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Open Access

Occurrence of multiclass pesticide residues in tomato samples collected from different markets of Iran

Journal of Environmental Health Science and Engineering2018:296

https://doi.org/10.1007/s40201-018-0296-4

Received: 29 November 2016

Accepted: 16 January 2018

Published: 7 May 2018

Abstract

Background

Pesticides are a reason for popular concern due to their possible unfavorable results on human safety. Most pesticide residues are present in food owing to the direct application of a pesticide to a crop. The aims of this study were; development a multiresidue method for analysis of 81 pesticides in tomato using GC/MS, and detection and quantitation of the studied pesticides in tomato samples gathered from various stores of Iran.

Methods

The pesticides were assessed concurrently in a single run applying GC/MS after extraction with QuEChERS method. Homogenized tomato samples were weighed into centrifuge tubes. The studied pesticides were extracted using acetonitrile, followed by the addition of a mixture of anhydrous magnesium sulfate and sodium acetate. In order to remove excess water and other components of tomato a combination of primary secondary amine and magnesium sulfate was applied, and then the extracted components were analyzed by GC-MS.

Results

The calibration curves for all analytes were linear in the range of 20–200 ng/g with a determination coefficient (R2) in the range between 0.993 and 0.999. The LODs and LOQs were in the range between 2.5–6.7 and 7.5–20 ng/g respectively, and the mean recoveries obtained for three fortification levels (25,50 and 100 ng/g -five replicates each) were 72–116% with RSD < 20%. Six residues were found in 31 (20.7%) samples. Iprodione was the most common detected residues (6.0%), followed by permethrine (4.7%), esfenvalerate (4.7%), chlorpyrifos (3.3%), diazinon (2.0%), and penconazole (1.3%).

Conclusions

Among the detected pesticides, only Iprodione, permethrine, chlorpyrifos and diazinon are registered for tomato production in Iran. With exception of Chlorpyrifos and diazinon the concentrations of iprodione and permethrine were found below the maximum residue levels (MRLs) established by Iranian National Standard Organization (INSO). Esfenvalerate and penconazole are not registered for tomato production in Iran. Therefore, it is necessary to control and management of their residues in tomato.

Keywords

Pesticide residuesSelected ion monitoringGC-MSIranTomato

Background

Pesticides consist of a large number of chemicals that are utilized to prevent, destroy, repel, attract, or reduce pest organisms at different stages of cultivation. Up to now, at least 1000 chemicals have been synthesized as active pesticide ingredients in the world and are produced in various formulations by manufacturer. Metabolism and environmental degradation are two major routes that convert pesticides to the different metabolites. Pesticides and their metabolites display very large differences in chemical structure and physical properties [1]. Chemically, they are completely heterogeneous such as organochlorines, carbamates, pyrethroids and substituted ureas [2]. Despite the remarkable economic and agricultural benefits of pesticides, they are a reason of popular concern as a result of their likely harmful results on human safety [3].

Although human exposure to pesticides occurs through different ways, consumption of agricultural commodities containing pesticides is the major route. Most pesticide residues are appeared in food because of the direct usage of a pesticide to agricultural products or in the period of storage. For example, Lacina et al. reported that organophosphates such as chlorpyrifos-methyl and malathion were principal residues in wheat samples in the storage times [4]. Nowadays, because of food security, application of pesticides is inevitable in the world. Therefore, different countries and international organizations have included various regulations for supporting of human health [5, 6]. Consequently, sound management of pesticide residues in agricultural products, according to national and international regulations require advanced analytical methods.

A good analytical method for detecting pesticide residues in various foods must be able to measure residues at extremely low amounts, and must prepare unequivocal document to establish both the identification and quantitation of residues [7, 8]. In recent decades, various sample preparation techniques have been introduced for quantitation of pesticide residues in food matrices and the most used named QuEChERS (Quick, Easy, Cheap, Effective, Rugged and Safe). This technique supplies different polar, semi-polar and non-polar pesticide in food samples. Sample preparation technique in QuEChERS method includes three major steps. Firstly, blended samples are extracted with acetonitrile, then magnesium sulfate was added for salting-out partitioning. Finally, matrix molecules are removed using primary secondary amine (PSA) sorbent [9]. Nowadays, combination of the mentioned procedure and liquid and gas chromatography coupled mass spectrometry have been successfully used to assess various pesticides in different food samples [1016].

Tomato (Lycopersicon esculentum Mill) is one of the main agricultural products in the world, including Iran. The use of pesticides in order to increase tomato production affects the whole system of tomato. In addition to commonly used pesticides, the presence of banned pesticides in tomato is another important challenge. Therefore, monitoring of the commonly used and forbidden pesticides in tomato crops requires modern techniques.

In this investigation, a validated multi-residue technique was developed for identification and determination of various pesticide residues in tomato, applying GC-MS and QuEChERS method. Thereafter, the validated method was used for detection and quantitation of 81 pesticide residues in 150 tomato samples gathered from various regions of Iran.

Methods

Chemicals and reagents

Reference standards of studied pesticides (Table 1), triphenylphosphate (TTP), and anhydrous magnesium sulfate (MgSO4), were obtained from Sigma-Aldrich (Germany). Methanol (MeOH) and HPLC-grade acetonitrile (MeCN) were obtained from Acros (Belgium). Ethyl acetate (EtAc), glacial acetic acid (HOAc) and sodium acetate were purchased from Merck (Darmstadt, Germany). Bondesil-primary secondary amine (PSA, 40 μm) was supplied from Interchim (France). HPLC grade water was obtained by purifying demineralized water on a Milli-Q Plus ultra-pure water system (Millipore, Molsheim, France).
Table 1

Summary of names, molecular weights, retention times, diagnostic and quantitative ions for the studied pesticides

No.

Compound

Molecular weight (g/mol)

Diagnostic ions

Quantitative ion

Retention time (min)

1

Teflubenzuron

381.11

160, 225, 355

223

6.71

2

Molinate

187.3

187, 83

126

9.21

3

Diphenylamine

169.23

168,167,170

169

10.97

4

Phorate

260.38

121,97,170

75

12.85

5

Thiometon

246.35

125, 89,93

88

13.47

6

Dimethoate

229.26

93

87

13.96

7

Beta-HCH

290.83

219, 183,217

181

14.91

8

Lindane

290.83

183, 219,217

181

15.18

9

Quintozene

295.36

249, 239,217

237

15.50

10

Diazinon

304.35

137, 199

304

16.08

11

Disulfoton

274.4

89

88

16.45

12

Delta-HCH

290.83

219, 183,

181

16.78

13

Chlorothalonil

265.91

264, 268

266

17.23

14

Propanil

218.08

163,217

161

18.69

15

Primicarb

238.29

72,238

166

17.85

16

Vinclozolin

286.11

198, 187,285

212

19.05

17

Chlorpyrifos-methyl

322.5

289, 290, 288

286

19.36

18

Carbaryl

201.22

115,116

144

20.08

19

Alachlor

269.76

188,146

160

19.87

20

Metalaxyl

279.33

132, 160,192

206

20.24

21

Fenitrothion

277.23

277,109

260

21.32

22

Pirimiphos-methyl

305.33

276,305

290

21.43

23

Dichlofluanid

333.23

167,224

123

21.57

24

Malathion

330.35

125,127

173

22.08

25

Aldrin-R

364.91

265

263

22.32

26

Fenthion

278.33

125, 169,109

278

22.74

27

Chlorpyrifos

350.59

199, 314

197

22.88

28

Dicofol

370.48

141

139

23.09

29

Triadimefon

291.73

181,128

208

23.13

30

Cyprodinil

225.29

225

224

24.84

31

Heptachlor epoxide (cis)

389.31

354

353

25.32

32

Penconazole

284.18

248

159

25.45

33

Heptachlor epoxide (trans)

389.31

217

183

25.67

34

Captan

300.59

149,117

79

25.40

35

Fipronil

437.15

369, 351

367

26.29

36

Triadimenol

295.76

168,128

112

26.33

37

Triflumazole

345.08

206, 179, 287

278

27.05

38

Methidathion

302.3

85

145

27.33

39

o,p-DDE

318.02

248, 176

246

27.62

40

Endosulfan-alpha

406.93

237, 339, 265

241

28.10

41

Butachlor

311.84

160

176

28.48

42

Fenamiphos

303.35

154

303

29.18

43

Imazalil

297.18

173, 217

215

29.73

44

Tricyclazole

189.23

162,161

189

29.32

45

Profenphos

373.63

208

139

29.88

46

Pretilachlor

311.85

238, 176, 202

162

30.16

47

p,p-DDE

318.02

318, 316, 248

246

30.15

48

Oxadiazon

345.22

177, 344,302,258

175

30.59

49

Carboxin

235.3

235

143

30.97

50

o,p-DDD

320.04

237,165

235

30.84

51

Buprofezin

305.44

172

105

31.01

52

Endosulfan-beta

406.93

237, 3389, 267

195

32.69

53

p,p-DDD

320.04

237,165

235

33.59

54

o,p-DDT

354.49

237,165

235

33.78

55

Ethion

384.48

97, 153

231

34.07

56

Triazophos

313.31

162,172

161

35.22

57

Benalaxyl

325.4

91

148

35.90

58

Edifenphos

310.37

173, 310

109

36.01

59

Endosulfan-sulfate

406.93

387,389,385

272

36.28

60

Propiconazole I

342.22

259,175

173

36.30

61

Fenhexamide

302.19

177

97

35.54

62

Propiconazole II

342.22

259,175

173

36.79

63

Tebuconazole

307.82

250

125

37.61

64

Triphenylphosphate*

326.28

325

326

38.09

65

Iprodione

330.17

316, 187

314

39.58

66

Phosmet

317.32

161, 133,93

160

39.88

67

Bifenthrin

422.87

166, 123

181

40.32

68

Methoxychlor

345.65

228

227

40.48

69

Fenpropathrin

349.43

181, 208

97

40.67

70

Azinphos-methyl

317.32

132, 160

160

42.15

71

Phosalone

367.81

121,154

182

42.15

72

Amitraz

293.41

162,174,121

293

43.05

73

Lambda Cyhalothrin

449.85

197, 208

181

43.36

74

Fenarimol

331.2

219

139

43.58

75

Bitertanol

337.41

168

170

45.03

76

Permethrin I

391.28

163, 183, 184

183

45.24

77

Permethrin II

391.28

163, 183, 184

183

45.54

78

Prochloraz

376.67

310

180

45.94

79

Fenbuconazole

336.82

198

129

46.58

80

Cypermethrin-alpha

416.3

181, 208

163

47.62

81

Esfenvalerate

419.9

167,181

125

49.82

82

Deltamethrin

505.21

253,255

181

51.231

*Internal standard

Individual standard stock solutions (1.0 mg/mL) of the investigated pesticides were prepared at 20 °C by dissolving in EtAc or MeOH. For validation studies, a mixed standard solution (5 μg/mL) was prepared by diluting of the stock standard solutions in MeOH. A stock solution of TTP in ethyl acetate at a concentration of 20 μg/mL was used as internal standard. Some of the investigated pesticides were selected based on chemicals used for tomato production in Iran and Iranian National Standard Organization (INSO) has established MRLs for them. The other pesticides are forbidden to be use in Iran.

Tomato samples

One hundred and fifty tomato samples produced in different regions of Iran were collected for analysis. In order to avoid possible thermal decomposition of pesticide residues, a 100-g portion of the collected samples was grinded with 100 g dry ice and immediately analyzed.

Gas chromatography-mass Spectrometry (GC-MS)

Gas chromatography (Model 7890 A, Agilent technologies, USA) with a single quadruple mass Spectrometry detector (Model 5975 C, Agilent technologies, USA) equipped with split/splitless injector and an Agilent auto-sampler with a HP-5 19091S-436 Agilent capillary column (60 m × 0.25 mm I.D., 0.25 μm film thicknesses) was used.

GC-MS analysis

Helium (99.999%) was employed as the carrier gas at a constant flow rate of 1.6 mL/ min. The oven temperature was programmed from 60 °C (held 1 min), at 30 °C/min to 180 °C, at 2 °C/min ramp to 230 °C, at 5 °C/min ramp to 280 °C, followed by 10 °C/min ramp to 300 °C for 4 min. Injection port was adjusted at 250 °C and splitless mode was employed. After acquiring the ion chromatogram in selected ion monitoring (SIM) mode, peaks were identified by their retention time and mass spectra. The most abundant ion that had the highest signal-to-noise ratio and showed no evidence of chromatographic interference was taken for quantification.

Sample preparation

Sample preparation was carried out by the original QuEChERS method [9]. Five grams of homogenized tomato sample was weighed into a 50 mL centrifuge tube and 200 ng/g TTP was added as internal standard. Ten mL of acetonitrile (MeCN) was added and the mixture was vigorously shaked for 2.0 min, followed by the addition of a mixture of 2 g anhydrous MgSO4 and 1.5 g sodium acetate and vortex mixing for 2.0 min again. The tube was tightly closed and the mixture was centrifuged for 5 min at 9000 rpm. Five mL of supernatant was transferred to a tube containing 60 mg anhydrous MgSO4 and 20 mg PSA (primary secondary amine). The mixture was shaked vigorously for 2 min and centrifuged for 5 min at 9000 rpm. Finally, a 0.5 mL of the cleaned supernatant was transferred into a screw cap vial and 1.0 μL of the solution was injected into GC-MS.

Method validation

According to the European SANCO guidelines [17], the validation study was tested to assess for linearity, recovery, precision, and limits of detection (LOD) and quantitation (LOQ). The linearity of the method was studied applying matrix-matched calibrations by analyzing six concentration levels, between 20 and 200 ng/g. For determination of mean recoveries (to estimate the accuracy of the method) and precision (repeatability, expressed as coefficient of variation in %), five spiked blank tomato samples at concentration levels of 25, 50 and 100 ng/g were prepared and then treated according to the procedure earlier described in sample preparation. Limits of LOD and LOQ were calculated to be the concentrations of pesticide that result in a signal-to-noise ratio of 3 and 10, respectively.

Quantitation of pesticide residues

The amounts of pesticide residues in the positive samples were calculated by comparing signal from each pesticide with signal from internal standard in the sample on the matrix-matched calibration curve. In order to correct for the losses of pesticide residues during sample preparation, internal standard (TPP) was employed. Excel software was used for statistical calculations.

Data availability

The authors do not wish to share their data. All the necessary data have been mentioned in the paper. Please contact corresponding author for data requests.

Results

GC-MS determination

For analysis of the studied pesticides, the SIM mode was applied. Quantitation and confirmation of pesticides were performed based on the use of: one quantitative ion, at least one diagnostic (or qualifier) ion, and retention times. Table 1 summarizes molar weights, retention time, and SIM parameters obtained for the studied pesticides.

Method validation

The investigated method was validated by determining the limits of detection (LOD) and quantitation (LOQ), the recovery and precision at different levels of the fortification. The method validation revealed that the calibration curves for each analyte were linear in the concentration range of 20–200 ng/g with a determination coefficient (R2) in the range between 0.993 and 0.999. As shown in Table 2, the LODs and LOQs were in the range between 2.5–6.7 ng/g and 7.5–20 ng/g respectively. The mean recoveries obtained for three fortification levels (25, 50 and 100 ng/g -five replicates each) were 72–116% with satisfactory precision (RSD < 20%), meeting EU guidelines method performance criteria [17].
Table 2

Mean recoveries (%), relative standard deviations (RSD, %), LOQs and LODs (ng/g) obtained for studied pesticides in tomato samples, spiked at 25, 50 and 100 ng/g levels (n = 5)

No.

Compounds

25 ng/g

50 ng/g

100 ng/g

LOQa

LODb

Mean

RSD

Mean

RSD

Mean

RSD

  

1

Teflubenzuron

101

12

105

6

95

10

16.0

5.3

2

Molinate

103

14

79

9

93

11

9.5

3.2

3

Diphenylamine

115

8

86

13

107

5

10.5

3.5

4

Phorate

92

10

94

8

93

12

15.5

5.2

5

Thiometon

89

7

86

11

91

3

20.0

6.7

6

Dimethoate

98

9

97

9

80

7

16.5

5.5

7

Beta-HCH

92

16

106

4

89

7

9.0

3.0

8

Lindane

114

11

109

9

83

6

10.5

3.5

9

Quintozene

96

4

103

5

85

6

17.0

5.7

10

Diazinon

90

15

95

12

100

9

16.0

5.3

11

Disulfoton

95

6

95

4

85

9

11.5

3.8

12

Delta-HCH

86

13

99

9

100

6

13.0

4.3

13

Chlorothalonil

92

15

104

6

89

8

14.5

4.8

14

Propanil

75

10

83

6

77

7

15.0

5.0

15

Primicarb

85

5

98

8

95

11

11.0

3.7

16

Vinclozolin

83

12

99

4

97

4

14.0

4.7

17

Chlorpyrifos-methyl

111

2

84

6

86

2

19.0

6.3

18

Carbaryl

109

5

98

7

89

3

20.0

6.7

19

Alachlor

96

9

80

3

100

2

16.5

5.5

20

Metalaxyl

90

12

85

8

97

2

11.5

3.8

21

Fenitrothion

108

9

105

7

95

3

9.0

3.0

22

Pirimiphos-methyl

89

1

102

6

88

6

7.5

2.5

23

Dichlofluanid

108

8

92

12

111

5

9.5

3.2

24

Malathion

98

4

81

7

100

2

13.5

4.5

25

Aldrin-R

101

13

94

6

99

7

18.0

6.0

26

Fenthion

85

12

93

16

103

9

19.5

6.5

27

Chlorpyrifos

106

13

93

11

97

6

13.0

4.3

28

Dicofol

112

5

89

9

100

7

14.0

4.7

29

Triadimefon

95

3

88

1

89

6

15.0

5.0

30

Cyprodinil

102

7

98

12

95

11

17.0

5.7

31

Heptachlor epoxide (cis)

102

8

85

9

99

2

8.0

2.7

32

Penconazole

82

9

88

5

109

10

9.5

3.2

33

Heptachlor epoxide (trans)

80

5

96

2

100

1

10.0

3.3

34

Captan

113

7

82

6

106

2

12.0

4.0

35

Fipronil

95

5

98

2

112

8

17.5

5.8

36

Triadimenol

107

4

100

6

83

4

18.0

6.0

37

Triflumazole

96

7

85

12

110

4

20.0

6.7

38

Methidathion

88

11

87

8

109

6

14.0

4.7

39

o,p-DDE

86

9

88

16

87

10

10.0

3.3

40

Endosulfan-alpha

72

8

86

13

107

9

11.0

3.7

41

Butachlor

102

6

86

14

105

8

14.5

4.8

42

Fenamiphos

109

14

88

16

97

9

17.0

5.7

43

Imazalil

86

11

96

9

100

3

16.5

5.5

44

Tricyclazole

103

2

97

7

90

6

17.0

5.7

45

Profenphos

101

5

90

11

110

9

18.5

6.2

46

Pretilachlor

89

9

86

6

95

9

17.0

5.7

47

p,p-DDE

112

6

87

8

108

3

17.5

5.8

48

Oxadiazon

95

7

88

12

106

6

13.5

4.5

49

Carboxin

80

9

78

11

98

9

12.5

4.2

50

o,p-DDD

88

12

95

6

107

11

10.5

3.5

51

Buprofezin

98

11

89

6

104

10

12.5

4.2

52

Endosulfan-beta

79

6

96

12

80

10

8.0

2.7

53

p,p-DDD

81

8

94

3

110

2

13.0

4.3

54

o,p-DDT

109

2

93

5

87

3

18.0

6.0

55

Ethion

101

9

89

5

113

9

17.0

5.7

56

Triazophos

97

8

110

9

83

13

15.5

5.2

57

Benalaxyl

105

6

98

3

108

5

15.0

5.0

58

Edifenphos

100

9

111

7

114

6

19.5

6.5

59

Endosulfan-sulfate

98

12

98

16

105

10

19.0

6.3

60

Propiconazole I

90

7

88

10

103

9

17.0

5.7

61

Fenhexamide

95

9

101

3

111

6

19.0

6.3

62

Propiconazole II

113

15

88

11

78

15

18.0

6.0

63

Tebuconazole

87

11

92

4

100

13

15.0

5.0

64

Iprodione

97

9

87

2

98

9

8.0

2.7

65

Phosmet

107

17

99

10

112

2

18.5

6.2

66

Bifenthrin

116

6

100

11

96

6

13.0

4.3

67

Methoxychlor

100

2

89

8

77

3

14.5

4.8

68

Fenpropathrin

100

7

98

2

90

1

13.5

4.5

69

Azinphos-methyl

85

3

99

7

94

1

19.0

6.3

70

Phosalone

108

5

102

2

86

7

15.0

5.0

71

Amitraz

100

11

84

7

91

8

19.0

6.3

72

Lambda Cyhalothrin

89

8

102

2

105

3

19.5

6.5

73

Fenarimol

84

6

112

14

98

10

19.5

6.5

74

Bitertanol

99

3

106

11

111

10

13.5

4.5

75

Permethrin I

114

7

97

6

87

3

9.5

3.2

76

Permethrin II

105

6

89

3

112

5

10.0

3.3

77

Prochloraz

84

9

108

10

103

4

19.5

6.5

78

Fenbuconazole

87

4

97

2

96

3

20.0

6.7

79

Cypermethrin-alpha

88

8

96

6

88

10

20.0

6.7

80

Esfenvalerate

89

4

97

11

84

9

11.5

3.8

81

Deltamethrin

89

13

101

5

100

9

10.5

3.5

aLimit of quantitation

bLimit of detection

Analysis of real samples

The validated method was applied for analysis of 150 tomato samples collected from different regions of Iran. As shown in Table 3, six pesticides including; iprodione, permethrine (sum of permethrine I and II), esfenvalerate, chlorpyrifos, diazinon and penconazole were detected in 31 (20.7%) samples. Among the detected pesticides, iprodione was the most common pesticide residues (6.0%), followed by (4.7%), permethrine (4.7%), esfenvalerate (4.7%), chlorpyrifos (3.3%), diazinon (2.0%) and penconazole (1.3%).
Table 3

Pesticide residues determined in tomato samples collected from different regions of Iran

No.

Pesticides

No. of positive samples

LODa (ng/g)

LOQb (ng/g)

Min level (ng/g)

Max level (ng/g)

No. of positive samples>MRL

INSOʾsc MRL (ng/g)

1

Iprodione

9(6.0%)

2.7

8.0

14

359

5000

2

Permethrined

7(4.7%)

3.2

9.5

44

347

1000

3

Esfenvaleratee

7(4.7%)

3.8

11.5

13

51

4

Chlorpyrifos

5(3.3%)

4.3

13

24

219

2(40%)

100

5

Diazinon

3(2.0%)

5.3

16

38

232

2(66.7%)

50

6

Penconazolee

2(1.3%)

3.2

9.5

92

102

aLimit of Detection

bLimit of Quantitation

cIranian National Standard Organization

dSum of permethrine I and II

eProhibited pesticides for tomato production in Iran

Discussion

Tomato (Lycopersicon esculentum Mill.) is one of the most important vegetables in the world. Tomato contains nutrients such as vitamin A, vitamin C, potassium, phosphorus, magnesium, and calcium [18]. It also contains lycopene, an antioxidant that reduces the risk of cancer [19]. World and Iran tomato production in 2015 were more than 163 and 6 million tons of fresh fruit, respectively [20]. During tomato production, different insects and mites attack different parts of tomato. Therefore, prevention and control of pests in tomato is very important. In Iran, different classes of pesticides are registered to control of pests in tomato. However, most pesticide residues can remain in tomato and affect human health.

According to the Iranian regulations, the studied pesticides can be divided into three groups: 1) forbidden or banned pesticides, 2) registered and, 3) not registered pesticides for tomato production in Iran. Group 1, including, azinphos-methyl, aldrin, delta- HCH, phorate, lindane, methidathion, methoxychlor, triazophos and DDT are forbidden for crop production, including tomato in Iran. These pesticides severely affected human health and, their chronic toxicity has been documented. For example, it has been shown that phorate, an organophosphorus pesticide, causes genotoxicity [21] and leading to prostate cancer [22]. Therefore, it is necessary to detect banned pesticides in tomato. The results showed that none of the detected pesticide was forbidden However, Bakore et al. detected organochlorine residues of DDT, HCH and aldrin in all of the studied tomato samples in India [23].

Group 2, including deltamethrin, permethrine, diazinon, chlorpyrifos, malathion, carbaryl, fenitrothion, fenthion, captan, iprodione, tebuconazole, propiconazole, carboxin and dimethoate are registered for tomato production in Iran and the MRLs for them have been established by the Iranian National Standard Organization. As shown in Table 3, among the registered pesticides, only iprodione, permethrine, chlorpyrifos and diazinon found in positive tomato samples. With exception of Chlorpyrifos and diazinon the concentrations of iprodione and permethrine were found below the INSO-specified MRLs. Chlorpyrifos and diazinon are effective organophosphate chemicals applied largely across the world in agricultural and domestic pest control. They have three major ways of toxicity in animals: blockage of the acetylcholine esterase enzyme (AChE), oxidative damage, and interruption of endocrine systems. Inhibition of AChE causes over-stimulation of related neurons in the CNS, resulting in sensorial and behavioral disturbances, general weakness, increased secretions such as urination, salivation and lacrimation, depression of motor function and respiration, ataxia, tremor, convulsions, coma and death [24]. Several investigations have shown that chlorpyrifos causes oxidative damage in animals. Oxidative stress and AChE inhibition, underlies the prenatal neurotoxicity of chlorpyrifos [25]. Furthermore, oxidative stress induces dopaminergic damages in the central nervous system may lead to Parkinson’s disease [26]. Chlorpyrifos can strongly block CYP450 enzymes in the liver and, long exposure can lead to the liver hurt and various metabolic disorders [27]. Chronic toxicity of chlorpyrifos can impair kidney structure that may lead to renal failure [28]. In addition, a number of investigations show that chlorpyrifos may be lead to lung and rectal cancers in humans [29].

The other pesticides in Table 1 belong to group 3. These chemicals are allowed to be used in other crop production, like apple, cucumber, rice etc., but are not registered for tomato production, and MRLs have not been established for them by INSO. Among the detected pesticides, esfenvalerate and penconazole belong to this group and their occurrence in tomato samples is a major concern. Additionally, some tomato samples included more than one pesticide; the reason being that tomato cultivated under some conditions is highly sensitive to pests and requires successive applications of different pesticide treatments.

Conclusions

In the present study, an accurate, precise, sensitive and selective method was developed for the simultaneous detection, quantification and confirmation of 81 pesticide residues (belonging to different chemical families) in tomato employing QuEChERS sample preparation procedure and GC-MS. The validated results showed excellent recoveries (71–119%) and precision (RSDs <20%) for all studied pesticides, meeting EU guidelines method performance criteria. The method was applied successfully for the analyses of 150 tomato samples collected from different market of Tehran. Six compounds were found in 31 positive samples. Iprodione was the most common detected residues, followed by permethrine, esfenvalerate, chlorpyrifos, diazinon, and penconazole. Chronically, the detected pesticides in tomato can affect Iranian consumers in long time. Therefore, it is necessary to control and management of their residues in tomato by applying Good Agricultural Practice (GAP) and implementing integrated pest management (IPM) in Iran.

Declarations

Funding

All sources of this study were supported by Food Safety Research Center, Shahid Beheshti University of Medical Sciences of Tehran.

Authors’ contributions

JS, was contributed in set up and validation the method and Instrumental analysis. AS, planned the experiment, main supervisor and head of scientific team. VM, collected the samples and drafted the manuscript. All authors read and approved the final manuscript.

Compliance with Ethical Standards

Ethics Approval and Consent to Participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors’ Affiliations

(1)
Food Safety Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
(2)
Department of Clinical Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran
(3)
Vice-Chancellor for Food and Drug Affairs, Shahid Beheshti University of Medical Sciences, Tehran, Iran
(4)
Department of Food Science and Technology, Science and Research Branch, Islamic Azad University, Tehran, Iran

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Copyright

© The Author(s) 2018

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