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. 2020 Aug 1;29(11):1573–1586. doi: 10.1007/s10068-020-00798-4

Determination of 66 pesticide residues in livestock products using QuEChERS and GC–MS/MS

Hye Soon Kang 1,2, MeeKyung Kim 1,, Eun Jeong Kim 1, Won-Jo Choe 3
PMCID: PMC7561644  PMID: 33088606

Abstract

Determinations of 66 pesticide residues in different matrices including beef, pork, chicken, eggs, and milk were conducted using GC–MS/MS combined with the quick easy cheap effective rugged safe (QuEChERS) method for sample extraction. A high linearity was achieved in the concentration range from 2.5 to 1000 µg/L (R2 ≥ 0.99), and the limit of quantification for multi-class pesticides ranged from 0.74 to 23.1 µg/kg. The recovery ranged from 70.0 to 120%, while the reproducibility of the measurements was between 0.23 and 19.9%. Monitoring was conducted for livestock products purchased from local markets. Chlorpyrifos and fenitrothion in beef and chlorpyrifos in pork were detected below the maximum residue limits for the respective samples. No detectable residues were found in the other samples. Due to its high efficiency, reproducibility, and simple analytical operation, the proposed method can be applied to the regular monitoring of multi-residue pesticides in livestock products.

Keywords: Pesticide, Meat, Eggs, Milk, QuEChERS, GC–MS/MS

Introduction

The use of pesticides in modern agriculture has played a major role in boosting agricultural productivity; however, their misuse is a growing problem. Such misuse, including the application of pesticides to livestock and to improve the farm environment, can lead to the transfer of pesticide residues to livestock products (LeDoux, 2011). As such, pesticides are ubiquitous in the environment and are commonly found in livestock products, leading to their incorporation into the food chain. For example, in 2017 in Korea, the metabolites of fipronil, a pesticide used to control mites, were found to have contaminated chickens and eggs, resulting in the death of a cow that consumed contaminated rice straw feed (Ko et al., 2015; Rahman et al., 2016). The pathways by which livestock are exposed to pesticides include skin absorption, inhalation, and ingestion. The absorbed substances can then be metabolized or accumulate within the body and subsequently serve as an interim host for consumption by other animals (Covaci et al., 2004; Pagliuca et al., 2005). Due to such issues, the appropriate management of pesticide residues is crucial. Many countries therefore operate inspection programs to manage the pesticide residues present in livestock products, with examples including the National Residue Survey of the Australian Ministry of Agriculture and Fisheries, the National Chemical Residues Programme of the New Zealand Food Safety Agency, the National Chemical Residue Monitoring Program of the Canadian Food Inspection Agency, and the National Residue Program of the US Department of Agriculture (USDA, 2019). In addition, Korea has a pesticide monitoring and management system through the National Residue Program for domestic and imported products. Since the maximum residue limits (MRLs) were established for 16 pesticides in livestock products in 1995, new standard limits have been continuously added by 2019 to become 99 pesticides (MFDS, 2019).

Currently, the majority of organochlorine pesticides are banned, but they are still found in the environment (Surma et al., 2014). For example, aldrin and dieldrin are known as persistent organic pollutants, as categorized by the UN Environment Programme. Although organophosphorus pesticides are degradable, they tend to be used in large quantities, and so continuous monitoring is required, and method development based on the use of mass spectrometry (MS) is necessary for the determination of low concentration multi-residue pesticides in livestock products. Indeed, the development and verification of analytical methods for pesticide residues in various foodstuffs are essential to ensure food safety. Such methods involve the monitoring of pesticide residues in livestock products according to changes in the pesticide residual acceptance criteria for different livestock products (Oh et al., 2009). Continued improvements to analytical methods are also required as the number of pesticides increases and the MRLs decrease. To date, pesticide residues have typically been analyzed by multi-component gas chromatography (GC) (Molina-Ruiz et al., 2015; Yang et al., 2011) and liquid chromatography (LC) (da Costa Morais et al., 2018; Stachniuk and Fornal, 2016), with various MS techniques also enabling the simultaneous analysis of hundreds of pesticides (Facco et al., 2015; He et al., 2015; Huang et al., 2010; Hunter et al., 2010; Samadi et al., 2012; Zhang et al., 2013). Although liquid–liquid extraction and solid-phase extraction are the most commonly used processes in terms of sample preparation for pesticide analysis, these processes are time-consuming, and the high volumes of solvent required can be detrimental to the environment (Bidari et al., 2011; Cho et al., 2008). Thus, the quick, easy, cheap, effective, rugged, and safe (QuEChERS) method is a popular alternative for the pre-treatment of pesticide analytical samples and veterinary drugs (Anastassiades et al., 2003; Qin et al., 2016; Xu et al., 2019). We therefore consider that the QuEChERS method could be applied to the analysis of pesticides in livestock products, especially for different matrices, such as meat, eggs, and milk. Several studies have been conducted to analyze pesticides in livestock products (Hercegová et al., 2007; Juhler, 1997; Rimkus et al., 1996). However, there are still complex steps and difficulties in extracting the fat compartment. In this study, we investigated methods of simultaneous analysis of multi-component pesticides in livestock products that contain a large amount of fat and a high level of interference such as proteins. Thus, we herein report the simultaneous analysis of 66 pesticides, including 24 insecticides, 15 fungicides, and 27 acaricides, in livestock products through the development of a combined QuEChERS and GC–MS/MS method to achieve simple and effective quantitation within the MRL criteria.

Materials and methods

Chemicals and reagents

Standards of the 66 pesticides were purchased from AccuStandard (New Haven, CT, USA), Chem Service (West Chester, PA, USA), Dr. Ehrenstorfer (Augsburg, Germany), Sigma-Aldrich (St. Louise, MO, USA), Toronto Research Chemicals (North York, ON, Canada), and Wako Pure Chemical Industries (Osaka, Japan). Acetonitrile, hexane, and acetone were purchased from Burdick & Jackson (Muskegon, MI, USA). All reagents were either of analytical or HPLC grade. Standard solutions were prepared by dilution of the stock solutions with acetone, and stored in amber bottles at 4 °C. Ultrapure water was obtained from a Milli-Q water purification system (Millipore, Bedford, MA, USA; resistivity ≥ 18.2 MΩ cm at 25 °C). A HyperSep™ florisil solid phase extraction (SPE) cartridge (6 mL, 1 g, ThermoFisher Scientific, Waltham, MA, USA) was used for sample purification.

GC–MS/MS analysis

GC–MS/MS (TSQ EVO 8000, Thermo Scientific, Waltham, MA, USA) was used for analysis of the pesticides. Chromatographic separation was carried out using an HP-5MS capillary column (30 m × 0.25 mm ID, 0.25 μm film thickness). The GC oven temperature was programmed as follows: initial temperature of 70 °C, hold at 70 °C for 2 min, increase the temperature to 300 °C at a rate of 20 °C/min, hold at 300 °C for 8 min. The injection port temperature was set at 150 °C, and helium was used as the carrier gas at a flow rate of 1.0 mL/min. Splitless injection was used for trace analysis of the residual pesticides. For the MS measurements, the ion source and interface temperatures were 300 and 280 °C, respectively, and the electron impact voltage was 70 eV. MS was performed by measuring the retention time of the total ion chromatogram obtained in full scan mode (m/z 50–500) then selecting the retention times, precursor ions, and product ions of the 66 pesticides (Table 1). To increase the selectivity, two product ions were selected. Collision energy values were obtained and multiple reaction monitoring conditions were set.

Table 1.

Optimum conditions for multiple reaction monitoring of GC–MS/MS analysis

Pesticide Retention time (min) Precursor ion (m/z) Product ion (m/z) Collision energy (eV)
Dichlorvos 6.70 109/185/185 79/93/109 6/12/16
Methacrifos 8.45 125/208/180 79/93/165 8/14/6
Diphenyl0amine 9.23 168/169/167 167/168/166 14/12/18
Phorate 9.65 121/231/260 65/129/75 10/22/7
Dimethoate 9.85 87/93/125 86/63/79 6/8/8
BHC-gamma 10.09 181/183/217 145/147/181 14/12/8
Terbufos 10.11 153/231/231 97/129/175 10/22/12
Quintozene 10.18 142/212/237 107/177/119 24/12/20
Diazinon 10.19 137/179/304 84/137/179 12/16/8
Disulfoton 10.29 88/153/142 60/97/81 6/10/12
Etrimfos 10.36 181/292/292 153/181/153 8/6/18
Primicarb 10.47 238/166/166 166/86/71 8/14/24
Pentachloraniline 10.60 263/265/230 192/194/195 18/18/10
Chlorpyrifos-methyl 10.74 125/286/286 79/93/271 6/20/12
Vinclozolin 10.72 212/200/214 172/147/174 12/14/22
Heptachlor 10.87 272/270/235 237/235/141 12/12/24
Primiphos methyl 10.99 233/290/276 151/125/244 8/20/8
Fenitrothion 11.00 277/277/260 260/109/125 6/16/12
Pentachlorothioanisole 11.10 296/244/294 263/174/261 12/28/12
Fenthion 11.19 278/245/279 156/97/81 18/12/16
Chlorpyrifos 11.21 197/286/314 169/258/258 12/8/12
Aldrin 11.23 257/261/263 222/191/193 12/30/30
Triadimefon 11.25 208/181/208 111/127/127 20/6/14
Penconazole 11.58 159/248/186 123/206/115 18/12/30
Isofenphos 11.61 213/255/255 121/121/185 14/22/10
Chlorfenvinphos 11.62 267/323/295 159/267/267 14/12/8
Mecarbam 11.63 159/160/131 131/132/86 6/8/12
Oxychlordane 11.64 149/115/115 85/51/87 8/22/10
Triadimenol 11.66 168/128/128 70/65/100 8/18/12
Phenthoate 11.66 274/246/125 121/121/79 10/6/8
Heptachlor epoxide 11.67 217/217/353 147/182/263 28/18/12
Methidathion 11.82 145/85/93 85/58/63 6/6/8
Chinomethionat 11.85 234/206/116 206/148/89 8/12/12
Chlordane-trans 11.86 375/373/371 266/266/264 18/20/20
Endosulfan alpha 11.99 241/195/243 206/159/208 10/6/10
Chlordane-cis 12.01 264/373/264 194/264/229 34/18/22
Profenfos 12.10 139/337/339 97/267/269 6/12/12
p,p′-DDE 12.15 246/248/316 176/176/246 28/28/18
Myclobutanil 12.20 179/150/152 125/123/125 14/16/8
Kresoxim methyl 12.21 116/206/206 89/116/131 14/6/10
Flusilazole 12.22 233/206/206 165/151/137 16/14/18
Dieldrin 12.24 261/263/271 191/193/241 30/30/8
Endrin 12.46 261/245/263 191/173/193 28/24/28
Fensulfothion 12.49 292/293/140 156/97/81 15/20/25
Endosulfan beta 12.54 241/195/195 206/159/125 12/8/22
p,p′-DDD 12.55 235/200/199 165/165/163 22/10/30
Ethion 12.57 125/153/231 97/97/129 6/10/22
o,p-DDT 12.65 235/237/235 165/165/199 22/22/12
Trizaofos 12.69 161/161/257 134/106/162 8/12/6
Edifenphos 12.87 173/201/201 109/109/173 8/14/6
Propiconazole 12.90 173/259/259 145/173/69 4/14/10
Endosulfan sulfate 12.94 272/195/195 237/159/125 12/8/22
p,p′-DDT 12.94 235/165/199 165/164/163 20/24/28
Propagite 13.03 135/201/173 107/81/107 12/8/22
Bifenthrin 13.32 181/166/182 165/165/166 24/14/24
Phosmet 13.38 160/160/133 77/133/77 22/10/12
Fenpropathrin 13.41 181/265/125 152/210/97 22/8/6
keto Endrin 13.41 243/317/317 173/281/245 24/8/14
Phosalone 13.72 182/182/367 111/75/182 14/28/6
Pyriproxyfen 13.72 136/136/226 79/96/186 20/10/12
Fenarimol 14.00 139/219/251 111/107/139 14/10/12
Permethrin 14.34 183/183/163 168/153/91 10/10/12
Prochloraz 14.50 180/310/308 138/70/70 10/12/12
Fenbuconazole 14.70 129/198/125 102/129/89 14/8/14
Cypermethrin 14.95 127/181/163 91/152/91 8/22/12
Fenvalerate 15.70 167/125/225 125/89/119 8/18/16

Sample preparation

The homogenized sample (10 g) was transferred to a shaking bottle, a solution of acetonitrile containing 1% formic acid (50 mL) was added, and the resulting mixture was shaken for 30 min. After this time, anhydrous magnesium sulfate (4 g) and sodium chloride (1 g, to increase the ionic strength and distribution efficiency) were added, and the mixture was shaken for 10 min prior to centrifugation for 10 min at 4000 rpm. The supernatant (25 mL) was then added to acetone containing 2% diethylene glycol (0.2 mL) and the solvent was evaporated to dryness. The resulting extract was redissolved in a mixture of acetone/hexane (2:8, v/v, 4 mL), which was subsequently loaded onto an SPE-florisil cartridge that was activated with hexane (5 mL) and acetone/hexane (2:8, v/v, 5 mL) for sample purification. It should be noted that florisil cartridges are the most widely used adsorbents for pigments, maintenance, and removal, and are often used to remove the fats and residues present in livestock products (Chae et al., 2013). The extract was then filtered through the cartridge with the addition of acetonitrile/hexane (2:8, v/v, 5 mL). The obtained eluent was concentrated to dryness under a flow of nitrogen gas, and then redissolved in acetonitrile/hexane (2:8, v/v, 1 mL) for GC–MS/MS analysis.

Method validation

To verify the applicability of the developed method for the target pesticides, representative samples of beef, pork, chicken, eggs, and milk were used to determine the recovery rate. Five replicates were prepared by adding the standard solution mixture to each of the five representative food samples at three concentrations, 5, 10, and 100 µg/kg. Validation was determined by measurement of the linearity, limit of detection (LOD), limit of quantification (LOQ), recovery, and reproducibility, according to the standard procedure for the preparation of test methods, the Codex Alimentarius Guideline, CAC/GL 40 (2003). The method selectivity was confirmed using the total ion peak areas of the pesticide standards in the blank solution and in each matrix. The linearity was calculated using the correlation coefficient (R2) of the calibration curves obtained using pesticide concentrations of 10, 20, 50, 100, 500, and 1000 µg/kg. The LOD and LOQ values were determined as 3 and 10 times the signal-to-noise ratio (S/N), respectively. The accuracy (recovery measurement) was calculated at three different pesticide concentrations (5, 10, and 100 µg/kg) for the five products (beef, pork, chicken, eggs, and milk) as the representative matrices. The precision was assessed using the relative standard deviation (RSD) of the recovery.

Results and discussion

Verification of the GC–MS/MS conditions

The GC–MS/MS conditions for determination of the pesticide residues present in the various matrices were optimized using an HP5MS separation column. The total ion chromatogram of the 66 pesticides is shown in Fig. 1, where the concentrations of the standard pesticides in acetone were 100 μg/mL, and the various peaks were observed between 6 and 16 min. The peak numbers and corresponding retention times are presented in Table 1, along with the precursor ions (m/z), product ions (m/z), and collision energies of the quantification and confirmatory transitions for the 66 pesticides.

Fig. 1.

Fig. 1

Total ion chromatogram of 66 pesticides. The names of pesticides for the numbers indicated on the peaks are listed in Table 1

Specificity, LOD, and LOQ

To verify the specificity of the developed technique, the retention times and selected ions were confirmed. In terms of the pesticide retention times, only the selected precursor and product ions were detected in the samples to which the standard, blank, and mixed standard solutions were added. The lowest LODs were obtained as 0.4 µg/kg for beef and pork, and 0.2 µg/kg for chicken, eggs, and milk. The lowest LOQ was obtained as 0.74 µg/kg for the bifenthrin content in milk, and the highest LOQ was obtained as 23.1 µg/kg for the heptachlor epoxide content in pork (Table 2). Manav et al. (2019) reported LODs for permethrin in milk and endosulfan sulfate in dairy products of 0.40 and 0.48 µg/kg, respectively using GC–MS and the QuEChERS method, which are similar to those determined in this study. In contrast, some studies have reported relatively high LODs (5.2–14 µg/kg) and LOQs (1.5–44 µg/kg) (Hamadamin and Hassan, 2020) and relatively low LOQs (less than 5 ng/g) (Sapozhnikova, 2018) compared with this study. As demonstrated by several studies, multi-class pesticide analysis using the QuEChERS method and MS is a simple, excellent approach, with low LODs and LOQs and high recoveries.

Table 2.

Linearity, limit of detection (LOD) and limit of quantification (LOQ) in various matrices for 66 pesticides

Pesticide Linearity (R2) LOD (μg/kg) LOQ (μg/kg)
Beef Pork Chicken Eggs Milk Beef Pork Chicken Eggs Milk
Aldrin 0.9986 1.91 2.31 1.04 0.79 1.63 6.30 7.61 3.43 2.62 5.39
BHC-gamma 0.9989 1.42 1.14 0.52 0.85 0.38 4.70 3.75 1.71 2.80 1.25
Bifenthrin 0.9999 0.35 0.78 0.37 0.43 0.22 1.16 2.58 1.23 1.41 0.74
Chinomethionat 0.9999 2.29 0.87 0.51 0.43 0.87 7.55 2.88 1.68 1.43 2.87
Chlordane-cis 0.9982 2.15 5.01 2.82 2.31 2.60 7.08 16.5 9.32 7.62 8.56
Chlordane-trans 0.9986 1.89 1.46 0.60 0.81 1.20 6.22 4.81 1.97 2.69 3.96
Chlorfenvinphos 0.9992 3.68 1.30 0.57 0.68 0.94 12.1 4.29 1.89 2.25 3.09
Chlorpyrifos 0.9996 2.99 2.44 0.80 0.81 0.66 9.88 8.05 2.64 2.69 2.16
Chlorpyrifos-methyl 0.9997 3.92 5.07 0.88 1.27 2.31 12.9 16.7 2.91 4.20 7.62
Cypermethrin 0.9968 1.01 2.18 1.10 0.78 1.89 3.33 7.20 3.64 2.58 6.24
p,p′-DDD 0.9999 0.87 0.67 0.23 0.48 0.40 2.85 2.20 0.75 1.60 1.33
p,p′-DDE 1.0000 0.94 1.08 0.64 0.61 0.89 3.09 3.55 2.13 2.02 2.94
o,p-DDT 0.9978 0.79 1.80 0.60 0.84 0.91 2.60 5.95 1.97 2.77 2.99
p,p′-DDT 0.9973 1.67 0.76 0.73 0.59 0.34 5.50 2.50 2.42 1.93 1.13
Diazinon 0.9998 0.56 1.51 5.57 0.42 1.08 1.85 4.97 18.4 1.38 3.55
Dichlorvos 0.9999 0.77 1.87 1.16 0.86 1.90 2.55 6.16 3.81 2.85 6.25
Dieldrin 0.9976 3.36 4.34 2.41 1.38 2.77 11.1 14.3 7.95 4.55 9.14
Dimethoate 0.9989 2.56 2.77 1.09 0.62 0.52 8.45 9.14 3.61 2.05 1.71
Diphenylamine 0.9999 0.96 0.36 0.29 0.30 0.33 3.15 1.20 0.96 1.00 1.10
Disulfoton 0.9998 0.49 0.85 0.60 0.35 0.68 1.63 2.81 1.98 1.15 2.25
Edifenphos 0.9996 0.73 1.33 0.69 0.65 0.52 2.40 4.39 2.29 2.15 1.71
Endosulfan alpha 0.9951 2.13 2.02 2.12 1.80 0.86 7.04 6.67 7.00 5.92 2.84
Endosulfan beta 0.9969 1.91 3.49 2.57 2.55 3.11 6.31 11.5 8.47 8.42 10.25
Endosulfan sulfate 0.9991 5.77 3.88 1.01 4.17 0.89 19.0 12.8 3.33 13.8 2.95
Endrin 0.9995 2.42 3.38 1.05 0.75 2.91 8.00 11.1 3.45 2.49 9.60
Ethion 0.9851 1.22 4.29 2.43 0.56 3.08 4.01 14.1 8.01 1.83 10.2
Etrimfos 0.9998 0.57 1.26 0.43 0.33 0.80 1.89 4.16 1.43 1.09 2.62
Fenarimol 0.9997 0.23 0.60 0.43 0.53 0.88 0.75 1.99 1.43 1.74 2.91
Fenbuconazole 0.9999 0.30 0.55 0.34 0.24 0.27 0.98 1.82 1.12 0.78 0.88
Fenitrothion 0.9998 2.27 1.42 0.69 1.31 0.37 7.50 4.69 2.28 4.33 1.22
Fenpropathrin 0.9999 2.91 1.02 0.96 0.63 0.76 9.62 3.37 3.17 2.08 2.52
Fensulfothion 0.9944 3.45 4.99 2.58 2.21 2.48 11.4 16.5 8.50 7.28 8.20
Fenthion 0.9989 1.39 1.23 0.73 0.56 1.02 4.59 4.07 2.41 1.86 3.38
Fenvalerate 0.9998 0.93 4.43 0.37 0.90 2.32 3.08 14.6 1.23 2.96 7.65
Flusilazole 0.9996 0.88 0.57 0.79 0.33 0.85 2.90 1.89 2.62 1.10 2.80
Heptachlor 0.9995 1.96 2.02 0.57 1.07 1.20 6.46 6.68 1.88 3.51 3.96
Heptachlor epoxide 0.9974 1.93 5.82 3.10 1.21 1.11 6.37 19.2 10.2 3.99 3.69
Isofenphos 0.9994 0.80 1.27 0.76 0.70 0.51 2.64 4.18 2.52 2.32 1.67
keto Endrin 0.9984 3.25 3.09 1.17 1.18 1.34 10.7 10.2 3.87 3.90 4.43
Kresoxim methyl 0.9997 1.20 0.87 0.38 0.69 0.59 3.95 2.86 1.26 2.28 1.94
Mecarbam 0.9988 2.25 3.44 4.34 0.71 1.78 7.42 11.4 14.3 2.35 5.89
Methacrifos 1.0000 0.96 2.53 1.16 0.96 1.34 3.17 8.35 3.81 3.15 4.43
Methidathion 0.9978 1.89 1.32 0.69 0.58 0.79 6.22 4.37 2.29 1.91 2.60
Myclobutanil 0.9998 1.10 0.68 0.65 0.46 1.02 3.63 2.23 2.14 1.53 3.35
Oxychlordane 0.9994 0.96 1.72 1.55 1.08 1.73 3.18 5.66 5.10 3.56 5.71
Penconazole 0.9999 0.77 2.53 0.66 0.76 1.42 2.53 8.36 2.17 2.50 4.69
Pentachloraniline 0.9996 0.72 1.16 1.03 0.67 1.64 2.37 3.83 3.41 2.21 5.43
Pentachlorothioanisole 0.9989 3.12 2.57 0.84 1.65 1.66 10.3 8.48 2.78 5.45 5.49
Permethrin 0.9999 1.88 1.98 2.30 2.31 0.63 6.20 6.53 7.58 7.62 2.08
Phenthoate 0.9980 1.10 0.94 1.05 0.53 0.74 3.64 3.11 3.46 1.74 2.46
Phorate 0.9998 0.86 0.46 0.39 0.44 0.95 2.83 1.53 1.28 1.46 3.14
Phosalone 0.9998 1.10 0.85 1.55 0.56 1.19 3.61 2.81 5.10 1.83 3.92
Phosmet 0.9999 3.48 1.62 0.70 0.45 0.49 11.5 5.36 2.29 1.47 1.61
Primicarb 0.9985 0.37 0.65 0.46 0.19 0.41 1.23 2.13 1.52 0.62 1.35
Primiphos methyl 0.9988 4.61 1.66 1.99 0.87 1.15 15.2 5.48 6.56 2.85 3.78
Prochloraz 0.9992 1.17 1.77 1.30 3.03 0.48 3.87 5.83 4.28 10.01 1.59
Profenphos 0.9926 0.68 2.20 2.68 1.38 0.62 2.25 7.26 8.8 4.57 2.03
Propagite 0.9972 2.14 3.20 3.21 2.33 4.91 7.05 10.6 10.6 7.70 16.2
Propiconazole 0.9959 3.89 7.01 1.78 2.19 0.79 12.9 23.1 5.87 7.21 2.60
Pyriproxyfen 0.9993 0.82 1.42 2.94 0.88 0.95 2.70 4.69 9.70 2.89 3.13
Quintozene 0.9979 3.25 3.87 2.16 1.02 1.08 10.7 12.8 7.11 3.36 3.57
Terbufos 0.9995 2.87 1.73 4.82 5.65 3.24 9.4 5.70 15.9 18.7 10.7
Triadimefon 0.9976 0.68 1.95 1.28 0.58 0.93 2.26 6.43 4.24 1.92 3.05
Triadimenol 0.9959 3.34 2.13 2.46 2.37 2.45 11.0 7.03 8.12 7.81 8.09
Trizaofos 0.9982 1.54 3.52 0.69 0.55 1.11 5.07 11.6 2.29 1.83 3.66
Vinclozolin 0.9982 0.91 1.26 0.95 1.07 1.19 3.00 4.15 3.14 3.54 3.94

Linearity

The matrix-matched calibration curve was used to reduce the matrix effect of the method. During substance analysis, the intensity of the instrumental response should show a linearity that is quantitatively proportional to the amount of residue in the sample. This linearity can be confirmed using an internal standard material or by the addition of a standard to the matrix. In this study, the linearity of the calibration curve obtained by GC–MS/MS was observed at concentrations of 2.5, 10, 50, 100, 500, and 1000 µg/L with 5 replicates. Chromatograms of the pesticides in each time period contain the MS information of each ion; thus, a calibration curve can be produced using the MS intensity at each concentration. The correlation coefficients (R2) for the 66 substances reached 0.99–1.0 (Table 2), indicating a satisfactory agreement with the level (R2 > 0.99) recommended by the International Commission on Food Standards (CAC/GL 40, 2003). These results indicate that the proposed method is suitable for the calculation of residual amounts of the examined pesticides in the samples of interest and over the concentration range employed herein.

Accuracy and precision

To verify the efficiency and reliability of the proposed analytical method, the recovery was used to determine the accuracy, while the RSD was used to obtain the precision. The standard pesticide solutions were added to each matrix at concentrations of 5, 10, and 100 µg/kg for five replicates to determine recovery and RSD. A high-concentration standard (100 µg/kg) was included to validate the method for pesticides with high Korean MRLs in livestock products such as endrin (1.0 mg/kg for poultry meat, 0.1 mg/kg for pig muscle), DDT (0.3 mg/kg for poultry meat, 0.1 mg/kg for eggs), chlorfenvinphos (0.2 mg/kg for cattle meat), and permethrin (0.1 mg/kg for milk). The results presented in Table 3 indicate that the pesticides showed similar tendencies for all samples, and the various pesticides were successfully recovered in all cases, likely due to the inclusion of 1% formic acid in the acetonitrile extraction solvent, i.e., the recovery was improved by the auxiliary role of the acid (AOAC, 2010; Codex, 2003; USFDA, 1999). In addition, a previous study showed that the recovery increased upon increasing the concentration from 5 to 10 µg/kg and then to 100 µg/kg due to a smaller matrix effect (Mastovska et al., 2005); however, no significant differences were observed herein when different concentrations were employed. The recoveries ranged from 70.1 to 118% for beef, 70.1 to 116% for pork, 70.0 to 120% for chicken, 70.1 to 120% for eggs, and 70.1 to 105% for milk, giving an overall recovery range of 70.0–120%. Figure 2 shows the distribution of the average recovery ranges of the pesticides for each product. The main recovery distribution was located differently for each product. Of the tested pesticides, 88% had recoveries of 70–80% for beef and 35% had recoveries of 81–90% for pork. The highest recovery rates were 91–100% for chicken, 101–110% for eggs, and 111–120% for milk, but the distribution rates were not significantly different.

Table 3.

Recovery and relative standard deviation (RSD) at three concentrations of pesticides in livestock products

Pesticide Fortified Concentration (mg/kg) Beef Pork Chicken Eggs Milk
Recovery (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%)
Aldrin 0.005 71.6 10.1 70.8 8.79 76.7 13.2 87.6 10.0 85.7 11.4
0.01 72.3 3.73 70.9 6.57 85.5 6.65 85.6 16.3 95.5 8.05
0.1 70.4 6.42 70.1 4.45 90.2 12.3 90.0 11.7 93.7 2.93
BHC-gamma 0.005 72.7 16.7 70.6 6.99 75.4 15.9 95.1 1.26 92.2 8.69
0.01 72.0 3.90 70.5 6.30 77.8 9.09 85.0 11.0 88.7 4.31
0.1 72.5 9.80 74.4 6.64 73.2 18.6 90.0 8.45 88.9 3.98
Bifenthrin 0.005 75.1 8.26 82.3 4.83 89.4 4.96 116 4.68 90.6 5.76
0.01 79.9 5.88 76.2 6.57 90.0 3.90 111 13.1 86.1 3.81
0.1 75.8 6.87 85.9 3.60 116 3.08 120 10.7 84.2 2.99
Chinomethionat 0.005 71.2 8.44 72.0 10.0 103 7.86 73.0 3.61 95.1 9.34
0.01 75.8 4.85 70.1 9.41 105 6.90 71.1 6.43 95.3 3.67
0.1 74.5 7.12 74.3 12.4 114 9.62 70.6 14.7 90.9 3.67
Chlordane-cis 0.005 102 9.12 77.8 15.1 81.1 17.2 110 12.7 100 11.7
0.01 92.4 5.30 73.9 12.9 86.9 12.6 97.7 15.9 97.4 3.35
0.1 71.4 6.16 74.3 17.1 105 7.18 77.1 19.5 94.7 5.90
Chlordane-trans 0.005 74.6 10.8 78.2 14.1 85.9 14.2 74.9 2.43 73.3 12.3
0.01 72.5 5.31 77.3 12.1 89.2 9.88 71.5 11.4 76.9 12.2
0.1 70.5 10.0 83.2 7.13 116 8.81 71.0 11.9 91.1 8.42
Chlorfenvinphos 0.005 76.6 12.7 83.4 6.44 85.3 9.43 78.4 13.7 92.9 7.21
0.01 81.0 5.37 74.2 6.73 85.9 4.65 84.3 8.16 84.2 3.65
0.1 70.6 8.56 86.8 3.78 85.4 8.56 87.5 13.3 95.9 3.10
Chlorpyrifos 0.005 73.4 10.8 86.5 9.52 86.7 7.38 116 6.27 95.2 9.80
0.01 78.9 1.56 72.2 7.30 91.8 8.62 104 12.0 95.4 4.60
0.1 74.7 19.1 81.5 2.76 103 5.07 111 10.9 97.2 3.34
Chlorpyrifos-methyl 0.005 81.4 12.8 95.3 6.84 81.9 13.2 91.7 15.2 81.9 10.6
0.01 92.6 5.47 80.0 4.25 84.0 4.21 92.8 16.4 87.9 8.33
0.1 75.0 9.02 97.8 2.79 86.7 14.7 99.1 8.36 95.8 1.81
Cypermethrin 0.005 88.6 3.04 104 8.01 86.9 5.25 109 10.4 89.7 4.64
0.01 93.8 4.66 93.5 7.78 90.6 3.58 119 16.2 84.6 2.38
0.1 77.9 7.29 101 3.91 109 4.99 120 9.76 92.2 5.20
p,p′-DDD 0.005 72.7 14.3 81.2 3.91 87.3 9.25 114 2.93 93.5 5.96
0.01 71.4 5.03 74.7 7.19 89.2 8.52 114 13.4 89.1 3.77
0.1 70.3 11.6 89.1 4.52 112 5.24 118 12.1 95.2 4.31
p,p′-DDE 0.005 70.5 8.81 71.8 8.35 88.9 6.90 108 0.44 89.6 4.63
0.01 70.3 4.25 70.9 7.94 93.0 5.77 91.7 16.1 85.5 2.70
0.1 70.2 6.96 71.1 13.9 118 3.81 94.9 13.0 72.6 3.73
o, p-DDT 0.005 113 11.3 74.1 3.75 85.5 5.17 82.4 9.18 80.4 7.57
0.01 71.3 18.1 75.7 6.71 83.8 9.56 75.8 15.8 90.1 2.73
0.1 70.2 16.3 77.1 7.66 103 1.55 74.9 8.90 79.2 3.72
p,p′-DDT 0.005 70.7 14.7 75.7 5.15 73.8 6.02 102 19.2 74.9 5.57
0.01 75.9 8.64 78.6 6.60 71.3 3.25 106 4.92 70.1 5.01
0.1 72.2 13.1 75.9 5.39 89.4 8.10 88.6 12.2 72.6 3.73
Diazinon 0.005 72.0 12.7 71.3 7.86 72.0 12.7 99.4 3.99 71.3 15.4
0.01 76.6 2.41 70.6 8.41 76.6 2.41 88.2 10.8 73.4 5.54
0.1 74.6 7.84 77.9 5.71 74.6 7.84 94.4 12.4 70.5 6.99
Dichlorvos 0.005 103 13.1 76.5 19.8 73.9 3.04 77.5 11.9 73.5 13.1
0.01 110 4.92 74.4 11.8 72.1 8.02 70.9 9.74 71.9 5.19
0.1 113 5.22 77.7 14.5 70.2 3.38 71.5 19.6 70.6 7.90
Dieldrin 0.005 77.9 15.2 116 7.41 83.9 11.0 98.2 2.59 86.6 7.09
0.01 72.4 8.69 70.9 10.8 87.6 10.6 81.7 8.80 88.1 3.72
0.1 76.2 7.99 74.8 7.28 102 3.75 85.1 10.6 81.4 3.17
Dimethoate 0.005 79.5 15.0 87.4 8.86 90.3 7.16 91.5 15.2 76.8 8.85
0.01 90.4 5.61 86.8 6.90 82.9 11.2 104 13.7 70.9 6.08
0.1 81.7 11.3 104 1.86 116 5.65 96.8 8.09 82.4 3.54
Diphenylamine 0.005 113 11.5 70.5 17.7 107 13.1 84.3 3.41 80.9 11.8
0.01 111 3.33 112 9.94 114 11.4 75.7 4.71 94.5 10.9
0.1 88.7 6.54 97.8 11.0 107 5.25 72.4 6.48 93.8 9.91
Disulfoton 0.005 96.7 13.1 91.9 4.07 71.4 11.4 99.5 2.16 81.0 7.38
0.01 102 8.19 105 13.5 79.9 5.16 89.9 11.7 78.9 4.22
0.1 86.8 8.09 79.7 13.2 73.3 8.91 77.1 9.07 77.2 5.68
Edifenphos 0.005 73.0 15.3 84.3 8.68 75.1 4.58 77.1 9.02 75.5 6.40
0.01 82.0 4.13 75.9 13.1 75.8 6.13 70.5 10.6 71.9 3.86
0.1 74.9 12.4 99.6 10.3 97.9 5.57 79.6 15.3 71.3 5.40
Endosulfan alpha 0.005 70.9 15.8 77.2 18.5 91.6 9.83 102 3.44 97.8 10.5
0.01 72.8 12.0 72.5 12.7 97.7 13.4 98.0 12.3 96.3 3.49
0.1 71.7 14.6 75.5 14.9 107 9.28 71.0 8.24 94.3 2.34
Endosulfan beta 0.005 108 10.7 77.4 16.2 83.6 12.4 114 2.22 95.9 12.7
0.01 71.2 19.7 70.6 5.92 90.4 12.4 95.2 15.8 83.4 6.16
0.1 71.6 10.7 79.4 2.83 109 2.94 114 8.18 95.5 4.54
Endosulfan sulfate 0.005 74.4 12.3 84.1 6.82 71.7 4.12 73.8 8.69 99.9 10.9
0.01 70.5 6.40 77.6 10.1 80.5 4.23 86.5 18.1 91.7 4.17
0.1 70.6 12.2 87.8 8.92 114 6.35 84.9 9.86 92.1 2.88
Endrin 0.005 70.7 15.7 75.9 11.3 84.3 15.1 93.8 15.7 92.2 7.15
0.01 77.0 8.13 70.8 5.34 86.7 6.96 86.5 18.1 79.9 5.68
0.1 71.7 12.9 77.0 5.69 99.2 4.27 84.9 9.86 79.5 2.71
Ethion 0.005 89.8 11.7 74.3 19.9 76.2 10.6 115 0.23 92.9 11.5
0.01 78.1 11.9 71.5 17.8 77.8 12.0 110 0.52 84.1 5.41
0.1 90.0 3.44 91.2 19.1 99.3 4.18 115 6.29 96.2 2.07
Etrimfos 0.005 70.1 11.9 76.8 5.42 70.6 17.7 97.5 0.24 76.7 8.09
0.01 73.2 3.05 77.4 5.79 70.5 2.28 83.5 9.61 76.7 6.27
0.1 72.5 9.04 74.8 4.10 70.2 7.20 88.0 6.32 76.3 4.67
Fenarimol 0.005 75.6 10.8 85.4 7.38 80.6 14.2 111 11.9 93.4 4.09
0.01 84.3 6.30 81.3 6.91 88.0 2.07 111 12.0 94.9 2.10
0.1 71.6 7.77 89.4 5.12 102 8.56 119 10.0 96.3 3.28
Fenbuconazole 0.005 84.2 9.81 88.5 7.16 82.2 14.7 119 15.4 85.3 9.05
0.01 90.2 6.05 86.2 6.99 82.0 2.72 119 9.62 80.2 2.77
0.1 76.8 6.88 95.0 4.22 108 9.73 117 12.3 87.2 1.55
Fenitrothion 0.005 72.6 13.4 70.8 4.83 80.0 8.37 111 2.40 83.2 9.77
0.01 80.5 4.89 80.1 5.49 87.3 9.80 95.1 8.32 86.0 4.91
0.1 71.0 11.4 90.7 6.26 100 8.56 72.4 18.0 85.4 5.59
Fenpropathrin 0.005 79.0 7.11 82.3 4.42 89.0 5.91 110 8.43 90.2 3.95
0.01 83.8 4.76 79.4 7.48 88.9 7.12 113 11.2 88.4 3.41
0.1 73.6 7.61 90.3 3.24 115 0.57 119 9.94 92.7 4.01
Fensulfothion 0.005 73.7 8.67 72.3 18.7 75.7 9.16 73.8 12.2 72.4 16.6
0.01 71.3 11.7 71.3 7.77 82.8 10.7 78.5 5.63 75.9 11.5
0.1 70.8 10.5 72.4 10.9 103 11.8 70.4 10.3 71.1 14.7
Fenthion 0.005 72.8 10.3 72.0 7.33 76.6 6.90 108 2.52 93.0 9.64
0.01 72.6 4.02 71.1 4.74 76.6 9.12 87.4 12.1 83.6 4.05
0.1 72.2 8.18 71.9 8.97 79.1 12.7 93.9 9.45 90.3 4.73
Fenvalerate 0.005 87.2 8.51 99.4 2.76 88.1 6.90 111 15.6 98.4 5.29
0.01 89.9 5.29 91.9 7.08 87.6 5.19 107 14.5 91.8 2.92
0.1 76.3 7.14 100 3.69 109 6.90 113 9.61 82.0 3.78
Flusilazole 0.005 76.3 11.0 74.6 8.31 87.1 10.6 114 6.34 91.0 6.69
0.01 82.5 3.87 78.2 6.36 86.7 6.50 107 13.8 82.0 4.72
0.1 70.2 9.68 80.3 4.51 116 6.50 113 11.9 89.0 1.92
Heptachlor 0.005 71.9 15.0 74.5 6.95 73.3 1.73 92.6 2.55 89.4 9.89
0.01 72.1 3.70 75.5 7.26 77.9 8.80 80.7 10.4 83.6 9.75
0.1 70.5 7.83 72.1 10.3 97.6 3.22 78.7 7.59 93.2 6.93
Heptachlor epoxide 0.005 73.5 16.3 75.5 15.4 80.0 12.0 85.3 1.95 95.0 12.3
0.01 70.6 10.4 71.0 9.65 95.8 11.3 87.9 5.46 95.6 3.71
0.1 72.0 6.90 79.3 3.61 102 8.02 101 7.50 94.6 1.22
Isofenphos 0.005 76.0 6.87 80.2 6.66 85.0 9.72 96.0 3.46 93.6 7.31
0.01 77.1 4.21 72.6 7.13 83.9 6.18 87.6 11.0 89.8 4.43
0.1 75.3 9.32 81.3 2.13 86.4 10.5 99.1 10.2 90.7 2.54
keto Endrin 0.005 97.6 17.0 70.2 9.77 78.7 11.5 107 5.14 89.7 7.45
0.01 70.6 15.2 70.2 6.71 80.2 8.10 91.3 14.3 97.9 4.85
0.1 71.3 10.9 71.8 14.4 109 2.07 97.2 11.3 95.4 3.43
Kresoxim methyl 0.005 71.1 9.98 81.1 6.46 82.4 15.2 118 4.51 90.9 6.34
0.01 70.7 4.17 72.4 7.14 86.5 11.2 112 15.3 72.4 6.73
0.1 70.8 7.64 72.7 11.4 106 9.76 113 15.7 87.8 5.70
Mecarbam 0.005 81.0 9.76 94.1 15.7 89.8 6.61 112 3.00 98.7 11.7
0.01 76.0 2.82 82.5 19.9 85.3 14.8 110 2.88 93.0 6.21
0.1 71.7 9.78 81.5 3.76 113 6.41 106 9.67 89.4 3.20
Methacrifos 0.005 110 12.0 70.4 17.9 81.0 9.76 81.9 2.93 70.2 12.0
0.01 72.5 19.4 71.3 4.74 76.0 2.82 85.8 12.2 70.4 9.82
0.1 72.5 19.1 76.5 8.05 71.7 9.78 84.7 5.89 73.2 11.1
Methidathion 0.005 71.8 10.0 71.1 10.8 105 8.20 70.1 12.4 94.4 6.69
0.01 71.4 4.93 70.4 7.06 101 4.92 71.1 10.7 91.5 3.27
0.1 75.7 7.83 71.8 7.90 120 9.98 71.5 13.7 88.0 2.56
Myclobutanil 0.005 75.3 9.05 77.1 9.11 83.0 18.2 117 15.8 86.8 7.09
0.01 71.1 5.68 70.5 7.01 85.8 8.41 118 16.2 86.9 5.77
0.1 71.2 7.40 77.6 8.19 112 8.03 115 13.4 92.3 4.62
Oxychlordane 0.005 72.3 11.6 73.8 8.78 93.5 9.65 102 6.83 92.5 11.6
0.01 72.0 8.33 72.0 10.8 90.0 4.28 93.5 6.20 93.9 4.21
0.1 72.3 9.81 75.5 5.06 102 10.4 105 10.5 91.2 3.77
Penconazole 0.005 79.8 8.54 92.4 10.6 97.5 6.41 109 3.16 93.8 8.93
0.01 81.4 7.29 82.5 8.07 91.7 8.28 101 10.5 95.4 3.09
0.1 72.7 7.94 93.2 3.12 118 4.12 110 10.3 88.5 3.03
Pentachloraniline 0.005 71.3 9.68 75.9 4.57 82.6 13.7 84.0 0.33 89.1 11.5
0.01 70.2 2.78 71.6 8.05 86.5 2.78 81.3 10.6 76.7 4.73
0.1 71.6 5.47 80.1 3.16 87.8 11.7 83.9 9.23 84.7 11.7
Pentachlorothioanisole 0.005 70.1 19.2 72.1 3.15 85.2 2.55 90.8 9.53 82.4 5.68
0.01 70.6 11.7 71.4 4.40 87.0 5.37 83.6 14.0 92.0 5.98
0.1 71.9 12.9 78.1 4.55 97.5 17.5 86.5 9.59 99.0 6.30
Permethrin 0.005 77.2 4.96 72.8 4.09 94.4 4.56 117 7.87 81.9 9.70
0.01 73.2 6.01 72.2 8.39 93.7 9.63 111 11.2 76.1 2.05
0.1 75.4 6.93 94.2 4.17 110 6.54 116 10.1 80.4 3.53
Phenthoate 0.005 73.2 10.6 80.3 7.18 90.4 8.99 100 2.26 94.0 6.86
0.01 78.6 4.52 70.1 7.04 90.2 7.38 93.7 11.7 86.8 5.46
0.1 75.4 7.54 79.4 1.94 88.4 7.84 94.6 10.8 91.5 4.74
Phorate 0.005 86.8 17.3 70.3 10.8 88.4 15.8 93.8 2.75 86.6 8.16
0.01 110 5.27 84.9 3.96 118 7.47 87.3 11.8 80.9 6.75
0.1 92.3 5.20 74.3 4.28 116 5.69 90.4 6.63 80.6 4.99
Phosalone 0.005 79.6 13.4 91.3 3.28 83.7 11.8 105 11.0 83.1 4.47
0.01 84.6 4.40 83.2 7.35 88.5 6.03 93.4 12.0 90.7 6.96
0.1 71.0 9.27 92.4 3.11 107 3.90 101 10.7 96.4 5.71
Phosmet 0.005 75.3 13.2 87.6 6.97 73.4 9.46 93.2 19.8 90.1 2.91
0.01 82.8 7.43 84.1 8.68 74.4 5.84 83.7 10.6 85.2 3.14
0.1 72.6 10.8 99.4 3.45 99.9 5.64 87.2 14.2 87.0 3.19
Primicarb 0.005 72.4 10.5 76.9 9.61 76.1 15.4 101 9.37 73.3 12.6
0.01 76.2 3.87 71.1 6.77 72.0 1.69 92.0 8.83 71.3 7.73
0.1 81.5 6.87 79.6 3.54 86.1 11.7 95.6 7.88 74.3 6.11
Primiphos methyl 0.005 70.1 18.3 74.4 11.3 72.5 12.0 72.4 8.62 74.9 15.5
0.01 77.4 4.18 74.8 9.06 78.9 6.27 74.1 6.52 71.3 6.11
0.1 72.4 11.6 83.6 5.50 85.8 10.2 72.7 16.6 72.5 3.74
Prochloraz 0.005 77.1 10.0 81.7 7.64 80.1 12.8 115 9.44 79.5 9.51
0.01 82.9 6.66 79.0 8.18 77.8 5.30 96.3 11.8 74.0 6.81
0.1 70.2 8.38 88.0 5.25 97.0 8.77 98.3 13.6 77.3 2.69
Profenphos 0.005 118 9.12 92.4 15.9 118 9.12 80.2 10.6 71.1 19.7
0.01 94.9 6.01 76.0 16.9 94.9 6.01 91.2 11.2 71.0 13.7
0.1 70.3 14.8 72.7 17.0 70.3 14.5 85.3 12.3 90.0 4.71
Propagite 0.005 104 16.3 74.2 19.4 70.2 1.78 70.1 3.05 74.3 8.53
0.01 75.2 15.2 70.6 14.5 70.5 3.67 74.2 4.77 75.1 6.94
0.1 72.6 6.96 73.3 4.24 70.0 4.60 71.2 2.98 77.2 3.16
Propiconazole 0.005 71.6 16.1 85.9 19.9 71.6 16.1 107 14.8 92.8 10.9
0.01 109 6.59 77.8 15.4 109 6.59 84.2 15.2 70.9 5.02
0.1 71.7 7.38 71.0 3.22 71.7 7.38 73.0 14.5 73.9 3.13
Pyriproxyfen 0.005 84.9 10.2 86.7 5.13 74.1 15.1 112 17.1 87.9 8.26
0.01 85.2 7.02 80.1 6.85 83.7 6.06 113 14.5 91.6 5.18
0.1 71.8 7.75 88.0 3.61 114 4.91 119 9.96 89.9 6.26
Quintozene 0.005 102 14.2 74.0 6.62 77.2 15.2 81.4 2.16 88.0 7.68
0.01 99.2 4.33 75.5 7.47 79.6 5.55 77.0 13.6 87.4 5.60
0.1 82.3 4.98 90.6 1.71 102 1.30 77.0 6.53 86.8 3.41
Terbufos 0.005 79.3 15.0 112 10.1 79.3 15.0 81.4 18.4 82.2 11.4
0.01 77.3 18.2 83.0 5.20 77.3 18.2 104 7.62 105 11.2
0.1 76.1 11.2 87.0 3.49 76.1 11.2 89.2 8.83 85.1 5.02
Triadimefon 0.005 78.1 13.0 79.9 10.2 86.6 12.6 109 6.78 82.9 13.0
0.01 79.6 9.36 72.0 7.33 86.2 2.41 99.4 8.45 76.5 6.35
0.1 71.2 7.80 84.1 4.13 109 7.23 106 10.7 87.3 3.08
Triadimenol 0.005 83.3 15.1 99.7 11.9 86.7 5.41 105 6.69 72.2 4.37
0.01 73.9 1.79 71.7 10.9 72.6 12.5 115 4.99 73.1 4.31
0.1 76.2 6.03 73.5 8.46 104 12.3 117 9.98 75.1 3.10
Trizaofos 0.005 81.0 7.93 83.3 7.49 74.1 9.60 118 9.84 89.7 7.13
0.01 84.6 5.43 78.9 6.17 81.7 12.7 115 11.1 83.9 4.77
0.1 71.4 6.89 88.1 3.71 101 7.41 118 10.9 93.7 4.27
Vinclozolin 0.005 90.6 8.08 82.2 2.74 83.8 14.3 100 1.92 95.1 7.07
0.01 92.8 4.24 82.9 8.53 86.0 5.35 97.9 10.1 89.1 4.20
0.1 79.9 8.10 95.2 1.94 96.3 6.47 99.2 9.03 85.3 3.04

Fig. 2.

Fig. 2

Distribution of the average recovery of pesticides in beef, pork, chicken, eggs, and milk

The method precision was then obtained by calculating the RSD of the pesticide recoveries from the beef, pork, chicken, egg, and milk samples. The RSD ranged from 1.56 to 19.7% for beef, 1.71 to 19.9% for pork, 0.57 to 19.9% for chicken, 0.23 to 19.8% for eggs, and 1.22 to 19.7% for milk (Table 3). These results confirm that for all samples, the RSD satisfied the CAC/GL 40 criteria of < 20% at concentrations of > 0.01 mg/kg and ≤ 0.1 mg/kg.

Monitoring of market samples

Monitoring was conducted for a total of 89 samples (14 beef, 15 pork, 15 chicken, 15 eggs, and 15 milk) collected from Seoul, Busan, and Incheon markets in Korea, and the contents of the 66 pesticides in these samples were simultaneously analyzed. Chlorpyrifos and fenitrothion in beef and chlorpyrifos in pork were detected at levels lower than the respective MRLs (chlorpyrifos: 1.0 mg/kg in cattle fat; 0.02 mg/kg in pig fat; fenitrothion 0.05 mg/kg in mammal fat). No other pesticides were found in any of the samples. In addition, 15 samples of lamb, the consumption of which has increased in Korea were also collected for monitoring; however, none of the 66 target pesticides were detected. These results were compared with Surma et al. (2014), who found organochlorine pesticides, DDT, BHC and its isomers in ham. Additionally, Rejczak and Tuzimski (2017) reported that low (ng/mL) levels of monuron, methabenzthiazuron, buturon, linuron, aziprotryne, bitertanol, and clofentezine were detected in natural milk samples. However, no pesticides were found in milk in this study. Since pesticides are ubiquitous in the environment and are commonly found as residues in livestock products, continuous pesticide monitoring is required, as is the development of improved methods to allow for the determination of low–concentration multi-residue pesticides in these matrices.

In conclusion, the simultaneous analysis of pesticides presented in this study indicated the potential of the method for the rapid monitoring of residual pesticides in livestock products, due to its short run time, inexpensive nature, simple procedure, and high efficiency. An efficient extraction method was developed using a florisil cartridge as an adsorbent to simultaneously analyze 66 pesticides, including organic phosphorus and chlorine, in a single experiment. The experimental steps were simple and resulted in low LODs and LOQs. The highly sensitive method satisfies the Codex’s criteria and is environmentally friendly with less solvent and waste than conventional approaches. The results of this study will help in establishing a continuous, precise and reliable monitoring system for livestock products in a fast and efficient manner. Expanding the simultaneous analysis of pesticide residues in livestock products will continue to receive focus in our future studies.

Acknowledgements

This study was supported by a Grant (18161MFDS014) from the Ministry of Food and Drug Safety, Korea.

Compliance with ethical standards

Conflict of interest

No potential conflicts of interest are reported by the authors.

Footnotes

Publisher's Note

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Contributor Information

Hye Soon Kang, Email: cobaltblue@korea.kr.

MeeKyung Kim, Email: mkim@korea.kr.

Eun Jeong Kim, Email: hisclif@korea.kr.

Won-Jo Choe, Email: aragara06@korea.kr.

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