The use of advanced oxidation processes in the degradation ...
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The use of advanced oxidation processes in the degradation of the pesticide chlorpyrifos
and reduction of microbial contamination on apples
By
Jordan Ho
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
© Jordan Ho, December, 2019
ABSTRACT
The use of advanced oxidation processes in the degradation of the pesticide chlorpyrifos and
reduction of microbial contamination on apples
Jordan Ho Advisors:
University of Guelph, 2019 Dr. Keith Warriner
Dr. Ryan Prosser
A method based on Advanced Oxidation Process (AOP) was validated for the degradation of
chlorpyrifos on apples and inactivating Escherichia coli O157:H7, along with Aspergillus niger
spores. AOP generates free-radicals using UV-C light (at 254 nm), hydrogen peroxide, and
ozone. The use of gaseous ozone alone was ineffective in chlorpyrifos degradation and was
therefore excluded from AOP use. Response surface methodology (RSM) was used to find that
the degradation of chlorpyrifos was primarily dependent on UV-C dose and hydrogen peroxide
temperature but not hydrogen peroxide concentration. The maximal degradation of chlorpyrifos
on apples was achieved through an AOP treatment applying 68.4 kJ/m2 UV dose and 1.22% v/v
H2O2 at 66°C that resulted in a 47% reduction (92µg) of the pesticide with < 0.004 µg
accumulation of chlorpyrifos-oxon. The same treatment supported a >6.56 log CFU reduction in
E. coli O157:H7 and >6.56 log CFU reduction of A. niger spores.
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ACKNOWLEDGEMENTS
First, I’d like to thank my advisor Dr. Keith Warriner for taking me on as a graduate student, a
cautionary tale I’m sure he would not repeat. Thanks for these two years, I’ve learned a lot in the
field of food safety and enjoyed every minute of it. I also learned, more than I wanted, about how
the world of academia works which is why I would hate to pursue a PhD degree! Too much
politics and drama, although entertaining as a spectator, it doesn’t seem fun as a participant. I’d
also like to thank my committee members Dr. Ryan Prosser and Dr. David Lubitz for helping me
develop my presentation skills during my committee presentations as well as helping me edit this
thesis. I hope you both well wishes and I couldn’t have asked for a better committee.
Thank you everyone in my lab, especially Fan, Mahdiyeh, and Joanna for helping me out with my
experiments. Next, I’d like to thank my friends and family for their support, especially Emma,
Jesse, Nick, and Siva. Special thanks to Andrew Green for helping answer any questions I had
about microbiology and life too maybe. Also special thanks to Katherine Katie Kathy Petker, and
Dr. Shane Walker for not throwing a toaster at me for my constant annoyance. May WW continue
again someday even though I am no longer there.
Lastly, thank you OMAFRA Agri-Food and Innovation for funding this project along with Clean
Works Corp. for their donation of equipment and consultancy.
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TABLE OF CONTENTS
ABSTRACT ............................................................................................................................................... ii
ACKNOWLEDGEMENTS ........................................................................................................................... iii
TABLE OF CONTENTS .............................................................................................................................. iv
LIST OF TABLES ....................................................................................................................................... vi
LIST OF FIGURES ....................................................................................................................................viii
LIST OF ABBREVIATIONS ......................................................................................................................... xi
Chapter 1: Introduction and Literature Review ........................................................................................ 1
1.1 Introduction ................................................................................................................................... 1
1.2 Size of the Fresh Produce Sector .................................................................................................... 2
1.3 Climate change and fresh produce safety ....................................................................................... 3
1.4 Pesticides ....................................................................................................................................... 4
1.4.1 Chlorpyrifos .......................................................................................................................... 10
1.4.2 Chlorpyrifos-Oxon ................................................................................................................. 13
1.5 Microbial Hazards ........................................................................................................................ 15
1.5.1 Escherichia coli O157:H7 ....................................................................................................... 16
1.5.2 Aspergillus niger spores......................................................................................................... 19
1.6 Current Treatments to Decrease Pesticide Residues Found on Produce ....................................... 21
1.6.1 Ultraviolet Radiation ............................................................................................................. 24
1.6.2 Ozone ................................................................................................................................... 26
1.7 Advanced Oxidation Process ........................................................................................................ 29
1.7.1 UV-based Advanced Oxidation Process ................................................................................. 32
1.7.2 Ozone-based Advanced Oxidation Process ............................................................................ 34
1.8 Response Surface Methodology ................................................................................................... 36
Hypothesis and Objectives..................................................................................................................... 38
2. Materials and Methods...................................................................................................................... 39
2.1 Materials ..................................................................................................................................... 39
2.2 Advanced Oxidation Process Reactor ........................................................................................... 39
2.3 Response Surface Methodology ................................................................................................... 41
2.4 AOP Treatment of Apple skins Spiked with Chlorpyrifos ............................................................... 43
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2.5 Validation Trial ............................................................................................................................. 45
2.6 UV Only Trial ................................................................................................................................ 45
2.7 Ozone Treatment of Apple Skins Spiked with Chlorpyrifos............................................................ 46
2.8 HPLC Analysis ............................................................................................................................... 48
2.9 Determination of Chlorpyrifos-Oxon Production by AOP Treatment using Q-ToF analysis ............ 48
2.10 Inactivation of Escherichia coli O157:H7 and Aspergillus niger .................................................... 50
2.11 Experimental plan and statistics ................................................................................................. 52
3. Results and Discussion ....................................................................................................................... 52
3.1 Optimization of Recovery Method and HPLC Analysis .................................................................. 52
3.2 Response Surface Methodology ................................................................................................... 54
3.3 Ultraviolet light mediated degradation of CPY .............................................................................. 63
3.4 CPY-O production from AOP exposure ......................................................................................... 65
3.5 Ozone Treatment ......................................................................................................................... 66
3.6 Microbial Inactivation .................................................................................................................. 68
4. Conclusions ....................................................................................................................................... 71
Future work ........................................................................................................................................... 72
References ............................................................................................................................................ 74
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LIST OF TABLES Table 1. Types of pesticides and their target organisms with examples that are currently used in
agriculture. .............................................................................................................................................. 4
Table 2. Different types of insecticides and their mechanism of action. Sourced from (NPIC, 2019). ...... 7
Table 3. Produce with the highest and lowest pesticide residues scores. Adapted from Environmental
Working Group. ...................................................................................................................................... 8
Table 4. Produce-linked foodborne outbreaks of Escherichia coli O157:H7 in North American between
1996 and 2018. Modified from (Green, 2018). ....................................................................................... 16
Table 5. Reduction of pesticide residues on produce by current washing treatments. .............................. 22
Table 6. Degradation of pesticides using AOPs and individual processes. .............................................. 29
Table 7. Oxidation potential of reactive species. Adapted from Parsons (2004). ..................................... 31
Table 8. Contamination and waste products treated with AOP technologies with pesticides and
microorganisms highlighted. Modified from Vogelpohl (2003). ............................................................. 32
Table 9. RSM trials (20) using various test parameters of UV-C dose (kJ/m2), temperature (°C) and
concentration (%) of hydrogen peroxide. ............................................................................................... 42
Table 10: Six center point replicate trials determining the replicability and precision of the experimental
method. Arranged from lowest to highest reduction corrected with the average (n=177) positive control
recovery of 89.4%. The standard deviation between reductions was 3.6 µg. ........................................... 43
Table 11. RSM trials with amount of CPY reduction (µg) observed using various test parameters of UV-C
dose (kJ/m2), temperature (°C) and concentration (%) of hydrogen peroxide. Reduction from each trial
was corrected using the average positive control recovery of 89.4% (n=177). ........................................ 58
Table 12: Six center point replicate trials determining the replicability and precision of the experimental
method. Arranged from lowest to highest reduction corrected with the average (n=177) positive control
recovery of 89.4%. The standard deviation between reductions was 3.6 µg. ........................................... 59
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Table 13. ANOVA analysis table of the linear model indicating that values lower than P < 0.05 are
significant. In this case, UV-C dose and H2O2 temperature are significant whereas H2O2 concentration
was not significant. * indicates P < 0.05................................................................................................. 59
Table 14. Q-ToF analysis of CPY-O on apple skins spiked with CPY. It can be observed that apple skin
samples treated with AOP produced the by-product CPY-O while samples spiked with CPY but not
treated with AOP had concentrations below the limit of detection. ......................................................... 66
Table 15. Log count reduction of Escherichia coli O157:H7 and Aspergillus niger spores inoculated onto
apple peel sections then treated with UV-C (at 254 nm), hydrogen peroxide (1.22% v/v at 66C) or a
combination of UV-C and hydrogen peroxide ........................................................................................ 70
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LIST OF FIGURES
Figure 1. Bioaccumulation of the pesticide DDT throughout the food chain. Modified from Penn State
Pesticide Education Manual. .................................................................................................................... 5
Figure 2. Mechanism of action of acetylcholinesterase breaking down acetylcholine into choline and
acetic acid. .............................................................................................................................................. 6
Figure 3. Fate of pesticides after application and factors affecting them. Adapted from Declour et al.
(2015). .................................................................................................................................................. 10
Figure 4. Structures of chlorpyrifos and its active form chlorpyrifos-oxon as well as the inactive form
TCP. Adapted from USEPA (n.d). ......................................................................................................... 14
Figure 5. Mechanism of action of chlorpyrifos-oxon. It can phosphorylate AChE to permanently
inactivate the enzyme or it can temporarily inactivate it. Adapted from Solomon (2014). ....................... 14
Figure 6. Mechanism of action of STEC in causing cell death. 1.) STEC adheres to intestinal lumen, 2.)
Shiga toxin (Stx) is produced, 3.) Stx adhering onto cell, 4.) Endocytosis of Stx into the cell, 5.) Stx in a
vesicle to be transported into the Golgi complex, 6.) Stx in the Golgi complex, 7.) Stx breaks apart and
the toxic A1 subunit is released, 8.) A1 subunit attaches to rRNA, 9.) RNA cannot be translated due to the
A1 subunit so protein synthesis is inhibited, 10.) Lack of protein synthesis leads to cell death. Modified
from V. Castro, Carvalho, Conte Junior, & Figueiredo (2017). ............................................................... 17
Figure 7. Transmission routes of STEC from farm cattle ingesting STEC (1) then contaminating the
environment with fecal shedding (2) leading to contamination of food and water (3 and 4) consumed by
humans. People can also transmit STEC from one to another (5). Adapted from Fairbrother and Nadeau
(2006). .................................................................................................................................................. 19
Figure 8. The UV light spectrum of the electromagnetic spectrum. Modified from Evoqua Water
Technologies, LLC. https://www.evoqua.com/en/brands/ETS_UV/Pages/how-ets-uv-works.aspx .......... 25
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Figure 9. Schematic of ozone production using a corona discharge ozone generator. Modified from
Oxidation Technologies, LLC. https://www.oxidationtech.com/ozone/ozone-production/corona-
discharge.html ....................................................................................................................................... 27
Figure 10. Absorbance spectra of hydrogen peroxide at different wavelengths in Angstroms (254 nm =
2540 Angstroms). Modified from USP technologies. http://www.h2o2.com/technical-library/physical-
chemical-properties/radiation-properties/default.aspx?pid=65&name=Ultraviolet-Absorption-Spectrum 33
Figure 11. Photolysis reaction of ozone when exposed to UV-C light at 254 nm. One oxygen molecule
and hydroxyl radical is produced. Modified from Spartan Environmental Technologies, LLC. ............... 35
Figure 12. Response surface methodology design with center points and star points. Modified from Stat-
Ease, Inc. ............................................................................................................................................... 37
Figure 13. Schematic diagram (A) and photograph (B) of the advanced oxidation process reactor used for
chlorpyrifos degradation and microbial inactivation. .............................................................................. 40
Figure 14. Schematic (A) and photograph (B) of ozone chamber treatment of CPY spiked apple skins. . 47
Figure 15. Calibration curve of chlorpyrifos-oxon standards ranging in concentrations from 0.01 – 0.31
µg/mL. Concentrations of 0.16 and 0.31 µg/mL were removed due to low accuracy. R2 value = 0.9993. 50
Figure 16. 3D surface graph of different interaction effects of an advanced oxidation process for
degrading CPY on apples. CPY was introduced onto apple peel and treated with various combinations of
hydrogen peroxide and UV dose with the decrease in pesticide levels being recorded. The plots illustrate
UV dose and H2O2 temperature (A), UV dose and H2O2 concentration (B) & H2O2 concentration and
H2O2 temperature (C). ........................................................................................................................... 62
Figure 17. Predicted vs actual reduction of CPY table and graph illustrating the accuracy of the RSM
model in predicting CPY degradation under known conditions. ............................................................. 63
Figure 18. Graph of CPY reduction using only UV radiation with a linear trend line (orange line).
Reductions were calculated using HPLC analysis. A R2 value of 0.982 was calculated using 5 data points
of varying UV doses (kJ/m2) and CPY reduction (µg). ........................................................................... 64
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Figure 19. Log counts of Escherichia coli O157:H7 and Aspergillus niger spores. *<2.3 CFU/mL is the
limit of enumeration. All treatments are determined to be statistically significant for both organisms. .... 70
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LIST OF ABBREVIATIONS 2,4-D…………………………………………………...…………2,4-Dichlorophenoxyacetic acid
ACh……………………………………………………………………..…………...Acetylcholine
AChE…………………………………………………………………..……..Acetylcholinesterase
ANOVA………………………………………………………..…………..…Analysis of variance
AOP……………………………………………….………………….Advanced oxidation process
BBD…………………………………………………………………………..Box-Behnkin design
CCD……………………………………………………………….……..Central composite design
CFU……………………………………………………………………...……Colony forming unit
CPY………………………………………………………………………………..….Chlorpyrifos
CPY-O……………………………………………………………………….….Chlorpyrifos-oxon
DDT………………………………………………………..…….Dichlorodiphenyltrichloroethane
EHEC……………………………………………………………………Enterohemorrhagic E.coli
EWG…………………………………………………..…………. Environmental Working Group
FDA………………………………………………………………..Food and Drug Administration
GRAS……………………………………………………...………....Generally recognized as safe
HPLC…………………………...………………………High performance liquid chromatography
HUS………………………………………………..…………………Hemolytic uremic syndrome
LOD……………………………………………………………………………..Limit of detection
LOQ………………………………………………………………….……..Limit of quantification
LPM……………………………………………………………..………….Low pressure mercury
MDL………………………………………………………………..………Method detection limit
MPM…………………………………………………………...……….Medium pressure mercury
MRL……………………………………………………………………….Maximum residue level
OP………………………………………………………………………..………Organophosphate
PDA………………………………………………………………………..….Potato dextrose agar
PON1………………………………………………………………………………..Paraoxonase 1
Q-ToF…………………………………………………………...……..Quadrupole Time of Flight
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RSM……………………………………………………………….Response surface methodology
Stx………………………………………………………………………………………Shiga toxin
STEC……………………………………………...………………….Shiga toxin producing E.coli
R2….……………………………………………………….………….coefficient of determination
TCP…………………………………………………….……………..3,5,6 – trichloro-2-pyridinol
TSB………………………………………………………………..………………Trypic soy broth
USE…………………………………………………………………..Ultrasonic solvent extraction
USEPA…………………………………….…….United States Environmental Protection Agency
UV light……………………………………………………………………………Ultraviolet light
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Chapter 1: Introduction and Literature Review
1.1 Introduction
Pesticides are an important part of modern day farming and are necessary in the growth and
production of fresh fruits and vegetables due to their ability to eliminate pests (Randall, Hock,
Crow, Hudak-Wise, & Kasai, 2014). Despite their necessity in agriculture, they have been
associated with numerous human health concerns as well as damage to the environment
(Stoytcheva, 2011). One of the most controversial pesticides is chlorpyrifos (CPY), which could
cause adverse effects on the nervous system of children (M. Bouchard, F. et al., 2011). Humans
can be exposed to pesticides through a number of different routes, one of them being through
ingestion of contaminated produce (Giesy et al., 2014).
The most common current approach to remaining CPY on produce is through washing, however,
this process results in a redistribution of not only pesticides but also pathogenic microorganisms
between produce batches and further dissemination within the environment via wastewater
disposal (Burkul, Ranade, & Pangarkar, 2015; Köck-Schulmeyer et al., 2013). A more effective
approach is to use water-free technologies to decontaminate fruits and vegetables thereby
reducing pesticide levels entering down-stream washing processes. One potential approach is
based on the advanced oxidation process (AOP) that has previously been shown to inactivate
Listeria monocytogenes on apples (Murray et al., 2018). AOP involves generating hydroxyl
radicals from the degradation of ozone and/or hydrogen peroxide. The generation of free radicals
can be achieved through the interaction between ozone and hydrogen peroxide, or more rapidly
via UV-C (254nm) mediated decomposition of the oxidants (Abramovic, Banic, & Sojic, 2010;
Femia, Mariani, Zalazar, & Tiscornia, 2013; Marican & Durán-Lara, 2018).
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In the following study the AOP originally developed to decontaminate apples was applied for
CPY degradation as well as inactivate the pathogen Escherichia coli O157:H7 due to the
previous links to foodborne illness outbreaks linked to apples (Kenney, Burnett, & Beuchat,
2001). Aspergillus niger was also selected as a test microbe due to its inherent resistance to UV
in the spore form, in addition to acting as a surrogate for potential mycotoxin producing molds
(Taylor-Edmonds, Lichi, Rotstein-Mayer, & Mamane, 2015). A key part of the AOP is
optimizing the hydrogen peroxide concentration and temperature along with UV-C dose. In the
current study response surface methodology (RSM) was used to determine which factors and
their settings affect the degradation of CPY.
1.2 Size of the Fresh Produce Sector
Fresh produce is important to Canadians, with about 28.6% of Canadians aged 12 and over
(approximately 8.3 million people) reported to consume 5 or more fruits and vegetables per day
(Statistics Canada, 2017). Fresh produce is also important to the Canadian economy, grossing
approximately $2.24 billion in 2017 (Agriculture and Agri-Food Canada, 2017a, 2017b;
Statistics Canada, 2017). The fruit industry makes up about $1.04 billion annually while
vegetables make up the rest (Agriculture and Agri-Food Canada, 2017a). Of this value, apples
have been the highest grossing fruit since 2013, making approximately $224.6 million in 2017
(Agriculture and Agri-Food Canada, 2017a). Apples are one of the most widely grown fruit
species in the world with approximately 5.2 million hectares in production worldwide in 2016
(Agriculture and Agri-Food Canada, 2017a). According to Statistics Canada, apples are the most
widely produced fruit in Canada with an estimated 424,709 tons being produced in 2018. In
comparison, the second most widely produced fruit in Canada is cranberries with only 195,196
tons (Statistics Canada, 2018).
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1.3 Climate change and fresh produce safety
Climate change is believed to be caused by an accumulation of various greenhouse gases, mostly
carbon dioxide, which in effect is increasing a trend of warm and humid weather (Butler, 2018).
Climate change has been shown to increase the prevalence of pests such as insects, pathogenic
microorganisms, and weeds (Delcour, Spanoghe, & Uyttendaele, 2015; Gregory, Johnson,
Newton, & Ingram, 2009; Roos, Hopkins, Kvarnheden, & Dixelius, 2011; Ziska, Teasdale, &
Bunce, 1999). Although some crops are capable of growing faster at higher temperatures, they
may be subjected to an increase in pests and pathogens that also benefit from higher
temperatures and humidity (Gregory et al., 2009). Increased temperatures can be associated with
an enhanced metabolic rate in various insects which would increase both their rate of food
consumption and rate of reproduction (Delcour et al., 2015; Deutsch et al., 2018). Due to this, it
has been predicted that yields of grain such as maize, rice and wheat will decrease by 10 to 25%
per degree of global mean surface warming (Deutsch et al., 2018). This prediction is based on
various models that show a 2 °C increase in global temperature is capable of causing an average
yield loss of 46, 19, and 31% for wheat, rice and maize, respectively (Deutsch et al., 2018).
These predictions differ from previous models which showed a rice yield reduction of 5% per °C
rise above 32 °C (Walker, Steffen, Canadell, & Ingram, 1999) and a reduction of 10% maize
yield (Jones & Thornton, 2003).
Along with a change in temperature, changes in precipitation, light exposure, and humidity can
also affect the growth of pests and pathogens (Delcour et al., 2015; Holland & Sinclair, 2004;
Keikotlhaile, 2011). Higher moisture is also associated with various plant diseases since
microorganisms are capable of thriving in wet conditions, promoting the growth of mold and
bacteria as well as spore germination (Roos et al., 2011).
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1.4 Pesticides
Pesticides are substances, either chemical or biological, used by humans for controlling pests that
are capable of harming human health and crop yield (Randall et al., 2014). Pests can be weeds,
insects, animals, and even pathogenic microorganisms that can cause harm to both humans and
plants (Randall et al., 2014). Chemical pesticides were used as early as 2500 B.C. when sulphur
compounds were used for insect control by ancient Sumerians (Randall et al., 2014). Nowadays,
there are multiple types of pesticides including fungicides, herbicides, insecticides, repellents,
and disinfectants which control fungi, plants, insects/invertebrates, animals, and pathogenic
microorganisms respectively (Randall et al., 2014) (Table 1).
Table 1. Types of pesticides and their target organisms with examples that are currently used in
agriculture.
Type of Pesticide Target Organism Examples
Bactericides Bacteria Alcohols, disinfectants
Fungicides Fungi Tea tree oil, Bacillus subtilis
Herbicides Plants Glyphosate, 2-4 D
Insecticides Insects Chlorpyrifos, imidacloprid
Larvicides Larvae Methoprene, temephos
Rodenticides Rodents Anticoagulants, metal
phosphides
Many classes of synthetic chemical pesticides used in the modern era were originally produced
researched for use in warfare during World War II, with some of these early synthetic pesticides
still being used today for agricultural purposes (Sanborn, Cole, Helena Sanin, & Bassil, 2004).
The most notable of those pesticides being 2,4-Dichlorophenoxyacetic acid (2,4-D), a phenoxy
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herbicide that kills weeds by causing uncontrolled and unsustainable growth (Randall et al.,
2014; Sanborn et al., 2004). Another noteworthy pesticide is dichlorodiphenyltrichloroethane
(DDT), an insecticide which was used in war to prevent malaria and typhus (Beard, 2006). In the
United States, it was approved for use in agriculture and households from 1945 until 1972 when
it was eventually banned in 1972 (Beard, 2006). This ban was due to the fact that DDT was
shown to be very persistent in the environment while maintaining its residual effects and it can
biomagnify in the food chain (Figure 1) (Beard, 2006; Randall et al., 2014). To this day, DDT
still persists in the environment and it is believed that every living organism on Earth has been
exposed to DDT resulting in body fat storage (Nicolopoulou-Stamati, Maipas, Kotampasi,
Stamatis, & Hens, 2016).
After DDT was banned from being used in the United States, farmers started to use more
organophosphate (OP) insecticides which have a relatively high mammalian toxicity but do not
persist in the environment and are effective for a wide spectrum of insects compared to other
insecticides (Davis, 2014).
Figure 1. Bioaccumulation of the pesticide DDT throughout the food chain. Modified from Penn
State Pesticide Education Manual.
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OPs are effective at controlling insects and mammalian pests through their ability to inactivate
acetylcholinesterase (AChE), an enzyme required for proper nervous system function
(Williamson, Terry, & Bartlett, 2006). AChE breaks down acetylcholine (ACh), a
neurotransmitter that stimulates nerve fibres and muscles, into choline and acetic acid (Figure 2)
(Fukuto, 1990). If AChE is inhibited, ACh will continue to stimulate nerve fibres and muscles
uncontrollably which in effect will cause muscle spasms and involuntary movement (Fukuto,
1990). Besides mammals and insects, AChE is also present in birds, fish and reptiles (Fukuto,
1990). Exposure to high enough concentrations of OPs can lead to unintentional deaths of these
animals.
Figure 2. Mechanism of action of acetylcholinesterase breaking down acetylcholine into choline and
acetic acid.
Although pesticides are crucial in food production, they are capable of causing harm to human
health, especially insecticides (Ansari, Moraiet, & Ahmad, 2014). There are multiple types of
insecticides that have mechanism of actions, that target the nervous system of insects (Casida &
Durkin, 2013) (Table 2). Like DDT, residues of these insecticides can remain on produce after
being harvested from the fields (Bajwa & Sandhu, 2014) and may also be found in water, soil,
and/or air following field application (Ansari et al., 2014). It has been estimated that every year,
over 26 million people, especially those working in the agriculture industry, are poisoned by
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pesticides, resulting in over 220,000 deaths (Ansari et al., 2014). One of the major human health
concerns associated with insecticides is neurotoxicity (Casida & Durkin, 2013).
Table 2. Different types of insecticides and their mechanism of action. Sourced from (NPIC, 2019).
Type of Insecticide Mechanism of Action Example
Carbamates Acetylcholinesterase inhibitor Carbaryl
Organochlorine Opens nerve cell sodium
channels DDT
Organophosphates
Acetylcholinesterase inhibitor
more toxic and longer lasting
than carbamates
Chlorpyrifos
Phenylpyrazoles Blocks glutamate-acitivated
chloride channels Fipronil
Pyrethroids Modulates sodium channels Cypermethrin
Neonicotinoids Nicotinic Acetylcholine
receptor agonist Imidacloprid
Ryanoids Binds to calcium channels to
block nerve transmission Chlorantraniliprole
Consumers are concerned about pesticides used in agriculture and in their food (Consumer
Reports, 2015; Koch, Astrid Epp, Mark Lohmann, & Gaby-Fleur Böl, 2017). A survey by
Consumer Reports in 2015 showed that of 1050 Americans surveyed, approximately 85% were
concerned about pesticides in their food (Consumer Reports, 2015). The Environmental Working
Group (EWG) states that in 2019, the top five fruits and vegetables linked to the highest end-user
pesticide exposure are: strawberries, spinach, kale, nectarines, and apples (Table 3). The EWG
also state that two or more pesticide residues were detected in about 90% of strawberries, apples,
cherries, spinach, nectarines, and kale samples tested (EWG, 2019).
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Table 3. Produce with the highest and lowest pesticide residues scores. Adapted from
Environmental Working Group.
The CDC states that approximately 29 pesticides can be found in trace amounts in the average
human body in the United States. When exposed to the same concentration of pesticides,
children are more susceptible to danger than adults due to the difference in body sizes (Eskenazi,
Bradman, & Castorina, 1999). Children also have a different metabolism than adults so their
bodies are unable to remove toxins as quickly (Eskenazi et al., 1999). Due to these factors,
maximum residue limits (MRLs) are put in place to ensure that pesticide levels are safe for
children and infants. Studies have shown a correlation between pesticides and human health risks
such as lower IQ in children, Alzheimer’s disease, Parkinson’s disease, and ADHD to name a
few (M. Bouchard, F. et al., 2011; M. F. Bouchard, Bellinger, Wright, & Weisskopf, 2010;
Brown, Rumsby, Capleton, Rushton, & Levy, 2006; Eskenazi et al., 1999; Kim, Lee, Lee,
Jacobs, & Lee, 2015; Kuehn, 2010). Cancer development due to pesticide exposure is also a
great concern for both children and adults. Multiple studies have shown a link between pesticide
exposure and tumour growth (Bassil et al., 2007). Due to this, it has been suggested that a
reduction of pesticide use, especially for non-commercial purposes, should be considered (Bassil
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et al., 2007). As a result of these concerns, organophosphate insecticide use in the United States
has decreased from 70 million lbs in 2000 to 20 million lbs in 2012 (Atwood & Paisley-Jones,
2017). The use of all insecticides have also decreased from 99 million lbs in 2000 to 60 million
lbs in 2012 (Atwood & Paisley-Jones, 2017). Although the use of insecticides has decreased, the
sale and usage of all pesticides combined are increasing. In 2008, about 4850 million lbs of
pesticides were being used but in 2012, an estimated 5821 million lbs were used (Atwood &
Paisley-Jones, 2017). Despite the current effort to reduce the use of pesticides, the need for them
may soon increase due to climate change (Delcour et al., 2015).
Increased temperature, humidity and CO2 can induce a higher growth rate of plants which in
effect will lead to a dilution of pesticide concentrations thus reducing residue levels which will
require more frequent applications as the plant matures (Holland & Sinclair, 2004). Higher levels
of precipitation and higher moisture levels can cause pesticides to dissipate faster which will also
lead to reduced residue concentrations found on plants and require more applications (Delcour et
al., 2015). Higher CO2 levels have also been shown to increase weed tolerance to herbicides
which may lead to the use of more potent herbicides (Ziska et al., 1999). Due to these factors
decreasing the amount of pesticide residues found on crops, the frequency of pesticide
application would increase which in effect leads to an increase in the risk of pesticide residue
carriage on produce (Delcour et al., 2015). When pesticides are applied, they can be transported
to different components of the environment, including: air, soil, ground water, and surface water
(Figure 3).
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Figure 3. Fate of pesticides after application and factors affecting them. Adapted from Declour et
al. (2015).
1.4.1 Chlorpyrifos
One pesticide of great interest is chlorpyrifos (O,O-diethyl-O-3,5,6-trichloro-2-
pyridylphosphorothioate), a broad spectrum OP insecticide that is widely used in the agricultural
industry (Mladenova & Shtereva, 2009; K. R. Solomon et al., 2014; USEPA, 2006). In 2012,
CPY was ranked as the 14th most used pesticide and the most widely used insecticide in the
United States by the United States Department of Agriculture – National Agricultural Statistics
Service (Atwood & Paisley-Jones, 2017). CPY is capable of controlling insects that commonly
consume maize, fruit still on trees or vines, and root vegetables (Gomez, 2009; K. R. Solomon et
al., 2014). It has been estimated that CPY is used to treat over 50 different crops (Gomez, 2009)
11
and fruits grown on trees such as apples account for approximately 10 percent of CPY usage
(Eaton et al., 2008).
CPY has been shown to be a neurotoxin which can affect the mental development of children
(Trasande, 2017). Longitudinal studies have shown that prenatal exposure to OPs is associated
with neurological deficits in children (M. Bouchard, F. et al., 2011; Rauh et al., 2012). Bouchard
et al. (2011) conducted a 7-year birth cohort study (n = 329) and reported that children exposed
to higher levels of OPs had an average of 7 lower IQ points than children exposed to lower levels
of OPs.
CPY exposure can occur in a number of ways including ingestion through food or water, skin
contact, and inhalation through air (Giesy & Solomon, 2014). CPY can be used on crops
throughout the year and its use is determined by the amount of pests present at a given time. It
can be used in the winter season on tree crops and used in the summer season on field crops
(Giesy & Solomon, 2014). The United States National Institutes of Health (NIH) has stated that
the half-life of CPY is approximately 4.2 days in the summer and 9.7 days in the winter (Toxnet,
2014). CPY is capable of absorbing light in the UV range with a maximum absorbance of 290
nm (Zalat, Elsayed, Fayed, & Abd El Megid, 2014). The lower half-life in the summer is due to
photolysis by sunlight because of this absorption (Toxnet, 2014). Photolysis requires the
presence of water to occur (Eto, 1974). Under dry conditions, only an estimated 2%
decomposition of CPY after 1200 hours of irradiation is predicted (Eto, 1974).
Some jurisdictions have decided the risk of CPY to human health and the environment is too
great to allow continued use in agriculture. For example, the State of Hawaii has recently banned
the use of CPY starting in 2022, being the first State to do so in the United States of America
12
(State of Hawaii, 2017). New York has also proposed to ban all use of CPY by 2021 ("Assembly
Bill A2477B," 2019). Although Hawaii and New York may have banned the use of CPY, other
jurisdictions have not followed the same course of action. In 2017, a petition to ban the use of
CPY was denied by the U.S. Environmental Protection Agency (EPA) stating that “the pesticide
is crucial to U.S. agriculture.” (Environmental Protection Agency, 2017, March 29). As CPY
continues to be used in agriculture, it is necessary to limit exposure to the public. Currently, the
maximum residue limit (MRL) for CPY on apples in Canada is set at 0.01 µg/g (Health Canada,
2012, October 1). In the United States, the limit on apples is also set at 0.01 µg/g and due to its
possible detrimental effects, produce such as spinach, squash and carrots cannot be treated using
CPY as they are commonly fed to children (USEPA, 2006). If residue is found on these crops,
they are considered to be adulterated which allows the FDA to consider enforcement actions
(FDA, 1995).
If humans are exposed to high enough concentrations of CPY (LD50 in rats was determined to
be 60 mg/kg bw (EXTOXNET, 1993), adverse effects including nausea, dizziness, respiratory
paralysis and even death can occur (USEPA, 2006). It has also been shown recently that CPY
exposure can promote the growth of mammary tumors and may be a risk factor for breast cancer
development (Ventura et al., 2019). Various diseases that affect the nervous system such as
Alzheimer’s and Parkinson’s disease have also been associated with, exposure to, insecticides
but more research is required (Brown et al., 2006; Casida & Durkin, 2013; Kim et al., 2015). In
response to this, it is important to have post-harvest techniques and treatments in place to
minimize the amount of pesticide residue on produce to protect consumers.
13
1.4.2 Chlorpyrifos-Oxon
CPY can be degraded into two different metabolites, chlorpyrifos-oxon (CPY-O) and 3,5,6 –
trichloro-2-pyridinol (TCP). CPY-O is the active form of CPY and is capable of irreversibly
binding to AChE through phosphorylation (Giesy et al., 2014; Williamson et al., 2006).
Structurally, CPY-O and CPY are similar but CPY-O contains a phosphorus-oxygen double
bond (P=O) group whereas CPY contains a phosphothionate (P=S) group (Figure 4). Due to this
structural difference, CPY-O is more efficient at binding to AChE than CPY (Giesy et al., 2014).
The mechanism of action of CPY is to be transformed into CPY-O which prevents AChE action
(Figure 5). This transformation has been shown to occur in the environment due to oxidative
desulfonation which can be accelerated by photolysis (USEPA, n.d.-a) and in animals through
multifunction oxidase (MFO) (Giesy et al., 2014). El-Merhibi et al (2004) showed in aquatic
organisms, when MFO is inhibited, the toxicity of CPY can be reduced by up to six-fold (El-
Merhibi, Kumar, & Smeaton, 2004; Giesy et al., 2014). Acute CPY poisoning will show
symptoms when over 70% of AChE molecules have been bound (Connors et al., 2008). It has
also been suggested by the USEPA that CPY-O can exert the same or greater levels of toxicity
than CPY (Slotkin, Seidler, Wu, MacKillop, & Linden, 2009).They reported that CPY-O is 41
more times toxic than CPY when tested on aquatic animals (USEPA, n.d.-a). CPY-O can be
detoxified in human bodies through hydrolysis facilitated by the enzyme paraoxonase 1 (PON1)
(Costa, Giordano, Cole, Marsillach, & Furlong, 2013). When hydrolyzed, CPY-O will turn into
the less harmful TCP metabolite and be excreted through urine (Costa et al., 2013).
14
Figure 4. Structures of chlorpyrifos and its active form chlorpyrifos-oxon as well as the inactive
form TCP. Adapted from USEPA (n.d).
Figure 5. Mechanism of action of chlorpyrifos-oxon. It can phosphorylate AChE to permanently
inactivate the enzyme or it can temporarily inactivate it. Adapted from Solomon (2014).
15
TCP is the inactive form of CPY and is filtered by the kidney without toxic effects. However, It
has been reported in one study by Kashanian et al. (2012) that TCP has DNA binding effects
implying that TCP may exert mutagenic effects (Kashanian, Shariati, Roshanfekr, & Ghobadi,
2012). The USEPA concluded however that TCP is significantly less toxic than CPY and is
considered to be toxicologically insignificant (USEPA, n.d.-a). An animal study conducted by
Hanley et al. (2000), reported a LD50 oral dose of 800 mg/kg for TCP. They concluded that
because TCP lacks the phosphate group seen in CPY it cannot inhibit AChE and would therefore
be less toxic than its parent compound (Hanley, Carney, & Johnson, 2000). They also stated that
CPY is quickly broken down into TCP in mammalian systems through hydrolysis which would
effectively detoxify CPY (Hanley et al., 2000).
1.5 Microbial Hazards
Besides chemical contamination via pesticides, microbial contamination can also be present on
produce and some pathogens are capable of causing severe illness and even death for consumers
(Rangel, Sparling, Crowe, Griffin, & Swerdlow, 2005). One pathogen of concern is Escherichia
coli O157:H7 which has been implicated in numerous produce-linked foodborne outbreaks
(Table 4). A recent outbreak occurred in Canada in 2018 when romaine lettuce imported from
California was contaminated with E.coli O157:H7 which affected 29 individuals, 2 of which
developed hemolytic uremic syndrome (Canada, 2019).
16
Table 4. Produce-linked foodborne outbreaks of Escherichia coli O157:H7 in North American
between 1996 and 2018. Modified from (Green, 2018).
Year Source Area(s) affected Total cases
2019 Romaine lettuce 23 states in the USA 102
2018 Romaine lettuce British Columbia,
Alberta,
Saskatchewan,
Ontario, Quebec; 36
states in the USA
8 (Canada) + 210
(USA)
2018 Leafy greens Ontario, Quebec,
New Brunswick,
Nova Scotia, and
Newfoundland and
Labrador; 15 states
in the USA
67
2018 Alfalfa sprouts Minnesota,
Wisconsin (USA)
11
2017 Leafy greens 15 States in the USA 25
2015 Leafy greens Alberta,
Saskatchewan,
Ontario,
Newfoundland and
Labrador (Canada)
13
2013 Shredded lettuce Ontario, New
Brunswick, Nova
Scotia (Canada)
30
2013 Ready to eat salads Washington,
California, Arizona,
Texas (USA)
33
2012 Organic spinach and
spring mix
Ney York,
Pennsylvania,
Virginia, Maine,
Connecticut (USA)
33
2012 Romaine lettuce 9 states in the USA 58
2006 Spinach
26 states in the USA
199
1.5.1 Escherichia coli O157:H7
E. coli O157:H7 is classified as an enterohemorrhagic E.coli (EHEC) which can cause
gastroenteritis, enterocolitis, and bloody diarrhea in infected humans due to the production of
shiga toxins (Stx), one of the most potent biological poisons (Lim, Yoon, & Hovde, 2010;
17
Melton-Celsa, 2014). EHEC is a subgroup of Stx producing E.coli (STEC) that can induce
apoptosis in cells (Figure 6) which causes bloody diarrhea and in worse cases, hemolytic-uremic
syndrome (HUS), a condition involving kidney failure, haemolytic anemia, and
thrombocytopenia (a reduction in blood platelets that help in blood clot formation) (Melton-
Celsa, 2014). An estimated 8% of STEC infections leads to HUS (D. E. Thomas & Elliott, 2013).
Figure 6. Mechanism of action of STEC in causing cell death. 1.) STEC adheres to intestinal lumen,
2.) Shiga toxin (Stx) is produced, 3.) Stx adhering onto cell, 4.) Endocytosis of Stx into the cell, 5.)
Stx in a vesicle to be transported into the Golgi complex, 6.) Stx in the Golgi complex, 7.) Stx breaks
apart and the toxic A1 subunit is released, 8.) A1 subunit attaches to rRNA, 9.) RNA cannot be
translated due to the A1 subunit so protein synthesis is inhibited, 10.) Lack of protein synthesis
leads to cell death. Modified from V. Castro, Carvalho, Conte Junior, & Figueiredo (2017).
18
STEC can be transferred from person-to-person and contaminated food and drinking water
(Figure 7) (Fairbrother & Nadeau, 2006; Lim et al., 2010; Salvadori et al., 2009). The most
common route of STEC transmission is through consumption of contaminated food and
beverages, commonly linked to undercooked ground beef and raw milk (CDC, 2016; Gally &
Stevens, 2017; Lim et al., 2010). STEC has often been linked back to cattle manure runoff;
approximately 30% of feed cattle shed E.coli O157:H7 in their manure (D. E. Thomas & Elliott,
2013). It has been estimated that less than 100 cells of E.coli O157:H7 can cause disease in
susceptible hosts (Leach, Stroot, & Lim, 2010). The products most associated with human
exposure are: ground meat, leafy greens, raw milk, and apple juice/cider (Lim et al., 2010).
Leafy greens such as lettuce can be contaminated through a number of ways including: human
transfer, manure runoff, and irrigation water (E. B. Solomon, Yaron, & Matthews, 2002). It was
demonstrated by Solomon, Yaron, and Matthews (2002) that E.coli O157:H7 can enter the root
system of mature lettuce and be found in the edible leafy portions. They concluded that due to
this route of entry, E.coli O157:H7 can avoid complete disinfection through surface sanitation of
lettuce. In the 1990s, seven cases of E. coli O157:H7 outbreaks from contaminated apple
products such as apple juice and apple cider were reported (Rangel et al., 2005). Due to being
able to tolerate low pH levels, below 2, E.coli O157:H7 can grow in apple products without
difficulty which is why nowadays, apple juices and ciders require pasteurization (Miller &
Kaspar, 1994). One case occurring in 1996 determined that apples were contaminated in the
orchard by contacting manure left by wildlife carrying E.coli O157:H7 as well as the use of
rotten apples (Cody et al., 1999). From these events, it was suggested that washing apples could
reduce the risk of transmission (Besser et al., 1993).
19
Figure 7. Transmission routes of STEC from farm cattle ingesting STEC (1) then contaminating the
environment with fecal shedding (2) leading to contamination of food and water (3 and 4) consumed
by humans. People can also transmit STEC from one to another (5). Adapted from Fairbrother and
Nadeau (2006).
1.5.2 Aspergillus niger spores
Another organism of interest is Aspergillus niger (A. niger) which is commonly implicated in
spoilage of produce. Aspergillus niger is a saprophytic filamentous fungus with a brown to dark
brown colour that is commonly found in soil, compost and decaying plants (Schuster, Dunn-
Coleman, Frisvad, & van Dijck, 2002). It is capable of growing at temperatures ranging from 25
– 40 °C, a pH range of 1.4 – 9.8 and a water activity down to 0.88 (Gautam, Sharma, Avasthi, &
Bhadauria, 2011; Ladaniya, 2008). These conditions mean warm and humid environments are
ideal for supporting growth on fruits (Gautam et al., 2011). Aspergillus niger reproduces
asexually, resulting in the growth of vegetative mycelium and conidiophores that leads to spore
formation (Krijgsheld et al., 2013). Once spores are formed they are able to survive in
20
environments outside of its usual growth parameters and then germinate once proper growth
conditions occur (Krijgsheld et al., 2013).
Aspergillus niger is labelled as “generally recognized as safe (GRAS)” by the FDA for use in
citric acid and enzyme production (R. Sharma, 2012) however multiple Aspergillus species are
capable of causing harm to human health (Al-hindi, Alnajada, & Mohamed, 2011). For example,
Aspergillus fumigatus is capable of causing allergic reactions as well as life threatening
infections in humans (Paulussen et al., 2017). Aspergillus fumigatus is responsible for 90% of
aspergillus related infections followed by Aspergillus flavus and A. niger (Dagenais & Keller,
2009; Paulussen et al., 2017). Aspergillus niger has been found to be an opportunistic infectious
organism to humans (R. Sharma, 2012). There have been rare cases of A. niger spores infecting
patients with severe immunodeficiency (Schuster et al., 2002). One such case involved a patient
with invasive pulmonary aspergillosis, a lung infection caused by aspergillus species which leads
to necrosis of lung tissue (Person, Chudgar, Norton, Tong, & Stout, 2010). Various strains of A.
niger are also capable of producing mycotoxins: aflatoxin, ochratoxin, and fumonisin B2
(Frisvad, Smedsgaard, Samson, Larsen, & Thrane, 2007; Gautam et al., 2011; Schuster et al.,
2002). These mycotoxins are dangerous when consumed by humans and are capable of inducing
hepatotoxicity, nephrotoxicity, immunotoxicity, and possible carcinogenicity (Gautam et al.,
2011; Schuster et al., 2002).
Aspergillus niger is widely used in industry due to its ability to produce citric acid in copious
amounts while also being economical (Gautam et al., 2011; Show et al., 2015). Aspergillus niger
can also produce various other organic acids as well as food enzymes such as pectinase,
proteases, and glucoamylase (Schuster et al., 2002). Due to its ability to produce organic acids
and enzymes, A. niger can cause decay in nuts, legumes, cereals, and fresh produce such as
21
apples (Gautam et al., 2011). Aspergillus niger is one of the most prevalent spoilage
microorganisms. One studied showed that A. niger was the most common fungi found in infected
fruits such as pineapples, watermelon, and oranges with a 38% occurrence frequency (Mailafia,
Okoh, Olabode, & Osanupin, 2017).
1.6 Current Treatments to Decrease Pesticide Residues Found on Produce
The most common current technology used to remove pesticide residues from produce is through
post-harvest washing with clean, potable water (Table 5). Rawn and colleagues showed that
washing and rubbing apples under running de-ionized water could effectively remove pesticide
residues by approximately 50% (Rawn et al., 2008). Washing was shown to be effective,
reducing CPY levels on fruits and vegetables by 30-50% (Mi-Gyung Lee, 2001; Rawn et al.,
2008). It was also shown that washing removed approximately 60% of CPY on rice grains (Lee,
Mourer, & Shibamoto, 1991). Another study showed that when shaken in water, red peppers
that were artificially spiked with CPY had a 30-40% reduction after 5 minutes (Mi-Gyung Lee,
2001). Washing produce with different low concentration solutions of acetic acid, citric acid and
potassium permanganate have also been shown to reduce pesticide concentrations in date fruits
(Osman, Al-Humaid, Al-Redhaiman, & El-Mergawi, 2014). The problem with batch washing
produce is that pesticides are removed from the surface of the product which in effect generates
wastewater containing pesticides that can lead to cross contamination between batches (Burkul et
al., 2015; Kayla Murray, Wu, Shi, Jun Xue, & Warriner, 2017). Although washing can reduce
pesticide concentrations on produce, it does not degrade pesticides but rather redistributes it
between batches and into the environment via the disposal of spent wash water (Burkul et al.,
2015; Köck-Schulmeyer et al., 2013).
22
Table 5. Reduction of pesticide residues on produce by current washing treatments.
Treatment Reduction Reference
Washing apples using
deionized water 50% Reduction of Captan (Rawn et al., 2008)
Washing of red peppers using
tap water 30-40% Reduction of CPY (Mi-Gyung Lee, 2001)
Washing of red peppers using
tap water then hot-air dried
for 26 hrs
67% Reduction of CPY
(Chun & Lee, 2006)
Washing of red peppers using
tap water then hot-air dried
and UV treated for 26 hrs
73% Reduction of CPY
Washing of red peppers using
20% hydrogen peroxide
solution
22% Reduction of CPY
Washing of rice using tap
water 60% Reduction of CPY (Lee et al., 1991)
Pesticides are also able to adhere onto soft skins and some may even be absorbed into the plant
(Yang et al., 2017). Yang and colleagues showed that washing with a baking soda solution was
more effective than with water or hypochlorite. They also found that the systemic pesticide
thiabendazole is capable of penetrating the skin of apples which makes it harder to be removed
through washing alone (Yang et al., 2017).
23
Approximately 6% of consumers do not wash their produce or choose to wash produce only
when deemed necessary (Parnell & Harris, 2003). In 2016, the FDA conducted a survey asking
consumers if they washed their produce before consumption. Only 54% replied “yes” when
asked if they wash their lettuce before consumption and 56% washed their avocadoes (Lando,
Verrill, Liu, & Smith, 2016). They also noted that when asked if they washed their strawberries
or tomatoes before consumption, close to 100% responded “yes”. Washing has also been shown
to be effective at removing microorganisms off the skin of produce (Parnell & Harris, 2003).
Parnell and Harris showed, in the lab, that a 3.2 log reduction of Salmonella on apples can be
achieved through rubbing and rinsing with 200 mL of water for 5 seconds in combination with
drying using a sterile paper towel. They also demonstrated that washing with a 5% vinegar or
200 µg/mL chlorine solution were better at reducing Salmonella than water with reductions
ranging from 5.2 – 6.2 logs (Parnell & Harris, 2003). Another study also showed that chlorine
bleach wash was more effective than running water at reducing Salmonella as well as E.coli
O157:H7 (Fishburn, Tang, & Frank, 2012). Fishburn and colleagues (2012) showed that when
washing lettuce under running water, log reductions of 1.58 and 1.69 can be observed for
Salmonella and E.coli O157:H7 respectively while chlorine bleach reduced 2.05 and 2.34 logs.
In commercial testing, it was shown that washing only resulted in a 1 – 2 log reduction of E.coli
(Murray et al., 2017, Barrera, 2012).
In-kitchen techniques and the application of heat (cooking and boiling) have also shown to be
effective in reducing pesticide residues (Bajwa & Sandhu, 2014). It was also reported by Sharma
and his colleagues in 2001, peeling in combination with cooking methods (boiling, steaming,
etc.) to be the most effective method of removing the pesticide mancozeb from the surface of
apples. They showed that washing alone reduced 20-52% of residues and when combined with
24
cooking led to 53-73% reduction (I. D. Sharma, Patyal, Nath, & Joshi, 2001). Cooking alone has
been shown to not completely remove all pesticides in tea leaves and crops such as spinach,
strawberries (made into jam), and oranges (Nagayama, 1996). Washing was also shown to be
ineffective at reducing levels of CPY to below the maximum residue limit (MRL) (Nagesh &
Verma, 1997). Lee and his colleagues also showed that approximately 30% of CPY residue
remained on rice after cooking (Lee et al., 1991). Singh et al. (2017) conducted heat treatments
such as boiling, pasteurization, and sterilization on CPY and found that after boiling for 5
minutes, 44% of CPY was degraded whereas sterilization at 121 °C for 15 minutes degraded
68% CPY (S. Singh, Krishnaiah, Rao, Pushpa, & Reddy, 2017). One possible explanation for
CPY not being fully degraded may be because CPY decomposes at 160 °C, above the boiling
point of water. These results suggests that heat may be a significant factor in CPY reduction.
1.6.1 Ultraviolet Radiation
The use of ultraviolet (UV) light has gained popularity over the years for food decontamination
because it is cost effective, easy to use and monitor, and residue-free as no chemicals are
required (Keklik, Krishnamurthy, & Demirci, 2012; National Environmental Services Center
[NESC], 2000). The UV light spectrum ranges from 100-400 nm and can be generated by low or
medium pressure mercury lamps (Keklik et al., 2012). This spectrum is categorized into four
sections: UV-A (315-400 nm), UV-B (280-315 nm), UV-C (200-280 nm) and Vacuum UV (100-
200 nm) (Figure 8). The region of interest is UV-C light at 254 nm which has been shown to be
the most effective at inactivating microorganisms (Keklik et al., 2012). UV-C light can induce a
germicidal effect on microorganisms through the absorption of UV light by living cells which
damages DNA (Keklik et al., 2012). Due to this damage, bacterial cells are incapable of
replicating DNA thus causing the cell to become inactivated (Keklik et al., 2012).
25
Low pressure mercury (LPM) lamps are capable of emitting this wavelength of 254 nm
monochromatically whereas medium pressure mercury (MPM) lamps emit polychromatic light at
wavelengths between 185-600 nm (Bohrerova, Shemer, Lantis, Impellitteri, & Linden, 2008).
These lamps operate by using electricity to excite mercury vapor within a silica or quartz tube
which then generates UV radiation when the mercury vapor returns to a lower energy level
(Bohrerova et al., 2008; Keklik et al., 2012). Exact wavelengths emitted depend on temperature
as well as the vapor pressure within the tube which is why LPM lamps produce a more
monochromatic wavelength compared to MPM lamps (Keklik et al., 2012). Low pressure lamps
have an operating temperature between 30 - 50 °C with vapor pressure between 0.1-10 Pa
whereas medium pressure lamps operate at temperatures between 600 – 900 °C with a vapor
pressure from 50 – 300 kPa (Keklik et al., 2012).
Figure 8. The UV light spectrum of the electromagnetic spectrum. Modified from Evoqua Water
Technologies, LLC. https://www.evoqua.com/en/brands/ETS_UV/Pages/how-ets-uv-
works.aspx
26
1.6.2 Ozone
The use of ozone for drinking water disinfection and oxidation has been around since the early
1900s in Europe (Langlais, Reckhow, & R. Brink, 1991). Nowadays it is not only employed in
water treatment but also in the food industry for increasing produce shelf life and ensuring
sanitation of surfaces (O'Donnell, Brijesh kumar, Cullen, & G. Rice, 2012; Wang, Wang, Wang,
Li, & Wu, 2019). It has been shown that ozone treatment is capable of reducing cellular
respiration and ethylene production which delays fruit ripening hence prolonging shelf life
(Wang et al., 2019). For ozone to be generated, a diatomic oxygen molecule needs to be broken
to create free radical oxygen which reacts with another diatomic oxygen thus forming a triatomic
ozone molecule (O'Donnell et al., 2012). There are multiple ways to generate ozone, including
the use of ultraviolet light at 188 nm which is capable of breaking the diatomic oxygen bond
(O'Donnell et al., 2012). Another method to produce ozone is corona discharge, in which
oxygen-containing gas is passed between two electrodes (Figure 9). These electrodes have a
voltage applied to them which produces electrons that dissociate the oxygen molecules to form
ozone (O'Donnell et al., 2012). It is estimated that if air is passed through the electrodes, only 1-
3% ozone is produced but if high-purity oxygen is passed through, production can be as high as
up to 16% (O'Donnell et al., 2012). In a contained environment, ozone concentration will reach
equilibrium with its surroundings when the generation and degradation rate is the same. Once
this point is reached, ozone concentrations cannot be increased any further (O'Donnell et al.,
2012).
27
Figure 9. Schematic of ozone production using a corona discharge ozone generator. Modified from
Oxidation Technologies, LLC. https://www.oxidationtech.com/ozone/ozone-
production/corona-discharge.html
Ozone has multiple uses in the food industry including plant sanitation, pest reduction,
packaging material disinfection as well as direct contact with food products to reduce
microorganisms that negatively impact food quality and safety (Jegadeeshwar, Shankar, Kumar,
& thottiam Vasudevan, 2017). In 2001, the FDA recognized ozone as an antimicrobial food
additive and labelled it as GRAS (O'Donnell et al., 2012). The FDA states that ozone can be used
as an additive in the “treatment, storage, and processing of foods” and currently has no limits set
(Regulations, 2018). However, the FDA also states that any devices that generate ozone at a level
over 0.05 ppm or accumulate ozone at a level over 0.05 ppm will be considered “adulterated
and/or mislabelled” in animal products (FDA, 2018). This is because ozone can harm human
health. It is capable of causing damage to the lungs, chest pain, coughing, shortness of breath and
even throat irritations (USEPA, n.d). The National Institute of Occupational Safety and Health
(NIOSH) recommends that ozone concentrations should not exceed 0.1 ppm at any time and the
Occupational Safety and Health Administration (OSHA) states that workers should not be
28
exposed to an average concentration of more than 0.1 ppm for 8 hours (USEPA, n.d). Ozone
must also be able to produce a minimum 5 log reduction for microorganisms commonly found in
juices in order to comply with 21 CFR 101.17(g)(7) (FDA, 1977). Ozone can be applied in either
an aqueous or gaseous form on produce to reduce the amount of pathogenic and spoilage
microorganisms by direct oxidation (O'Donnell et al., 2012). Ozone disperses rapidly and
decomposes into oxygen which leaves zero residues on food products (O'Donnell et al., 2012).
Since ozone does not leave residues on products and surfaces it has grown in popularity in its use
in the food industry (Jegadeeshwar et al., 2017). However, like UV treatments, ozone can
degrade pesticides into more dangerous by-products than its parent compound such as the
formation of oxons (Wang et al., 2019).
In the fruit and vegetable industry, ozone is generally used to inactivate pathogenic and spoilage-
causing microorganisms as well as to reduce the amount of post-harvest pesticide and chemical
residues (O'Donnell et al., 2012). Ozone is more effective when added to water due to increased
contact between the surface being decontaminated leading to the formation of hydroxyl radicals
which have a higher reaction rate and oxidizing power than ozone (Krishnan, Rawindran,
Sinnathambi, & Lim, 2017). Ozone is capable of decomposing into hydroxyl radicals faster in
water than air due to having a shorter half-life in water (LennTech, 2019). When in 20°C air,
ozone has a half-life of 3 days whereas in 20°C water (pH = 7), the half-life is 20 minutes
(LennTech, 2019). Achen and Yousef (2001) showed that apples treated with ozone being added
during water washing inactivated Escherichia coli O157:H7 better than apples placed in pre-
ozonated water with log reductions of 3.7 and 2.6, respectively. The time needed to generate
hydroxyl radicals can also be shortened through increased temperature, higher pH, decreased
concentrations of organic material, and increased dose of UV light (LennTech, 2019).
29
Maximizing the formation of hydroxyl radicals through optimizing the listed factors is known as
an advanced oxidation process (Abramovic et al., 2010; LennTech, 2019).
1.7 Advanced Oxidation Process
A potential method to decrease the public’s exposure to CPY is the use of advanced oxidation
processes (AOPs) combining UV-C light, hydrogen peroxide (H2O2), and ozone to degrade
various organic contaminants (Abramovic et al., 2010; Femia et al., 2013; Marican & Durán-
Lara, 2018). AOP has long been used in the treatment of wastewater (Andreozzi, Caprio, Insola,
& Marotta, 1999; Gottschalk, Saupe, & Libra, 2010; Oppenländer, 2003) and has been shown to
be effective in pesticide residue removal (Table 6) (Abramovic et al., 2010; Ikehata & Gamal El-
Din, 2005).
Table 6. Degradation of pesticides using AOPs and individual processes.
Target Pesticide Treatment Degradation Reference
UV/H2O2 exposure
for 120 minutes. 97% Degradation
(Abramovic et al.,
2010) Thiacloprid
UV exposure for 120
minutes No significant
degradation
H2O2 exposure for
120 minutes
Chlorpyrifos UV/H2O2 exposure
for 20 minutes
93% Degradation (14
mg/L) (Femia et al., 2013)
Chlorpyrifos UV exposure for 300
minutes
100% Degradation (5
mg/L) (Muhamad, 2010)
Chlorpyrifos Ozone exposure No significant
degradation
(Ikehata & Gamal El-
Din, 2005)
30
Target Pesticide Treatment Degradation Reference
Chlorpyrifos
Lychee fruit –
Gaseous ozone
exposure
45% Degradation (Whangchai,
Uthaibutra,
Phiyanalinmat,
Pengphol, & Nomura,
2011) Chlorpyrifos
Lychee fruit –
Aqueous ozone
exposure
10% Degradation
Chlorpyrifos
Apples – Aqueous
ozone exposure for 15
minute
69% Degradation
(0.36 µg/g)
(Swami et al., 2016) Apples – Aqueous
ozone exposure for 30
minute
95% Degradation
(0.06 µg/g)
AOPs are chemical treatments that produce hydroxyl radicals (·OH) in copious amounts to
oxidize organic and inorganic material in water and wastewater (Abramovic et al., 2010;
Andreozzi et al., 1999; Femia et al., 2013; Glaze, Kang, & H. Chapin, 1987; Marican & Durán-
Lara, 2018). Hydroxyl radicals are extremely reactive with little selectivity and a short life span
of less than a second (Deng & Zhao, 2015). According to Parsons, the oxidation potential of
hydroxyl radicals is +2.80 volts (V) which is almost as high as fluorine with a V of +3.06 (Table
7). The rate of oxidation is dependent on a number of factors including the concentrations of
radicals, oxygen, and pollutants (Parsons, 2004). One of the main goals when utilizing an AOP
is to elevate the production of hydroxyl radicals to increase oxidation of organic and inorganic
micropollutants (Katsoyiannis, Canonica, & von Gunten, 2011). It should be noted however that
due to the reactivity of hydroxyl radicals, a large number of reactions can occur and it would be
difficult to predict every product generated through oxidation (Parsons, 2004). Also, due to
hydroxyl reactivity, an equilibrium will be reached between the generation and dissipation of
hydroxyl radicals (Parsons, 2004).
31
Table 7. Oxidation potential of reactive species. Adapted from Parsons (2004).
When AOPs were first introduced for industrial purposes, they were mainly used in the treatment
of wastewater and were later utilized in the 1980s in the treatment of potable water (Deng &
Zhao, 2015). These early uses of AOP technologies used combinations of ozone, hydrogen
peroxide, and ultraviolet light to generate hydroxyl radicals (Glaze et al., 1987). Ozone and
hydrogen peroxide are the most commonly used chemicals to generate hydroxyl radicals with
ultraviolet light acting as a catalyst to start the reaction (Abramovic et al., 2010). Another early
use of AOPs was in the treatment of wastewater due to its strong oxidation potential to remove
both organic and inorganic pollutants such as benzene and iron (II) (Deng & Zhao, 2015).
Nowadays, AOP technologies are used to treat a number of different contaminants and wastes
(Table 8) (Vogelpohl, 2003). AOPs are useful in treating wastewater due to their ability to
reduce pathogens and pesticide concentrations (Abramovic et al., 2010; E. L. Thomas, Milligan,
Joyner, & Jefferson, 1994).
32
Table 8. Contamination and waste products reduced by AOP technology treatments. Modified from
Vogelpohl (2003).
Amino acids Parasites
Antibiotics Pesticide wastewater
Arsenic pesticides
Coliforms Phenolic wastewater
Cryptosprodium Natural organic matter
Escherichia coli Municipal wastewater
Hospital wastewater Taste and odour causing compounds
Insecticide Trinitrotoluene (TNT)
1.7.1 UV-based Advanced Oxidation Process
When using UV light by itself to destroy contaminants, photons from UV light must be able to
be absorbed and undergo degradation from their excited state (Parsons, 2004). This limits the
application of direct UV photolysis in industry. In an AOP system however, UV light is
generally used to initiate the production of hydroxyl radicals through decomposing ozone and
hydrogen peroxide (Abramovic et al., 2010). Hydrogen peroxide and oxygen radicals are
produced when UV light reacts with ozone and it is then cleaved into two hydroxyl radicals
(equation 1 and 2) (Deng & Zhao, 2015). This is possible due to hydrogen peroxide being able to
absorb the UV wavelength of 254 nm (Figure 10) (Gottschalk et al., 2010).
O3 + H2O + hv -> H2O2 + O2 (Equation 1)
H2O2 + hv-> 2OH (Equation 2)
33
Figure 10. Absorbance spectra of hydrogen peroxide at different wavelengths in Angstroms (254
nm = 2540 Angstroms). Modified from USP technologies. http://www.h2o2.com/technical-
library/physical-chemical-properties/radiation-
properties/default.aspx?pid=65&name=Ultraviolet-Absorption-Spectrum
One study using thiacloprid, a neonicotinoid insecticide, found that this pesticide can be
photodegraded when exposed to UV radiation between 200 – 280 nm with its maximum
absorbance wavelength being 242 nm (Abramovic et al., 2010). This study also showed that
when exposed to higher wavelengths, outside of the absorbance range (200 – 280 nm), pesticide
degradation was minimal. When UV is combined with hydrogen peroxide however, a synergistic
effect is observed due to the production of hydroxyl radicals (Abramovic et al., 2010;
Krzemińska, Neczaj, & Borowski, 2015).
34
It has been shown that CPY can be degraded into its oxon form when exposed to UV-C light
(Figure 4) (Savić et al., 2019). Other OPs have been observed to degrade under UV-C light
(Bustos, Cruz-Alcalde, Iriel, Fernández Cirelli, & Sans, 2019).
1.7.2 Ozone-based Advanced Oxidation Process
Since ozone degrades into hydroxyl radicals, it is necessary for AOPs to optimize the factors
listed in Section 1.6.2 affecting ozone degradation (Gottschalk et al., 2010). These processes can
involve the use of hydrogen peroxide and/or UV light as stated previously to increase ozone
degradation and hydroxyl radical formation (Deng & Zhao, 2015; EPA, 1999; O'Donnell et al.,
2012).
When ozone reacts with H2O2, which is commonly referred to as the peroxone process, hydroxyl
radicals are produced along with oxygen (Merényi, Lind, Naumov, & Sonntag, 2010). By adding
hydrogen peroxide into ozonated water, the decomposition of ozone is increased, in effect
elevating the concentration of hydroxyl radicals (Deng & Zhao, 2015; EPA, 1999).
H2O2 -> HO2- + H+ (Equation 3)
HO2- + O3 -> OH. + O2
- + O2 (Equation 4)
This process of generating hydroxyl radicals was optimized by Duguet et al. (1985) who
concluded that hydrogen peroxide should be added in a controlled amount after the oxidation of
highly reactive substances by ozone (P. Duguet, Brodard, Dussert, & Mallevialle, 1985). This
mechanism is driven by hydrogen peroxide decomposing into hydroperoxide anions which react
with ozone to produce hydroxyl radicals (Deng & Zhao, 2015). Due to improved oxidation
through elevated concentrations of hydroxyl radicals, the peroxone process is considered
superior to ozone on its own when degrading organic material and it has been shown to be able
35
to degrade difficult-to-treat organics such as geosmin, an organic compound with an earthy taste
(EPA, 1999). However, peroxone is less effective at oxidizing inorganic material such as iron
and manganese compared to ozone.
Peroxone is generally used for oxidizing taste and odor compounds, synthetic organic
compounds, pathogens and pesticide degradation for examples, geosmin, 1,1 – dichloropropene,
poliovirus, and atrazine (EPA, 1999). When dealing with pathogens and viruses in a peroxone
system, ozone has been shown to be the main cause for reductions due to the combination of
direct ozone contact and reactivity of hydroxyl radicals in the oxidation of pathogens (EPA,
1999).
When exposed to UV-C light, ozone undergoes a photolysis reaction (Figure 11) and hydroxyl
radicals are formed. This synergistic reaction can help reduce dissolved organic matter better
than UV light or ozone alone (USEPA, n.d.-b). It is estimated that the initial ozonation rate of
organic substances can be increased up to 10,000 times when combined with UV irradiation
which can help speed up the removal of total organic matter (USEPA, n.d.-b).
Figure 11. Photolysis reaction of ozone when exposed to UV-C light at 254 nm. One oxygen
molecule and hydroxyl radical is produced. Modified from Spartan Environmental Technologies,
LLC.
36
1.8 Response Surface Methodology
When determining whether a new technology such as AOP is capable of degrading pesticides, it
is necessary to observe which operational factors are significant and if they can be optimized to
achieve a maximal degradation. This study aimed to determine the significance of the following
factors: temperature of hydrogen peroxide, concentration of hydrogen peroxide, ozone
concentration, and UV dose. One way of determining the significance of these factors and their
optimized settings for pesticide degradation is by using response surface methodology (RSM), a
multivariable statistic technique that utilizes a set of mathematical and statistical techniques to
explore the relationship between multiple variables and their response variables (Bezerra,
Santelli, Oliveira, Villar, & Escaleira, 2008). In this study, the multiple variables (temperature of
hydrogen peroxide, concentration of hydrogen peroxide, ozone concentration, and UV dose) are
set at different parameters (high, medium, and low) and the response variable is the amount of
CPY degraded in micrograms (µg). By comparing these factors at different settings, RSM can
determine their significance in CPY degradation and predict an optimized setting for each factor
to achieve maximal response (Bezerra et al., 2008).
There are multiple types of RSM design, with central composite design (CCD) and Box-Behnkin
design (BBD) being the most widely used (Pennsylvania State University, 2018). CCD consists
of multiple parameter settings; a central point representing the medium setting of each factor,
several axial (or “star”) points (Figure 12) which represent the highest or lowest settings, and a
factorial design, either full or fractional, that observes several combinations of different factor
settings (Bezerra et al., 2008). Full factorial design experiments consists of multiple factors,
usually two or more, occurring in every possible combination with one another (Bezerra et al.,
2008). Fractional factorial designs are similar to full factorial designs but only have a select few
37
combinations to test (Bezerra et al., 2008). BBDs are similar to CCDs but avoid testing star
points and consists of fewer experiments which makes it more time efficient and less costly
(Bezerra et al., 2008). In analytical chemistry, CCDs are used far more often than BBD as they
provide more information and tests for star points. By testing for star points, a more complete
data set is given which will provide more accurate predictive values (NIST, 2013).
Figure 12. Response surface methodology design with center points and star points. Modified from
Stat-Ease, Inc.
The use of RSM for determining the optimal treatment for chemical degradation using AOPs has
been shown to be effective (Ahmadi, Mohammadi, Igwegbe, Rahdar, & Banach, 2018; Behin &
Farhadian, 2017). Ahmadi and colleagues found that reactive blue 19 dye removal using AOP
can be optimized through using RSM and the experimental degradation values were close to the
predicted values suggested by RSM. Behin and Farhadian (2017) found that the pesticide
trifluralin can be fully degraded, into chemically inactive byproducts, by using optimal treatment
values of: ozone flow rate, UV light exposure time, and hydrogen peroxide solution pH. These
values were determined through a full factorial central composite design (Behin & Farhadian,
2017).
38
Hypothesis and Objectives
It is expected that an optimized AOP treatment that applies ozone, UV radiation and hydrogen
peroxide in combination will degrade the pesticide CPY and inactivate microorganisms on the
surface of apples without leaving toxic by-product residues such as CPY-O. The objectives of
this study were to:
1.) Develop an analytical method to analyze CPY on apple skin.
2.) Develop a recovery method of CPY from apple skins that have been treated or not treated
in the AOP reactor.
3.) Use RSM to model the degradation of CPY by AOP treatments with the following
factors: Ozone concentration, UV dose, temperature of hydrogen peroxide, and
concentration of hydrogen peroxide.
4.) Validate the model, determine which factors are significant, and optimize the AOP
factors for maximal CPY degradation.
5.) Determine whether AOP treatment will degrade CPY into its more toxic by-product
chlorpyrifos-oxon.
6.) Determine if the optimized parameters can inactivate the microorganisms Escherichia
coli O157:H7 and Aspergillus niger.
39
2. Materials and Methods
2.1 Materials
Chlorpyrifos analytical standards (>99% purity, PESTANAL®), hydrogen peroxide solution
(30% v/v), trifluoroacetic acid (>99% purity) and nalidixic acid sodium salt were obtained from
Sigma Aldrich (St. Louis, MO, USA). Crispin apples were provided by Moyer’s Apple Products
Ltd. (Beamville, ON, Canada). Acetonitrile (Optima™, HPLC grade) was purchased from
Thermo Fisher Scientific (Waltham, MA, USA). Chlorpyrifos-oxon standards (>99% purity)
were purchased from Toronto Research Chemicals (North York, ON, Canada). Trypic soy broth
(TSB) and potato dextrose agar (PDA) were purchased from Oxoid (Hampshire, UK).
MacConkey agar with sorbitol, cefixime, and tellurite (CT-SMac) was purchased from Thermo-
Fisher Scientific.
2.2 Advanced Oxidation Process Reactor
The advanced oxidative process (AOP) reactor (Clean Works Corporation, Beamsville, ON, CA)
(Figure 13) was constructed from stainless steel with frame dimensions of 122 cm × 38 cm × 20
cm (length × width × height). The reactor was fitted with a lightbox (61 × 35 × 15 cm) housing 4
× 25 W UV-C lamps (60 cm length) emitting at 254 nm (Sani-Ray, Hauppauge, NY, USA). The
UV intensity was varied through altering the distance of the lamps from the samples from 10 cm
– 16 cm). A radiometer (Trojan Technologies Inc, London, ON, CA) was placed in the middle of
reactor and used to measure the UV-intensity with treatment times being used to deliver a
defined UV-dose. The initial UV intensity (start of AOP treatment) and final UV intensity (end
of AOP treatment) were recorded and the average was used along with treatment time to
calculate the total UV dose. Prior to introducing the apple samples into the UV reactor, the
40
hydrogen peroxide (0.2 mL) of defined concentration (1-6% v/v) and temperature (23 – 70°C)
was dispensed onto the sample.
Figure 13. Schematic diagram (A) and photograph (B) of the advanced oxidation process reactor
used for chlorpyrifos degradation and microbial inactivation.
A
B
Light box housing 4 x 254 nm UV lamps
Height adjustable rack
Samples on a tray
10 or 16 cm
Entrance
Distance between light box and sample surface
61 cm
122 cm
Radiometer
41
2.3 Response Surface Methodology
RSM was used in the experimental design to determine the effectiveness of AOP in degrading
the pesticide CPY. Design Expert® Software 11.1.0 (Stat-Ease Inc, Minneapolis, MN, USA) was
used to produce a fractional factorial central composite design investigating the effect of UV
dose (kJ/m2), temperature of hydrogen peroxide (°C), and concentration of hydrogen peroxide
(% v/v) on the degradation of CPY (Table 9). The experimental design of this study included a
total of 20 runs with six replicate center points (Table 10). Runs were performed in triplicate
involving the three previously mentioned factors. The response variable can be expressed as a
function (Eqn. 5) of the independent process variables according to the following response
surface quadratic model.
3 3 2 32
0
1 1 1 1
i i ii ij i j
i i i j i
Y a a x a x a x x
(Equation 5)
where Y is the predicted response, xi and xj are factors influencing the predicted response, αi, αii,
and αij are the coefficients of the linear, quadratic, and interaction terms respectively. Lastly, ε is
a random error.
Regression analysis for the quadratic equation model was determined using Design Expert®
11.1.0 software. First, the model fit was tested to determine the quality of the model using the
coefficient of determination (R2). ANOVA analysis was conducted to determine whether the test
variables listed are significant or not. This was done using F-test and P-values with 95%
confidence level.
42
Table 9. RSM trials (20) using various test parameters of UV-C dose (kJ/m2), temperature (°C) and
concentration (%) of hydrogen peroxide.
Trial UV dose
(kJ/m2)(X1)
Temperature of
H2O2 (°C) (X2) H2O2 (%) (X3)
1 34.8 46.5 3.5
2 22.5 32.5 5.0
3 54.0 32.5 5.0
4 37.0 46.5 1.0
5 22.4 60.5 5.0
6 38.3 70.0 3.5
7 39.4 46.5 3.5
8 39.4 46.5 3.5
9 11.7 46.5 3.5
10 38.9 46.5 3.5
11 56.1 60.5 2.0
12 50.3 32.5 2.0
13 37.9 46.5 6.0
14 21.8 32.5 2.0
15 39.3 46.5 3.5
16 37.2 46.5 3.5
17 62.3 46.5 3.5
18 38.5 23.0 3.5
19 22.3 60.5 2.0
20 53.3 60.5 5.0
43
Table 10: Six center point replicate trials determining the replicability and precision of the
experimental method. Arranged from lowest to highest reduction corrected with the average
(n=177) positive control recovery of 89.4%. The standard deviation between reductions was 3.6 µg.
Trial #
Temperature of
H2O2 (˚C)
Actual
Temperature
(˚C)
Percent H2O2
(% v/v)
UV-C
Dose
(kJ/m2)
1 46.5 45 3.5 34.8
15 46.5 46 3.5 39.3
8 46.5 46 3.5 39.4
7 46.5 47 3.5 39.4
10 46.5 45 3.5 38.9
16 46.5 47 3.5 37.2
2.4 AOP Treatment of Apple skins Spiked with Chlorpyrifos
Crispin apples were stored in a cold storage room at 4°C until required. Apples were taken out of
cold storage when needed then washed under running municipal tap water followed with towel
drying. The washed apples were then inspected for damage including spots, bumps, bruises and
discolouration. Apples were then peeled vertically from the bottom to the top with a vegetable
peeler. Peeled apple skins were then cut into two 2.5 cm × 3 cm pieces per fruit. The peel
sections were then placed on individually labelled aluminum weigh dishes. Aliquots (0.2 mL) of
a working 1000 µg/mL CPY stock solution, prepared by dissolving 10 mg of CPY standard into
10 mL of acetonitrile, were introduced onto the surface of the apple peel samples and allowed to
44
dry at room temperature (approximately 25 °C) in the dark until dried. Thus, 200 µg of CPY was
deposited onto each piece of apple skin. One sample was treated with the AOP and the other was
left in the dark, untreated (positive control). Each treatment involved three pieces of apple skin
containing CPY that were treated with the AOP, three pieces of apple skin containing CPY that
were not treated with the AOP (positive controls), and two negative controls. One piece of apple
skin that did not contain CPY and was treated with the AOP (negative control 1) and one piece
of apple skin that did not contain CPY and was not treated with the AOP (negative control 2).
The spiked samples along with a negative control were lined up lengthwise on a tray with
dimensions 31 x 23.5 cm (length x width) and set 5 cm apart from one another lengthwise.
Treatment with 1 of the 20 listed AOP treatment parameters were performed (Table 9), the tray
was introduced into the reactor through its entrance and placed on top of an adjustable rack set so
that samples were 16 cm away from the UV light source (Figure 13A).
After treatment, the tray containing samples was removed through the reactor entrance and all
apple skins (treated, positive controls, and negative controls) were then placed inside
individually labelled 50-mL centrifuge tubes. A 20-mL aliquot of acetonitrile was used to rinse
the aluminum dish and was then placed inside the centrifuge tube containing the corresponding
apple skin. Assuming no degradation, a final concentration of 10 µg/mL would be present in the
rinsate. All centrifuge tubes with an apple skin and rinsate were sonicated (Branson 2510,
Crystal Electronics, Newmarket, ON, CA) for 20 minutes at 40 kHz. Due to heat being generated
during sonication (up to 30C), water was replaced with cool tap water to keep sonicater water
temperature constant at approximately 23C ± 2C. After sonication, 1 mL of rinsate was
removed from each tube and placed into individually labelled high performance liquid
chromatography (HPLC) vials. This process was repeated two more times to produce a triplicate
45
set of samples for each treatment (n = 3). A total of 24 samples were produced per trial (9 spiked
and treated, 9 spiked and untreated (positive control), and 6 not spiked/untreated (negative
controls). Sample vials were stored at 4 C for a maximum period of 24 h before quantification
using HPLC analysis. It should be noted in the current study, the spiked concentration of CPY,
10 µg/mL is 1000 times higher than the MRL of CPY on apples in Canada (0.01 µg/mL) (Health
Canada, 2008).
2.5 Validation Trial
Once RSM was completed, results were analyzed using Design Expert® Software. A validation
trial was suggested by the software in order to confirm the accuracy and validity of the model.
The given parameters for this trial were as follows: 69 kJ/m2 UV dose and 1.22% v/v H2O2 at
66°C. The predicted reduction for this trial was 92 µg (46% reduction of spiked chlorpyrifos).
Samples were prepared and treated using the methodology as described above in Section 2.4.
2.6 UV Only Trial
Treatments with UV light only were conducted using the same sample preparation and HPLC
analysis methods describe above in Section 2.4. Five trials at different UV doses (11, 23, 41, 53,
and 66 kJ/m2) were tested. After these trials were completed, the UV lights were brought closer
to the samples to be treated. By reducing the distance between UV lights and samples, UV dose
per minute would be increased thus reducing treatment time. The trial 53 kJ/m2 was re-conducted
at this higher UV dose to compare the difference in treatment times between same UV doses.
The positive controls between the higher and lower UV intensities were averaged and were used
as the positive control corrections.
46
2.7 Ozone Treatment of Apple Skins Spiked with Chlorpyrifos
Crispin apples were prepared the same way as described above in Section 2.4. Nine apple skin
sections were spiked with 0.2 mL of 1000 µg/mL CPY solution (200 µg) and dried in the dark
before treatment. Twelve apple skins were left blank (no spike) to act as a negative control.
Treatment occurred in a 30-L plastic container containing 2 holes, 1 for tubing connected to an
ozone monitor (linear dynamic range of 0-100 mg/L) (Model 106-L, 2B Technologies, Colorado,
USA) the other for tubing connected to a 2 g/h corona discharge ozone generator provided by Dr.
Thomas Graham (University of Guelph, School of Environmental Science) (Figure 14). Three
spiked skins along with 1 negative control was placed into the container with the lid closed.
These samples were treated with ozone gas for 30 minutes then placed into 50-mL centrifuge
tubes and filled with 20 mL of acetonitrile (ACN). These tubes were then sonicated (Branson
2510, Crystal Electronics, Newmarket, ON, CA) at 40 Hz for 20 minutes. After sonication, 1 mL
of sample was removed from the tube and placed into a 2-mL HPLC vial. This was repeated for
each sample and the extracts were then analyzed using an Agilent 1100 Series HPLC (Agilent,
Fair Lawn, CA, USA).
47
Figure 14. Schematic (A) and photograph (B) of ozone chamber treatment of CPY spiked apple
skins.
A
A
B
48
2.8 HPLC Analysis
High performance liquid chromatography was performed with an Agilent 1100 Series HPLC
instrument equipped with a photodiode array detector (Agilent, Fair Lawn, CA, USA). An
Agilent Zorbax Eclipse Plus C18 analytical column (4.6 x 150 mm, 5.0 µm) (Agilent, Santa
Clara, CA, USA) equipped with an Agilent Zorbax Eclipse Plus C18 analytical guard column
(4.6 x 12.5 mm, 5- micron, Agilent, Santa Clara, CA, USA) was used as a stationary phase with
a flow rate of 1.0 mL/min and the column temperature was uncontrolled with an average room
temperature of 23°C. The injection volume for samples and standards was 40 µL. The mobile
phase was in isocratic mode with a composition of 85:15 (%, v/v) acetonitrile/ water with 0.1%
trifluoroacetic acid (Millipore Sigma, St Louis, MO, USA). The detection wavelength was set at
290 nm. The concentration of CPY samples were quantified by the use of an x-point calibration
curve. Calibration standards for CPY were prepared in acetonitrile at concentrations of: 2.5, 5,
10, 20, and 40 µg/mL. The method detection limit (MDL) was determined by spiking apple skin
pieces with 200 µg of CPY (resultant concentration of rinsate 10 µg/mL) and extracting the CPY
to get a measure of the methods accuracy and precision (n = 7) (Shrivastava & Gupta, 2011). The
average recovery was 81.1%. The LOD and LOQ were 0.5 µg/mL and 1.7 µg/mL, respectively.
Replicate trials from the RSM table conducted on separate days were also compared to determine
the replicability of trials.
2.9 Determination of Chlorpyrifos-Oxon Production by AOP Treatment using Q-
ToF analysis
Apple skin samples were prepared as per Section 2.4 and were treated under the optimized
conditions described in Section 2.5. Untreated spiked samples and treated samples prepared using
the optimal treatment along with analytical standards of CPY, CPY-O and TCP were submitted to
49
the Mass Spectrometry Facility of the Advanced Analysis Centre at the University of Guelph for
Quadrupole Time of Flight (Q-ToF) mass spectrometry analysis to determine the presence or
absence of these compounds.
Liquid chromatography–mass spectrometry analyses was performed on an Agilent 1200 HPLC
liquid chromatograph (Agilent, Fair Lawn, CA, USA) interfaced with an Agilent UHD 6530 Q-
Tof mass spectrometer (Agilent, Fair Lawn, CA, USA). An Agilent Poroshell 120 C18 column (
EC-C18 50 mm x 3.0 mm 2.7 µm) was used for chromatographic separation with the following
solvents water with 0.1% formic acid (A) and acetonitrile with 0.1% formic acid (B). The mobile
phase gradient was as follows: initial conditions were 10% B hold for 1 min then increasing to
100% B in 29 min followed by column wash at 100% B for 5 min and 20 min re-equilibration.
The flow rate was maintained at 0.4 mL/min and sample injection volume was 10 µL. The mass
spectrometer electrospray capillary voltage was maintained at 4.0 kV and the drying gas
temperature at 250 °C with a flow rate of 8 L/min. Nebulizer pressure was 30 psi and the
fragmentor was set to 160 °C. Nitrogen was used as both nebulizing and drying gas. The mass-to-
charge ratio was scanned across the m/z range of 50-1500 m/z in 4GHz (extended dynamic range)
positive and negative ion modes. The acquisition rate was set at 2 spectra/s. The instrument was
externally calibrated with the ESI TuneMix (Agilent, Santa Clara, CA, USA). Mass spectrometer
control, data acquisition and data analysis were performed with MassHunter® Workstation
software (B.04.00).
The concentration of CPY-O samples were quantified using an x-point calibration curve.
Calibration standards for CPY-O were prepared in acetonitrile at concentrations of 0.01, 0.02,
0.04, 0.08, 0.16, and 0.31 µg/mL. Concentrations of 0.16 and 0.31 µg/mL were removed due to
low accuracy of the result which did not conform to the linearity of the lower concentrations below
50
0.16 µg/mL. The R2 value of the remaining 4 standards was 0.9993 (Figure 15) and the LOD was
below 0.01 µg/mL.
Figure 15. Calibration curve of chlorpyrifos-oxon standards ranging in concentrations from 0.01 –
0.31 µg/mL. Concentrations of 0.16 and 0.31 µg/mL were removed due to low accuracy. R2 value =
0.9993.
2.10 Inactivation of Escherichia coli O157:H7 and Aspergillus niger
Escherichia coli O157:H7 PH1 (stx2, eae, nalidixic acid resistant) originally isolated from a
clinical case was provided by the Public Health Agency of Canada (Guelph. Ontario, Canada).
Escherichia coli O157:H7 was cultivated in TSB at 37C for 16 h. The cells were harvested by
centrifugation (Sorvall ST8, Thermo Fisher Scientific, Waltham, MA, USA) at 4000 rpm for 10
minutes and resuspended in saline and then optical density at 600 nm was measured and adjusted
51
to 0.2 to obtain approximately 8 log CFU/mL. The suspension was held at 4 C until required for
testing.
Aspergillus niger spores NU320 previously isolated from environmental sources was used in this
study. Aspergillus niger spores were produced by inoculating the mold onto PDA and incubating
for 14 days at 25 C. The spores were harvested by flooding the plate with sterile distilled water
and scraping with a spreader. The spore suspension was then harvested by centrifugation for 15
minutes at 4000 rpm followed by the pellet being resuspended in sterile distilled water prior to
storing at 4 C until required for testing.
Apple skin sections were inoculated with either E. coli O157:H7 or A. niger spores to give a final
cell density of 8 and 7 log CFU/sample, respectively. The inoculated apple samples were then
placed within a biosafety hood and allowed to dry at room temperature for 3.5 h. Three skin
samples were treated with UV and 0.2 mL of 1.2 % v/v hydrogen peroxide (diluted from 30 %
v/v hydrogen peroxide with milli-Q water; Sigma-Aldrich, Oakville, Ontario, Canada), three
other samples were treated with only UV with a dose of 69 kJ/m2 and another three samples were
treated with hydrogen peroxide only (1.2 % v/v). Optimal treatment parameters were used to
treat another three samples (1.2 % hydrogen peroxide heated to 69 °C and UV dose of 69 kJ/m2).
The treated samples and non-treated controls were placed in 20 mL of saline and vortexed for 10
seconds to release microbes from the apple skin samples. A dilution series was prepared in saline
and plated onto agar. Escherichia coli O157:H7 was plated onto TSA supplemented with 50
µg/mL nalidixic acid that was subsequently incubated at 37 C for 24 h. Colonies grown on
plates were then swabbed onto CT-SMac agar and incubated for another 24 h at 37 C to confirm
52
identification of E.coli 0157:H7. Aspergillus niger was enumerated on PDA plates incubated at
25 C for 5 days.
2.11 Experimental plan and statistics
For RSM, trials were conducted with varying parameters of UV dose (kJ/m2), temperature (°C)
and concentration (% v/v) of hydrogen peroxide. Each trial was conducted in triplicates with
three samples per replicate. A total of 9 samples were produced per trial. Six trials were
conducted around the central points with 54 samples produced under the same conditions. For
the additional testing conditions (UV only, ozone fumigation), trials were performed at least
twice. Analysis of variance (ANOVA) was performed on the data using Design Expert®
Software 11.1.0. Statistical significance was determined at P > 0.05. Calculations of means and
standard deviations were performed using Microsoft Excel.
For microbial trials, the log count reduction calculation was performed using Microsoft Excel
2013 and determined by comparing the log transformed CFU/sample of treated and positive
control (inoculated but not treated) samples. Statistical significance between log CFUs or log
count reductions were determined using a Welch’s t-test in Microsoft Excel 2013 at P > 0.05.
3. Results and Discussion
3.1 Optimization of Recovery Method and HPLC Analysis
The method of recovering CPY from apples skins involved several steps in order to achieve a
maximal recovery of ~89%. One step in the recovery method was the use of a sonicator which
utilizes acoustic cavitation to generate bubbles which help in extracting deposited CPY from the
apple skin thus facilitating higher recoveries of CPY. Without sonication, recovery rates of CPY
were less than 80% but when sonication was utilized, recovery rates were consistently greater
53
than 85%. Other studies have shown that ultrasonic solvent extraction (USE) is effective at
improving recoveries of pesticides from produce (Pan, Xia, & Liang, 2008; Ramos, Rial-Otero,
Ramos, & Capelo, 2008). Pan et al. (2008) showed that recoveries of the pesticides
monocrotophos, dimethoate, carbendazim, carbaryl, imidacloprid and simazine could be
optimized to over 90% when sonicated for 35 minutes at 28 kHz. In comparison to this result,
they demonstrated that recovery rates were lower with decreased sonication time, for example,
imidacloprid sonicated for 25 minutes at 28 kHz had a recovery of 71% (Pan et al., 2008). They
also observed that increasing the volume of solvent was positively correlated with pesticide
recovery with 40 mL per gram of sample proving optimal. For example, when comparing
different volumes of ethyl acetate at 25 minutes of sonication with 5 g of pesticide-spiked
spinach sample, a recovery of 40% of monocrotophos was observed using 10 mL of solvent
whereas a recovery of 90% could be seen when using 40 mL (Pan et al., 2008). These factors
were optimized in the current study and it was observed that a sonication time of 20 minutes and
20 mL of solvent (ACN) would support a sufficient and consistent recovery. Higher sonication
times and solvent volume did not increase recovery rates above 85%.
Apple skin constituents had a negligible effect on the HPLC analysis of CPY with no major
interfering peaks. One unknown peak derived from apple skins eluted around 3.9 min while CPY
had an elution time of 2.3 min when using a 1 mL/min flow rate. The CPY peak had a tailing
effect after elution resulting in it partially co-eluting with the peak associated with constituents of
the apple skin. Water and hydrogen peroxide also initially reduced peak resolution with an
elution time around 1.8 min. In order to separate these peaks, the HPLC column was changed
from an initial 5 micron pore size stationary phase to 3.5 micron size. The mobile phase
concentration ratios were also changed from 90:10 ACN/water with 0.1% TFA to 85:15. This
54
allowed for better resolution between peaks with no overlap due to an increase in CPY elution
time to 4.6 min. This longer elution time also removed tailing due to eluting after the unknown
apple skin peak. Because resolution was well established between peaks, there was no need for a
clean-up procedure of extracts which is commonly employed when working with produce
(Harshit, Charmy, & Nrupesh, 2017).
3.2 Response Surface Methodology
The average recovery (n = 177) of CPY from apple peels by using the applied methodology from
Section 2.4 was 89.4% 3.8%. In comparison, Osmann et al. (2012) had recoveries of CPY
between 87 – 92% from date fruits (n = 10) using GC-MS. Their method of extraction however
used acetone as the extraction solvent rather than acetonitrile (Osman et al., 2014). Whangchai et
al. (2011) also employed GC rather than HPLC and used acetone as the extraction solvent for
removing CPY from lychee fruit but did not include % recovery in their study. Rawn et al.
(2008) extracted captan, a fungicide, from apples and had an average recovery (n = 31) of 81%
using GC-MS as well. Their recovery method may be lower due to involving a clean-up step
which subjected the samples to gel permeation chromatography and then a Florisil column
(Rawn et al., 2008).
The mean recovery was used as a recovery correction factor for AOP treated samples. The
percent degradation of CPY across the various AOP treatments ranged from 28 % to 92 % (Table
11). The extent of CPY degradation was analyzed using Design Expert® 11.1.0 software and
was determined to fit a linear model (Table 13). ANOVA analysis showed the linear terms X1
(UV dose) and X2 (H2O2 temperature) were significant (P < 0.05) in CPY degradation whereas
X3 (H2O2 concentration) was not significant (Table 13).
55
The RSM approach demonstrated that AOP could degrade CPY via a process that was primarily
dependent on the UV-C dose and temperature of hydrogen peroxide. It has been reported that
CPY in aqueous solution is relatively stable to UV-C light with the addition of hydrogen
peroxide or iron (Fe3+) required to support degradation of the pesticide (Gandhi, Lari, Tripathi, &
Kanade, 2016). Further studies have confirmed the finding that UV-C degradation enhances the
degradation of CPY when applied as part of an advanced oxidation process (Gandhi et al., 2016;
Savic et al., 2019; Thind, Kumari, & John, 2018; Utzig et al., 2019). Thind et al. (2018) reported
that hydrogen peroxide within the range of 0.5 – 1.5 % v/v supported a 42 % decrease in CPY
levels but could be increased to 53 % reduction when used in combination with UV-C. A further
increase in CPY degradation up to 74 % was obtained by using a combination of hydrogen
peroxide, titanium dioxide and UV-C therefore suggesting a synergistic effect. Oliveria et al.
(2014) also showed that low concentrations of hydrogen peroxide between concentrations of
0.025 % to 0.2 % had an effect on the degradation of CPY ranging from 49.2% to 73.9%
reduction. In contrast to Oliveria et al. (2014), this study used concentrations ranging from 1.0 –
6.0%. Another study concluded that 0.16 mg of chlorpyrifos was degraded per mg of H2O2
consumed and this relationship was observed up to a maximum concentration 0.09% H2O2
(Femia et al., 2013). Utzig et al (2019) reported the degradation of CPY in acetonitrile with UV
supporting complete degradation of 200 µg/L within 120 min treatment and the process was
accelerated to 30 minutes with the inclusion of 12 mg/L hydrogen peroxide. The authors
determined that at a UV-C radiation intensity of 0.75 mW/cm2 caused the half- life of CPY
utilizing UV-C radiation alone would be 12.9 min whereas when combined with hydrogen
peroxide, the half-life decreased to 5.8 min.
56
Previous reports on the AOP mediated degradation of CPY have mainly focused on aqueous or
ethanolic solutions. In the current study, where the AOP process was performed on the surface of
apples, it was evident that hydrogen peroxide had a minor role on the overall degradation process
compared to when applied in an aqueous phase. The presence of increasing levels of hydrogen
peroxide in the AOP reduced the degree of CPY degradation by UV-C light. It has been stated
that higher concentrations of hydrogen peroxide may form water and a hydroperoxyl radical
(HO2) which is capable of interfering with chlorpyrifos degradation (Oliveira et al., 2014).
Another issue with using hydrogen peroxide and UV light is that hydrogen peroxide does not
absorb 254 nm light well due to its low molecular extinction coefficient of 19 L/ molcm (Figure
10) (Gottschalk et al., 2010) so OH radical production is low which will require longer UV
exposure times and a surplus of hydrogen peroxide (Gottschalk et al., 2010).
There could be several reasons underlying the differences observed in the degradation of CPY on
the surface of apples compared to in aqueous solution. For example, it is known that the
concentration of hydrogen peroxide has to be balanced with generating sufficient free-radicals to
react with CPY and an excess peroxide concentration can impede CPY degradation (Oliveira et
al., 2014). In the case of aqueous solutions, diffusion of hydrogen peroxide and generation of
hydroxyl radicals can prevent the reaction from being impeded. It is also conceivable that in air
the UV-C transmission to the surface of apples would be greater than in water, especially if
absorbing contaminants are present. Therefore, in aqueous solutions the hydrogen peroxide
would constitute the primary element of the AOP given the absorption of UV-C by the water
constituents. By directly illuminating the surface of apples, the generation of radicals can occur
but CPY degradation would be primarily due to UV-C photon exposure rather than hydrogen
peroxide. Additional possibilities are the aqueous phase forms a relative constant matrix to
57
support the reaction of radicals with CPY. For example, high alkaline pH and presence of Fe can
promote the CPY degradation but which could be less controlled on the apple surface (Behin &
Farhadian, 2017). Regardless of this fact, the results indicate that AOP studies performed in the
aqueous phase do not always translate to treating whole fruit in air.
In the current study the degradation of CPY was positively correlated to temperature which is in
agreement with others (Cengiz, Catal, Erler, & Bilgin, 2015; Oliveira et al., 2014). A study
conducted by Oliveria et al. (2014) investigating the degradation of CPY in an aqueous system
using AOP also showed that an increase in temperature slightly influenced CPY degradation.
They suggested that higher temperatures used in combination with UV radiation supported
higher degradation compared to elevated temperatures used in combination with AOP involving
UV exposure for 8 hours (no dose or intensity given) and hydrogen peroxide (0.1%) (Oliveira et
al., 2014). The same result was observed in this study, with AOP treatments producing a lower
reduction than UV used alone at the same dose. This may be due to hydrogen peroxide
scavenging UV-C radiation, which may be more significant in CPY degradation, to generate
minimal amounts of hydroxyl radicals (Gottschalk et al., 2010). In a different study conducted by
Cengiz et al. (2015), it was observed that the reduction of chlorpyrifos-ethyl could be as high as
0.56 µg/kg when treated for 60 minutes at 90°C whereas a lower heat treatment of 60°C at the
same time produced a reduction of 0.37 µg/kg (Cengiz et al., 2015). The mechanism of thermal
decomposition of CPY involves a series of stepwise elimination reactions that cleaves ethylene
residues to leave 3,5,6,-trichloro-2-pyridinol as the main degradation product (Kennedy &
Mackie, 2018). Although greater temperatures have been shown to increase degradation of CPY,
the temperature sensitivity of fruits would make higher temperatures non relevant in the context
of commercial food processing.
58
Table 11. RSM trials with amount of CPY reduction (µg) observed using various test parameters of
UV-C dose (kJ/m2), temperature (°C) and concentration (%) of hydrogen peroxide. Reduction from
each trial was corrected using the average positive control recovery of 89.4% (n=177).
Trial UV dose
(kJ/m2)(X1)
Temperature of
H2O2 (°C) (X2) H2O2 (%) (X3)
CPY
Reduction
(µg)(Y)
1 34.8 46.5 3.5 50
2 22.5 32.5 5.0 32
3 54.0 32.5 5.0 52
4 37.0 46.5 1.0 60
5 22.4 60.5 5.0 54
6 38.3 70.0 3.5 58
7 39.4 46.5 3.5 52
8 39.4 46.5 3.5 54
9 11.7 46.5 3.5 28
10 38.9 46.5 3.5 56
11 56.1 60.5 2.0 88
12 50.3 32.5 2.0 74
13 37.9 46.5 6.0 54
14 21.8 32.5 2.0 30
15 39.3 46.5 3.5 52
16 37.2 46.5 3.5 62
17 62.3 46.5 3.5 92
18 38.5 23.0 3.5 58
19 22.3 60.5 2.0 52
20 53.3 60.5 5.0 74
Max 62.3 70.0 6.0 92
Min 11.7 23.0 1.0 28
59
Table 12: Six center point replicate trials determining the replicability and precision of the
experimental method. Arranged from lowest to highest reduction corrected with the average
(n=177) positive control recovery of 89.4%. The standard deviation between reductions was 3.6 µg.
Trial # Temperature of
H2O2 (˚C)
Actual
Temperature
(˚C)
Percent H2O2
(%)
UV-C
Dose
(kJ/m2)
Correction using
Average Pos
Control (µg)
1 46.5 45 3.5 34.8 50
15 46.5 46 3.5 39.3 52
8 46.5 46 3.5 39.4 54
7 46.5 47 3.5 39.4 52
10 46.5 45 3.5 38.9 56
16 46.5 47 3.5 37.2 62
Table 13. ANOVA analysis table of the linear model indicating that values lower than P < 0.05 are
significant. In this case, UV-C dose and H2O2 temperature are significant whereas H2O2
concentration was not significant. * indicates P < 0.05.
Source Sum of
Squares df* Mean Square F-Value P-value
Model 7.70 3 2.57 23.72 < 0.0001*
A-UV Dose 6.48 1 6.48 59.93 < 0.0001*
B-H2O2 Temperature 0.8333 1 0.8333 7.70 0.0135*
C-H2O2 Concentration 0.3080 1 0.3080 2.85 0.1109
Residual 1.73 16 0.1082
Lack of Fit 1.73 15 0.1150 23.01 0.1623
Pure Error 0.0050 1 0.0050
*df is the degrees of freedom.
60
Surface response plots generated by Design Expert® software illustrates the effects of UV-C
dose, hydrogen peroxide concentration and temperature in degrading CPY (Figure 16). A
synergistic effect between hydrogen peroxide temperature and UV dose on the degradation of
CPY was observed (Figure 16A). In contrast, there was no significant (P > 0.05) interaction
between hydrogen peroxide concentration and the applied UV-C dose (Figure 16B). In a similar
manner, there was a relatively negligible interaction between the concentration and temperature
of hydrogen peroxide on CPY degradation (Figure 16C).
A
61
B
C
62
Figure 16. 3D surface graph of different interaction effects of an advanced oxidation process for
degrading CPY on apples. CPY was introduced onto apple peel and treated with various
combinations of hydrogen peroxide and UV dose with the decrease in pesticide levels being
recorded. The plots illustrate UV dose and H2O2 temperature (A), UV dose and H2O2 concentration
(B) & H2O2 concentration and H2O2 temperature (C).
From the interaction between the three parameters it was possible to generate a predictive
equation (Eqn. 6) used to describe the observed reduction of CPY. Reduction of CPY from the
six center points ranged from 50 – 62 µg (25 – 31% of initial concentration) with a standard
deviation of 3.6 µg, demonstrating reproducibility of the predictive model (Table 12). This
shows that the data is replicable with minimal variation between samples. In addition, through
verification, a 94 µg (47%) degradation of CPY was achieved using an optimal AOP treatment
of 68.4 kJ/m2 UV dose and 1.22% v/v H2O2 at 66°C. This reduction agreed with a predictive
value of 92 µg suggested by Design Expert software (Eqn. 6) and was within a ± 5% standard
deviation (87 - 97 µg). It can also be seen from the predicted vs actual degradation graph that the
model is capable of accurately predicting CPY degradation following specified parameters
(Figure 17).
𝑌 = 5.742 + 1.071 𝑋1 + 0.390 𝑋2 − 2.241 𝑋3 @ 36𝐽
𝑠 ∙ 𝑚2
(Equation 6)
63
Figure 17. Predicted vs actual reduction of CPY table and graph illustrating the accuracy of the
RSM model in predicting CPY degradation under known conditions.
3.3 Ultraviolet light mediated degradation of CPY
The average positive control samples recovery was 90.5 ± 1.8 % (n = 42) and was used as the
correction factor in subsequent trials. The UV-C mediated degradation of CPY followed linear
kinetics with (r2 = 0.982) with 66 kJ/m2 dose supported a 140 µg (70%) reduction of CPY
(Figure 18).
When the distance between the sample and the UV light was altered from 16 cm to 10 cm, the
average UV intensities changed from 36 J/sm2 to 43 J/sm2, respectively. At this higher intensity
(10 cm, 43 J/sm2), the average (n=17) positive control recovery of 87.7% ± 5.0% was used to
correct reduction from treatments. Treatments at higher and lower UV intensities were compared
64
with UV exposure times remaining the same which resulted in different UV doses. UV exposure
times of 25 minutes were compared. An average (n=15) positive control recovery of 87.8% ±
5.2% CPY was used for the reduction correction. After 25 minutes of UV exposure, the lower
UV intensity treatment (16 cm between UV light and sample) was subjected to a total UV dose
of 53 kJ/m2 which achieved a CPY reduction of 106 µg (53%). In comparison, the higher UV
intensity treatment (10 cm between UV light and sample) produced a total UV dose of 64 kJ/m2.
CPY reduction of 141 µg (71%) was observed at this higher UV dose. When comparing the same
UV dose of 53 kJ/m2 at different UV exposure treatment times of 20.5 and 25 minutes, no
significant difference was observed with both producing CPY reductions of 106 µg (53%). These
results showed that by increasing UV intensity and by decreasing the distance between the UV
source and sample, treatment times could be shortened.
Figure 18. Graph of CPY reduction using only UV radiation with a linear trend line (orange line).
Reductions were calculated using HPLC analysis. A R2 value of 0.982 was calculated using 5 data
points of varying UV doses (kJ/m2) and CPY reduction (µg).
65
3.4 CPY-O production from AOP exposure
The positive control apple skins (spiked with CPY but not treated) showed concentrations of
CPY-O below the limit of detection (0.001 µg). CYP-O was not detected in negative control
apple skins (not spiked with CPY) by Q-ToF analysis. Of the 9 treated apple skin samples spiked
with CPY, a single sample showed levels of CPY-O below the limit of detection. The other 8
samples showed concentrations ranging from 0.002 – 0.004 µg. These results indicate that CPY-
O was generated when treated with AOP technologies (Table 14 and Figure 4). This result
agreed with other studies that also observed the generation of CPY-O due to AOP exposure
(Bavcon, Franko, & Trebše, 2007; Savić et al., 2019; Utzig et al., 2019). CPY, like other OP
pesticides, contains a P=S group which has been known to be converted to its oxon derivate
group (P=O) by metabolic oxidation (Savić et al., 2019). Bavcon et al. (2007) demonstrated
using GC-MS that CPY-O was the main degradation product of CPY from photoexcitation via
xenon lamp emitting below 400 nm. They observed, after 60 minutes of exposure, CPY-O
generation did not exceed 1% of the initial CPY concentration (Bavcon et al., 2007). Savic et al.
(2019) concluded that UV-C irradiation of CPY resulted in the generation of CPY-O with
maximum generation of >1% of the initial CPY concentration after 80 minutes of exposure.
Utzig et al. (2019) reported that although CPY degradation could be observed when using UV
and hydrogen peroxide, the generation of CPY-O was also observed when the AOP was applied,
but not when UV-C was applied alone. These studies however did not state the UV dose but
rather included UV exposure time instead.
66
Table 14. Q-ToF analysis of CPY-O on apple skins spiked with CPY. It can be observed that apple
skin samples treated with AOP produced the by-product CPY-O while samples spiked with CPY
but not treated with AOP had concentrations below the limit of detection.
Positive Control (µg) Treated Sample (µg)
< 0.000 0.002
< 0.000 0.004
< 0.000 0.004
< 0.000 < 0.000
< 0.000 0.004
< 0.000 0.004
< 0.000 0.002
< 0.000 0.004
< 0.000 0.004
3.5 Ozone Treatment
In the first replicate, the average % recovery for positive controls (spiked, untreated) apple skins
was 66% (n=8), and the treated samples had a recovery of 65% (n=9). HPLC analysis showed
that ozone gas treatment for 30 minutes (~ 1 g of gaseous ozone) had no effect on CPY
degradation. The concentration of ozone was above the linear dynamic range of the ozone
monitor of 100 mg/L. This experiment was repeated but with a higher relative humidity (>70%
RH) and the % recovery for positive controls was 82% (n=6) compared to treated samples with
85% (n=6). Recovery may have been lower in the first experiment due to sample preparation and
storage errors. Another repeat of this experiment was conducted and showed an 82% (n=5)
recovery of positive controls and 85% (n=6) for treated samples. These results showed that the
average recoveries for both positive controls and treated samples were not significantly different
67
when compared using Welch’s t test (P <0.05). This suggests that the ozone treatment did not
have a measureable effect on CPY on the surface of apple skins.
In other studies, gaseous ozone was seen to be successful at degrading pesticides. Whangchai et
al. (2011) concluded that gaseous ozone fumigation for 1 hour at 240 mg/L could degrade 45%
(4.5 mg/L) of CPY on lychee fruit. This result however was not supported in the current study.
One possible reason for this may be due to the difference in the concentration of ozone generated
and exposure time. Karaca et al (2012) demonstrated that 3 out of 5 tested fungicides stored in
ozone enriched air degraded residues faster than storage in ambient air conditions (2°C and 95%
RH). They observed reductions of 34.7%, 51.6%, and 64.5% in cyprodinil, pyrimethanil, and
fenhexamid respectively (Karaca, Walse, & Smilanick, 2012). Research conducted on using
ozone in reducing pesticides dissolved in water has been shown to be effective (Ikehata & Gamal
El-Din, 2005; Swami et al., 2016; Wu, Luan, Lan, Lo, & Chan, 2007). Swami et al (2016)
demonstrated that CPY degradation of 95% (0.06 µg/g) could be achieved when aqueous
samples were treated for 30 minutes using a 200 mg/h ozone generator Wu et al. (2006) observed
different reductions of the insecticide cypermethrin on vegetables (Brassica rapa) such as bok
choy treated with differing concentrations of ozonated water and exposure times. When treated
for 15 minutes with tap water or ozonated water at 1.4 mg/L, and 2.0 mg/L, reductions of 26%,
33%, and 54% was observed, respectively (Wu et al., 2007). After 30 minutes of exposure,
reductions of 31%, 54%, and 61% were observed (Wu et al., 2007). They concluded that higher
concentrations and longer exposure times increased removal of cpyermethrin on vegetables.
They also saw the same results when using other pesticides including methyl-parathion,
parathion, and diazinon.
68
3.6 Microbial Inactivation
The initial loading of E .coli O157:H7 and A. niger were determined to be 8.59 ± 0.52 and 6.98 ±
0.35 log CFU/sample, respectively (Figure 19). The maximal CPY degradation reduction
treatment with a UV-C dose of 69 kJ/m2 and 1.22% v/v H2O2 at 66°C supported a >7 log CFU
reduction of E. coli O157:H7 and a >4.68 log CFU/sample reduction of A. niger (Table 15).
These reductions were determined to be statistically significant when assessed using Welch’s t-
test. When determining individual factors, 1.22% v/v hydrogen peroxide alone applied at 66C
for 29 minutes (approximate equivalent amount of time for UV-C dose to reach 69 kJ/m2) also
supported >8 log CFU reduction of E.coli but only supported a 1.65 log CFU/sample reduction
of A. niger spores (Table 15). According to Welch’s t-test, both of these reductions using heated
hydrogen peroxide were determined to be statistically significant (P < 0.05). It was suspected
that the use of heat alone could significantly reduce E.coli O157:H7, perhaps more than the
hydrogen peroxide itself. To test this theory, triplicate trials were conducted with sterile, room
temperature or heated (~66°C) milli-Q water. The initial load of E.coli O157:H7 was 5.92 ± 0.09
log CFU/sample. After treatments, the average log CFU/sample for the room temperature and
heated water treatments were 5.86 ± 0.06 and 5.81 ± 0.06 for room temperature and heat
treatment, respectively, and they were not significantly different from the initial load (P > 0.05).
Consequently, it can be assumed that heat alone played a minor role in E.coli O157:H7
reduction. This could be due to E.coli having the ability to survive in temperatures over 66°C for
an extended period of time (Droffner & Brinton, 1995; R. Singh, Kim, Shepherd, Luo, & Jiang,
2011). Droffner and Brinton (1995) showed that E.coli could survive in temperatures between 60
– 70 °C for 9 days under dry conditions. Singh et al. (2011) showed that E.coli O157:H7 could
survive in compost at 50% moisture for 1 day at 60 °C. In this study, heated solution was applied
69
onto room temperature apple skins which would in theory, begin cooling down the heated
solution when it comes in contact with surface of the apple. This may explain why a heated
solution did not be significantly reduce E.coli O157:H7. In comparison, hydrogen peroxide
treatments were re-conducted but with both room temperature and heated (~66°C) solutions and
an initial load of 5.84 ± 0.14 log CFU/sample of E.coli O157:H7. The resultant load of E.coli
O157:H7 was < 2.3 log CFU/sample for both room temperature and heated treatments. This
result showed that hydrogen peroxide could exert a germicidal effect on E.coli O157:H7 without
the addition of heat. A UV-C dose of 69 kJ/m2 alone was also determined to be statistically
significant, resulting in a >6.56 log CFU/sample decrease in E. coli O157:H7. In comparison, A.
niger spores with UV-C alone resulted in a >4.68 log CFU/sample reduction.
A UV-C process alone could be used to degrade CPY but for inactivation of E. coli O157:H7
there was a significant contribution from hydrogen peroxide exposure. Although hydrogen
peroxide does not have as large of a contribution to A. niger reduction relative to E. coli
O157:H7, it is still considered to be statistically significant.
The results are in agreement with other reports on the inactivation of microbes on fresh produce
and egg shell surfaces by AOP treatment (Hadjok, Mittal, & Warriner, 2008; K. Murray, Moyer,
Wu, Goyette, & Warriner, 2018; Rehkopf, Byrd, Coufal, & Duong, 2017; Xie, Hajdok, Mittal, &
Warriner, 2008). It is thought that the free radicals generated on the surface of the sample can
access microbes shielded from UV-C by surface structures. It is possible that the proportion of
free radicals required to inactive microbes is less than that needed for CPY oxidation. The results
suggest that hydrogen peroxide makes a greater contribution to antimicrobial action of AOP,
while photo-oxidation by UV-C makes a greater contribution to the degradation of CPY, and it
can be enhanced by temperature. In this respect, the optimum AOP treatment parameters
70
identified in this study can collectively act to reduce microbial and chemical hazards in fresh
produce.
Figure 19. Log counts of Escherichia coli O157:H7 and Aspergillus niger spores. *<2.3 CFU/mL is
the limit of enumeration. All treatments are determined to be statistically significant for both
organisms.
Table 15. Log count reduction of Escherichia coli O157:H7 and Aspergillus niger spores inoculated
onto apple peel sections then treated with UV-C (at 254 nm), hydrogen peroxide (1.22% v/v at
66C) or a combination of UV-C and hydrogen peroxide.
Microbe Treatment Log CFU/Sample
Initial
Loading
Post-Treatment LCR
Escherichia coli
O157:H7
Control
(Non-treated)
8.590.52
H2O2 (1.22% v/v) <2.30* >6.56a
UV-C (69 kJ/m2) 2.690.41 5.890.41b
71
UV-C + H2O2(69
kJ/m2 and 1.22%
v/v)
<2.30* >6.56a
Aspergillus
niger
Control
(Non-treated)
6.980.35
H2O2 (1.22% v/v) 5.320.40 1.650.40a
UV-C (69 kJ/m2) <2.30* >4.68b
UV-C + H2O2 (69
kJ/m2 and 1.22%
v/v)
<2.30* >4.68b
Mean values for each of the test microbes, followed by the same letter are not significantly
(P>0.05) different.
*Limit of enumeration = 2.30 log CFU/Sample
4. Conclusions
This study found that the use of AOPs involving UV radiation at 254 nm and hydrogen peroxide
were successful in degrading the pesticide chlorpyrifos (CPY) on the surface of apple skins. An
HPLC analysis method and recovery method for determining residual CPY levels on apples was
shown to be effective and accurate with an average positive control recovery of 89.4% 3.8%
(n=177). Through multiple ozone fumigation trials, it was shown that ozone gas was incapable of
degrading CPY on apple skins after 30 minutes of exposure in an enclosed space. A set of
experiments designed using RSM showed that hydrogen peroxide concentration is an
insignificant factor in degrading CPY while UV radiation and hydrogen peroxide temperature
were significant factors. When using the optimized treatment parameters of 68.4 kJ/m2 UV dose
and 1.22% v/v H2O2 at 66°C, an average degradation of 94 µg (47% of the initial concentration)
(n = 9) was observed. However, it was shown that UV radiation on its own was more effective
than when used in combination with hydrogen peroxide; a UV dose of 64 kJ/m2 alone produced
72
an average CPY degradation of 141 µg (n = 9). Although degradation of CPY was observed, Q-
ToF analysis showed that CPY degradation resulted in the production of chlorpyrifos-oxon
(CPY-O), the active and more toxic form of CPY. Treatment of 10 µg/mL CPY with optimized
degradation parameters resulted in the production of 0.004 µg (0.02 µg/mL) CPY-O. The spike
amount used in this study was 1000 times the MRL for CPY on apples in Canada of 0.01 µg/mL
which suggests that the production of CPY-O from treated apples with CPY concentrations near
the MRL would be minimal and not pose a significant risk to human health. Decreasing the
contact distance between the UV lamp source and apple skin surface resulted in the UV dose
being increased due to an increased UV intensity, thus reducing the treatment time required for
the same effect. AOP treatment was also successful in reducing microbial colonies of both the
pathogen E.coli O157:H7 and A. niger. Despite being insignificant in degrading CPY, the
addition of hydrogen peroxide is useful for treating microbial contamination, and was significant
in reducing E.coli O157:H7 to below the limit of enumeration (2.30 log CFU/sample).
Future work
This study focused only on the treatment of apples, which have a relatively smooth surface
compared to most other fruits and vegetables. Different types of produce should be tested with
the AOP to determine its effectiveness in reducing CPY and microbial contaminants. Other types
of insecticides besides CPY should be tested as well including: carbamates, organochlorides,
phenylpyrazole, pyrethroids, neonicotinoids, and ryanoids. Other types of pesticides can also be
tested such as fungicides, bactericides, and especially herbicides, which are the most widely used
type of pesticide in the world. Modern day pesticide analysis involves testing for multiple
pesticide residues at the same time. A known concentration pesticide solution containing
multiple pesticides should be spiked onto apple skin samples and analyzed using triple-quad LC-
73
MS-MS in order to determine the degradation of multiple pesticides at the same time rather than
using HPLC to determine the degradation of a single pesticide as performed in the current study.
Other future work of interest may be to use AOP to treat lower CPY spike concentrations, down
to 0.01 µg/mL (maximal residue limit on apples in Canada). It may also be worth investigating
how to obtain a higher UV dose in order to decrease treatment time, which will impact the rate of
food production.
Different microbial organisms can also be tested on apples or different types of produce
including: salmonella and if possible, viruses. UV-C radiation has been known to inactivate
viruses as well as bacteria and molds (Tseng & Li, 2007; Watanabe et al., 2010)
74
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