
a
contrradictory too suggest thaat patulin could
be degraded
d
byy pressure treatment
t
w
whilst
the raw
w characterristics are preserved. There
T
have been no detailed sttudies perfoormed on the
t chemistry of patuulin under high
presssure althou
ugh it mayy be possibble to prediict behavio
our by reviewing reseearch
perfformed on other food constituentts. In this respect,
r
the most relev
vant example is
vitaamin C thaat like patuulin represeents a reacttive compo
ound encou
untered in food
systtems and exxhibits highher stability under aciddic condition
ns compareed to neutrall pH
(Sukkhmanov, Shatalov,
S
Peetrova, Bircca, & Gaceuu, 2014). From researcch performeed to
datee it has beeen demonsstrated the pressure innduced deggradation of vitamin C is
dependent on the
t processing time an
nd continuees during poost-treatmennt storage. Yet,
the extent of viitamin C loss is indepeendent of thhe applied pressure in th
he range off 350
– 5000 MPa (Figgure 1.21).
Figuure 1. 21- Vitamin
V
C looss by high hydrostatic pressure prrocessing
Souurce: Keenann, Brunton, Gormley, Butler,
B
Tiwaari, and Patrras (2010)
44
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.
45
Table 1. 5- HHP processing on bioactive components in fruit and vegetable juices
Product
Treatment conditions Major findings
Reference
( Torres, Tiwari,
Vit C losses less than
Orange juice
400-600
Patras, Cullen,
MPa/20 °C/15 min, 7 6 % after HP. First
Brunton, &
week storage at 4 and order degradation
O'Donnell, 2011)
kinetics for Vit C.
10 °C
500-600 MPa/35Vit C degradation rates (Polydera,
40 °C/3-4 min
lower than pasteurized Stoforos, &
juice immediately after Taoukis, 2003,
2005a, 2005b)
HP and during
subsequent storage.
Lower TAC loss of HP
samples during storage.
100-800 MPa/30Pressure induced folic
(Nguyen,
100 °C/0-90 min
acid degradation. TAC Indrawati, &
decreased as a function Hendrickx, 2003)
of time.
Strawberry
200-600
Vit C losses lower than (Sancho, Lambert,
beverage
MPa/20 °C/30 min
12 % after HP.
Demazeau,
Largeteau,
Bouvier, &
Narbonne, 1999)
Vegetable
100-400 MPa/20Vit C losses lower than (Barba, Esteve, &
Frigola, 2010)
beverage
42 °C/2-9 min
9 % and 16 to 48 %
losses in TC after HP.
TAC decreased as
treatment pressure
increased.
Blueberry
200-600 MPa/20Vit C losses lower than (Barba, Esteve, &
juice
42 °C/5-15 min
9 %.
Frigola, 2013)
(Plaza, SanchezVegetable
150-350
Decrease in carotene
Moreno, De
soup
MPa/60 °C/15 min
concentration as
Ancos, & Cano,
treatment pressure
2006)
increased.
Carrot juice
100-800 MPa/305-methyltetrahydrofolic (Indrawati,
Verlinde, Ottoy,
100 °C/0-90 min
acid is rather unstable
Van Loey, &
at pressures exceeding
Hendrickx, 2004)
500 MPa.
46
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.
47
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
Topaz
gold
10.5±4.5 8.5±4.8 10.8±3.8 46.6±51.7 8.3±3.7 12.5±11.3
Ascorbic
acid(mg/100
ml)
Source: Kolniak-Ostek, Oszmianski, and Wojdylo (2013)
48
Table 1. 7- Summary of patulin degradation in apple juice in previous studies.
Type of sample
Patulin Ascorbic Storage Degradation Reference
conc.
acid
(days)
(%)
(ppb)
addition
(mg/l)
Aqueous buffer 5000
solution, pH 3.5
0
8
20
Canned
juice
apple 4000
0
21
20-25
Apple
cloudy
juice, 82
81
81
103
501
999
14
14
14
45
35
64
Source: Drusch, Kopka, and Kaeding (2007)
49
(Brackett &
Marth,
1979a)
(P. M. Scott
& Somers,
1968)
(Steiner,
Werner, &
Washuettl,
1999)
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.
50
Table 1. 8-Summary of the significant thiols present in various fruits and vegetables
Source: Zhimin, Demirkol, Ercal, and Adams (2005)
51
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.
52
Table 1. 9- Nitrate content in the selected vegetables during different seasons
Vegetables
Winter (November-March)
Summer (April-October)
(mg/kg)
(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).
53
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).
54
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.
55
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.
56
Chapter Two
Electrochemical Based Sensor for
Quantification of Patulin in Beverages
57
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
58
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
59
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.
60
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
61
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.
62
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
63
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, &
64
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.
25
Current (μA)
20
15
10
5
0
0
20
40
60
80
100
Time (minute)
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.
65
100
A
80
60
potential(mV)
40
20
0
‐20
‐40
‐60
3
3.5
4
4.5
5
5.5
6
6.5
pH
30
B
25
Current(μA)
20
15
10
5
0
3
3.5
4
4.5
5
5.5
6
6.5
pH
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.
66
pH5
pH4
pH3.5
pH3
pH5.5
pH6
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
67
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.
68
90
A
80
potential(mV)
70
60
50
40
30
20
10
0
0.7
0.9
1.1
1.3
1.5
5
1.7
1.9
2.1
2
Potential
B
Figuure 2. 5- Thhe effect off the potentiial applied on
o the posittion (A) and
d current (B
B) of
the decrease inn oxidationn peak to control
c
(10000 ppb pyrrrole and 500
5 ppb pattulin
mixture)
mixxture to 10000 ppb pyrroole and 0 pppb patulin m
Notte: 0.1 M phhosphate buuffer of pH 5,
5 screen priinted electro
ode cards. The
T step chaange
wass 4 mV, S.W
W. amplitudee was 25 mV
V and the S.W.
S
frequen
ncy of 20 Hz.
H
2.3.5 Effect off the S.W. frequency
fr
Thee principle of
o SWV is to apply a po
otential stepp with the frequency
fr
beeing the invverse
of thhe pulse tim
me. The low
wer the frequuency, the longer
l
the pulse
p
duration and the time
of ccurrent meaasurement will
w be. Whhen high freequencies are
a applied the pulse is
i of
shorrter durationn and hencee likely inclludes a propportion of caapacitive cuurrent. From
m the
69
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.
70
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.
71
Current(μA)
50
45
40
35
30
25
20
15
10
5
0
y = 0.3455x + 16.485
R² = 0.9916
0
20
40
60
80
S.W. frequency(Hz)
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.
72
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
73
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.
74
900
y = 9.6194x + 29.884
R² = 0.9916
800
patulin(ppb)
700
600
500
400
300
200
100
0
0
20
40
60
80
100
Current (μA)
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.
75
Table 2. 1- Determination of patulin concentration using HPLC and the developed
electrochemical sensor
Sample number HPLC detected(ppb)
1 2 3 4 5 134.38±1.12
248.15±1.46
198.36±1.37
423.96±1.54
362.17±1.68
Electrochemical sensor detected (ppb) 135.16±1.62
246.96±1.28
197.75±1.84
425.18±1.26
362.84±1.38
Values are means ± standard deviations (n = 3) for all analyses.
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
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.
77
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.
78
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.
79
Chapter Three
High Hydrostatic Pressure Assisted Degradation
of Patulin in Fruit and Vegetable Beverages
80
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
81
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 SHaddition 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.
82
Ascoorbic acid
P
Patulin
Thiool
Hyddrogen
perooxide
Nitriite
Figuure 3. 1- The
T schemattic diagram
m of the interaction beetween the aforementiooned
com
mponents annd patulin
Souurce: Fliege and Metzleer (1999, 2000b); Karacca and Veliooglu (2009))
3.2 Materialls and Meethods
3.2.1 Reagentss
Patuulin, acetonnitrile (ACN
N), methanol, ethyl acettate, acetic acid, metapphosphoric acid,
a
5,5'--dithiobis-(2-nitrobenzzoic acid) (D
DTNB), boovine serum
m albumin (BSA),
(
ascoorbic
acidd, hydrogenn peroxide solution (30 % v/v inn H2O), iron(II) chloriide and soddium
83
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
84
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 96well 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.
85
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.
86
600 MPa, 300 s
Acetic acid buffer system, pH 4
Patulin and
(BSA 0 and 30 mg/ml, 20 ppm patulin)
sulfhydryl group
determination
Thiol and patulin
Acetic acid buffer system, pH 4
(Aa 0 and1000 ppm, 200ppb patulin)
600 MPa, 300 s
Patulin analysis
AS juice
(Aa 0 and1000 ppm added, 200 ppb patulin)
Ascorbic acid (Aa) and patulin
Apple juice
600 MPa, 300 s
(200 ppb patulin,
Patulin analysis
different concentration of
H2 O2 )
Hydrogen peroxide and patulin
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
87
o
AS juice
Preheat 50 C, 180 s
(200 ppb patulin)
AS juice
600 MPa, 180 s
Patulin analysis
(200 ppb patulin)
o
AS juice
(200 ppb patulin)
Preheat 50 C, 180 s
600 MPa, 180 s
o
AS juice
Preheat 50 C, 180 s
Patulin and nitrite analysis
(20 ppm patulin)
600 MPa, 180 s
Nitrite and patulin
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
88
Sulfhydryl protein model system
(1, 2 and 3 mg/ml BSA acetate buffer)
200
Oxidizing agent model system
(0.3 %, 0.5 % and 0.7 % H O +1 mM/L ferrous ions)
2
ppb
patulin spiked
2
Nitrite model system
Vacuum
(5.7, 11.4 and 17.1 mg/L nitrite +1 mM/L ferrous ions)
sealed
HPLC
HHP
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
89
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).
90
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 analysis
All the experiments were performed with three replicates. The results were expressed
as mean values and standard deviations (SD). The results were analyzed using oneway 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).
91
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)
Sulfhydryl Nitrite
Juice pH
Brix
Ascorbic
(mg/L)
group
types
acid
(mg/100ml) (µM/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).
92
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.
93
70
AS Juice
A
Patulin reduction (ppb)
60
50
600MPa
40
30
500MPa
20
10
400MPa
0
0
60
120
180
240
300
Time (s)
Patulin reduction (ppb)
70
PAM Juice
B
60
600MPa
50
40
500MPa
30
20
400MPa
10
0
0
60
120
180
240
300
Time(s)
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).
94
70
CAB Juice
C
Patulin reduction (ppb)
60
50
600MPa
40
30
500MPa
20
400MPa
10
0
0
60
120
18
80
240
300
Tim
me(s)
D
Figuure 3. 7- Paatulin degraddation in AS
A juice (A: Apple and spinach juiice), PAM juice
j
(B: Apple, pineapple and mint juice)), CAB juicce (C: Applle, carrot, beet,
b
lemon and
a
GJ juiice (D: Appple, romainne, celery, cucumber, spinach, kkale,
gingger juice) and
parssley and lem
mon juice).
95
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
PAM
2.63
2.63
4.40
4.40
6.65
CAB
2.58
2.58
6.39
6.39
11.50
GJ
8.02
4.34
10.28
4.81
15.65
96
8.72
6.65
7.27
7.79
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±0.9
91.38±0.71
2
600MPa/180s
172.29±0.56
55.38±1.09
87.41±1.0 171.12±1.34
8
600MPa/300s
174.29±0.62
83.87±1.01 111.64±1.2 177.40±1.02
2
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.
97
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.
98
Patulin (ppb)
50
45
40
35
30
25
20
15
10
5
0
y = 320.9x + 1.1646
R² = 0.9531
0
0.05
0.1
0.15
Ascorbic acid (mg/100ml)
Patulin (ppb)
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)
50
45
40
35
30
25
20
15
10
5
0
y = 67.172x + 3.1704
R² = 0.9546
0
0.2
0.4
0.6
0.8
Thiol content(uM/L)
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)
99
200
y = 81.493x ‐ 0.5687
R² = 0.9888
180
Patulin (ppb)
160
140
120
100
80
60
40
20
0
0
0.5
1
1.5
2
2.5
Nitrite content(mg/L)
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
100
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).
101
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.
Acetic acid buffer system, pH 4
Patulin
(BSA 0 mg/ml, 20 ppm patulin)
0%
degraded
by
600 MPa, 300s
Acetic acid buffer system, pH 4
Patulin degraded by
(BSA 30 mg/ml, 20 ppm patulin)
10.84 % and thiol
group by 17.3 μM/L
Patulin reduction (%)
Figure 3. 11- Determination of patulin decrease and thiol group decrease after HHP
processing
80.0
60.0
40.0
20.0
0.0
0%
2%
4%
6%
8%
10%
12%
Hydrogen peroxide content (v/v)
Figure 3. 12- Relationship between patulin degradation in apple juice and hydrogen
peroxide content under HHP treatment at 600 MPa for 300 s
102
o
AS juice
Preheat 50 C, 180 s
No patulin degradation
(200 ppb patulin)
AS juice
600 MPa, 180 s
18.23 % patulin degradation
(200 ppb patulin)
o
AS juice
(200 ppb patulin)
Preheat 50 C, 180 s
94.73 % patulin reduction
600 MPa, 180 s
o
AS juice
(20ppm patulin)
Preheat 50 C, 180 s
38.14 % patulin degradation
Nitrite degraded by 5.14 mg/L
600 MPa, 180 s
Figure 3. 13- Determination of patulin amount and nitrite content after HHP processing
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
103
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+0.05X2X37.96E-007X12-0.06X22-1.51E-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.
104
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
BSA
Patulin k
RMSE (10system (pHconc.
Shape (a)
r2
3
-5
10 /s
)
pressure)
mg/ml
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
F Value
p-value
Square
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
105
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
106
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
F Value
p-value
Square
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
107
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 DesignExpert 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+2.33E005 X1X3-8.53E-004 X2X3
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 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+4.83E004X1X3+0.10X2X3+3.52E-006X12+8.10E-004X22-1.58X32
108
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 shape constant (R2=0.9893)
(Table 3.10) in the hydrogen peroxide model solution system under HHP processing.
109
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
H2 O2
RMSE (10Patulin k (10Shape (a)
r2
5
3
system
conc.
/s)
)
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
F Value
p-value
Square
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
110
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
111
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
F Value
p-value
Square
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
112
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-006X1X32.34E-004X2X3-1.10E-008X12-7.03E-003X22+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+1.20E003X2X3-3.31E-006X12-0.15X22-8.62E-006X32
113
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.
114
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
Nitrite
RMSE (10Patulin k (10-5/s) Shape (a)
r2
3
system
conc.
)
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
F Value
p-value
Square
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
115
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
116
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
7
Residual
3.176E-003
4.538E-004
Cor Total
16
0.035
R-Squared 0.9103
117
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
118
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 Nacetyl-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 Nacetylcysteine 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
119
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.
120
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
121
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 preheating 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
122
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.
123
Chapter Four
Potential Toxic Effects of Patulin Degradation
Products Assessed using Fruit Fly (Drosophila
melanogaster) Toxicology Model
124
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.
125
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).
126
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.
127
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-methylhydroxybenzoate, 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
128
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.
129
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
130
(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 (HHPT) 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).
131
A
B
Figuure 4. 1- Th
he HHP-dettoxification
n assay usinng D. melan
nogaster moodel system
m for
the hydrogen peroxide
p
addded juice
Notte: A: The preparatioon for the HHP-T saamples and HHP-C saamples forr the
hyddrogen perox
xide added juice. HHP
P-T sampless were juice samples sp
piked with 5000
5
ppm
m of patulinn and then they were treated by HHP (600
0 MPa for 300 s). HH
HP-C
sam
mples were patulin-free
p
HP treatmennt samples.
juice samples with equuivalent HH
B: T
The HHP-d
detoxificatioon assay usiing D. melaanogaster model
m
system
m. The HH
HP-T
and HHP-C saamples weree prepared as shown inn Figure 4.1A. HHP-B
B samples were
w
mples withoout patulin spiked andd without H
HHP
hyddrogen perooxide addedd juice sam
treaatment. PAT
T-C samplees were hyd
drogen peroxide added juice samp
ples spiked with
5000 ppm of patulin
p
withhout HHP treatment,
t
w
which
weree prepared the
t same ass the
P-T samplees before thee HHP treattment. PAT
T-S sampless were juicee samples addded
HHP
withh the same concentration of patuliin in HHP-T
T samples after
a
HHP treatment.
t
n
n=18
(HH
HP treatmennt with threee replicatees, six repeeated samplles for fruiit fly assayy per
treaatment)
132
Figuure 4. 2- The
T preparaation for the HHP-T samples
s
andd HHP-C samples
s
forr the
nitriite added juuice
Notte: HHP-T samples
s
weere juice sam
mples spikeed with 50000 ppm of patulin
p
and then
theyy were treatted by prehheat and HH
HP (600 MPa
M for 300
0 s). HHP-C
C samples were
w
patuulin-free juice samples with equivaalent preheaat and HHP
P treatment samples.
s
Figuure 4. 3- So
okolowski laab fly food in
i 12-well plates
p
f
fly egggs
4.2.5 Collectioon and inocculation of fruit
Wild type Oregon
O
R from Sokolow
wski
Aduult male andd female D.. melanogasster flies (W
Labboratory, Unniversity off Toronto) were placeed onto appple juice aggar mixed with
yeasst extract in
n a containner topped with
w a perfforated filteer to permitt gas exchaange.
Thee eggs of fru
uit flies werre collected after 16 houurs. The egggs were harrvested from
m the
agarr surface ussing a plastiic scraper and
a then surrface disinfeected by subbmersion inn 10 %
bleaach for 2 min
m prior to rinsing witth sterile waater. Approoximately 30
3 eggs (277-34)
werre inoculated into eachh well of thee 12-well plate
p
(the labb fly food inside
i
the well)
w
and visualizedd using a stereo
s
micrroscope (C
Carl Zeiss Microscopy
M
y GmbH, Jena,
J
133
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
134
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.
135
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 Hatching rate at
Development rate of Development rate of
patulin (mg·L-1)
Day 6 (%) a
pupa at Day 10 (%) a
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
0±0
B
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.
136
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.
137
A
C
B
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
D
E
F
G
H
Figure 4. 4- Pictures of larva at day 6
138
A
B
C
D
E
F
G
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
H
Figure 4. 5- Pictures of pupa at day 10
139
A
B
C
D
E
F
G
H
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
Figure 4. 6- Pictures of adult fly at day 15
140
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 PATS 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
HHP treatment
Final patulin
Samples
Spiked patulin conc.
conc. in juice
in BSA modified AS
(ppm)
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
141
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
HHP treatment Final
patulin
Samples
Spiked patulin conc. in
conc. in juice
H2O2 modified AS juice
(ppm)
(ppm)
HHP-B
0
No
0
HHP-C
0
Yes
0
PAT-C
5000
No
5000
HHP-T
5000
Yes
2140
PAT-S
2140
No
2140
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
HHP treatment
Final patulin
Samples Spiked patulin conc. in
conc. in juice
nitrite modified AS
(ppm)
juice (ppm)
HHP-B
0
No
0
HHP-C
0
Yes
0
PAT-C
5000
No
5000
HHP-T
5000
Yes
1320
PAT-S
1320
No
1320
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
142
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
143
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).
144
60
Egg hatching(%)
50
40
HHP‐B
PAT‐S
30
PAT‐C
20
HHP‐T
10
HHP‐C
0
0
2
4
6
8
Day
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)
70
Pupation rate(%)
60
50
HHP‐B
40
PAT‐S
30
PAT‐C
HHP‐T
20
HHP‐C
10
0
0
5
10
15
Day
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)
145
Development rate of adult fly (%)
80
70
60
50
HHP‐B
40
PAT‐S
30
PAT‐C
20
HHP‐T
HHP‐C
10
0
0
5
10
15
20
Day
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)
146
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
Development rate of Development rate of
Day 6 (%) a
pupa at Day 10 (%) a
adult at Day 15 (%) 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
0
±0 B
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)
147
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.
148
60
Egg hatching(%)
50
40
HHP‐B
30
PAT‐S
PAT‐C
20
HHP‐T
10
HHP‐C
0
0
2
4
6
8
Day
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)
0.7
Pupation rate(%)
0.6
0.5
HHP‐B
0.4
PAT‐S
0.3
PAT‐C
0.2
HHP‐T
0.1
HHP‐C
0
0
5
10
15
Day
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)
149
Development rate of adult fly (%)
60
50
40
HHP‐B
30
PAT‐S
PAT‐C
20
HHP‐T
10
HHP‐C
0
0
5
10
15
20
Day
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)
150
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
Development rate of Development rate of
Day 6 (%) a
pupa at Day 10 (%) a
adult at Day 15 (%) a
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
0 ±0 B
B
HHP-T
53.6 ± 2.0 A
58.3± 3.1
53.7 ± 4.7 A
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)
151
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 (HHPB), 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)
152
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.
60
Egg hatching(%)
50
40
HHP‐B
30
PAT‐S
20
PAT‐C
HHP‐T
10
HHP‐C
0
0
2
4
6
8
Day
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)
153
70
Pupation rate(%)
60
50
HHP‐B
40
PAT‐S
30
PAT‐C
20
HHP‐T
10
HHP‐C
0
0
5
10
15
Day
Development rate of adult fly (%)
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)
70
60
50
HHP‐B
40
PAT‐S
30
PAT‐C
20
HHP‐T
10
HHP‐C
0
0
5
10
Day
15
20
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)
154
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
Development rate of Development rate of
Day 6 (%) a
pupa at Day 10 (%) a adult at Day 15 (%) a
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
0 ±0
B
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)
155
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
156
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.
157
Chapter Five
Conclusions and Recommendations
158
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
159
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, thiolcontaining 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 thiolcontaining 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:
160
(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).
161
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