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

VIII

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

IX

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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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.