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Ph.D. Thesis
QUANTITATIVE DETERMINATION OF PESTICIDES IN HUMAN
BIOLOGICAL FLUIDS AND FOOD STUFFS
YAWAR LATIF
National Centre of Excellence in Analytical Chemistry
University of Sindh, Jamshoro-76080, Pakistan
2012
Dissertation submitted towards University of Sindh in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Analytical
Chemistry
University of Sindh, Jamshoro
Ph.D Thesis
QUANTITATIVE DETERMINATION OF PESTICIDES IN HUMAN BIOLOGICAL FLUIDS AND FOOD STUFFS
By
YAWAR LATIF
National Centre of Excellence in Analytical Chemistry, University of Sindh, Jamshoro – PAKISTAN
2012
Certificate
This is to certify that Mr. YAWAR LATIF has carried out his research work on the topic
“QUANTITATIVE DETERMINATION OF PESTICIDES IN HUMAN BIOLOGICAL FLUIDS AND
FOOD STUFFS” under our supervision at the laboratories of National Centre of Excellence in
Analytical chemistry, University of Sindh, Jamshoro. The work reported in this thesis is original
and distinct. His dissertation is worthy of presentation to the University of Sindh for the award of
degree of Doctor of Philosophy in Analytical Chemistry.
Dr. Syed Tufail Hussain Sherazi Professor Supervisor National Centre of Excellence in Analytical Chemistry, University of Sindh, Jamshoro, Pakistan
Dr. Muhammad Iqbal Bhanger Professor Co–Supervisor National Centre of Excellence in Analytical Chemistry, University of Sindh, Jamshoro, Pakistan
Contents Dedication I
Acknowledgments II
List of figures III
List of tables IV
Abbreviations V
Abstract VII
CHAPTER-1 Pages INTRODUCTION 1-12 1.1 Pesticide and their classification 1 1.2 Applications of pesticides 2 1.2.1 Applications of pesticides in Pakistan 3 1.3 Toxicity and Potential Health Effects of Pesticides 5 1.4 Levels of Pesticides in Food and Food Safety Aspects 7 1.5 Analysis of pesticide residues in vegetables, fruits and human blood samples…. 9 1.5.1 Contemporary analytical methods and techniques for pesticide residues in food and
human biological fluids 11
CHAPTER-2 LITRATURE REVIEW 13-42 2.1 Assessment of pesticide residues in vegetables and fruits 13 2.2 Investigation of pesticide residues in human biological fluids (blood, urine) 23 2.3 Analytical techniques and methodologies used for pesticide residues in fruits and
Vegetables 26
2.3.1 Analysis of fruits and vegetables for pesticide residues 30 2.3.2 Application of Gas chromatography (GC) for pesticide residues in fruits and
vegetables 29
2.3.3 Applications of High pressure / performance liquid chromatography for pesticide residues in fruits and vegetables
32
2.3.4 Application of thin layer chromatography (TLC) for pesticide residues in fruits and vegetables
35
2.4 Analytical techniques and methodologies used for pesticide residues in human biological fluids (blood, urine)
37
2.4.1 Application of Gas chromatography for pesticide residues in human biological fluids (blood, urine)
37
2.4.2 Application of High performance liquid chromatography for pesticide residues in human biological fluids (blood, urine)
40
CHAPTER-3 EXPERIMENTAL 43-51 3.1 Assessment of pesticide residues in commonly used vegetables 43 3.1.1 Vegetable samples 43 3.1.2 Chemical standards and reagents 43 3.1.3 Extraction procedure 43 3.1.4 GC-MS analysis 44 3.2 Method developed for the assessment of pesticide residues in commonly used
fruits 45
3.2.1 Reagents 45 3.2.2 Instruments 45 3.2.3 Instrumental conditions 46 3.2.4 Fruit samples 47 3.2.5 Extraction and clean-up procedure 47 3.3 Monitoring of pesticide residues in commonly used fruits 48 3.3.1 Sample collection and preparation 48 3.3.2 Extraction procedure 48 3.3.3 Gas chromatographic analysis 48 3.4 Assessment of pesticide residues in human blood samples 49 3.4.1 Selection and description of sampling population 49 3.4.2 Sample collection 49 3.4.3 Reagents 50 3.4.4 Extraction and cleanup 50 3.4.5 Instrumentation 51 CHAPTER-4 RESULTS AND DISCUSSION 52-95 4.1 Assessment of pesticide residues in commonly used vegetables 52 4.2 Method developed for the assessment of pesticide residues in commonly used
fruits 59
4.2.1 Gas chromatographic determination 59 4.2.2 Optimization of extraction procedure 60 4.2.3 Method Validation 63 4.2.3.1 Linearity 63 4.2.3.2 Repeatability 63 4.2.3.3 Recovery 67 4.2.3.4 Detection and Quantification limits 67 4.2.3.5 Confirmation by GC-MS 70 4.2.3.6 Evaluation of method 70 4.3 Monitoring of pesticide residues in commonly used fruits 72 4.4 Assessment of pesticide residues in human blood samples 83
CONCLUSIONS 96
RECOMMENDATIONS 98 REFERENCES 99 AUTHOR’S PUBLICATIONS
III
LIST OF FIGURES
4.2.1 (A) GC-μECD chromatogram of the blank sample extract. (B) GC-μECD chromatogram of standard mixture in blank spiked sample of the same concentration in Et/Ac (1 μg g-1)
60
4.2.2 GC-μECD chromatogram of a standard mixture. Peak numbers are named in the order of increasing tR in Table 4.2.1
62
4.2.3 Effect of sonication on pesticide recovery in the extraction procedure samples were fortified at 1.0 μg g-1
63
4.4.1 Representative chromatograms of blood samples containing chlorpyrifos (A) and endosulfan (B) with their confirmative main ion fragments shown in mass spectrum
94
IV
LIST OF TABLES
4.1.1 Calibration data of individual pesticide in the vegetable samples with the limit of detection and limit of quantification
53
4.1.2 Recoveries (% ± CV) of the investigated pesticides from samples 54 4.1.3 Main ions selected (m/z) for detection and determination analysis of individual
pesticides in the vegetable samples
55 4.1.4 Pesticide concentrations found in vegetable samples mg/kg 57 4.2.1 Retention times (tR), calibration data, and repeatability of the pesticides analyzed
by GC-μECD
64 4.2.2 Recovery of pesticides from spiked samples 65 4.2.3 Limits of detection (LOD, μg kg-1) and limits of quantification (LOQ μg kg-1) of
pesticides assayed by GC-μECD
68 4.2.4 Selected ions from MS of the studied pesticides 69 4.2.5 Summarized results of pesticide residues found in monitoring study of fruits 71 4.3.1 Pesticide names, chemical active group, usage, molecular weight, retention times
and selected MS main ions (m/z)
73 4.3.2 Maximum residue limits (MRLs) of targeted pesticides 74 4.3.3 Pesticide residue levels (µg/kg) found in fruits collected from fruit market No.1 75 4.3.4 Pesticide residue levels (µg/kg) found in fruits collected from fruit market No.2 76 4.3.5 Pesticide residue levels (µg/kg) found in fruits collected from fruit market No.3 78 4.3.6 Total number of samples collected from all markets, frequencies of pesticides
found and number of samples exceeds MRLs
79 4.4.1 Location, No. of volunteers assessed, agro and non-agro professionals lived in
agricultural environment, male / female ratios and their mean Age with S.D
84 4.4.2 Number of agro-professional volunteers with their exposure duration, and
proportions of each group with respect to the total number of residues detected volunteers
85 4.4.3 Number of non-agro professional volunteers who have detected pesticide residues
in their blood samples
85 4.4.4 Number of residue detected agro-professional volunteers with their years of
exposure, and mean concentrations of pesticide residues found in their blood samples
88 4.4.5 Number of residue detected non-agro professional volunteers with their years of
exposure, and mean concentrations of pesticide residues found in their blood samples
88 4.4.6 Mean concentrations and range of detected pesticide residues based on the gender
of agro-professional volunteers
90 4.4.7 Mean concentrations and range of detected pesticide residues based on the gender
of non-agro professional volunteers
92
V
Abbreviations
ADIs Acceptable Daily Intakes AMD Automated Multiple Development ANOVA Analysis of variance BPU Benzoylphenylurea CAC Codex Alimentarius Commission CCPR Codex Committee on Pesticides Residues CEDIs Cumulative Estimated Daily Intakes CI Chemical Ionization CV Coefficient of Variation DAD Diode Array Detector DAP Dialkylphosphate DBP Dibutylphosphate DCCA Dimethylcyclopropane carboxylic acid DCM Dichloromethane DDD Dichlorodiphenyldichloroethane DDE Dichlorodiphenyldichloroethylene DDT Dichlorodiphenyltrichloroethane DEDTP Diethyldithiophosphate DEP Diethylphosphate DETP Diethylthiophosphate DMDTP Dimethyldithiophosphate DMP Dimethylphosphate DMTP Dimethythiophosphate ECD Electron-Capture Detector EI Electron Ionization EPA Environmental Protection Agency eV Electron volt FAO Food and Agriculture Organization FCSs food Contact Substances FID Flame Ionization Detector FPD Flame Photometric Detector GC Gas Chromatography GCB Graphitized Carbon Black GC-MS Gas chromatography-Mass spectrometry GDP Gross Domestic Product HCB Hexachlorobenzene HCH Hexachlorocyclohexane HPLC High Performance Liquid Chromatography HPTLC High Performance Thin Layer Chromatography HS-SPME Headspace Solid Phase Micro Extraction IPM Integrated Pest Management LC Liquid Chromatography LC-ESI-MS Liquid chromatography-Electron Spry Ionization-Mass spectrometry
VI
LC-MS Liquid chromatography-Mass spectrometry LC-MS-MS Liquid chromatography Tandem Mass spectrometry LOD Limit of detection LOQ Limits of quantification m/z Mass to charge ratio MRLs Maximum Residue Levels MRM Multiple Reaction Monitoring MSD Mass Spectrometry Detector MSPD Matrix Solid-Phase Dispersion NCEAC National Center of Excellence in Analytical Chemistry ND Not detected NE Not Established NPD Nitrogen Phosphorus Detector OCs Organochlorines OFAS Organizations of Food Additive Safety OPs Organophosphates PBA Phenoxybenzoic acid PHI Pre Harvest Interval PNP Para-nitrophenol PPSGDP Punjab Private Sector Groundwater Development Project PSA Primary Secondary Amine RSD Relative Standard Deviation SD Standard deviation SIM Selected Ion Mode SPE Solid-Phase Extraction TLC Thin Layer Chromatography TPCY Trichloropyridinol tR Retention time UAE Ultrasonic Assisted Extraction UNEP United Nation Environment Program UV Ultra Violet WHO World Health Organization α– HCH Alpha Hexachlorocyclohexane β– HCH Beta Hexachlorocyclohexane γ– HCH Gamma Hexachlorocyclohexane δ– HCH Delta Hexachlorocyclohexane μ– ECD Micro Electron-Capture Detector
VII
ABSTRACT
The aim of present study was to assess pesticide residues in vegetables, fruits and
human blood samples in the selected region of Sindh province, Pakistan. The concentrations
of six pesticides were determined by gas chromatography coupled with mass selective
detector (GC-MSD) in locally produced vegetables purchased from wholesale markets. A
total of 200 samples of eight vegetables viz. cauliflower, green chili, eggplant, tomato, peas,
bitter gourd, spinach and apple gourd were analyzed for pesticide residues. The results
indicated that almost all samples were contained pesticides, only 39% contained pesticide
residues at or below maximum residue limits (MRLs), and 61% contained pesticide residues
above MRLs. From the six analyzed pesticides, carbofuran and chlorpyrifos were found
above to MRLs with concentrations ranging from 0.01-0.39 and 0.05-0.96 mg kg-1,
respectively.
A very sensitive analytical method for the determination of 26 pesticides in some
fruits based on solid phase extraction (SPE) cleanup was developed using gas
chromatography (GC) coupled with micro electron capture detector (μECD). The identity of
the pesticides was confirmed by gas chromatography mass spectroscopy (GC-MS) using
selected ion monitoring (SIM) mode. Ethyl acetate was used as a solvent for the extraction of
pesticide residues with assistance of sonication. For cleanup an octadecyl, C18 SPE column
was used. A linear response of μECD was observed for all pesticides with good correlation
coefficients (>0.9992). Proposed method was successfully applied for the determination of
pesticide residues in the orange, apple, and grape fruits. Average recoveries achieved for all
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of the pesticides at fortification levels of 0.05, 1.0 and 2.0 μg g-1 in analyzed fruits were
above 90% with relative standard deviations (RSD) less than 6%.
A market based survey was carried out to evaluate the level of 26 pesticides in some
commonly used fruits in Hyderabad region, Pakistan. Gas chromatography coupled with
micro electron capture detector was used to assess the levels of pesticide residues. Gas
chromatography-mass spectrometry (GC-MS) was also applied for the confirmation of
results. Out of total 131 analyzed samples, 53 (40%) were found contaminated with pesticide
residues while only 3 (2%) samples were exceeded the MRLs of some pesticides.
Chlorpyrifos and dieldrin were detected in almost all analyzed samples. Residues of
chlorpyrifos (1256 μg kg-1) and endosulfan sulfate (1236 μg kg-1) were found higher in
orange and apple samples, respectively.
To evaluate the pesticide residues in human blood samples, two districts of Sindh
Province i.e. Hyderabad and Mirpurkhas were selected. The volunteers of both districts were
divided in to four groups on the basis of their exposure period to pesticides i.e. Group A- 5
to 9 years, Group B-10 to 14 years, Group C-15 to19 years and Group D-above 20 years. Out
of total 188 volunteers, 145 volunteers (77.1%) were agro–professionals and 43 volunteers
(32.9%) were non–agro professionals. Chlorpyrifos, endosulfan, 1, 1, 1-trichloro-2, 2-bis (p-
chorophenyl) ethane (p-p–DDT) and parathion residues were detected in many samples. The
predominant pesticides found in blood samples of both districts volunteers were chlorpyrifos
(with highest mean concentration of 0.37 mg kg-1 in the D group of Mirpurkhas) and
endosulfan (with highest mean concentration of 0.30 mg kg-1 in the D group of Hyderabad).
The quantity of pesticide residues detected in some blood samples of agro-professionals were
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found to be at the alarming level. The results provided important information on the current
pesticide contamination status of some commonly used vegetables and pointed an urgent
need to control the use of some excessively applied and potentially persistent pesticides, such
as carbofuran, chlorpyrifos and endosulfan. The findings of this study provided important
data about contamination of pesticide residue in some fruits sold in Hyderabad, Pakistan, and
recommended that monitoring studies should be expanded to other fruits grown in different
agro climatic regions, which may serve as basis for future policy about the standards and
quality control of pesticides.
Chapter 01
INTRODUCTION
1
Chapter-01
INTRODUCTION
1.1 Pesticides and their classification
Generally, any natural or synthetic chemical substance or a mixture of substances
which could control or repel any pest such as weeds, insects or fungi etc is recognized as
pesticides. There are many pesticides are available in the markets with different formulations
from different manufacturers in the form of emulsifiable concentrates or solids like dust,
grains, soluble powder, or wettable fine particles. Commonly, commercial formulations are
often diluted with water before use to improve pesticide withholding and absorption
capability of leaves or shoots. On the basis of application, pesticides are classified in to many
classes which may be herbicides, applied to kill weeds and other plants grown in places
where they are not needed; insecticides, used to destroy insects and other arthropods; and
fungicides used to eradicate fungi. Other kinds of pesticides are acaricides, nematicides,
molluscicides, pheromones, plant augmentation regulators, repellents, and rodenticides.
Several chemical substances have been introduced by many manufacturers to control pests
from the agricultural farms. Initially, inorganic compounds such as arsenic, sulfur, mercury,
and lead were employed. In 1939, the innovation of dichlorodiphenyltrichloroethane (DDT)
as an insecticide by Paul Müller caused a great blow in the management of pests and very
soon its usage was spread all over the world.
2
1.2 Applications of Pesticides
Improper use of pesticides is potential health risk to consumers. But every year pests
demolish nearly half of the world's food crops. Hence, the intention to fulfill the
requirements of food globally; the application of pesticides is indispensable to protect each
crop to increase the per acre yield. However, unsystematic and indiscreet employment of
pesticides has caused extensive contamination of foodstuffs with pesticide residues
(Agnihotri, 1999). Pesticides are imperative for farmers in struggle to fight with pests and
upgrade the economy of the country. After twenty years of earliest pesticides application
(Carson, 1962), it was declared that pesticide residues are associated with cancer threat
(UNEP, 1993). According to Pimentel (1995) and FAO (2002), 2.5 million tons of pest
repellent chemicals are being utilized across the world per annum and increasing with the
passage of time. Thus, proper use of pesticides infect improves the availability of foods by
declining the cost. Numerous controls, both cost-effective and regulatory are employed to
persuade the sensible use of pesticides.
Nowadays, application of pesticides is compulsory in modern cultivation to enhance
the productivity, eliminating pests and as well as diseases that spoil vegetables and fruits
(Juraske et al., 2007/2008/2009). More than thousand compounds are being recommended
for agricultural crops in order to control unwanted moulds, insects and weeds (Ortelli et al.,
2006).
The main reason of the poisoning and death cases related to pesticide residues are due
to inappropriate handling practices of pesticide and use of excessive poisonous pesticides by
the farmers. According WHO (1990); and FAO (2000) more or less 3 million people got
poisoned and 0.2 million expired per year worldwide due to inappropriate use of pesticides.
3
The problems are swear in developing and under developed countries because people related
to the agricultural farming are not so much familiar with proper application and selection of
specific pesticides for the particular crops (Wilson and Tisdell, 2001; Sankararamakrishnan
et al., 2005).
1.2.1 Applications of Pesticides in Pakistan
The issue of pesticide residues in fruits and vegetables is an important concern in
many countries as well as in Pakistan. The application of pesticides on fruits and vegetables
is common practice in Pakistan since last few decades. In 1954, about 254 metric tons of
chemicals related to the pesticides and agricultural sector were imported (Tariq et al., 2007),
and in the era of 1960-70s utilization of pesticides was reached above 7,000 tons per year. As
the imports of pesticide transferred to private sector in 1980s, the consumption of pesticides
was enormously raised to 14,607 and 31,893 metric tons in the decades of 1980-89 and 1990-
99, respectively (Feenstra et al., 2000; Economic Survey of Pakistan, 2005–2006). In the last
decade 2000-2010, a little decrease in the consumption of pesticides was reported as 27,995
metric tons (Economic Survey of Pakistan, 2009–2010). For the duration of 1980-1990, huge
quantities of pesticides were used in the farming areas of Pakistan. The companies of
pesticide marketing annoyed the farmers to apply pesticides more than to their suggested
dosages for different crops through media advertising. That might be one of the reasons of
high concentrations of pesticides bring into being in a variety of crops (Tariq, 2005).
In accordance with PPSGDP (2002), probably over one hundred and eight (108)
varieties of insecticides, thirty nine (39) varieties of weedicides, thirty (30) varieties of
fungicides, five (5) varieties of acaricides and six (6) different varieties of rodenticides were
4
utilized in the Pakistan. From the total consumption of pesticides in country, about one fourth
(27%) were used on vegetables and fruits (Hussain et al., 2002). Agriculture is one of the
main supports of Pakistan’s economy and contributes approximately 25% to GDP including
the production of vegetables and fruits (Economic Survey of Pakistan, 2003-2004). Pakistan
also exports a large quantity of vegetables and fruits to the Gulf nations and many other
countries. The share of foodstuff is about 13.2% in whole export business including fruits
(Anon., 2008). Regrettably, the production of both vegetables and fruits is significantly
condensed by invasion of a range of pests, and caused about 30 to 40% losses to the final
yield and sometimes the losses reached up to the height of 60 to 70% (Salim, 1999).
In a country like Pakistan, the application of pesticides has become inevitable to
uphold and improve existing stage of harvest production by shielding the crop from pests.
The climate of Pakistan as being a sub-tropical countryside, observes varying temperatures
and humidity profile throughout the year, which conveys a vast range of pests to be tackled.
A number of pests are found to assault multiple objects (a range of crops) and have been
attained resistance from prolong application of common pesticides. This threat put in force
the cultivators to select newer variety or higher amounts of the existing ones leading into the
greater exposure because of widespread use in agricultural and environmental pest control
(Fleming et al., 1999). The levels of pesticides use in Pakistan is lower than the developed
countries, but because of lack of education or low literacy rate , ineffective legislation, lack
of technical know-how about handling and unawareness about harmful effects of pesticides
among farming community, use of pesticide is not being properly regulated. Due to lack of
education, awareness and general information with regard to the use of pesticides from
government organizations/agencies, farmers are suffering from the ill effects of pesticides
5
during improper handling, disposal and especially when they are not covered with persona
protective equipments. Mostly the farmers rely on the use of synthetic pesticides. Although,
majority of them know that these pesticides are dangerous chemicals and hazardous to their
health but still they are using frequently to get more yields from their cultivated lands.
However, they are completely unaware to integrated pest management (IPM) approach.
1.3 Toxicity and Potential Health Effects of Pesticides
Pesticides, well-known in the agriculture sector, are the mainly reasonable and
economical approach used to manage insects and pests, although they are the chief
contaminants of our atmosphere and are highly toxic to non-target living beings. The spray-
workers or farmers, during the moments of applying pesticides by spraying on crops, as well
as during mixing and handling are openly exposed to pesticides. In addition, they may also be
exposed to pesticides by means of air, contaminated soil, drinking water, intake of food and
smoking at place of work. In general, pesticides may be proficiently absorbed by the
ingestion, inhalation as well as penetration through the skin. The incidences of poisoning
depend on the rate of pesticide absorption (Nicholas and John, 1994). Various pesticides
cause considerable small and long-lasting health risks (WHO, 1990), along with extensive
environmental indulge/pollution (Conway and Pretty, 1991). Pesticides are well-known to
upset the physiological and biochemical activities of lymphocytes as well as erythrocytes
(Banerjee et al., 1999). By the effects of pesticide exposure the health risks include a chain of
chronic end-points including neurotoxic (Kamel and Hoppin, 2004), cancer (Settimi et al.,
2003; Alavanja et al., 2004), developmental (Colborn, 2006), immunotoxic (Galloway and
Handy, 2003), reproductive system (Garcia et al., 1999; Yucra et al., 2006), endocrine
6
(Barlow, 2005) and neurobehavioral effects (Amr et al., 1993). Thus, the terrific usage of
pesticides has promoted toxicological studies in spraying community.
In contrast to many countries which developed and introduced legislations for the
safety of consumer's healthiness from threat of toxic pesticides, there is no such policies have
been imposed in Pakistan, might be due to the unavailability of enough data and sources on
the current status of pesticide residue in agricultural products in the countryside. In Pakistan,
more than 47 scientific studies were conducted during the last 40 years on the determination
of pesticides level in many matrices like water streams, soil dust, crops and human biological
fluids (blood, serum, urine). No any nationalized program has initiated for monitoring of
pesticide in vegetables. Only in Punjab province a study was conducted in detail on the
ground water for pesticide analysis (PPSGDP, 2002). Effects of pesticide residues have been
described in feed, milk, fruits, cottonseed, vegetables and in the meal of fish at different
periods all through the countryside (Masud and Farhat, 1985; Cheema and Shah, 1987;
Parveen and Masud, 1988a, b; Masud and Hasan, 1992; Parveen et al., 1996, 2004, 2005;
Hussain et al., 2002; Munshi et al., 2004; Saqib et al., 2005). With exceptions of some
monitoring studies taken out at different intervals throughout the countryside (Masud and
Hassan, 1995; Tahir et al., 2001; Hussain et al., 2002 & 2004; Parveen et al., 2004 & 2005;
Ahmad, 2004; Anwar, et al., 2004; Hassan, et al., 2007; and Tahir et al., 2011), no broad and
comprehensive studies have been carried out to investigate the residues of pesticide in fruits
and vegetables in the country.
7
1.4 Levels of Pesticides in Food and Food Safety Aspects
On one side, pesticides are very useful to increase harvest productivity, while on the
other side, these may lead to some drawbacks in shape of pesticide residues which is
potential health risk to their end users (Conacher and Mes., 1993; Nieto et al., 2009; Nia et
al., 2009). Therefore, pesticides are supposed to be controlled at the level as minimum as
possible due to their relative toxicity to the environment (Jiang et al., 2009; Mayank and
Ajay, 2007). Investigation of pesticide residue levels in food commodities is a main concern
of many researchers to evade possible risks of toxicity to human health (Osman et al., 2010).
Additionally, use of high doses of pesticides lead to the contamination of their products
resulting to potential risk for the consumer’s health.
Therefore, governments and private organizations of international level have
established maximum residue levels (MRLs), which usually guide to control the amount of
pesticides in foods. Initially, the plan to adjust pesticides residues to harmless points was set
up via the Expert Committee on Food Additives of joint FAO/WHO in 1955, and for the
implementation of joint FAO/WHO Food Standards Programs, a commission was established
in 1964 named as Codex Alimentarius Commission which comprises of 120 member nations.
A subsidiary body Codex Committee on Pesticides Residues (CCPR) of Codex Alimentarius
Commission counseled the entire matters linked to pesticide residues, and the primary goal of
this body is to form Maximum Residue Limits (MRLs) as to guard the health of consumer
even as make easy global trade. MRL for residues of pesticide correspond to the highest
concentration of that residue (which expressed in mg/kg) specifically and legally permitted in
an appropriate food item. The founding of MRL is based on excellent non violating farming
practice data on food derived as of commodities (Nasreddine & Parent-Massin, 2002).
8
Additionally, as component of the pre-market notification practice for food contact
substances (FCSs), the organizations of food additive safety (OFAS) are on the way for
developing and making freely available database of cumulative estimated daily intakes
(CEDIs) as well as acceptable daily intakes (ADIs) meant for a large number of FCSs.
The database mentioned above, is referred to as the CEDI/ADI database
(http://www.health.gov.au/internet/main/publishing.nsf/content/ocs–adi-list.htm).
Due to the persistency in the environment, the majority of the pesticides are no longer
permissible to be use in many countries including Pakistan, but some developing countries
still allow their use in agriculture and public health. Besides their affirmative effects,
employment of pesticides poses health-risk to consumers when keep hold of in the form of
residues in or on fruits and vegetables (Bolognesi & Morasso, 2000). Residues of pesticide
possibly found in processed goods for example juices of fruits, which are usually consumed
the same as soft drinks, chiefly by children. So, pesticides ought to be restricted at optimum
level owing to their high toxicity to the surroundings and human health (Jiang et al., 2009).
Pesticides are persistent in nature, but due to different chemical properties, every pesticide
has a different withholding age, drift period, waiting stage or pre harvest interval (PHI),
which may be termed as the minimum number of particular days needed to drift, among the
time of last concluding application of pesticide and harvest, for residues to reduce below the
tolerance limit set up for that harvest. PHI could be different from pesticide to pesticide and
from crop to crop. After the lapse of withholding period, the food products can only become
safe for consumption. Due to unawareness and be short of education, the farmers of our
country without taking into account the withholding period picked/harvested the treated fruits
and vegetables.
9
Variety of pesticides is used in current agricultural practice through which mostly
applied are organophosphates (OPs), carbamates and pyrethroids. While, organochlorines
(OCs) have been banned on account of prolong persistent nature, toxicity plus
bioaccumulation into the environment (Molto et al., 1991). In fact, as compared to the
organophosphates, carbamates and pyrethroids are less in persistency but the knowledge of
withholding periods for even less persistent insecticides becomes important particularly in
veggies and fruits since these crops are pulled out/gathered soon later than the application of
pesticide. The threat of pesticide residues contamination in foods is become a reason of
worry for almost every one and everywhere worldwide. Because of the relative toxicity of
pesticides, many developed countries have established regular monitoring programs which
deal with the determination of height of contamination in different food goods and also
determined those feasible circumstances in which pesticide residues exceeds through their
allowed maximum residue limits (MRLs) caused by wrong farming practices. In crops, the
excessive levels of pesticide residues from their tolerance limits at harvest are a cause of big
concern internationally and nationally. Therefore, the problem of pesticide residues in foods
has received a good deal of attention globally.
1.5 Analysis of pesticide residues in vegetables, fruits and human blood samples
Worldwide, a range of products of different pesticide groups have been examined for
their toxic end points. Biological examinations regarding pesticide exposures could be
conducted by investigating whole main compounds or their metabolites in urine, serum,
whole blood, or plasma (Aprea et al., 2002). The levels of some organochlorine and
organophosphorus pesticide residues were detected in blood samples of school children
10
(Mohammed et al., 2001), which prompt the adult studies in the openly exposed spray
personnel. A lot of efforts have been done on the determination of residues of toxic pesticides
and its growing effect on humans in the well developed countries. Such as, the residue levels
of DDE, DDT and HCH have been uncovered to generate dangerous effects in persons
(Kohan et al., 1994). The occurrence of pesticide residue in an urban and two rural
populations reported in Portugal (Cruz et al., 2003). In Pakistan, the information on pesticide
residues contamination in human blood and tissues is extremely narrow. On the other hand,
occurrence of pesticide poisoning has been reported and there are a number of reports from
hospital and community studies, which illustrates that pesticides account for a huge
percentage of acute poisoning cases in the country. In combination to acute poisoning,
chronic poisoning is also general. In few studies on accumulation of pesticide residues in
blood and tissues, 70 to 100% of the people were found positive (Feenstra et al., 2000). In
Pakistan, existence of pesticide residues in the blood has been reported in some studies
(Ansari et al., 1997; Naqvi and Jahan, 1999; Khan et al., 2000; Azmi et al., 2005& 2006;
Soomro et al., 2008; Hayat et al., 2010). Some work was reported in Sindh and other
provinces of Pakistan by Tariq et al., (2007); Zia et al., (2009), which recommended the
requirement for more studies to observe the exposure of highly hazardous pesticides via
pesticide residues detection and their effects on cholinesterase enzyme among the spray
personnel.
11
1.5.1 Contemporary analytical methods and techniques for pesticide residues in food and human biological fluids
For the analysis of pesticide residues in fruits and vegetables most frequently used
technique is gas chromatography (GC) with diverse selective detectors such as nitrogen-
phosphorus detector (NPD) (Ueno et al., 2001), flame photometric detector (FPD) (Ueno et
al., 2003) and electron-capture detector (ECD) (Gelsomino et al., 1997; Ueno et al., 2004).
Several methods use gas chromatography attached with mass spectrometry (GC-MS) (Gamo´
n et al., 2001; Lehotay et al., 2005), by reason of the opportunity of confirming pesticide
identity in these matrices. For non-volatile and/or thermally instable and/or polar pesticides
and metabolites, liquid chromatography (LC) with diode array detector (DAD) (Lagana et al.,
1997) and fluorescence detection (Fillion et al., 1995) has been also engaged. Liquid
chromatography in combination with mass spectrometry (LC–MS) (Pous et al., 2001; Pico´
et al., 2000) or with tandem mass spectrometry (LC–MS–MS) (Frenich et al., 2004; Mol et
al., 2003) has recently turn out to be a commanding analytical technique for the identification
and quantification of pesticide residues in vegetables and fruits.
The monitoring of pesticide residues in biological samples usually requires the
application of cleanup steps to eliminate interferences and reduce the detection limits of the
procedures. A number of methodologies are exists for the preparation of samples prior to
investigation of pesticide residues from biological as well as environmental samples. In
plenty of cases, methods use typical practice for extraction that can be time as well as solvent
consuming and prone to experimental inaccuracy. Solid-phase extraction (SPE) provides
superior selectivity, cleaner extracts, and good reproducible outcomes as compare to liquid-
liquid extraction. Various clean-up techniques of different complexity have been reported.
12
Dealing with sulfuric acid has been extensively used in combination with solvent extraction
by means of hexane (Otero et al., 1997) or acetone-petroleum ether (Waliszewski and
Szymczynski, 1991). In a few cases, in combination with solid-phase extraction (SPE)
sulfuric acid has been also applied using Florisil (Gill et al., 1996) or C18 (Pauwels et al.,
1999) as adsorbents. Previously, most of the methods used to determine pesticides and their
major metabolites in human serum or urine samples employed gas chromatography coupled
with electron capture detector (GC-ECD) (Cruz et al., 2003), gas chromatography-mass
spectrometry (GC-MS) (Vasilic et al., 1999; Weiyue et al., 2010; Hayat et al., 2010), high
pressure liquid chromatography coupled with ultraviolet detector (HPLC-UV) (Futagami et
al., 1997; Azmi et al., 2006), liquid chromatography-ionspray-mass spectrometry (LC-MS)
(Kawasaki et al., 1992; Itoh et al., 1996) or liquid chromatography tandem mass
spectrometry (LC/MS/MS) (Araoud et al., 2010). A few of these methods comprises of
laborious and time consuming extraction and dervitization protocols which are difficult to
adopt in emergency cases of severe poisoning. Therefore it is imperative to develop selective,
reliable and rapid methods that can be helpful in the identification and quantification of as
many pesticides as possible in human biological fluids.
There is a crucial need to do organized research for the determination of pesticide
residues in fruits and vegetables as to deal with the current global market. For Pakistan, it is
mandatory to synchronize the food regulations by means of Codex Alimentarius Commission
(CAC) principles by obliging parallel strategy for act out pesticide residue limits and
standards. Tarnishing of food stuffs by pesticide residues could be prohibited in the course of
food directives as has been done in developed countries. The improper use of pesticides has
show the way to terrific financial losses and dangers to human health.
Chapter 02
LITERATURE REVIEW
13
Chapter-02
LITERATURE REVIEW
2.1 Assessment of pesticide residues in vegetables and fruits
To control pests, chemical substances have been used by human from the beginning
of agriculture. Now they are extensively applied on fruits, vegetables and other crops on a
massive scale. The hazards of these pesticides in the form of toxic residues may possibly
reduce if they used in accordance with Good Agriculture Practice. Through regular
monitoring procedures, the data about the contamination levels of noxious residues occurring
in foodstuffs could be obtained. Monitoring surveys regarding pesticide residues are not only
helpful into providing the data, but serve to point out whether or not the ethics of good
agriculture practice are being followed as well. In numerous countries of the globe analytical
laboratories have ascertained to examine the levels of pesticide residues in vegetables, fruits
and supplementary foodstuffs (Dogheim et al., 1999; Dogheim et al., 2001). Nowadays,
consumers as well as legislators mutually have shown curiosity greater than before in the
protection of food stuffs from residues of pesticides.
During 1990-1992, researchers Masud and Hassan (1995) conducted a survey by
gathering samples of vegetables and fruits from different farmer’s fields and also from main
commercial fruit market of North West Frontier Province (NWFP), Quetta/Pishin the districts
of Balochistan and Islamabad. The result shows among the total 300 analyzed samples, 121
samples (40%) were found contaminated with different pesticides in varying amounts. In 38
samples the residues were found above to the MRLs in accordance with FAO/ WHO, and all
of the other remaining food samples were found free from any detectable pesticide residues.
14
A study was conducted by Dethe et al., (1995), on the residues of pesticides
(dimethoate, endosulfan, monocrotophos, cypermethrin and mancozeb) which are most
commonly applied on vegetables cultivated in India. In 33.3% samples of tomatoes, the
residues of monocrotophos, endosulfan and dimethoate were found at detectable levels. Out
of all samples, 14.3% samples of okra residues of endosulfan were found present. 73.3% of
brinjal samples contained residues of cypermethrin, endosulfan, fenvalerate, dimethoate,
quinalphos and monocrotophos. In 88.9% of cabbage samples residues of fenvalerate,
dimethoate and endosulfan were found and in all of the cauliflowers samples (100%)
residues of monocrotophos, cypermethrin, dimethoate, endosulfan and febvalerate were
found. While, levels of all of the residues found were below the prescribed MRLs.
During a research study, residues of organochlorine and organophosphorous
pesticides have been determined in food collected from Egyptian local markets (Dogheim et
al., 1996). They examined some citrus fruits, potatoes and fish for the presence of
organochlorine and organophosphorous pesticide residues which were gathered from the
local markets of Egypt. Compliant with Maximum Residue Limits (MRLs) the residues of γ-
hexachlorocyclohexane were found above in eight (8) samples of potatoes and in two (2)
samples DDT also found exceeded the limits. The presence of fenitrothion in potatoes with
the highest residue levels (3.8 ppm) might be as a result of its repeated pre and post harvest
use. All organochlorine pesticides were found below to their MRLs.
Reddy et al., (1998) evaluate some vegetables for the presence of pesticide residues
collected at harvest from farmer’s fields around three districts Hyderabad, Srikakulam and
Guntur of Andhra Pradesh during the period of 1992-93. The vegetable samples Brinjal,
spinach and chillies collected from Hyderabad district were found above the MRLs of 0.25
15
ppm in respect of HCH and contained residues at levels of 0.588, 0.250 and 1.513 ppm,
respectively. In tomatoes, chillies and brinjal the residues of DDT were found below the
MRLs and residues cypermethrin were also detected below the MRLs in tomatoes. In
vegetables (cucumbers, chillies, okra and bitter gourd) collected from the district Guntur, the
residues of HCH were found below the MRLs and had levels of 0.412, 0.308, 0.271, and
0.367 ppm respectively. The only pesticide which detected above MRLs was mancozeb
found in bitter gourd at level of 2 ppm. The residues of HCH, DDT, aldrin, dieldrin,
endosulfan and methyl parathion had low levels in the vegetable samples gathered from the
district Srikakulam and found below the MRLs.
Ahuja et al., (1998) examined vegetable samples cauliflowers, cabbages, brinjal,
cucumber, tomatoes, okras, field beans and French beans for the assessment of residues of
HCH and its isomers, cypermethrin, dimethoate, endosulfan, quinalphos, monocrotophos,
fenvalerate and carbendazim (fungicide). Most of the analyzed samples were found
contaminated by the detectable residues of endosulfan, HCH with its isomers,
monocrotophos, dimethoate, carbendazim and quinalphos.
Dogheim et al., (1999) monitored some Egyptian fruits and vegetables for the
residues of organophosphorous, dithiocarbamtes and few synthetic pyrethroid pesticides
commonly used in Egypt, in addition to those organochlorines pesticides which had been
termed as persistent and prohibited to use on foodstuffs several years ago. From 8 local
markets, total of 397 fruit and vegetable samples were collected and analyzed for 52
pesticides. Out of total 397 samples, there were 42.8% were found positive and contained
residues at detectable levels, out of which 1.76% found above to the MRLs. Residues of
organochlorine pesticides were not found in most of the samples. Cauliflower, guava and
16
onion samples were found free from any pesticide residues otherwise among all samples, 65
grape samples contained 11 pesticide residues, 22 samples of strawberry contained 10
pesticide residues and 62 samples of tomato contained 13 different pesticide residues. The
most frequently detected pesticide was dithiocarbamtes. Out of 98 samples residues of
dithiocarbamtes were found in 70.4% and only one sample of grape contained residues above
to the MRLs. Samples of eggplant and carrot were found contaminated by the trace amounts
of residues of pp’-DDT and pp’-DDE pesticides.
Adeyeye and Osibanjo (1999) worked out to monitor the actual residue intensity of
some organochlorine pesticides in raw fruits, tubers as well as vegetables collected from
Nigerian markets. Aldrin, HCH, and total DDT were identified in samples of fruits in 38, 77
and 30% of whole samples, correspondingly. Residues of whole HCH, HCB, total DDT and
aldrin were found in samples of vegetables in 95, 53, 50 and 30%, respectively, of total
samples. In tuber samples, residues were found such as Aldrin and dieldrin (98), total HCH
(79), and total DDT (49%) of total samples. All other pesticides were found under their
MRLs.
Bolles et al., (1999) conducted a market basket survey to evaluate the variety of
foodstuffs (fruits, fruit juices, vegetables, milk, ground beef etc.) for the presence of residues
of insecticide chorpyrifos, gathered via two hundred (200) grocery supplier stores across the
United States during a 12 month period. About 90% of the samples were found free from any
measurable concentrations of chlorpyrifos and all of the observed residues were found
underneath the prescribed MRLs.
Ripley et al., (2000) worked out on the study plan to investigate the pesticide residues
present in the Ontario-produced foods (vegetables and fruits) during 5-year period 1991 to
17
1995. Total of 802 fruit samples and 1536 vegetable samples were analyzed. The result
shows that out of overall 31.5% of the analyzed samples had no any detectable pesticide
residues, on the other hand 68.5% of the analyzed samples contain one or more residues. In
comparison between fruit and vegetable samples, more fruit samples (91.4%) contain
detectable residues and about 56.6% of vegetable samples were found contaminated by
residues of pesticides. The most frequently pesticides found in this study were endosulfan,
captan, the dithiocarbamate fungicides, phosmet, iprodione, azinphos-methyl and parathion.
Andersen and Poulsen (2001) conducted a Danish pesticide monitoring program for
fruit and vegetables to evaluate maximum residue levels and to check the residue levels to
assess the exposure of pesticide on the Danish population. From all of the samples, 2% were
organically grown and 300 were frozen products. Of the samples, 35% were of Danish origin
and all other 65% were derived from other countries. 54% of the fruit samples were contain
detectable levels of pesticide residues but in vegetables only 13% were found contaminated.
In 4% of all fruit samples levels of pesticide residues were found above MRLs and only 1%
of all vegetable samples found exceeding MRLs.
Tahir et al., (2001) conducted a study for the determination of pesticide residue levels
in vegetables and fruits collected from the market of Islamabad, Pakistan. In apple, banana,
brinjal, cauliflower and arvi residues of dimethoate were evaluated in the quantity of 0.032,
0.110, 0.004, 1.80 and 0.13 mg/ kg, respectively. The residues of Fenvalerate were
determined in the quantity of 0.010 mg/kg in apple and chlorpyrifos was determined having
concentration of 0.004 mg/kg in brinjal.
A monitoring survey of pesticide residues has been conducted during a 5-year period
(April 1995-March 2000) by Akiyama et al., (2002). For analysis, total 765 samples
18
including 478 domestic and 287 imported collected from Hyogo Prefecture, Japan. The main
objective of the study was to encourage consumer protection by excluding the food illegally
containing pesticide residues from markets. Taken as a whole, 32% of imported samples and
51 % of domestic had no detectable residues. In 146 (51%) of imported samples and 152
(32%) of domestic multiple residues were found. 3 samples, diazinon in chrysanthemums,
bitertanol in bananas and dieldrin in cucumbers found violating the MRLs.
Mukherjee (2003) monitored 30 insecticides, 15 organochlorines and 6
organophosphorous insecticides, 9 synthetic pyrethroids and 2 herbicide pesticide residues in
vegetable samples collected from in and around Delhi. The result of study indicates that
though entire of the vegetable samples were found contaminated, only 31% of the samples
had levels of pesticide residues above to the prescribed MRLs.
A study was carried out for the determination of dithiocarbamate pesticide residues in
food samples including strawberry, potato, papaya, apple, orange, banana, dry beans, tomato
and rice, gathered via local market of the Federal District, Brazil (Caldas et al., 2004). The
methodology used in this study was comprises to determine dithiocarbamates in foodstuffs,
involved the investigation of CS2 produced following the hydrolysis of compound present in
the analyzed sample. Out of total 520 samples, CS2 found in 60.8% of the samples with
detectable levels of ≥ 0.10 mg/kg, with the highest concentrations (equal to 3.8 mg/kg) in
papaya, strawberry and banana. Only 1 sample of dry bean contained measurable levels of
the fungicides and no any of the residues were observed in the samples of rice. Measurable
levels of residues were found in 50–62% of the analyzed samples of the pulp of banana,
oranges and papaya (with seeds).
19
Chang et al., (2005) collected the samples of vegetables and fruits from 4 regions of
Taiwan to monitor the pesticide residues and to compare the statistics of pesticide residue
data in 4 regions. Samples of fruits and vegetables (1999) collected from different super
markets and traditional markets in central Taiwan (1999-2004) and examined for the analysis
of 70~79 pesticide residues. For central Taiwan (1999-2004), Only 4 samples (0.2%, of
1999) were found exceeding the MRLs of pesticide residues and in all other 99.8% of the
samples pesticide residues were either not present or compliant with the MRLs. Pesticide
residues were detected in 13.9% of the 9955 samples collected from the whole Taiwan
(1997-2003) and only 1.2% were found exceeding MRLs.
Góralczyk et al., (2005) worked out on an efficient system established by Poland a
member state of European Union. Main objectives of this program in case of pesticide
residues is to take out investigation and official control of different verities of foods
consecutively to verify fulfillment with MRLs system by Polish Regulation. The
investigation of food samples was made in sixteen incorporated local laboratories of National
Sanitary Inspection on yearly developed plans of sampling. In the year 2004, total 868
samples have been analyzed collected from retail and wholesale markets. The analyzed
samples were comprises of 67% vegetables and fruits, and 14% of the total were baby foods.
All of the samples get monitored for more than fifty pesticides during 2004; MRLs exceeded
in fourteen samples (2%) of vegetables, cereals and fruits. The detected pesticide residues in
violated samples were of hexachlorobenzene, benomyl group endosulfan, maneb group,
methyl bromide, and mecarbam.
Blasco et al., (2006) analyzed 160 oranges and tangerine samples gathered by way of
an agricultural supportive of the Valencian Community (Spain) for the determination of
20
residues of hexythiazox, imidacloprid, bitertanol, imazalil, carbendazim, methiocarb,
thiabendazole, methidathion, pyriproxyfen and trichlorfon. The residues of trichlorfon,
pyriproxyfen, bitertanol and thiabendazole were not found in any sample. In the samples (52)
which were found positive for pesticide residues, hexythiazox was found in twenty two
(42.3%) within the concentration of 0.02–0.05 mg/ kg, imidacloprid observed in five (9.6%)
within a range of 0.02–0.07 mg/ kg, carbendazim in 27 (51.9%) within the quantity of 0.02–
0.04 mg/ kg, imazalil in 8 (15.0%) in the range of 0.02–1.2 mg/ kg, methiocarb detected in 1
(2%) at a concentration of 0.02 mg/ kg and methidathion found in 17 (32.6%) in the range of
0.06–1.3 mg/ kg. No sample was found exceeded the MRLs.
Bai et al., (2006) investigated the residues of eight organophosphorus pesticides in
vegetables, fruits and cereals gathered from the markets located in Shaanxi area of China. Of
200 samples, 18 samples contained 5 organophosphorous pesticide residues including
dimethoate, parathion-methyl, pirimiphos-methyl, parathion and dichlorvos in the quantity
ranging from 0.004 to 0.257 mg/kg. Only the mean levels of parathion in vegetables and
dimethoate in fruits were found exceeding through the MRLs, permissible by the Chinese
Health Ministry. Overall other detectable pesticides were found below to their MRLs.
Sadło et al., (2007) conducted a research work to investigate the presence of pesticide
residues in food samples (vegetables and fruits) during the period of 2004-05. Pesticide
residues were analyzed in 747 samples of 39 different fresh fruit and vegetables. The highest
residues of pesticides found were bupirimate, captan, ethylenebisdithiocarbamate,
tolylfluanid, procymidone and chlorpyrifos with concentrations of 2.19, 1.82, 1.6, 1.44, 1.19
and 1.01 mg/kg, respectively. In only 3.6% of analyzed samples, residues were exceeded
national MRLs.
21
Knežević and Serdar (2009) worked out on a study to examine residues of some
pesticides in foods marketed in Croatia. 240 samples of fresh fruits and vegetables import
and domestic production were examined. Of 240 samples, pesticide residues were found in
25.8% of analyzed samples at or below MRLs, in 66.7% samples no residues were found and
in 7.5% of the analyzed samples residues were found above to their MRLs. Imazalil was the
pesticide found most frequently (found in 35 samples) and after that chlorpyrifos was also
found frequently (found in 24 samples).
Tahir et al., (2009) conducted a study to evaluate the health hazards faced by the
consumers through probable ingestion of noxious chemicals contained in the fruits and
vegetables. Samples of different fruits and vegetables including tomato, apple and cucumber
were collected from 4 main markets of Lahore and analyzed for the determination of 9
pesticide residues. After the analyses, the results illustrated that most of the samples did not
have any residues of the 9 selected pesticides and only 2 tomato samples had detectable
residues of imidacloprid pesticide, which were within the prescribed limits set by the WHO.
Osman et al., (2010) monitored 23 pesticide residues in 160 vegetable samples
collected from 4 major super markets located in Al-Qassim region, Saudi Arabia. 89 out of
160 samples contained detectable levels of pesticide residues out of which 53 samples were
found above to the MRLs. Carbaryl followed by biphenyl and then carbofuran were the most
frequently found pesticides. Out of all vegetable samples, the most positive and violated
MRLs was found in cabbage (16 and 11 samples), after that carrot and green pepper (12 and
7 samples). The highest amount of pesticide residues were detected in lettuce of ethiofencarb
(7.648 mg/kg), followed by tomato which contained tolclofos-methyl with concentration of
7.312 mg/kg.
22
Tahir et al., (2011) monitored residues of pesticide of organophosphate (OP),
pyrethroid and organochlorine (OC) (i.e., dichlorvos, fenvalerate, dimethoate, methyl
parathion, fenitrothion, cypermethrin, endosulfan, deltamethrin, mevinphos, chlorpyriphos,
profenofos and dicofol) in 8 samples of fruit i.e., orange, apple, pear, guava, grapes, banana,
persimmon, and pear collected from the local markets of district Nawabshah, Sindh. Except
banana, all the fruit samples were found contaminated with pesticide residues and among
these only apple samples exceeded the MRLs of Codex Alimentarius Commission.
Srivastava et al., (2011) evaluated residues of 48 pesticides in vegetables including 10
synthetic pyrethriods, 13 organochlorines, 8 herbicides and 17 organophosphates. 20
vegetable samples including root, leafy, modified stem and fruity vegetables such as jack
fruit, onion, bitter gourd, french-bean, capsicum, colocassia, fenugreek seeds, pointed gourd,
spinach, carrot, potato, beetroot, radish, cauliflower, cucumber, brinjal, bottle gourd,
cabbage, okra and tomato has been collected from different markets. Out of total 48
pesticides, 23 pesticides were detected in all 60 analyzed vegetables with the range of 0.005-
12.35 mg/ kg. With the exemption of some vegetables such as cucumber, cabbage, radish,
cauliflower and okra all other vegetable samples were contained levels of pesticide residues
below to the detection limits or MRLs. The pesticides found above to their MRLs were Σ-
HCH, permethrin-II, dichlorvos, and chlorofenvinfos.
Farag et al., (2011) monitored 132 samples of fruits, spices, herbs and vegetables
gathered from the local Egyptian markets for pesticide residues. 45.45% of the samples
found free from contamination of pesticide residues. While, remaining 54.55% samples were
found contaminated with pesticide residues. Only 1 sample out of 132 analyzed samples
found violated the MRLs of the Codex Committee. The residues detected of six of the
23
pesticides in analyzed samples were considered to be carcinogens at different levels of
assurance.
2.2 Investigation of pesticide residues in human biological fluids (Blood, Urine)
A collaborated work of the National Human Monitoring Program of the U.S.
Environmental Protection Agency (EPA) with the National Centre for Health Statistics has
been done in the period of 4 years to assess the exposure of some selected pesticides
(organochlorine, carbamate, chlorophenoxy and organophosphorus) by examination of serum
and urine samples of general population (Murphy et al., 1983). Samples were collected from
64 locations all over the U.S, of persons aged 12-74 years. Following the examination of
blood serum and urine specimens, the preliminary results indicates that the general
population is being exposed to a few of these types of pesticides.
Monitoring of organochlorine pesticide residues in samples of human blood has been
done by Ansari et al., (1997). Blood samples were collected during 1995-96 from the
troubled volunteers of Multan division (Pakistan), suspecting dermal, inhalation or oral
exposure to heptachlor and endosulfan, either occupationally, or environmentally. In
comparison to the residues of heptachlor, endosulfan was found higher in all samples. In the
population of Multan the highest concentration of endosulfan residues was found as 90.29
g/kg and in Mailsi region the highest concentration was found as 82.14 g/kg, and lowest as
58.13 g/kg and 60.13 g/kg, respectively. However, residues of heptachlor had highest level as
12.978 g/kg and 9.997 g/kg, minimum as 0.37 g/kg and 1.23 g/kg, respectively.
24
Cruz et al., (2003) has worked out for the investigation of organochlorine pesticide
residues in human serum collected from two rural and an urban population of Portugal, to get
knowledge about the residual level of pesticides in Portuguese population. Out of total 12
pesticides, the residues of β-HCH, α-hexachlorocyclohexane (HCH), p,p’DDD and p,p’DDE
were found most frequently. Concentrations of p,p' DDE residues were ranged from
undetected to 43.5 μg/l and to 171.2 μg/l in both rural samples and from undetected to 390.5
μg/l in urban samples. The highest concentration level of α-HCH was 261.3 and 45.5 μg/l in
both rural samples and 114.4 μg/l in urban samples. Comparatively in all of the three
populations, the greater part of the results which were above the LOQ for p, p’ DDE were
found among the female sex.
Soomro et al., (2008) conducted research work to calculate the residue concentrations
of 4 pesticides including monocrotophos, cypermethrin, endosulfan and carbaryl in the blood
samples of pesticide spray-workers, as well as to monitor significant effects by analytical
means on serum cholinesterase level (p<0.001) through ANOVA. The concentrations of
pesticide residues detected in the blood samples of spray-workers were as: endosulfan (0.009
mg/kg), monocrotophos (0.005mg/kg), carbaryl (0.05mg/kg) and cypermethrin (0.08 mg/kg)
body weight.
Ingelido et al., (2009) carried out a human biomonitoring study which was aimed to
give baseline information on background exposure of the Italian common population to beta-
hexachlorocyclohexane (β-HCH) pesticide, which has been banned in the EU in 1978 and
progressively at a global level. In this study, 116 samples of blood serum were analyzed from
groups of subjects of both sexes from the common population residing in 3 Italian towns at
different latitudes. The residues of β-HCH were found in serum samples resulted to be
25
comprised between 1.64 and 300 ng/g fat, while median value of 18.0 ng/g fat and a 90th
percentile of 65.9 ng/g fat. The concentrations found are in line with those detected in nearly
all Western European countries.
Panuwet et al., (2009) monitored pesticide residues amongst the students of
secondary school located in Thailand, of age group twelve to thirteen (12, 13) years. The
urinary metabolites which are specific for pesticides were used as biomarkers of exposure for
a number of pesticides (synthetic pyrethroids, selected herbicides and organophosphorus
insecticides). There were 4 groups in which students were classified in accordance with the
parental livelihoods such as: merchants and traders (N=39), laborers (N=56), farmers (N=60)
and government and private employees (N=52). From Thai students, a total of 207 urine
samples were collected and analyzed for the determination of 18 specific pesticide
metabolites. The results illustrated that 14 metabolites were detected in urine samples, out of
which 7 metabolites were detected with a frequency of 17%. The metabolites which were
most frequently detected were para-nitrophenol (PNP), 2,4-dichlorophenoxyacetic acid (2,4-
D), 2-[(dimethoxyphosphorothioyl) sulfanyl] succinic acid (malathion dicarboxylic acid),
3,5,6-trichloro-2-pyridinol (TPCY; metabolite of chlorpyrifos), 3-phenoxybenzoic acid (3-
PBA; metabolite of pyrethroids). and cis- and trans-3-(2,2-dichlorovinyl)-2,2-
dimethylcyclopropane-1-carboxylic acids (c-DCCA and t-DCCA; metabolite of permethrin).
In comparison to other children, children of farmers had extensively higher urinary levels of
pyrethroid insecticide metabolites (p<0.05).
Determination of 14 organochlorine pesticides and comparison of their levels has
been done in the blood of 220 young males in Southern Spain (Carreño et al., 2007). Endrin,
Aldrin, methoxychlor, dieldrin, endosulfans, lindane, DDT as well as its metabolites were
26
identified. In 96% of serum samples detectable levels of p, p′-DDE were found, while in 65%
of blood serum samples remaining DDTs, o, p′-DDD were most commonly detected. In all
serum samples, measurable levels of endosulfan I or II and its metabolites (endosulfan-diol,
or -sulfate) were found, in which the metabolite endosulfan-diol was the most frequently
detected (92%) as compare to sulfate.
Hayat et al., (2010) analyzed blood samples of field workers involved in the pesticide
application at 3 different farms located in tahsil Mailsi; district Vehari (Punjab), Pakistan, for
the evaluation of pesticide residues. 27 field workers selected for this study (including 3
controls), were ranging from 16 to 50 years of age and having 1 to 9 years of pesticide
application practice were tested. In this study, blood samples were tested for the
determination of 383 pesticides, while only chlorpyrifos and pyributicarb were detected at
concentration level of 0.009 mg/l and 0.001 mg/l, respectively.
2.3 Analytical techniques and methodologies used for pesticide residues in fruits and Vegetables
The techniques and methods for the assessment of pesticide residues are continuously
revised and improved as the new concepts and conventional techniques arrived. Diversity in
structures, properties and vast variety of classes of pesticides has made it a tough job to
develop a method which covers the determination of all types of pesticides in variety of
sample matrices. A number of methods have been published on determination of pesticide
residues in various types of food stuffs comprises of three major steps, (1) extraction of
pesticides from sample matrices by using an organic solvent; (2) clean-up of extracts to
eliminate any interfering components present in the extracts other than pesticides; (3)
27
quantification of pesticide residues by means of different investigative techniques i.e. gas
chromatography (GC) coupled with different selective detectors, thin layer chromatography
(TLC), high performance or high pressure liquid chromatography (HPLC),
spectrophotometry , supercritical fluid chromatography, capillary electrophoresis and
immunoassay.
The selection of different solvents for extraction purpose is mainly depends upon the
properties of the pesticides to be extracted and detected, the type and nature of matrices from
which extraction take place and the method of analysis. For extraction of different pesticides
from fruits and vegetables, a variety of solvents such as petroleum ether, cyclohexane, ethyl
acetate, n-hexane, acetone and methylene chloride and their mixtures in different proportions
have been used. While, for more polar pesticides such as organophosphorus, and triazine
more polar solvents like acetonitrile, chloroform, methanol were found to be excellent.
Startin et al., (2000) and Fernandez-Alba et al., (2000) in their research found that for the
extraction of pesticide residues from vegetables and fruits, ethyl acetate proved to be an
excellent solvent in comparison to other solvents due to its high polarity, thermally labile and
less volatile compound.
Assessment of 251 pesticides and degradation products in vegetables and fruits
samples has been described by Fillion et al., (2000). For extraction, ecetonitrile was used
followed by a salting out step. For cleanup, in first step extract of acetonitrile passed through
solid phase extraction cartridge contained octadecyl (C18), and in second step the extract
passed through an aminopropyl cartridge coupled to a carbon cartridge for the removal of co-
extractives. The analysis was performed with the assistance of gas chromatography coupled
with mass selective detector (GC-MS) in selected ion monitoring mode (SI), and liquid
28
chromatography with fluorescence detection of N-methyl carbamates. Method was validated
for the analysis of a range of vegetables and fruits. Range of limit of detections (LODs) for
most of the compound was found between 0.02 to 1.0 mg/kg. Over 80% of the compounds
have a limit of detection ≤ 0.04 mg/kg.
In another method by Columé et al., (2001), multiresude screening of 25 pesticides
including 16 pyrethroids and 9 organophosphates was done on the basis of solid-phase
extraction (SPE). Pesticide residues were extracted by using n-hexane as a organic solvent
from the lyophilized samples by means of mechanical shaking and after separation of two
layers, organic phase which contained pesticides was aspirated into a continuous module
which made up of a laboratory-made silica column for preconcentration of analyte and clean-
up of sample matrix. Limits of detection (LODs) were approximately 1–10 ng/g with
exceptions for captan and lindane (30 ng/g). With the exceptions of bifenthrin and
deltamethrin, the accuracy measured for the quantitative determination in terms of average
percentage recovery of the 25 compounds in 8 different varieties of vegetables was 93 ± 3.
Fenoll et al., (2003) developed an easy multiresidue analytical methodology for the
assessment of different classes of pesticides in vegetables. Pesticide residues was extracted
with acetone and partitioned into ethyl acetate/cyclohexane. Analysis was done by using gas
chromatography coupled with nitrogen-phosphorous detector (NPD) and confirmation was
made by gas chromatography with mass spectrometry detection (GC-MS) in SIM mode.
Retention times and comparison of primary and secondary ions were used for the
identification of compounds. Limits of the detection and quantification for the studied
pesticides for the prescribed method varied from 0.1 to 4.4 μg/ kg and 0.4 to 14.5 μg/ kg,
29
respectively. A good linearity over the range assayed 50–1500 μg/ l, achieved for the
developed method.
2.3.1 Analysis of fruits and vegetables for pesticide residues
There are many techniques are used for the analysis of pesticide residues in fruits and
vegetables (Richter et al., 2001), including gas chromatography (GC), high performance
liquid chromatography (HPLC) and thin layer chromatography (TLC).
2.3.2 Application of Gas chromatography (GC) for pesticide residues in fruits and vegetables
For the assessment and monitoring of pesticide residues gas chromatography is
commonly used in fruits and vegetables as compared to all other techniques due to its short
time consumption, sensitivity and extensive range of applications. Gas chromatography has
the ability to assess the significant number of pesticide residues as well as their metabolites
in various environmental samples and food stuffs (Frost, 1996). By using different selective
detectors such as Electron capture detector (ECD), Nitrogen-phosphorous detector (NPD),
Flame photometry detector (FPD) etc, in gas chromatography analysis of multiple pesticide
residues could be done in short time and also reduces the several post-extraction cleanup
steps for the removal of interfering co-extracted components. The combination of mass
selective detector (MSD) with gas chromatography permits not only detection but also
confirmation of a wide range of pesticides in complex matrices.
Yu et al., (2000) developed a rapid gas chromatographic method for the determination
of 20 organochlorine pesticides in fruits, vegetables and oils. For extraction from fruits and
30
vegetables mixture of petroleum ether-acetone was used, while oils were extracted with
acetonitrile-hexane. The purification of extracts was made by using Florisil column with
ethyl ether-hexane or ethyl ether-petroleum ether as eluent in proportions of (15:85, V/V) and
(15:85, V/V), respectively. The analysis was performed by using wide bore capillary column
gas chromatography with electron capture detection (ECD). Results of the proposed method
showed satisfactory separation and detection of these organochlorine pesticides. The
recoveries of the proposed method were 83.2%-106.8%, limits of detection (LOD) 1.0-20.0
ng/g (S/N = 5) and the relative standard deviations (RSD) were 2.0%-9.5%.
Vidal et al., (2002) devised a new analytical method for the determination of 31
multi-class pesticide residues from about 8000 fresh fruit and vegetable samples using gas
chromatography coupled with tandem mass spectrometry (GC–MS–MS). Methylene chloride
was used for the extraction of pesticide residues. In a single run, optical and chemical
ionization modes were used for each pesticide. To avoid additional cleanup, carbofrit was
used in liner and combined with the selectivity of the detector. The limits of detection and
quantification calculated were typically were less than 1 ng/g which were more below the
MRLs established by European legislations. At two different fortification levels (n=10 each)
that ranged between 7 and 300 ng/ g (depending on the pesticide), the average recoveries
obtained in cucumber ranged between 71 and 119%. For all compounds the relative standard
deviation was less than 19%.
A new analytical method for the determination of 81 multiclass pesticide residues in
vegetables has been proposed by Arrebola et al., (2003). This method based on a rapid
extraction of the pesticide residues with methylene chloride and analysis of the extract by
using gas chromatography–tandem mass spectrometry (GC–MS–MS). For that purpose, the
31
extract was carried out in a single injection using the optimum ionization mode either
electron ionization (EI) or chemical ionization (CI)) for each pesticide. This method reduces
the time of analysis with respect to those methods which proposed two different injections in
order to detect same number of compounds, being more appropriate for its usage in routine
laboratories. For all pesticides, average recoveries in cucumber at two different fortification
levels were calculated and ranged between 73% and 108% and relative standard deviations
(RSD) were below 22%. The method has been validated and successfully applied for the
evaluation of about 4000 real samples collected from El Ejido (Almer´ıa, Spain).
Albero et al., (2003) developed a rapid method for multiresidue determination of 9
organophosphorus pesticides in fruit juices. The Method was based on matrix solid-phase
dispersion (MSPD) of samples on Florisil columns followed by ultrasonic assisted extraction
with ethyl acetate. The analysis of pesticide residues was performed by gas chromatography
coupled by nitrogen-phosphorus detector (NPD). Gas chromatography with mass
spectrometric detection with selected ion monitoring was employed for the confirmation of
pesticide identity. The Average recoveries obtained were >70% for all of the pesticides in the
different juices and fortification levels with relative standard deviations (RSD) of <11%. The
limits of detection (LOD) were ranged from 0.1 to 0.6 μg/ kg. To determine pesticide residue
levels in fruit juices sold in Spanish supermarkets, the proposed MSPD was successfully
applied and only one pesticide was detected below to the MRLs in most of the samples.
Okihashi et al., (2005) established a rapid method for the determination of 180
pesticide residues in vegetables and fruits. Acetonitrile was used for the extraction of
residues, followed by a salting-out step with NaCl and anhydrous MgSO4. Sediment and
water was removed simultaneously by centrifugation. A double-layered SPE column, and
32
graphitized carbon black and primary secondary amine (GCB/PSA) SPE cleanup cartridge
were used for the removal of co-extractives. Without further cleanup, the eluate was analyzed
by gas chromatography with flame photometry detector (GC-FPD) and confirmation was
made by using GC/MS. After fortification of 9 matrices 0.05–0.1 μg/g recovery data were
obtained. Average recoveries were mainly 70-110% of 180 pesticides and relative standard
deviation (RSD) was lower than 25%. Detection limits were ranged between 0.01and 0.05
μg/g for all tested pesticides.
2.3.3 Applications of High pressure / performance liquid chromatography for pesticide residues in fruits and vegetables
Despite of several advantages of gas chromatography due to its sensitivity,
occurrence of GC-amenable pesticidal compounds in a broad range of samples and
separation power, many compounds impossible to monitor and calculate straight by GC due
to less volatile nature, elevated polarity index and thermal unsteadiness has grown-up
significantly (Fillion et al., 1995). So, the application of only GC for the detection of
pesticide residues is not sufficient in most of the cases. To overcome these problems, in the
analysis of residues complementary liquid chromatography (LC) could also be used with
combination of diode array detector (DAD) or fluorescence spectrophotometry (Osterdhal et
al., 1998). One of the basic differences in GC and HPLC is that GC depends upon the
volatilization of the compounds, while HPLC is dependent on the ability of the compound to
be dissolved in an appropriate solvent. Liquid chromatography with ultraviolet detection
(UV) is used as a sophisticated tool for the determination of pyrethroid insecticides in fruits
and vegetables. Another plus point for liquid chromatography may lie in the extensive clean-
33
up process of extracts which is essential in gas chromatography. Recently, the combination
of liquid chromatography (LC) with tandem MS (MS/MS) has made it promising to replace
numerous specific and tedious methods. In same analysis, LC-MS/MS has the ability to
identify both parent compounds and their (often more toxic) metabolites.
A work has been done by Hiemstra et al., (1999) with the assistance of high
performance liquid chromatography coupled with diode array detection (HPLC–DAD) for
the evaluation of benzoylphenylurea (BPU) insecticides residues in fruiting vegetables and
pome fruit. Residues were removed with acetone and got partitioned by petroleum ether-
dichloromethane and then cleaned up on amino-propyl bonded silica cartridges for the
removal of interfering components. Separations were executed on a reversed phase column
with acetonitrile-water gradient system. To monitor the residues diode array detector was
used at 260 nm. The LODs for all BPU insecticides were ranged from 20 to 50 μg/ kg. The
data for repeatability and recoveries of seven benzoylphenylurea insecticides were collected
in Chinese cabbage, cucumber and apple samples at one spike.
Martel and Porthault (2000), carried out a research work for the determination of
cymoxanil, iprodione and vinclozolin fungicide residues in lettuce and raspberries by using
three different chromatographic methods such as high performance liquid chromatography
with ultraviolet detection (HPLC-UV), by high performance thin layer chromatography
(HPTLC) with densitometric detection and by gas chromatography coupled with electron
capture detector (GC-ECD). The extraction of residues in all cases were carried out with
acetone and liquid-liquid portioning and finally cleaned up by silica gel column. The limits
of detection (LOD) of iprodione, vinclozolin and cymoxanil were 0.2, 0.43 and 0.5 ppm for
34
the HPTLC method, 0.01, 0.013 and 0.08 ppm for the HPLC method and 0.025, 0.004 and
0.03 ppm for the GC method, respectively.
Fernandez et al., (2000) proposed a very simple and sensitive method for the
determination of four benzimidazole pesticides including thiabendazole, thiophanate-methyl,
carbendazole and benomyl, and one imidacloprid in fruit and vegetables by using liquid
chromatography-atmospheric pressure ionization-mass spectrometry. Extraction of residues
was performed by ethyl acetate and separated on a reversed-phase C18 column. No any clean-
up was thought essential prior to the injection into the liquid chromatography system with
electrospray mass-spectrometry. The range of LODs for compounds was in μg/ l.
Bicchi et al., (2001) reports a method for the determination of daminozide residues in
apple pulps by using high performance liquid chromatography with ultraviolet detection
(HPLC-UV). The method included alkaline hydrolysis of daminozide to N‘, N‘-
dimethylhydrazine, followed by distillation and then derivatizated with salicyl aldehyde to
salicyl aldehyde-N, N-dimethylhydrazone in strongly basic conditions. The clean-up of the
resulting solution was performed with Extrelut 20 NT and dichloromethane as eluent. HPLC
with C18 column was employed for the analysis and a gradient mobile phase was
programmed from 50:50 acetonitrile/water to 100% acetonitrile. Through two diagnostic UV
absorption maxima (295 and 325 nm) the salicyl aldehyde-N, N-dimethylhydrazone was
selectively detected, which have strong molar absorbivities. At 0.01 mg/kg recoveries of
daminozide were above 80%. The limits of detection LODs and limits of quantification
LOQs for salicyl aldehyde-N, N-dimethylhydrazone expressed as daminozide concentration
were 100 pg/μL at 295 nm and 150 pg/μL at 325 nm, and 0.0013 mg/kg at 295 nm and
0.0022 mg/kg at 325 nm, respectively.
35
A method was developed by Topuz et al., (2005) on high performance liquid
chromatography with diode array detection (HPLC-DAD) for the determination of four
fungicides including folpet, chlorothalonil, quinomethionat and tetradifon in fruit juices. The
method involves the solid phase extraction cartridge containing octadecyl resin (C18) for the
preconcentraion of 25g fruit juice samples. For separation and quantification of pesticides
high performance liquid chromatography with ultraviolet detection at 220 and 260 nm was
employed. A concave gradient elution with acetonitrile and water on a C18 column was used
for separations. Recoveries ranged from 93.8% to 99.5% from spiked cherry juices, apple,
and peach nectar and relative standard deviations (RSD) were below 3.4% at concentration
range of 1–16 μg/kg. LODs for the investigated pesticides were in the range of 0.5–1 μg/kg
and linearity of calibration curves was >0.9988. For validation, the developed method tested
on canned pure juice samples of cherry, peach nectar and apple manufactured in Turkey.
2.3.4 Application of thin layer chromatography (TLC) for pesticide residues in fruits and vegetables
For the separation and identification of pesticide residues thin layer chromatography
considered as a most widely used technique. TLC technique actually retained its favor as a
primary analytical method due to its reliability, simplicity, selectivity of detection and low
cost.
A modern thin layer chromatographic method using multiple development technique
for the analysis of pesticides was developed by Sherma (1992). Plates of high performance
thin layer chromatography (HPTLC) coated with a layer of silica gel (200μm) were used for
standards and sample solutions. A suitable solvent (dichloromethane-methanol) was used for
36
the development of plates by multiple, pressure or horizontal way. An automated
densitometric scanning at an optimal wavelength was used for the measurement of visible
spots. The procedure of high performance thin layer chromatography/automated multiple
development (HPTLC/AMD) has effectively validated for the screening of carbamates,
triazines and phenylureas in accordance with European Economic Community drinking water
regulations. The results of the prescribed method revealed that the alteration in the gradient
and thickness increased the speed and sensitivity of the analysis.
A thin layer chromatography method was described by Pasha and Vijayashanker
(1993) for the determination of residues of deltamethrin, cypermethrin, fenvalerate,
pyrethroids, permethrin and allethrin. The plate was exposed to bromine vapors after its
spotting and elution and then sprayed with 0.1% o-toluidine solution. After exposing under
sunlight for 5 minutes intense blue spots appeared. LOD of the method was calculated as
0.25-1.00 μg.
Patil and Shingare (1993) determined organophosphorous insecticides (containing
nitrophenyl group) by using thin layer chromatography (TLC). The compounds were reduced
to amino derivatives by using stannous chloride in HCl-H2O in proportion of 1:1, which were
further diazotized and attached with 1-naphthylamine to show strong pink-orange spots.
37
2.4 Analytical techniques and methodologies used for pesticide residues in human biological fluids (blood, urine)
A number of analytical methodologies has been developed and reported for the
assessment of pesticide residues as well as for their metabolites in biological fluids of human
beings (urine, whole blood, and serum). The most widely used methods were comprises of
gas chromatographic (GC) separations and detections coupled with a selective and sensitive
detector or coupled with only one mass spectrometry or tandem (MS/MS) (Ramesh et al.,
2004; Frias et al., 2001). Nowadays, pesticides with higher polarity index are more
frequently utilized than non-polar as they are less persistent in nature. In case of the
investigation of pesticides or other noxious compounds which are thermally unstable,
exceedingly polar and non-volatile in nature, liquid chromatography (LC) in combination
with mass spectrometry (MS) is the most powerful technique.
2.4.1 Application of Gas chromatography for pesticide residues in human biological fluids (blood, urine)
Lino et al., (1998) examined the efficiency of solid-phase extraction (SPE) with
Florisil resin for the assessment of 12 organochlorine pesticide residues in human serum. The
recoveries achieved were greater than 84% with coefficients of variation (CV) better than
19%. A comparison was made with other methods such as column partition and matrix solid-
phase dispersion. The limits of quantification provides by a better method were ranged from
37.5 mg/ l for p, p̀ -DDT and 1.08 mg/ l for γ-HCH when gas chromatography coupled with
electron capture detector (GC-ECD) was used for the final analysis.
Pitarch et al., (2001) described two methods for the multiresidue simultaneous
determination of organophosphorus and organochlorine pesticides in human urine and serum
38
samples. The first method was based on simple liquid-liquid microextraction assisted by
dichloromethane and the second method involves solid-phase extraction with C18 cartridge.
The final analysis in both of the methods was done by using capillary gas chromatography
coupled with nitrogen-phosphorus detector (NPD) and electron capture detector (ECD). In all
of the procedures the limits of detection (LOD) were at the low ng/ ml levels. The solid –
phase extraction procedure was finally applied to real-world samples. NPD or ECD was used
for quantification purpose and for the identification of peaks mass spectrometry (MS) was
used.
Tarbah et al., (2001) worked out to develop a rapid, simple and sensitive method for
the determination of organophosphorus pesticides (OPs) by using gas chromatography with
nitrogen-phosphorus detection (GC-NPD) and electron impact mass spectrometry with
selected ion monitoring (GC-MS/SIM). The method was based on a selective single-step
extraction of different twenty three organophosphorus pesticides in whole blood, serum,
urine and some food samples such as soft drinks, baby food and instant soups suspected of
contamination from a blackmailing scare. The residues were extracted with 1 ml of toluene
from 0.7 ml aliquot of whole blood, serum or urine sample. An amount of 1 μl of supernatant
(toluene phase) was directly injected and analyzed by GC-NPD and GC-MS. The validation
of the prescribed method was made by using spiked human serum. The rates of recoveries
from freshly spiked human plasma were ranged between 133% (dialifos) and 50%
(dimethoate).
Frías et al., (2001) has developed as well as validated a reliable, sensitive and
selective methodology for the monitoring of organochlorinated compounds posing
endocrine-disrupting effects (aldrin, lindane, o, p'-DDT, vinclozolin, p, p'-DDE and p, p'-
39
DDT) in human serum. The analytical procedure was comprises of three steps; (1) Extraction
of serum with organic solvent, (2) The clean-up of the organic extracts by means of acid
treatment with H2SO4 and (3) The elution of the cleaned-up extracts by using liquid
chromatography system and final analysis by gas chromatography with electron capture
detection (GC-ECD) and tandem mass spectrometry (MS-MS). For both chromatographic
methods, the performance parameters such as accuracy, linearity, sensitivity, recovery and
precision were studied. The developed method was applied for the determination of target
compounds in serum samples of women living in agricultural areas of Almería (Spain). The
method presented advantage of the tandem mass spectrometry (MS–MS) operation mode for
the determination of endocrine disrupting compounds in complex matrices and comparison
of the MS–MS and the ECD results were also made.
Ramesh and Ravi (2003) developed a new and sensitive method for the determination
of residues of endosulfan in the human blood by using negative ion chemical ionization gas
chromatography/mass spectrometry (GC-MS/CI) in selective ion monitoring (SIM) mode.
The extraction of residues was performed through whole blood without separating the serum
by using 60% sulfuric acid at 10° C, followed by partition with hexane + acetone in the ratio
of 9 : 1 (by volume). The quantification of endosulfan was made as the sum of its isomers
such as α-endosulfan, β-endosulfan and endosulfan sulfate in selective ion monitoring (SIM)
mode. For that purpose, the mass-fragment ions were monitored in SIM mode including α-
endosulfan: 99, 242, 270, 406; endosulfan sulfate: 97, 353, 386; endosulfan diol: 95, 169,
214, 313 and β-endosulfan: 99, 242, 270, and 406. The concentration range of 1.0-100 pg/ ml
was used for recovery experiments. Recovery of total endosulfan from the whole blood
samples were ranged between 112-98% and relative standard deviation (RSD) was 1.49-
40
2.68%. The sensitivity of the method for the quantification of total endosulfan was found up
to the level of 0.1 pg/ ml. The applicability of the presented method was tested for the
determination of endosulfan residues in 106 human blood samples gathered from a
population living in Padre Village, Kasargode District, Kerala, India. The results revealed
that none of the blood sample found positive for the presence of endoslufan isomers (alpha-
endosulfan 4 beta-endosulfan + endosulfan sulfate).
Kasiotis et al., (2008) determined residues of fenthion in human serum samples by
developing a simple and effective analytical method. The headspace solid-phase micro
extraction (HS-SPME) with polyacrylate fiber was used for the sample treatment, which
requires low amount of serum (1 mL) without tedious pre-treatment. Gas chromatography-
mass spectrometry (GC-MS) was used for the determination of fenthion residues in serum
samples and the recoveries at two spiking levels for 6 replicates were ranged from 79 to
104%. The limits of detection (LOD) and the limits of quantification (LOQ) for this method
were calculated as 1.51 and 4.54 ng/ ml, respectively. Two metabolites of fenthion, fenthion–
sulfoxide and fenoxon were also identified.
2.4.2 Application of High performance liquid chromatography for pesticide residues in human biological fluids (blood, urine)
Itoh et al., (1996) discussed the purpose and advantages of high-performance liquid
chromatography (HPLC) in combination with atmospheric pressure chemical ionization mass
spectrometry used for the investigation of pesticides comprised of twenty one (21) different
types of organophosphorus and eight (8) different types of N-methylcarbamate. The
monitoring of both ions (positive and negative) to indentify 21 organophosphorus pesticides
41
was made. However, 8 N-methylcarbamate pesticides were recognized just by means of the
positive ions. In comparison to electron impact mode, the spectra achieved via this method
showed a pattern which was simple and easy, those mass spectra were distinct enough for the
identification of anonymous peaks on the chromatogram. With the high specificity of this
method through an enormously easy pre-treatment process quick analysis could be
performed.
Dulaurent et al., (2006) introduced an analytical methodology for the simultaneous
determination of the Dialkylphosphates (DAP) known to be urinary indicators of the
exposure to organophosphates pesticides, by using liquid chromatography–tandem mass
spectrometry (LC–MS/MS). DAP selected for this study were dimethythiophosphate
(DMTP), diethylthiophosphate (DETP), dimethylphosphate (DMP), dimethyldithiophosphate
(DMDTP), diethyldithiophosphate (DEDTP) and diethylphosphate (DEP). An internal
standard dibutylphosphate (DBP) was also used. The procedure involved liquid–liquid
extraction and detection by using mass spectrometric detector (MSD) with the negative ion
multiple reaction monitoring (MRM) modes, subsequently 2 ion alterations per compound.
The limits of quantification (LOQ) achieved for the six compounds was 2 μg/ l and
coefficients of variation (CV %) was calculated below than 20%. The developed analytical
method was successfully validated by the investigation of urine specimens from a small
cohort of non-exposed volunteers and at least one of the six DAP was found in each of the
urine sample. The results have shown the viability of a LC–MS/MS procedure for the
assessment of general population exposure to some commonly used organophosphate
pesticides.
42
Inoue et al., (2007) reported a rapid and simple method for the measurement of 10
organophosphorus pesticides in the serum of acute poisoning patients by using liquid
chromatography mass spectrometry (LC-MS). The 10 OPs selected for this study were
acephate, methidathion, dichlorvos, fenthion, EPN, diazinon, phenthoate, malathion,
fenitrothion, and cyanophos. An aliquot of the biological sample after deproteinization by
acetonitrile was injected into a C18 column using 10mM ammonium formate-methanol as
eluent. Satisfactory extraction recoveries were obtained in the range between 60.0 and
108.1% in serum. The LODs and LOQs in the serum were ranged from 0.125 to 1 μg/ml and
0.25 to 1.25 μg/ml, respectively. After successful application of this method on one actual
case of acute poisoning it was concluded that due to its accuracy and simplicity, it could be
useful for the determination of organophosphorus pesticides and could also be very helpful in
both clinical and forensic toxicology.
Araoud et al., (2010) worked out for the development of a method for the estimation
of carbamate and organophosphorus pesticide residues which are extensively utilized in
Tunisia. In this method a liquid-liquid extraction followed by liquid chromatography tandem
mass spectrometry (LC/MS/MS) in elctrospray mode was employed for the identification and
quantification of compounds. To monitor the MS/MS alteration for every compound,
multiple reactions monitoring (MRM) acquisition mode was used. At three different
fortification levels the average recoveries obtained for most of the pesticides were ranged
between 65% and 106% with exception for methamidophos. While, depending on the
analyte, linearity with correlation coefficient from 0.995 to 0.999 was in the range of 5 to 50
μg/ l. The LOD and LOQ calculated were 2 μg/ l and 5 μg/ l, respectively.
Chapter 03
EXPERIMENTAL
43
Chapter-03
EXPERIMENTAL
3.1 Assessment of pesticide residues in commonly used vegetables
3.1.1 Vegetable Samples
Pesticide residues were determined in 200 vegetable samples collected from the local
markets of urban and rural areas of Hyderabad, Pakistan, and transported to the laboratory
according to standard sampling procedure (Cook, 2002). The vegetable samples (25 of each
crop) surveyed for the present study were cauliflower, green chili, eggplant, tomato, peas,
bitter gourd, spinach and apple gourd. Samples were stored at 4 °C prior to extraction
procedure.
3.1.2 Chemical standards and reagents
Pesticide standards were purchased from (Sigma-Aldrich, Inc.Germany) with the
purity between 97% and 99%. Dichloromethane (DCM), cyclohexane and acetone and
sodium sulphate anhydrous were purchased from Scharlau (Barcelona, Spain). Individual
stock solution of each pesticide standard was prepared in acetone (gravimetrically) at a
concentration of 1mg /kg and stored in a freezer at -18 °C. Working standard solutions were
prepared by appropriate dilutions with cyclohexane and stored under refrigeration (4 °C).
3.1.3 Extraction procedure
Extraction was performed according to the reported method (Arrebola et al., 2003)
with the help of ultrasonic assisted extraction (UAE) to enhance the extraction of pesticide
residues. An aliquot of 15 g of chopped vegetable sample were weighed and mixed with 30
44
ml of dichloromethane in a homogenizer for 2-3 min. After homogenization, 30 g anhydrous
sodium sulphate were added and allowed to rest for 2 min in an ultrasonic bath at 40 °C,
filtered the above solution through a Buchner funnel and then again filtered the above filtrate
through filter paper with anhydrous sodium sulphate. Final filtrate was evaporated to the
dryness in a rotary evaporator, and the dried residue was re-dissolved with 10 ml of
cyclohexane. An aliquot of final extract was subjected to GC-MS for analysis.
3.1.4 GC-MS analysis
The extracts were analyzed using GC-MS under the conditions as follows: injector
port temperature 250 °C, injection volume 2µl in splitless mode, helium as carrier gas at a
flow rate of 1.2 ml/min; oven temperature program, 70 °C (2 min), increased at 25 °C/min to
150 °C, held for 2 min, then increased to 200 °C at 3 °C/min, and held for 2 min; and finally
increased at 8 °C/min to 290 °C and held for 5 min, solvent delay, 4.5 min. Transfer line
temperature was 300 °C. Ion energy for electron impact (EI) was always 70 eV. The ion
source (EI) and quadrupole temperatures were 230 and 150 °C, respectively. Mass detection
was performed in the single ion monitoring (SIM) mode (with consideration of the relative
intensities of selected ions).
45
3.2 Method developed for the assessment of pesticide residues in
commonly used fruits
3.2.1 Reagents
Reference standards of pesticides (99.9% purity) were bought from Sigma-Aldrich
(Seelze, Germany). Methanol, acetonitrile, ethyl acetate, hexane and anhydrous sodium
sulfate were purchased from Scharlau (Barcelona, Spain). Individual pesticide stock solutions
(500 μg ml-1) were prepared in ethyl acetate and kept in cold storage. A mixture of stock
solution holds all of the pesticides at 5 μg ml-1 were prepared. From each stock solution 1 ml
was transferred to a volumetric flask of 100 ml capacity and diluted to the mark by ethyl
acetate. To acquire linear response of the detector and for the fortification of samples,
standard working solutions of different concentrations were prepared with appropriate
dilutions by ethyl acetate and then stored at 4 °C.
3.2.2 Instruments
Agilent (CA, USA) model 7890 A GC system coupled with micro Electron Capture
Detector (μECD), with automatic split–splitless injector model Agilent 7683 B and 7683
Agilent autosampler was employed for the determination of pesticides. A HP-5 capillary
column (30 m × 0.32 mm × i.d., 0.25μm film thickness), supplied by Agilent Technologies,
was engaged.
GC-MS confirmation was carried out with an Agilent Technologies 6890N network
GC system equipped with a 5975 inert MSD run in Electron Impact ionization mode (EI),
and Agilent 7683 automatic split-splitless injector. HP-5MS capillary column (30 m × 0.25
mm × i.d., 0.25μm film width) provided by Agilent Technologies, was engaged. The carrier
46
gas used was helium with (99.9993%) purity. A rotary evaporator model R-210 Büchi,
(Flawil, Switzerland) and an ultrasonic bath Raypa, (Barcelona, Spain) were used for solvent
evaporation and sonication, respectively.
3.2.3 Instrumental Conditions
The operating conditions for GC-μECD were as described: The temperature of
injection port was 250 °C, injection volume 2μl in split ratio 50:1 and split flow 60 ml/min.
The detector temperature was 310 °C. Column temperature was programmed as, the first
temperature 70 °C for 0 min, after that increased at a rate of 30 °C/min to 210 °C and seized
for 2 min, then from 210 °C to 250 °C at a rate of 25 °C/min with held for 2 min, then
increased upto to 290 °C with the rate of 30 °C/min and finally held for 5 min. The carrier
gas, Nitrogen (purity 99.99%) at a flow rate of 1.2 ml/min was used. The whole analysis time
is less than 17 min, and the time for the equilibration of the system was put 0.5 min.
For GC-MS confirmation the working conditions were as: The temperature for
injector port was 250 °C, volume of injection was 2µl in splitless manner, helium (99.99%)
used as carrier gas at 1.2 ml/min flow rate. For column the temperature program was the
same as in GC-μECD. The MSD was run in electron impact ionization manner (I.E = 70 eV)
scanning as from m/z 50 to 550 at 4.4 scan/s. Temperatures of ionization source and
quadrupole were adjusted at 230 °C and 150 °C, respectively.
47
3.2.4 Fruit Samples
Fruit samples such as orange, apple and grape were purchased from the local fruit
markets of Hyderabad region, situated in the province of Sindh, Pakistan. Samples were
investigated following the method described underneath and those samples with
concentrations of pesticides below the detection limits were used as blank fruit samples for
recovery study.
3.2.5 Extraction and clean-up procedure
Whole, unwashed fruit samples were chopped and homogenized. An aliquot from
each sample (10 g) was weighed and extracted two times by means of 20 ml ethyl acetate.
For recovery studies, samples were fortified with different concentrations of prepared
pesticide standards. Extracts were kept in a sonicator for 2 min at 40 ± 2 °C. After sonication,
the extracts filtered through a filter paper by means of suction pump. Residues were washed
with ethyl acetate (10 ml) and extracts were shifted to the separatory funnel. The aqueous
part of the combined extracts was thrown away while organic part was passed all the way
through anhydrous sodium sulfate and vanished to dryness in a vacuum rotary evaporator.
Residues were dissolved in ethyl acetate (5 ml) and cleaned-up on solid phase extraction
column containing 1 g of C18 preconditioned by means of acetonitrile (3 ml) and water (5
ml). The extracted residues were shifted to the column and eluted two times with 5 ml of
ethyl acetate-hexane (1:1, v/v). The eluate shifted to a tube where it gets concentrated under a
gentle flow of nitrogen to a suitable quantity. An aliquot of the final extract was examined by
GC-μECD.
48
3.3 Monitoring of pesticide residues in commonly used fruits
3.3.1 Sample Collection and Preparation
For the evaluation of pesticide residues, a total of 131 samples of some fruits
including apples, grapes and oranges were collected during the period of October 2010 -April
2011 from three different main fruit markets located in urban areas of Hyderabad region,
Sindh, Pakistan. The size of the sample of each fruit was between 2 - 3 kg. 17 samples of
apple, 12 samples of grapes and 13 samples of oranges were purchased from the fruit market
No.1. Similarly 14 samples of apple, 14 samples of grapes and 11 samples of orange were
obtained from the fruit market No. 2. While from the fruit market No. 3, 16 samples of apple,
15 samples of grapes and 19 samples of oranges were purchased in different dates. Each
sample of fruit was chopped and 200 g portion get homogenized and kept in glass stopper
bottle and stored under freezing temperature until extraction.
3.3.2 Extraction procedure
The extraction procedure was used as same as described in section 3.2.5.
3.3.3 Gas Chromatographic Analysis
Analysis of pesticide residues was carried out on an Agilent (CA, USA) model 7890
A GC system coupled with micro Electron Capture Detector (μECD), in combination with
automatic split-splitless injector model Agilent 7683 B and 7683 Agilent autosampler. For
the separation of analytes a HP-5 glass capillary column (30 m × 0.32 mm × i.d., 0.25 μm
film thickness) supplied by Agilent Technologies, was installed. Injector and detector
temperatures were set up to 250°C and 310°C respectively. Temperature for column was
programmed as; the starting temperature was 70°C for 0 min, after that raised at a rate of
49
30°C/min to 210°C and seized for 2 min, then from 210°C to 250°C at a rate of 25°C /min
with held for 2 min, then increased up to 290°C with the rate of 30°C /min and lastly held for
5 min. Nitrogen (purity 99.99%) was used as carrier gas with flowing at 1.2 ml/min. For the
confirmation of detected residues Agilent Technologies 6890 N network GC system
equipped with a 5975 inert MSD with the combination of Electron Impact (EI) as source for
ionization and Agilent 7683 automatic split-splitless injector, was employed. The
temperatures of ionization source and quadrupole were kept at 230°C and 150°C,
respectively.
3.4 Assessment of pesticide residues in human blood samples
3.4.1 Selection and description of sampling population
Selection of areas was based on the higher pesticides consumption and extensive
agriculture production of numerous commodities. Before taking the blood samples from the
volunteers, interviews were conducted with reference to their occupational histories to get
knowledge about their years of involvement to pesticide exposure, age, sex and clinical
history.
3.4.2 Sample collection
The samples of blood were collected from 188 volunteers out of which 110 were
related to Hyderabad district and remaining 78 were from Mirpurkhas district. The volunteers
were categorized into two main groups on the basis of their occupation i.e. Group 1 Agro
professionals, those who were involved in farming practices such as spraying activity,
growing and harvesting of commodities and Group 2 non–agro professionals, those who
were not involved in any farming practices but belong to other profession such as
50
shopkeeper, barber, students, school teachers, house wives etc. The detail of volunteers is
described in Table 1. Blood samples (5cc) were collected by butterfly syringe from the veins
in the inner forearms of each volunteer. Whole blood was kept in decontaminated labeled
glass vials, preserved in an ice box and transported to the laboratory for analysis.
3.4.3 Reagents
Reference standards of pesticides were purchased from Sigma–Aldrich (Germany)
with purity between 98% – 99%. Acetone, dichloromethane, n–hexane were obtained from
Scharlau (Barcelona, Spain) and anhydrous sodium sulphate was acquired from Merck
(Germany). Stock solutions of each pesticide standard with concentration of 100 mg/kg were
prepared in n-hexane and stored in a freezer at –18 °C. A mixture from stock solution of all
pesticides standards was prepared by transferring 1 ml of each stock solution to a 100 ml
volumetric flask and diluted up to the mark with n–hexane (5 mg kg-1).
3.4.4 Extraction and cleanup
Extraction of pesticide residues from the whole blood was done according to the
reported method (Cruz et al 2003) with the addition of ultrasonic assistance. According to the
procedure 1 ml of methanol and 2 ml of blood sample was taken in 20 ml screw capped vial.
Extraction of pesticides was carried out with 10 ml of solvent system containing n–hexane
and acetone in the ratio of 9:1. Mixture was shaken for 1 min on vortex mixer. After addition
of anhydrous sodium sulphate the vial was placed in ultrasonic bath for 2min, and then
centrifuged at 3000 rpm for 5 min. The cleanup procedure was carried out using solid phase
extraction (SPE) cartridge containing octadecyl (C18) resin. Gradient system was used to
elute pesticides initially with 6 ml of pure n-hexane and then with 6 ml of a mixture of n-
51
hexane and dichloromethane in the ratio of 5:1. The combined eluates were concentrated
under the gentle stream of nitrogen, and an aliquot of the final concentrated extract was
analyzed by GC–μECD and GC–MS, respectively.
3.4.5 Instrumentation
Agilent GC system model 7890 A (CA, USA) in combination with micro electron
capture detector (μECD), automatic split-splitless injector model Agilent 7683 B and 7683
Agilent Autosampler was used for the analysis of pesticide residues. For the separation of
pesticide residues a HP-5 capillary column supplied by Agilent Technologies with
specifications 30 m × 0.32 mm × i.d., 0.25μm film thickness, was employed.
For the confirmation of pesticide residues in blood samples, Agilent technologies
6890N series GC system with Agilent 7683 automatic split-splitless injector, interfaced to
Agilent 5975 mass spectrometer detector (MSD) in Electron Impact (EI) ionization mode
was employed. A capillary column HP-5MS with specifications 30 m × 0.25 mm × i.d.,
0.25μm film width provided by Agilent technologies, was used. An ultrasonic bath (Raypa-
Barcelona, Spain) was used for ultrasonic assisted extraction.
Chapter 04
RESULTS & DISCUSSIONS
52
Chapter-04
RESULTS AND DISCUSSION
4.1 Assessment of pesticide residues in commonly used vegetables
The method was evaluated under the optimized conditions by determining the limits
of detection (LOD), limits of quantification (LOQ), the recovery and precision. The LODs of
each pesticide were calculated at a signal-to-signal ratio of 3, whereas the limits of LOQs
were obtained at a signal-to-signal ration of 10, as shown in Table 4.1.1. For recovery study,
vegetable samples which were initially free from any pesticide contamination, were fortified
at 0.05, 0.1, and 0.2 mg/kg as prior to the extraction step. Excellent recoveries (>90%) with
low coefficient of variations (< 4%) were obtained as shown in Table 4.1.2. For the linearity,
blank vegetable samples fortified with 0.05, 0.10 to 0.20 mg/ kg of each pesticide and
individual standards of targeted pesticides were run in to the GC-MS. Table 4.1.3 shows the
main ions of the pesticides selected for their detection and determination. All of the studied
compounds can be identified by their main ions, in the PEST library. Areas under the peak
versus concentrations were plotted and fit by simple linear regression to obtain the equation
for the standard curves to measure the unknown quantity of pesticides. The amount of each
pesticide in each sample was thus calculated based on the slope of the standard curve.
Response of the detector was found to be linear with excellent determination coefficient r2 ≥
0.995 for all pesticides. Calibration and validation data have been summarized in Table 4.1.1.
To evaluate the reproducibility of the results, same sample was run 5 times with an automatic
injector. An excellent reproducibility with small values of standard deviation (RSD) for the
peak areas and retention times was obtained (< 0.02 and 6.0%, respectively) as shown in
Table 4.1.1.
53
Table 4.1.1. Calibration data of individual pesticide in the vegetable samples with the
limit of detection and limit of quantification.
a Relative standard deviation of peak areas and retention time (n=5).
Pesticide Calibration Data
Equation R2
LOD LOQ Repeatability (RSD,%)a
Peak area tR
Carbofuran y = 1.14x – 3 ҳ 10-3 0.998 0.06 0.23 3.5 0.003
α-Endosulfan y = 3ҳ10-4x + 6 ҳ 10-4 0.995 0.01 0.05 4.5 0.009
β-Endosulfan y = 5ҳ10-4x + 3 ҳ 10-4 0.996 0.04 0.15 3.1 0.012
Fenvalerate y = 1 ҳ 10-3x + 7 ҳ 10-4 0.999 0.07 0.23 4.1 0.008
Malathion y = 1 ҳ 10-4x + 8 ҳ 10-4 0.997 0.07 0.26 3.8 0.018
Chlorpyrifos y = 1.92x + 8 ҳ 10-4 0.999 0.02 0.08 5.9 0.004
54
Table 4.1.2. Recoveries (% ± CV) of the investigated pesticides from samples
Pesticide Fortification levels (mg/kg)
0.05 0.1 0.2
Carbofuran 98.32 ± 2.5 97.44 ± 1.9 99.91 ± 2.5
α-Endosulfan 99.57 ± 3.1 98.42 ± 2.7 99.88 ± 1.7
β-Endosulfan 98.12 ± 2.8 99.92 ± 3.5 98.72 ± 2.9
Fenvalerate 97.88 ± 2.9 98.36 ± 2.1 97.51 ± 3.1
Malathion 96.42 ± 3.4 97.77 ± 3.9 97.32 ± 1.5
Chlorpyrifos 99.48 ± 3.2 97.67 ± 3.3 99.32 ± 3.7
55
Table 4.1.3. Main ions selected (m/z) for detection and determination analysis of
individual pesticides in the vegetable samples.
Pesticide Ions used in: (m/z) Qualitative analysis Quantitative analysis
Carbofuran 123, 165 165
α-Endosulfan 195, 241, 339 241
β-Endosulfan 195, 241, 339 241
Fenvalerate 125, 225 225
Malathion 127, 158, 173 173
Chlorpyrifos 197, 199, 258, 314 258
56
Total 200 vegetable samples were analyzed. From the total, 39% of the samples were
detected for pesticide residues at or below MRLs (www.pmfai.org/stat.htm), while 61%
contained pesticides residues exceeding the MRLs limit. The detected pesticides in the
vegetable are included the organophosphates, organochlorines, carbamates and pyrethrins
classes. The total number of analyzed samples, mean levels of six pesticides found in
samples, number of contaminated samples and number of samples exceed the MRLs are
shown in Table 4.1.4. Results shows that the most common pesticide residues found were
carbofuran and chlorpyrifos with the highest concentrations of 0.39 (apple gourd) and 0.96
mg/kg (bitter gourd) respectively, and their mean levels exceeds the MRLs. Remaining four
pesticides including α-endosulfan, β-endosulfan, fenvalerate and malathion are found at or
below to their MRLs and malathion was found in least amount in all analyzed vegetable
samples. Only six pesticides were screened herein study which were present in greater
amounts, while other pesticides could be present in very low level.
The analytical method used in the present study was little bit improved by the
assistance of ultrasonic heating to minimize the analysis time with assisting the rapid
extraction of pesticides. Acceptable recoveries were obtained for all pesticides. The good
reproducibility and accuracy of the proposed method allows its application for the accurate
determination of pesticide residues of all groups (organophosphorus, organochlorines,
carbamates and pyrethrins) in commonly used vegetables for commercial and routine lab
analyses.
Analysis of total 200 fresh vegetables collected from the local rural and urban
markets of Hyderabad region indicated the presence of targeted pesticide residues of different
groups. The residue contents varied depending upon the type of crop and pesticide used.
57
Table 4.1.4. Pesticide concentrations found in vegetable samples mg/kg.
Vegetables (number of samples)
Pesticide detected
Number of samples Analyzed Contaminated >MRL (mg kg-1)
MRLa (mg kg-1)
Mean Range (mg kg-1)
Eggplant (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
25 24 23 13 23 08
07 05 0 0 0 0
0.1 0.2 2 2 2 3
0.104 (0.05-0.17) 0.246 (ND-0.57) 0.636 (ND-1.57) 0.192 (ND-0.73) 0.652 (ND-1.31) 0.271 (ND-1.21)
Cauliflower (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
24 25 13 24 21 04
11 10 0 0 0 0
0.1 0.2 2 2 2 3
0.192 (ND-0.21) 0.214 (0.08-0.44) 0.582 (ND-0.29) 0.219 (ND - 0.9) 0.751 (ND-1.81) 0.056 (ND - 0.1)
Peas (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
24 25 14 23 12 05
08 09 0 0 0 0
0.1 0.2 2 2 2 3
0.184 (ND-0.21) 0.218 (0.07-0.42) 0.948 (ND-0.51) 0.563 (ND-1.48) 0.754 (ND-1.32) ND (ND - 0.01)
Bitter gourd (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
25 24 13 23 20 06
08 05 0 0 0 0
0.1 0.2 2 2 2 3
0.122 (0.01-0.15) 0.352 (ND-0.96) 0.941 (ND-1.51) 0.124 (ND-0.28) 0.416 (ND-0.91) 0.723 (ND-0.16)
Green chili (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
23 24 23 13 18 04
04 10 0 0 0 0
0.1 0.2 2 2 2 3
0.108 (ND-0.11) 0.264 (ND-0.27) 0.661 (ND-1.33) 0.061 (ND-0.11) 0.124 (ND-0.19) 0.042 (ND-0.09)
Spinach (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
24 25 13 14 25 03
04 09 0 0 0 0
0.1 0.2 2 2 2 3
0.188 (ND-0.32) 0.311 (0.05-0.85) 0.714 (ND-1.52) 0.064 (ND-0.13) 0.306 (0.11-0.57) 0.056 (ND-0.15)
Apple gourd (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
24 25 17 14 25 05
14 04 0 0 0 0
0.1 0.2 2 2 2 3
0.166 (ND-0.39) 0.368 (0.19-0.76) 0.386 (ND-0.91) 0.114 (ND-0.28) 0.392 (0.09-0.28) 0.191 (ND-0.81)
Tomato (25)
Carbofuran Chlorpyrifos α-Endosulfan β-Endosulfan Fenvalerate Malathion
25 25 25 25 25 25
25 25 14 19 22 07
10 03 0 0 0 0
0.1 0.2 2 2 2 3
0.114 (0.01-0.12) 0.215 (0.09-0.36) 0.314 (ND-0.58) 0.028 (ND-0.07) 0.336 (ND-0.81) 0.092 (ND-0.01)
8 x 25
6 200
200
121
awww.pmfai.org/stat.htm
58
It was observed that out of the total vegetable samples (200) analyzed, 121 samples
(61%) contained detectable residues that exceeded maximum residue limits (MRLs). It may
be due to lack of awareness of the farmers about the application dose, methods of application
and the appropriate interval between harvesting and pesticide treatment. The negligence or
non-availability of proper guidance about the pesticide application may be another reason
which can lead to contamination of vegetables with pesticide residues. These vegetables
could pose health hazards to the consumers.MRL values exceeded most in cauliflower (84%
of the total 25 samples) followed by apple gourd (72% of the total 25 samples), peas (68% of
the total 25 samples), bitter gourd, spinach and tomato (52% of the total 25 samples each)
and then eggplant (48% of the total 25 samples). Cauliflower gets spoil by many pests,
therefore farmers applied different pesticides ineluctably to eradicate pests of cauliflower. In
this region, the overuse of pesticides and random combination of pesticides of different
groups are serious problem in vegetables cultivated in farmer's field. As the summarized
results of this study shown in Table 4.1.4, the peak concentrations for the tested pesticides
exceeded MRLs were recorded with insecticide chlorpyrifos (bitter gourd) followed by the
nematicide carbofuran (apple gourd).
Carbofuran is most often exceeded MRL values (33% of the total 200 vegetable
samples) followed by chlorpyrifos (29% of the total 200 vegetable samples). Also the data
presented in Table 4.1.4 indicates that the carbofuran and chlorpyrifos were the most
frequently pesticides suggesting that these pesticide were in common use in vegetable
samples found in Hyderabad region. The higher concentrations of carbofuran and
chlorpyrifos residues in vegetable samples especially in cauliflower above their MRLs may
be due to their stability, poor compliance of the pre-harvest interval, especially after repeated
treatments with these pesticides and non-professional use.
59
4.2 Method developed for the assessment of pesticide residues in
commonly used fruits
4.2.1 Gas chromatographic determination
Figure 4.2.1. (A) GC-μECD chromatogram of the blank sample extract. (B) GC-
μECD chromatogram of standard mixture in blank spiked sample of the same
concentration in Et/Ac (1 μg g-1).
60
To overcome the matrix effect and to get improvement of the chromatographic
response, blank samples of fruits was spiked with the pesticides of known concentration. As
shown in Fig. 4.2.1. (A) chromatogram of a blank fruit sample extract and Fig. 4.2.1. (B) a
blank sample spiked with the mixture of pesticide standards at concentration 1 μg g-1. The
figure shows that blank fruit sample chromatogram showing lack of interferences at the
retention times of the targeted pesticides. So, the quantification has been conceded by
preparing standards with blank fruit samples. According to previous workings, separation of
these pesticides usually takes about 50–60 min. In order to get shorten analysis time with best
separation and resolution of chromatogram, optimization of appropriate temperature
programming was made. To get the absolute separation and best resolution of peaks, a
multistep temperature program was found to be more suitable. All of the targeted pesticides
get monitored in less than 17 min. It indicates a 4-fold gain in investigation time saved
compared to usual GC schemes. Fig. 4.2.2. shows the representative chromatogram of
standards mixture with good separation and resolution.
4.2.2 Optimization of extraction procedure
Solvents used in many pesticide residues determination methods for the extraction
purpose in fruits were usually acetone, dichloromethane, acetonitrile and ethyl acetate. For
best possible extraction, solvents like acetone, dichloromethane, and ethyl acetate used
individually and in combination with different ratios to extract the targeted analytes.
61
Figure 4.2.2. GC-μECD chromatogram of a standard mixture. Peak numbers
are named in the order of increasing tR in Table 4.2.1.
62
Figure 4.2.3. Effect of sonication on pesticide recovery in the extraction
procedure. Samples were fortified at 1.0 μg g-1.
63
The result shows that ethyl acetate gave superior results in comparison to the other
solvents. Therefore, ethyl acetate was selected for the extraction of samples for residue
determination. In addition to the solvent selection, the effect of sonication was also studied in
the optimization process of the extraction method. Pesticide recoveries ranged from 70% to
80% without sonication, but extraction assisted with sonication gave enhancement in
recoveries as shown in Fig. 4.2.3, particularly in orange as compare to the apple and grape,
which may be as a consequence of the thinner nature of apple and grape sample matrices.
Hence, the extraction of pesticides from samples in the proposed method was carried out
assisted by sonication.
4.2.3 Method Validation
4.2.3.1 Linearity
Those samples which were initially analyzed with pesticide concentrations below
detection limits were fortified at different concentration levels 50, 100, 500, 2000 and 5000
μg kg-1 for the determination of linearity of the proposed method. The response given by the
detector was tremendous and linear in the series of concentrations studied with excellent
values of determination coefficient (>0.9992) for each of the pesticide. Summarized data of
calibration and validation for the pesticides studied shown in Table 4.2.1.
4.2.3.2 Repeatability
To inspect the repeatability, a blank sample fortified at 10 μg g-1 has performed. The
sample inserted 10 times by means of an auto injector. Result shows a fine repeatability
attained in the term of relative standard deviation (RSDs) have achieved for peak areas and
retention times with values < 4% and 0.05, respectively as shown in Table 4.2.1.
64
Table 4.2.1. Retention times (tR), calibration data, and repeatability of the pesticides
analyzed by GC-μECD.
# Pesticide tR, min Calibration Data
Equation R2
Repeatabilitya (RSD, %)
tR peak area
01 Dichlorvos 4.29 y = 9.5753x + 1.6977 0.9998 0.02 1.4
02 Phosdrin 5.08 y = 6.1418x + 5×10-3 0.9995 0.03 1.5
03 α -HCH 6.68 y = 5.075x + 2.5952 0.9997 0.04 1.8
04 Dimethoate 6.82 y = 11.388x + 1.682 0.9994 0.01 1.2
05 β-HCH 7.00 y = 1.5534x + 1.1034 0.9998 0.02 2.8
06 γ -HCH 7.10 y = 5.1582x + 3.3399 0.99 0.01 2.2
07 Disulfoton 7.30 y = 4.3971x + 4×10-4 0.99 0.01 1.9
08 δ -HCH 7.38 y = 4.2158x + 2.7238 0.9996 0.02 2.7
09 Chlorpyrifos Methyl 7.65 y = 14.759x + 4.8829 0.9999 0.03 2.3
10 Propanil 7.69 y = 10.92x + 2.4567 0.9998 0.03 1.4
11 Metribuzin 7.74 y = 6.7901x + 2.8332 0.9993 0.02 2.5
12 Parathion Methyl 7.85 y = 13.005x + 2.8897 0.9994 0.01 2.3
13 Heptachlor 7.99 y = 16.436x + 9.1816 0.999 0.03 3.1
14 Bromacil 8.18 y = 15.081x + 4.8706 0.9999 0.02 2.3
15 Malathion 8.24 y = 10.136x + 1.5545 0.9997 0.04 1.2
16 Parathion 8.39 y = 6.1765x + 4.3059 0.9997 0.01 3.5
17 Aldrin 8.40 y = 15.002x + 11.291 0.9997 0.01 1.6
18 Chlorpyrifos 8.41 y = 9.4448x + 2.3975 0.9998 0.04 1.4
19 Triademofen 8.44 y = 8.8255x + 7.165 0.9998 0.02 2.7
20 Bromophos Methyl 8.65 y = 16.011x + 4.3919 0.9998 0.04 1.8
21 Allethrin 8.86 y = 13.786x + 5.9197 0.9996 0.02 1.0
22 Tolyfluanid 8.89 y = 16.603x + 9.4754 0.9999 0.03 3.0
23 Captan 8.98 y = 8.4931x + 4.1676 0.9997 0.02 3.1
24 Bromophos Ethyl 9.19 y = 16.509x + 6.0949 0.9998 0.01 2.2
25 α-Endosulfan 9.44 y = 10.839x + 6.6558 0.9995 0.03 2.3
26 Dieldrin 9.83 y = 2.6265x - 6×10-4 0.9997 0.02 1.7
27 β -Endosulfan 10.37 y = 4.5629x + 3.1647 0.9996 0.02 2.9
28 DDT 11.00 y = 15.357x + 7.3635 0.9997 0.02 1.8
29 Endosulfan sulfate 11.01 y = 14.443x + 7.7363 0.9998 0.01 3.7
30 Dialifos 12.73 y = 5.5514x + 4×10-4 0.9994 0.03 1.3 a Relative standard deviations of retention times and peak areas (n =10).
65
Table 4.2.2. Recovery of pesticides from spiked samplesa
Pesticide Fortification level (μg g-1)
Mean recovery ± RSDb (%)a
Orange Apple Grape
Aldrin 0.05 1.0 2.0
100.2 ± 4.0 96.1 ± 5.2 90.3 ± 3.9
92.7 ± 4.9 97.6 ± 2.7 90.4 ± 4.3
90.1 ± 3.2 95.3 ± 2.9 89.1 ± 1.7
Allethrin
0.05 1.0 2.0
96.2 ± 2.0 93.1 ± 4.2 91.3 ± 1.9
90.7 ± 3.9 99.3 ± 1.7 88.4 ± 2.3
91.6 ± 1.2 90.6 ± 2.4 89.1 ± 2.8
Bromacil
0.05 1.0 2.0
90.9 ± 3.0 92.1 ± 1.2 98.3 ± 2.0
100.7 ± 2.9 97.8 ± 3.7 95.4 ± 1.9
98.1 ± 3.7 91.2 ± 2.3 89.9 ± 2.7
Bromophos Methyl
0.05 1.0 2.0
87.2 ± 4.9 90.7 ± 2.8 92.6 ± 1.9
90.4 ± 4.9 91.4 ± 1.9 93.7 ± 1.7
88.9 ± 2.6 92.7 ± 2.2 89.8 ± 1.9
Bromophos Ethyl
0.05 1.0 2.0
98.9 ± 1.1 91.2 ± 3.9 93.8 ± 2.5
97.3 ± 2.4 94.8 ± 1.3 89.8 ± 2.4
88.1 ± 2.0 91.2 ± 3.3 89.3 ± 3.1
Captan
0.05 1.0 2.0
85.2 ± 2.5 96.1 ± 2.2 94.8 ± 2.9
88.4 ± 3.4 92.3 ± 1.2 96.9 ± 3.3
97.9 ± 2.8 95.4 ± 3.9 99.1 ±2.6
Chlorpyrifos
0.05 1.0 2.0
94.8 ± 2.3 99.0 ± 1.7 92.3 ± 0.9
104.0 ± 2.7 97.3 ± 1.7 96.2 ± 2.3
97.8 ± 3.6 91.4 ± 4.3 98.6± 3.9
Chlorpyrifos Methyl
0.05 1.0 2.0
90.4 ± 4.3 92.6 ± 4.5 93.8 ± 3.7
90.3 ± 3.9 99.4 ± 3.8 93.5 ± 3.6
92.1 ± 1.7 90.7 ± 3.0 97.3 ± 2.9
Dialifos
0.05 1.0 2.0
94.1 ± 3.8 86.5 ± 4.5 87.4 ± 3.6
92.5 ± 489 91.6 ± 1.7 92.4 ± 3.3
79.9 ± 4.2 85.3 ± 2.9 89.1 ± 3.7
Dichlorvos
0.05 1.0 2.0
115.0 ± 3.9 107.5 ± 3.0 93.8 ± 3.7
93.0 ± 3.1 98.6 ± 4.1 94.4 ± 4.0
94.8 ± 3.2 95.3 ± 1.9 90.1 ± 2.7
Dieldrin
0.05 1.0 2.0
107.5 ± 3.0 93.8 ± 3.7 93.0± 3.1
90.7 ± 3.9 97.6 ± 1.7 95.2 ± 3.3
84.5 ± 3.9 81.4 ± 3.7 80.8 ± 3.0
Dimethoate
0.05 1.0 2.0
90.4 ± 4.3 90.0 ± 5.2 92.6 ± 4.5
91.6 ± 1.5 83.9 ± 3.9 86.3 ± 3.9
86.3 ± 3.9 95.2 ± 5.2 91.7 ± 4.6
Disulfoton
0.05 1.0 2.0
93.4 ± 2.5 99.5 ± 4.9 97.5 ± 4.8
83.4 ± 1.5 93.4 ± 2.4 90.6 ± 4.8
84.1 ± 1.9 94.4 ± 4.6 81.5 ± 2.4
Endosulfan (α - β)
0.05
90.9 ± 2.0
82.7 ± 4.0
90.1 ± 3.2
66
1.0 2.0
94.9 ± 3.2 89.8 ± 1.9
92.8 ± 2.5 97.9 ± 2.3
95.3 ± 2.9 89.1 ± 1.7
Endosulfan sulfate
0.05 1.0 2.0
98.9 ± 3.0 90.9 ± 12 92.7 ± 2.4
94.1 ± 1.9 97.8 ± 4.7 97.3 ± 1.3
93.1 ± 4.2 96.6 ± 3.7 99.7 ± 2.1
HCH Isomers (α – β – γ – δ )
0.05 1.0 2.0
98.6 ± 2.1 96.1 ± 1.2 93.1 ± 4.4
93.4 ± 2.1 98.6 ± 1.5 92.4 ± 3.8
95.8 ± 3.4 99.3 ± 2.0 90.6 ± 3.7
Heptachlor
0.05 1.0 2.0
91.4 ± 3.3 90.7 ± 2.2 98.5 ± 1.9
107.5 ± 3.0 97.0 ± 3.7 100.4 ± 4.0
101.1 ± 3.2 98.6 ± 2.3 93.1 ± 3.7
Malathion
0.05 1.0 2.0
96.7 ± 3.2 90.7 ± 1.8 96.9 ± 1.0
98.7 ± 2.9 90.6 ± 4.4 94.9 ± 1.3
92.7 ± 1.2 90.2 ± 3.6 97.5 ± 2.6
Metribuzin
0.05 1.0 2.0
103.9 ± 2.1 96.9 ± 3.0 93.9 ± 1.0
97.7 ± 2.0 91.2 ± 4.0 96.7 ± 1.3
98.3 ± 1.2 97.7 ± 3.4 94.1 ± 2.7
Parathion Methyl
0.05 1.0 2.0
90.1 ± 3.6 95.9 ± 1.5 99.8 ± 3.7
90.1 ± 3.9 93.7 ± 1.6 98.9 ± 3.0
97.9 ± 1.9 92.7 ± 4.1 99.6 ± 2.1
Parathion
0.05 1.0 2.0
105.7 ± 2.8 98.2 ± 4.1 90.5 ± 1.8
82.5 ± 3.0 90.1 ± 3.8 89.7 ± 1.7
93.0± 3.1 80.7 ± 4.9 88.5 ± 2.6
Propanil
0.05 1.0 2.0
94.8 ± 2.1 90.8 ± 3.1 98.5 ± 2.1
92.5 ± 1.6 90.9 ± 1.9 97.3 ± 2.8
90.5 ± 2.0 90.3 ± 1.9 99.2 ± 4.1
Tolyfluanid
0.05 1.0 2.0
90.4 ± 2.8
106.9 ± 2.9 94.1 ± 1.6
93.7 ± 3.9 90.7 ± 2.3 92.7 ± 1.3
98.3 ± 4.2 90.8 ± 1.0 95.7 ± 2.6
Triademofen
0.05 1.0 2.0
90.3 ± 3.9 90.1 ± 2.2 97.2 ± 4.0
90.5 ± 3.5 92.4 ± 1.9 97.8 ± 2.1
99.3 ± 1.3 90.6 ± 1.3 92.0 ± 2.5
DDT
0.05 1.0 2.0
107.3 ± 1.2 99.3 ± 1.0 97.5 ± 3.7
96.5 ± 3.2 90.4 ± 1.4 90.7 ± 2.1
92.8 ± 2.0 95.0 ± 3.0 97.3 ± 4.8
Phosdrin
0.05 1.0 2.0
90.9 ± 3.1 99.9 ± 4.8
104.9 ± 1.5
90.3 ± 1.4 94.6 ± 1.8 98.0 ± 3.0
90.7 ± 4.9 95.6 ± 3.9 94.3 ± 3.0
a n = 5. b Relative standard deviation.
67
4.2.3.3 Recovery
Those samples which were initially analyzed to make sure the nonexistence of
pesticides studied were fortified at 0.05, 1.0 and 2.0 μg g-1 earlier than extraction and
analyzed for recovery study of the proposed method by GC-μECD. The average recoveries
achieved are exposed in Table 4.2.2. The recoveries gained for all pesticides ranged as of 90
to 107.5% with RSDs of <6%.
4.2.3.4 Detection and Quantification limits
Blank samples were used for the determination of detection and quantification limits
of each pesticide. By taking into consideration a value 3 times of the background noise
attained for blank samples limit of detection (LOD) of the proposed method has been
determined, and the LOQs were established considering a value 10 times the background
noise. A summarized data for LODs and LOQs obtained for the individual pesticides in the
different samples are shown in Table 4.2.3.
68
Table 4.2.3. Limits of detection (LOD, μg kg-1) and limits of quantification (LOQ μg kg-1)
of pesticides assayed by GC-μECD.
Pesticide Limits of detection (LOD, μg kg-1)
Oranges Apple Grapes
Limits of quantification (LOQ, μg kg-1)
Oranges Apple Grapes Aldrin 0.3 0.3 0.3 1.0 1.1 1.0 Allethrin 0.5 0.4 0.6 1.7 1.7 1.8 Bromacil 0.5 0.5 0.4 1.9 1.7 1.9 Bromophos Methyl 0.6 0.6 0.6 2.0 2.1 1.9 Bromophos Ethyl 0.6 0.5 0.4 2.2 1.8 2.0 Captan 0.6 0.4 0.6 2.1 2.0 2.1 Chlorpyrifos 1.8 2.1 2.0 6.2 6.0 6.1 Chlorpyrifos Methyl 0.6 0.5 0.6 2.3 2.2 2.0 Dialifos 7.9 7.5 7.0 26.3 26.0 26.3 Dichlorvos 1.5 1.5 1.4 5.0 4.9 5.1 Dieldrin 19.3 19.3 191 64.4 64.0 64.4 Dimethoate 1.7 1.7 1.7 5.9 5.8 5.9 Disulfoton 12.8 12.7 12.4 42.7 42.8 42.1 Endosulfan (α - β) 0.4
0.7 0.3 0.8
0.4 0.9
1.4 2.4
1.1 2.0
1.5 2.4
Endosulfan sulfate 0.3 0.4 0.3 1.0 1.2 1.0 HCH Isomers (α – β – γ – δ )
0.9 2.5 1.2 1.0
1.1 2.3 1.2 1.1
0.9 2.4 1.2 1.0
3.2 8.5 4.1 3.3
3.0 8.1 4.2 3.2
3.0 8.3 4.0 3.3
Heptachlor 0.2 0.2 0.2 0.8 0.8 0.8 Malathion 1.7 1.7 1.9 5.9 6.0 5.8 Metribuzin 0.8 0.6 0.7 2.7 2.9 2.9 Parathion Methyl 0.8 1.0 0.8 2.8 3.0 2.7 Parathion 0.7 0.8 0.7 2.6 2.4 2.5 Propanil 1.9 1.4 1.7 6.5 6.9 6.5 Tolyfluanid 0.2 0.5 0.2 0.8 0.7 0.8 Triademofen 7.4 7.0 7.1 24.8 20.1 24.5 DDT 3.7 4.0 3.9 12.6 13.0 12.6 Phosdrin 42.4 42.9 42.8 141.2 140.1 141.0
69
Table 4.2.4. Selected ions from MS of the studied pesticides.
Pesticide tR, min MS
Selected ions (m/z)
Aldrin 8.40 293, 263, 221
Allethrin 8.86 91,123, 136
Bromacil 8.18 207, 205, 231
Bromophos Methyl 8.65 331, 125
Bromophos Ethyl 9.19 303, 359, 331
Captan 8.98 79, 264, 299
Chlorpyrifos 8.41 197, 199, 258, 314
Chlorpyrifos Methyl 7.65 208, 288, 286
Dialifos 12.73 76, 181, 357
Dichlorvos 4.29 145, 141
Dieldrin 9.83 277, 345
Dimethoate 6.82 199, 230
Disulfoton 7.30 109, 157
Endosulfan (α - β) 9.44
10.37
195, 241, 339
195, 241, 339
Endosulfan sulfate 11.01 272, 387, 420
HCH Isomers
(α – β – γ – δ )
6.68
7.00
7.10
7.38
111,181, 219
111,181, 219
111,181, 219
111,181, 219
Heptachlor 7.99 100, 272
Malathion 8.24 127, 158, 173
Metribuzin 7.74 198, 144, 182
Parathion Methyl 7.85 109, 263, 125
Parathion 8.39 125, 291
Propanil 7.69 161, 217
Tolyfluanid 8.89 137, 238, 106, 63
Triademofen 8.44 208, 128, 181
DDT 11.00 165, 235, 237
Phosdrin 5.08 109, 127, 192
70
4.2.3.5 Confirmation by GC-MS
Identity of the targeted pesticides was verified by GC-MS by means of SIM mode. A
solution of standard mixture was previously run to obtain a total ion chromatogram for the
determination of their main ions and retention times. In Table 4.2.4, retention times and main
ions for the pesticide studied are shown. All of these pesticides can easily be identified by
their main ions by searching in the MS PEST library.
4.2.3.6 Evaluation of method
Proposed method applied to the real fruit samples to determine pesticide residue
levels, purchased from local markets. Pesticide levels encountered in the collected samples
(apple, grape, and orange), their ranges, frequencies and averages all are summarized in
Table 4.2.5.
71
Table 4.2.5. Summarized results of pesticide residues found in monitoring study of fruits.
Fruits No. of
samples collect
Contaminated Violating MRL
Pesticides found Frequency Range (min:max) (μg kg-1)
Average (μg kg-1)
Apple 20 08 03 Dieldrin Disulfoton Endosulfan sulfate Parathion Chlorpyrifos
03 04 03 05 07
05-196 98-298 43-110 256-681 278-530
100.5 198 76.5
468.5 404
Orange 18 05 02 Dieldrin Disulfoton Endosulfan sulfate Parathion Triadimefon Chlorpyrifos
02 02 02 03 03 04
90-187 08-280 2.8-10
340-149 14-710 280-570
138.5 179 6.4
244.5 362 425
Grape 15 04 01 Disulfoton Endosulfan sulfate Parathion Chlorpyrifos
03 01 02 04
45-280 0.9
59-150 60-680
162.5 0.9
104.5 370
72
4.3 Monitoring of Pesticide Residues in Commonly Used Fruits
For identification, the major ions (m/z) and retention times (tR) both were considered
and shown in Table 4.3.1. Maximum residue levels (MRLs) of the selected pesticides in
different fruits were shown in Table 4.3.2. For allethrin, bromacil, bromophos-methyl and
dialifos no MRLs established so far. Data given in Table 4.3.3. shows that 42 fruit samples
including apple, grape and orange, collected from fruit market No.1, were evaluated for 26
pesticides. In analyzed samples, level of chlorpyrifos was found to be exceeded MRL with
the highest concentration of 1256 μg/kg in apple, followed by disulfoton with concentration
of 398μg/kg in orange, which was within the MRL. Dieldrin was detected in 2 samples of
apple and 1 sample of orange. Maximum concentration (37μg/kg) was observed in apple.
Similarly, the fungicide, triadimefon was found only in 2 samples of apple (114 μg/kg),
which was below the MRL. Residues of insecticides, parathion (in 2 samples) and disulfoton
(in 1 sample) were also detected in the orange samples. Maximum levels of both pesticides
were detected as 311μg/kg and 398μg/kg, respectively.
73
Table 4.3.1. Pesticide names, chemical active group, usage, molecular weight, retention
times and selected MS main ions (m/z).
Pesticides Group Use MW tR, min MS Selected ions (m/z)
Dichlorvos Organophosphate Insecticide 221 4.29 109, 145, 185 Phosdrin Organophosphate Insecticide 224 5.08 109, 127, 192
α -HCH Organochlorine Insecticide 288 6.68 111,181, 219
Dimethoate Organophosphate Insecticide 229 6.82 87, 125
β-HCH Organochlorine Insecticide 288 7.00 111,181, 219 γ -HCH Organochlorine Insecticide 288 7.10 111,181, 219
Disulfoton Organophosphate Insecticide 274 7.30 109, 157
δ -HCH Organochlorine Insecticide 288 7.38 111,181, 219
Chlorpyrifos Methyl Organophosphate Insecticide 322 7.65 208, 288, 286 Propanil Acylanilide Herbicide 218 7.69 161, 217
Metribuzin Triazine Herbicide 214 7.74 198, 144, 182
Parathion Methyl Organophosphate Insecticide 263 7.85 109, 263, 125
Heptachlor Organochlorine Insecticide 389 7.99 100, 272 Bromacil Uracils Herbicide 261 8.18 207, 205, 231
Malathion Organophosphate Insecticide 330 8.24 127, 158, 173
Parathion Organophosphate Insecticide 291 8.39 125, 291
Aldrin Organochlorine Insecticide 364 8.40 293, 263, 221 Chlorpyrifos Organophosphate Insecticide 349 8.41 197, 199, 258, 314
Triadimefon Triazole Fungicide 293 8.44 208, 128, 181
Bromophos Methyl Organophosphate Insecticide 366 8.65 331, 125
Allethrin Pyrethroid Insecticide 302 8.86 91,123, 136 Tolyfluanid Phenylsulfamide Fungicide 347 8.89 137, 238, 106, 63
Captan Phthalimide Fungicide 300 8.98 79, 264, 299
Bromophos Ethyl Organophosphate Insecticide 394 9.19 303, 359, 331
α-Endosulfan Organochlorine Insecticide 406 9.44 195, 241, 339 Dieldrin Organochlorine Insecticide 378 9.83 277, 345
β -Endosulfan Organochlorine Insecticide 406 10.37 195, 241, 339
DDT Organochlorine Insecticide 354 11.00 165, 235, 237
Endosulfan sulfate Organochlorine Insecticide 422 11.01 272, 387, 420 Dialifos Organophosphate Insecticide 393 12.73 76, 181, 357
74
Table 4.3.2. Maximum residue limits (MRLs) of targeted pesticides.
Pesticides MRLs, (µg/kg)a
Apple Grape Orange Aldrin 50 100 50
Allethrin NE* NE NE
Bromacil NE NE NE
Bromophos Methyl NE NE NE
Bromophos Ethyl 50 50 50
Captan 15000 25000 15000
Chlorpyrifos 1000 500 1000
Chlorpyrifos Methyl 500 200 500
Dialifos NE NE NE
Dichlorvos 100 100 100
Dieldrin 50 100 50
Dimethoate 2000 2000 5000
Disulfoton 500 500 500
α - Endosulfan 2000 2000 2000
β - Endosulfan 2000 2000 2000
Endosulfan sulfate 2000 2000 2000
α -HCH 3000 3000 3000
β -HCH 3000 3000 3000
γ -HCH 3000 3000 3000
δ -HCH 3000 3000 3000
Heptachlor 10 10 10
Malathion 20 20 20
Metribuzin 100 100 100
Parathion Methyl 200 500 200
Parathion 500 500 500
Propanil 100 100 100
Tolyfluanid 5000 3000 50
Triadimefon 300 500 100
DDT 1000 1000 1000
Phosdrin 10 10 10
*NE = Not established, aAccording to Codex Alimentarius Commission and www.pmfai.org/stat.htm.
75
Table 4.3.3. Pesticide residue levels (µg/kg) found in fruits collected from fruit market
No.1. Pesticides Pesticide levels in (µg/kg)
Apple Grape Orange
Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg)
Chlorpyrifos 03 231-1256a 01 205 02 145-243
Parathion _ _ _ _ 02 102-311
Dieldrin 02 21-37 _ _ 01 13
Endosulfan sulfate
01 134 01 81 01 213
Triadimefon 02 37-114 _ _ _ _
Disulfoton _ _ _ _ 01 398
a Exceed the MRL.
76
Table 4.3.4. Pesticide residue levels (µg/kg) found in fruits collected from fruit market
No.2.
Pesticides Pesticide levels in (µg/kg)
Apple Grape Orange Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg)
Chlorpyrifos 02 167-684 02 05-401 02 253-1119a
Parathion 01 73 _ _ _ _
Dieldrin 02 11-34 _ _ 02 23-41
Endosulfan sulfate
02 14-307 01 15 01 117
Triadimefon 01 19 _ _ 01 34
a Exceed the MRL.
77
The levels of pesticides in 39 samples of fruits which were collected from the fruit
market No. 2 are shown in Table 4.3.4. Similar to the results of market No. 1, chlorpyrifos
was detected in higher concentration (1119 μg/kg) in orange and crossed the MRL, followed
by endosulfan sulfate with the concentration of 307μg/kg in apple, and also found in one
sample of orange with concentration of 117μg/kg. Only one sample of apple was
contaminated with parathion with the level of 73μg/kg. While, dieldrin was found in 2
samples of apple and 2 samples of orange of the market number 2 with the concentrations of
34μg/kg and 41 μg/kg, respectively, under MRL. The results also showed that, in 1 sample of
apple and 1 sample of orange residues of the fungicide triadimefon were detected with the
concentrations of 19μg/kg and 34μg/kg, respectively.
The data given in Table 4.3.5 demonstrated pesticide residue levels (μg/kg) found in
fruits collected from fruit market No. 3 of Hyderabad region. 50 fruit samples were collected
from this fruit market. In these samples, endosulfan sulfate and chlorpyrifos were found to in
greater concentration of 1236 μg/kg and 1091 μg/kg in orange and apple, respectively and
chlorpyrifos was exceeded the MRL. Chlorpyrifos also found in 2 samples of grapes and 2
samples of orange with the level of 172μg/kg and 882μg/kg, respectively. The samples of
apple and grapes were also found to be contaminated with the residues of insecticide
endosulfan sulfate with concentrations of 210μg/kg in apple and 55μg/kg in grapes. The
insecticide parathion was the only pesticide found in orange fruit of the main fruit market
number 3 with concentration of 21μg/kg. Dieldrin was the another insecticide found in 2
samples of apple with maximum concentration of 30 μg/kg and in 2 samples of orange with
the concentration of 41 μg/kg, which are under their MRLs. Residues of disulfoton were
detected in 1 sample of apple with concentration of 46 μg/kg and in 1 sample of orange with
the concentration of 31 μg/kg.
78
Table 4.3.5. Pesticide residue levels (µg/kg) found in fruits collected from fruit market
No.3.
Pesticides Pesticide levels in (µg/kg)
Apple Grape Orange Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg) Contaminated Min-Max(µg/kg)
Chlorpyrifos 03 328-1091a 02 26-172 02 345-882
Parathion _ _ _ _ 01 21
Dieldrin 02 14-30 _ _ 02 26-41
Endosulfan sulfate
01 210 01 55 03 13-1236
Disulfoton 01 46 _ _ 01 31
a Exceed the MRL.
79
Table 4.3.6. Total number of samples collected from all markets, frequencies of
pesticides found and number of samples exceeds MRLs.
Fruits Total samples
Pesticide type
Pesticide Name
Frequency Above MRLs
Apple
47
Insecticide Fungicide
Chlorpyrifos
Dieldrin
Endosulfan
sulfate
Parathion
Disulfoton
Triadimefon
08
06
04
01
01
03
02
_
_
_
_
_
Grape 41 Insecticide Chlorpyrifos
Endosulfan
sulfate
05
03
_
_
Orange 43 Insecticide
Fungicide
Chlorpyrifos
Dieldrin
Endosulfan
sulfate
Parathion
Disulfoton
Triadimefon
06
05
05
03
02
01
01
_
_
_
_
_
80
In this study, the residues of targeted pesticides were evaluated in 131 samples of
apple, grapes and orange obtained from the three fruit markets i.e. Towns Latifabad (market
number 1), Qasimabad (market number 2) and main Hyderabad city (market number 3). In
the analyzed samples, 7 pesticides belonging to the different chemical groups
(organophosphates, organochlorines and triazole) with different properties (6 insecticides and
1 fungicide) were detected. Total number of samples collected from each market, identified
classes of pesticides and numbers of samples above to the MRLs are illustrated in Table
4.3.6. Out of total 131 samples analyzed, 53 samples (40%) contained detectable amount of
pesticide residues, however in remaining 78 samples (60%) no pesticide residues were
detected. Out of which 3 samples (6%) were exceeded the MRLs, whereas 50 samples (94%)
contained pesticide residues below the MRLs. Most frequently detected pesticide was
chlorpyrifos (insecticide) found in 19 samples (36%), followed by the endosulfan sulfate
(insecticide) in 12 samples (23%) and dieldrin (insecticide) in 11 samples (21%). According
to the results, level of chlorpyrifos was exceeded from the MRL in 2 samples. Out of 43, 22
samples of oranges (51%) were found to be contaminated with pesticides with 1 sample (2%)
above the MRL. Similarly, on the bases of pesticides contamination, apple was found to be
second fruit, as 23 out of 47 samples (49%) were found to be contaminated and 2 samples
(4%) exceeded the MRLs. Grapes was the commodity contained lowest number of pesticides
contamination i.e. 8 out of total 41 samples (36%) found to be adulterated. No any
contaminated sample of grapes was found above to be above MRL. The results of the study
also shows that pesticides which was detected in greater amount was chlorpyrifos with the
concentration of 1256 μg/kg (apple), followed by endosulfan sulfate with level of 1236 μg/kg
(orange), while the concentrations of disulfoton, parathion, triadimefon and dieldrin were 398
81
μg/kg (orange), 311 μg/kg (orange), 114 μg/kg (apple) and 41 μg/kg (orange), respectively.
Frequent occurrence of pesticide residues in fruits may be due to the lack of awareness of the
growers about the dosage, right ways of application and the suitable interval between
harvesting and pesticide treatment. The carelessness or non-availability of correct guidance
concerning the pesticide application may be another reason for pesticide residues in the fruit
samples. These contaminated fruits are potential health risks to the consumers. In terms of
pesticide residues some of the samples contained more than one residue. The rationale for
that might be that fruits cultivated in greenhouse conditions are very much sensitive to pests
and be required to for consecutive applications of pesticide treatments, leaving in result
higher amount of residues that abided and defended from quick degradation by direct
sunbeams. In Hyderabad region, the misuse or overuse of pesticides and casual combinations
of pesticides of different groups without any prior guidance and knowledge are become
serious problems. The improper use of pesticides shows the way to terrific financial losses
and dangers to human health. Some studies have been already reported regarding the
pesticide residues in different fruits at different periods (Tahir et al., 2001; Ahmad, 2004;
Anwar et al., 2004; Hussain et al., 2004; Parveen et al., 2004 & 2005; Hassan et al., 2007).
Their data on fruits shows that the levels of pesticide residues were greater as compare to
present study. Taken as a whole, consumption of pesticides in the country was decreased
from 41406 tons in 2003-2004 to 20394 tons in the period of 2006-2007. Decline in number
of samples not exceeding MRLs may be associated with decrease in quantity of pesticide
consumption.
82
The outcomes of the present study authenticate the existence of pesticides such as
chlorpyrifos, dieldrin, endosulfan sulfate, parathion, disulfoton and triadimefon in fruit
samples which were applied in pre-harvest treatment. To avoid adverse effects on public
health it is a necessity to set up control measures so as to make sure that each pesticide
should be below MRLs in the fruits to be marketed. The study has presented significant
information regarding pesticide residues contamination on fruits from Hyderabad region. On
the bases of achieved results, it is recommended that regular evaluation of pesticide residue
should be carried out on each fruit for the planning and future policy about the formulation of
standards and quality control of pesticides.
83
4.4 Assessment of pesticide residues in human blood samples
Detail about the total number of volunteers containing the region, sex, male to female
ratio and their mean ages are shown in Table 4.4.1. Out of 110 volunteers from Hyderabad
district, 83 were agro-professionals (in which males and females were 61 and 22,
respectively) and 27 were non-agro professionals (in which 18 were males and 9 were
females). The mean age of volunteers from the Hyderabad district was 26.68 years with
standard deviation (S.D) of 10.6. Blood samples of 78 volunteers belong to Mirpurkhas
district were assessed, out of which 62 were agro-professionals (48 males and 14 females)
and 16 volunteers were non-agro professionals (13 were males and 3 were females). The
mean age of volunteers from Mirpurkhas district was 25.34±5.8.
To simplify the data analysis, volunteers of agro-professional were further
categorized according to their exposure period in farming activities i.e., Group A- 5 to 9
years, Group B- 10 to 14 years, Group C- 15 to19 years and Group D- above 20 years. The
detail of agro professional volunteers, their exposure duration, percentages of classified
groups with respect to total volunteers and proportions of residues detected in their blood
samples is shown in Table 4.4.2.
Out of total 83 agro professional volunteers from the Hyderabad district, pesticide
residues were detected in 59 (71.1%) volunteers. A comparatively high percentage (47.4%)
was found in volunteers of the C group from the Hyderabad district who have detected
residues in their blood samples, following 28.8% and 15.2% in D and B groups, respectively.
While 8.5% volunteers were members of group A in which pesticide residues were detected.
Similarly, out of total 62 agro professional volunteers from the Mirpurkhas district, 45
volunteers (72.6%) were found to be contained pesticide residues in their blood samples.
84
Table 4.4.1. Location, No. of volunteers assessed, agro and non-agro professionals lived
in agricultural environment, male / female ratios and their mean age with S.D.
S. No. Location No. of Volunteers assessed
Agro professionals
Non-Agro professionals
Age ± S.D
01 Hyderabad Male/female
110 79/31
83 61/22
27 18/9
26.68 ± 10.6
02 Mirpurkhas Male/female
78 61/17
62 48/14
16 13/3
25.34 ± 5.8
Total Male/female
188 140/48
145 109/36
43 31/12
85
Table 4.4.2. Number of agro-professional volunteers with their exposure duration, and proportions of each group with respect to the total number of residues detected volunteers.
Location Exposure
duration (years)
No. of volunteers assessed
No. with residues detected
Proportion (%)
Hyderabad (A) 5–9 18 05 8.5
(B) 10–14 11 09 15.2
(C) 15–19 35 28 47.4
Total
(D) Over 20 19
83
17
59
28.8
Mirpurkhas (A) 5–9 07 03 6.6
(B) 10–14 17 11 24.4
(C) 15–19 32 25 55.5
Total
(D) Over 20 06
62
06
45
13.3
Table 4.4.3. Number of non-agro professional volunteers who have detected pesticide residues in their blood samples.
Location No. of volunteers
assessed No. with residues detected
Proportion (%)
Hyderabad 27 09 33.3
Mirpurkhas 16 04 25
86
A relatively high percentage (55.5%) was found in the group C of Mirpurkhas district
who have detected pesticide residues in their blood samples, following 24.4% and 13.3% in
the B and D groups, respectively. Only 6.6% volunteers belonged to the A group were found
to be contaminated their blood samples with pesticide residues.
Table 4.4.3 shows that out of total 27 non-agro professional volunteers from
Hyderabad district, 9 volunteers (33.3%) were contained pesticide residues in their blood
samples. Similarly, out of total 16 non-agro professional volunteers from Mirpurkhas district,
4 volunteers (25%) were found to be positive for pesticide residues in their blood samples.
Data in Table 4.4.4 illustrates the number of residue detected in agro-professional
volunteers with their years of exposure, and mean concentrations of pesticide residues found
in their blood samples. In 59% volunteers from the Hyderabad district, the residues of
chlorpyrifos were detected in their blood samples with the highest mean concentration of
0.29 mg kg-1 in group D; while, residues of endosulfan, parathion and p-p–DDT were found
in 34%, 5% and 2% volunteers with the mean concentrations of 0.3, 0.15 and 0.17 mg kg-1,
respectively. Residues of parathion and p-p–DDT were not detected in the blood samples of
volunteers belonged to the A group. Similarly, volunteers in the B and C groups had not
detected residues of p-p–DDT in their blood samples. Furthermore, in group D of Hyderabad
district no any volunteer was found to be contaminated with residues of parathion in their
blood samples. Out of total 45 agro-professional volunteers from Mirpurkhas district, 51%
had residues of chlorpyrifos, and 36% had detected endosulfan residues in their blood
samples with mean concentrations of 0.37 and 0.29 mg kg-1, respectively. While, residues of
parathion and p-p–DDT were detected in about 11% and 5% of the volunteers with mean
concentrations of 0.31 and 0.20 mg kg-1, respectively. Volunteers of group A and B
belonging to Mirpurkhas district, were not shown any residues of p-p–DDT in their blood
87
samples. Whereas, residues of parathion were also not detected in the blood samples of
volunteers belonged to group A of Mirpurkhas district.
Table 4.4.5 shows out of total 9 non-agro professional volunteers from the Hyderabad
district, 5 volunteers (55%) had residues of chlorpyrifos and in 4 volunteers (45%) were
detected for endosulfan residues with mean concentrations of 0.1 and 0.14 mg kg-1,
respectively. From Mirpurkhas district, out of 4 non-agro professional volunteers, 2
volunteers (50%) were found to be positive for chlorpyrifos residues with a mean
concentration of 0.08 mg kg-1 in their blood samples. From the remaining 2 volunteers, 1
volunteer had residues of endosulfan and other had residues of p-p–DDT with concentrations
of 0.11 and 0.06 mg kg-1, respectively.
Table 4.4.6 shows mean concentrations and ranges of detected pesticide residues
based on the gender of agro-professional volunteers. According to the results, out of total 35
volunteers who had residues of chlorpyrifos from the Hyderabad district, 28 volunteers
(80%) were males with ages between 16 to 45 years, (20%) were females of ages between 22
to 51 years containing mean concentrations of 0.17 mg kg-1 and 0.15 mg kg-1, respectively.
The blood samples of 11 male volunteers (55%) out of total 20 were found to be positive for
the endosulfan residues. Their ages were ranged between 14 to 55 years with a mean
concentration of 0.21 mg kg-1.
88
Table 4.4.4. Number of residue detected agro-professional volunteers with their years of exposure, and mean concentrations of pesticide residues found in their blood samples.
Location Exposure
duration (years)
No. with residues detected
Number with mean pesticide concentration (mg kg-1)
Chlorpyrifos Endosulfan p-p DDT Parathion
Hyderabad (A) 5–9 05 03 (0.07) 02 (0.17) 00 (0.0) 00 (0.0)
(B) 10–14 09 05 (0.11) 03 (0.26) 00 (0.0) 01 (0.15)
(C) 15–19 28 15 (0.18) 11 (0.15) 00 (0.0) 02 (0.13)
(D) Over 20 17 12 (0.29) 04 (0.30) 01 (0.17) 00 (0.0)
Mirpurkhas (A) 5–9 03 01 (0.10) 02 (0.15) 00 (0.0) 00 (0.0)
(B) 10–14 11 07 (0.28) 03 (0.21) 00 (0.0) 01 (0.16)
(C) 15–19 25 12 (0.25) 09 (0.29) 01 (0.20) 03 (0.24)
(D) Over 20 06 03 (0.37) 02 (0.16) 01 (0.14) 01 (0.31)
Table 4.4.5. Number of residue detected non-agro professional volunteers with their years of exposure, and mean concentrations of pesticide residues found in their blood samples.
Location No. with residues detected
Number with mean pesticide concentration (mg kg-1)
Chlorpyrifos Endosulfan p-p–DDT
Hyderabad 09 05 (0.10) 04 (0.14) 00 (0.0)
Mirpurkhas 04 02 (0.08) 01 (0.11) 01 (0.06)
89
While, remaining 9 volunteers (45%) were females having ages between 27 to 39
years with a mean concentration of 0.16 mg kg-1. Only one blood sample of male volunteer
was found to be positive for p-p–DDT residues with age of 55 years and mean concentration
of 0.17 mg kg-1. Whereas, no blood samples of any female volunteer of Hyderabad district
was found to be positive for p-p–DDT residues. Out of total 3 volunteers, parathion residues
were found in 2 male volunteers (67%) of ages 43 and 54 years with a mean concentration of
0.13 mg kg-1, and 1 female volunteer of age 37 years with a concentration of 0.11 mg kg-1.
Out of the total 23 volunteers from Mirpurkhas district who had residues of chlorpyrifos, 17
volunteers (74%) were males with ages between 26 to 67 years and 6 volunteers (26%) were
females of ages between 30 to 45 years with mean concentrations of 0.21 and 0.17 mg kg-1,
respectively. While from total 16 volunteers who found to be positive for endosulfan
residues, 9 volunteers (56%) were males and 7 volunteers (44%) were females of ages
between 18 to 59 and 17 to 49 years with mean concentrations of 0.28 and 0.18 mg kg-1,
respectively. No any blood sample of female volunteers was found to be contaminated with
the residues of p-p–DDT in Mirpurkhas district as well, whereas 2 male volunteers of ages 34
and 61 years had residues of p-p–DDT in their blood samples with a mean concentration of
0.17 mg kg-1. The blood samples of 3 male volunteers (60%) out of total 5 were found to be
positive for parathion residues. Their ages were ranged between 37 to 48 years with a mean
concentration of 0.25 mg kg-1. While remaining 2 volunteers (40%) were females of ages 49
and 53 years with a mean concentration of 0.18 mg kg-1.
90
Table 4.4.6. Mean concentrations and range of detected pesticide residues based on the
gender of agro-professional volunteers.
Location Pesticides detected & Gender
No. of volunteers
Age range Residue concentrations (mg kg-1)
Range Mean
Hyderabad Chlorpyrifos
M
F
28
07
16–45
22–51
0.04–0.31
0.02–0.28
0.17
0.15
Endosulfan
M
F
11
09
14–55
27–39
0.08–0.35
0.05–0.28
0.21
0.16
p-p–DDT
M
F
01
–
55
–
0.17
–
0.17
–
Parathion
M
F
02
01
43–54
37
0.09–0.18
0.11
0.13
0.11
Mirpurkhas Chlorpyrifos
M
F
17
06
26–67
30–45
0.05–0.41
0.03–0.36
0.21
0.17
Endosulfan
M
F
09
07
18–59
17–49
0.06–0.44
0.08–0.34
0.28
0.18
p-p–DDT
M
F
02
–
34–61
–
0.14–0.20
–
0.17
–
Parathion
M
F
03
02
37–48
49–53
0.15–0.34
0.09–0.28
0.25
0.18
91
The data in Table 4.4.7 shows the mean concentrations and ranges of detected
pesticide residues based on the gender of non-agro professional volunteers. Out of total 5
volunteers from Hyderabad district, 4 volunteers (80%) were males of ages between 24 to 62
years and 1 volunteer (20%) was female of age 45 years found to contained residues of
chlorpyrifos in their blood samples with mean concentrations of 0.07 and 0.03 mg kg-1,
respectively. Out of total 4 volunteers who were found to be positive for the residues of
endosulfan in their blood samples, 2 volunteers (50%) were males of ages 17 and 43 years
and other 2 volunteers (50%) were females of ages 44 and 56 years with mean concentrations
of 0.10 and 0.11 mg kg-1, respectively. In Mirpurkhas district, chlorpyrifos were detected in
the blood samples of 2 male volunteers of ages 36 and 49 years with a mean concentration of
0.08 mg kg-1. The residues of endosulfan were detected in only one female volunteer of age
35 years with a concentration of 0.11 mg kg-1. Whereas, no any blood sample of male
volunteers from Mirpurkhas district was found to be positive for endosulfan residues. In only
one male volunteer of age 58 years the residues of p-p–DDT were detected with a
concentration of 0.06 mg kg-1, while no any blood sample of female volunteers was found to
be contaminated with the residues of p-p–DDT.
The pesticides detected in the blood samples of volunteers selected for this study are
classified as insecticides, generally used by the farm workers to control different kinds of
pests to protect their crops. The pattern showed by the two populations (Hyderabad and
Mirpurkhas) was found to be almost similar. This may be due to the same climatic conditions
and farming activities.
92
Table 4.4.7. Mean concentrations and range of detected pesticide residues based on the
gender of non-agro professional volunteers.
Location Pesticides detected & Gender
No. of volunteers
Age range Residue concentrations (mg kg-1)
Range Mean
Hyderabad Chlorpyrifos
M
F
04
01
24–62
45
0.04–0.11
0.03
0.07
0.03
Endosulfan
M
F
02
02
17–43
44–56
0.08–0.13
0.05–0.17
0.10
0.11
Mirpurkhas Chlorpyrifos
M
F
02
–
36–49
–
0.06–0.10
–
0.08
–
Endosulfan
M
F
–
01
–
35
–
0.11
–
0.11
p-p–DDT
M
F
01
–
58
–
0.06
–
0.06
–
93
Chlorpyrifos and endosulfan were the pesticides detected in most of the samples
taken from both districts. Out of total 104 agro-professional volunteers who found to be
contaminated with different pesticide residues in their blood samples, the residues of
chlorpyrifos were detected in 58 volunteers (56%), while residues of endosulfan were
detected in 36 volunteers (35%). Out of total 13 non-agro professional volunteers who had
pesticide residues in their blood samples, the residues of chlorpyrifos were detected in 7
volunteers (54%); while, residues endosulfan were detected in 5 volunteers (38%). The
representative chromatograms of blood samples containing residues of chlorpyrifos and
endosulfan with their respective mass spectrums have been shown in Fig. 4.4.1. Chlorpyrifos
is an organophosphate (OPs) insecticide. It is moderately persistent and toxic in nature and
suspected endocrine disruptor. It has found to be very effective against fly larvae, cabbage
root fly and aphids. Because of its most widely used in homes against mosquito, cockroaches
and termites it may be one reason of exposure for the non-agro professional volunteers. On
the other hand, endosulfan is an organochlorine insecticide and acts as a poison to a spacious
range of mites and insects on contact and as a stomach acaricide. Endosulfan has become
known as an extremely controversial agrichemical by reason of its function as an endocrine
disruptor, acute toxicity, and bioaccumulation potential. The technical grade endosulfan is a
mixture of α and β isomers in the ratio of 7:3, respectively. Comparatively, α isomer of
endosulfan insecticide has been found to be three times more toxic than the β isomer. It has
been noticed during data collection about the clinical history of agro-professional volunteers,
most of the volunteers (who had pesticide residues in their blood samples) complained of
vomiting, diarrhea, respiratory depression, productive cough, loss of consciousness, tingling
or creeping on skin, severe headache, nausea and general body weakness or tiredness, which
are the signs and symptoms of chlorpyrifos and endosulfan poisoning.
94
Representative chromatograms of blood samples containing chlorpyrifos (A) and
endosulfan (B) with their confirmative main ion fragments shown in mass
spectrum.
A
B
Fig 4.4.1.
95
Because of deficiencies in schooling, knowledge and broad information regarding the
application of pesticides from government associations / activities in these regions, farm
workers are suffering and getting unwell outcomes of pesticides during inappropriate usage,
discarding and predominantly when they are not sheltered with special protecting equipments
(gloves, rubber boots, safety goggles, masks, overalls with long sleeves etc.). The presence of
pesticide residues in volunteers (non-agro professionals) is also very alarming and indicative
of environmental exposure. After studying various other factors it is assumed that the
presence of chlorpyrifos and endosulfan residues in the blood of non-agro professional
volunteers may be due to the massive use of these pesticides since last couple of decades, or
may be other potential sources involved such as impurity of other pesticides or the direct use
of chlorpyrifos and endosulfan as pesticides. Based on gender, we observed prevalence
between males rather than females of both populations as shown in Table 4.4.6, but residue
levels did not show any statistically significant difference.
In conclusion, the results of our study will form part of an up-to-date report on the
contamination level of Hyderabad and Mirpurkhas regions including all kinds of populations
of different socioeconomic characteristics, which will make it promising to identify the
sources and trends of this contamination. Our study has shown that the volunteers monitored
from both groups (agro and non-agro professionals) have been occupationally and
environmentally exposed due to the excessive use of insecticides for pest control in their
areas of cultivations. There is a need to revitalize the pesticide regulation in view of the types
of insecticides commonly used and the residues detected in their blood. From this study, it is
also concluded that the existence of chlorpyrifos and endosulfan with higher frequencies are
being hauled the entire population towards numerous health hazards, so for now, the global
restrictions for the use of these pesticides should be observed in Pakistan.
CONCLUSIONS
CONCLUSIONS
96
CONCLUSIONS A new method has been proposed on GC-MS for rapid determination of pesticide residues
in various vegetables.
The results shows that from the total 200 vegetable samples, 61% of were found to be
contaminated with pesticide residues above MRL, which could pose adverse effects on the
health of consumers.
Carbofuran and chlorpyrifos were the most frequently detected pesticides in vegetable
samples suggesting that these pesticides were commonly used by vegetable growers in
Hyderabad region.
Among all vegetables, cauliflower was found prominent for detecting 84% samples above
MRL may be due to lack of awareness of farmers about application dose, methods of
application and appropriate interval between harvesting and pesticide treatment.
A simple, effective and quick method based on determination of 26 pesticides in fruits
using GC-µECD with extraction assisted by sonication and SPE clean-up has been
developed.
With the proposed method requirement of organic solvents for the extraction procedure
reduced as the sonication endow with improved extraction, which could be very obliging
into reducing the danger for human health and the environment with short time consuming
as well.
The good reproducibility, accuracy and low detection and quantification limits of the
proposed method allow its application for the accurate determination of pesticide residues
in fruits.
97
Investigation of real fruit samples illustrated the validity of method used and also
authenticates the existence of pesticides such as chlorpyrifos, dieldrin, endosulfan sulfate,
parathion, disulfoton and triadimefon in fruit samples which were applied in pre-harvest
treatment.
The study has presented significant information regarding pesticide residues contamination
on fruits from Hyderabad region.
From the results it can be concluded that farmers were not followed proper precautions
with regard to use of pesticides in appropriate dose and standard pre-harvest intervals
(PHI).
The results of study on blood samples will form part of an up-to-date report on the
contamination level of Hyderabad and Mirpurkhas regions including all kinds of
populations of different socioeconomic characteristics, which will make it promising to
identify the sources and trends of this contamination.
It is indicated by the results that the volunteers monitored from both groups (agro and non-
agro professionals) have been occupationally and environmentally exposed due to the
excessive use of insecticides for pest control in their areas of cultivations.
From this study, it is also concluded that the existence of chlorpyrifos and endosulfan with
higher frequencies are being hauled the entire population towards numerous health hazards.
RECOMMENDATIONS
98
RECOMMENDATIONS
Indecent use of pesticides pointed unawareness of farmers and lack of effective
legislation, therefore; government organization such as standards and quality control
authority (PSQCA) should play their effective role to manage this important issue for the
betterment of society.
Due to increasing trend in pesticide use, continuous monitoring of pesticide residues in
fruits and vegetables is recommended in order to develop the base line data on which
future strategy could be implemented.
To avoid adverse effects on public health, it is a necessity to set up control measures so as
to make sure that each pesticide should be below MRLs in the fruits and vegetables to be
marketed.
On the bases of achieved results, it is recommended that regular evaluation of pesticide
residue should be carried out on each fruit and vegetable for the planning and future
policy about the formulation of standards and quality control of pesticides.
Farm workers should be properly educated and trained by government or private health
organizations for the appropriate handling and usage of pesticides and should give
knowledge about the important precautions at the time of spray, so that they can prevent
themselves from exposure to these pesticides.
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99
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[http://www.fao.org/DOCREP/MEETING/004/AB428E.HTM Agenda Item 4.2 a, GF/ CRD Iran-1].
List of Publications
1. Assessment of pesticide residues in commonly used vegetables in Hyderabad, Pakistan.
Yawar Latif, S.T.H.Sherazi, M.I.Bhanger.
Ecotoxicology and Environmental Safety, 74, 2011, 2299–2303.
2. Assessment of pesticide residues in some fruits using gas chromatography coupled with
micro electron capture detector.
Yawar Latif, S.T.H.Sherazi, M.I.Bhanger.
Pakistan Journal of Analytical and Environmental Chemistry, Vol. 12, No. 1&2, 2011,
76–87.
3. Monitoring of pesticide residues in commonly used fruits in Hyderabad region, Pakistan.
Yawar Latif, S.T.H.Sherazi, M.I.Bhanger.
American Journal of Analytical Chemistry, 2011, 2, 46–52.
4. Evaluation of pesticide residues in human blood Samples of agro professionals and non-agro
professionals.
Yawar Latif, S.T.H.Sherazi, M.I.Bhanger, Shafi Nizamani.
American Journal of Analytical Chemistry, 2012, 3, 587–595.
Other publications
1. Variation in fatty acids composition including trans fat in different brands of potato chips by
GC-MS.
Aftab A. Kandhro, S. T. H. Sherazi1, S. A. Mahesar, M. Younis Talpur and Yawar Latif.
Pakistan Journal of Analytical and Environmental Chemistry. Vol. 11, No. 1, 2010, 36–41.
2. An efficient calix [4] arene based silica sorbent for the removal of endosulfan from water.
Sibghatullah Memon, Najma Memon, Shahabuddin Memon, Yawar Latif.
Journal of Hazardous Materials, 186, 2011, 1696–1703.