The Korean Society of Pesticide Science

The Korean Journal of Pesticide Science - Vol. 24 , No. 4

[ Original Article ]
The Korean Journal of Pesticide Science - Vol. 24, No. 4, pp.321-333
Abbreviation: Korean J. Pestic. Sci.
ISSN: 1226-6183 (Print) 2287-2051 (Online)
Print publication date 31 Dec 2020
Received 24 Sep 2020 Revised 22 Oct 2020 Accepted 28 Oct 2020
DOI: https://doi.org/10.7585/kjps.2020.24.4.321

Multi-Residue Determination of Pesticides in Farmed Aquatic Animal Products Using Gas Chromatography-Tandem Mass Spectrometry
Dasom Shin ; Joohye Kim1 ; Hui-Seung Kang1 ; Chi-Hwan Lim*
Department of Bio-Environmental Chemistry, College of Agriculture and Life Sciences, Chungnam National University, Daejeon 34134, Republic of Korea
1Pesticide and Veterinary Drug Residues Division, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Osong, Cheongju, Chungcheongbuk-do 28159, Republic of Korea

Correspondence to : *Email: chlim@cnu.ac.kr

Funding Information ▼

Abstract

In the present study, an analytical method was developed and optimized for screening and confirmation of multi-pesticide residues in farmed aquatic animal samples. Target pesticides (organochlorines, organophosphorus, and synthetic pyrethroids) were extracted via the QuEChERS (quick, easy, cheap, effective, rugged, and safe) approach. Ethyl acetate was used for extraction of pesticides from the samples (flatfish, eel, shrimp, and Manila clam), which were then purified using C18 and primary secondary amine. Finally, the extracts were filtered through a 0.22-μm polytetrafluoroethylene syringe filter and subsequently analyzed using gas chromatography coupled with mass spectrometry. The target analytes were ionized in the positive mode of electron impact ionization using multiple reaction monitoring. According to the CODEX CAC/GL-71 guideline, accuracy, precision, linearity, and limit of detection were evaluated for all matrices. The accuracy (recoveries) was between 62.4% and 120%, and precision (relative standard deviations) was below 20%. The linearity of the matrix calibration curves was r2>0.98. The limits of detection and quantification for all pesticides were ≤3 μg/kg and ≤10 μg/kg, respectively. In real sample (n=79) analysis, trifluralin was detected at 67 μg/kg in one Manila clam sample. Based on our results, the proposed method was satisfactory for pesticide residue determination in aquatic animal products.


Keywords: Analytical method, Fishery products, GC-MS/MS, Pesticide, Residue

Introduction

A wide range of pesticides (insecticide, fungicides, and herbicides) could potentially be transferred into aquatic animal tissue; however, little is known about pesticide accumulation in aquatic animal products. Although most persistent pesticides have been banned since the 1970s, they are still continuously being detected in seafood (Zhao et al., 2016). The organochlorine pesticides have low volatility, high stability, and lipophilic behavior, which are responsible for their persistence in the environment and concentration in fat and tissues. The unintended use of pyrethroids and organophosphorus pesticides is sufficient to reach rivers and the marine environment, thus affecting aquatic animal products. Owing to their metabolic activity in animals, pyrethroids tend to bioaccumulate, becoming a potential source of contamination in foodstuffs. Consequently, pesticide residues have to be monitored in foodstuffs to control food quality and prevent risks to human health (Stefanelli et al., 2009). In addition, a previous study reported that certain pesticides are illegally used in high concentrations for controlling and preventing parasitic and microbial diseases under stressful conditions in fish farms (Sabra & Mehana, 2015). Therefore, pesticide residues should also be monitored and controlled on aquaculture farms and the surrounding environment (Sapozhnikova & Lehotay, 2015).

Due to the structure of pesticides and their chemical properties, pesticide residues are usually analyzed using gas chromatography coupled with electron capture detection (GC/ECD) or using mass spectrometry (GC/MS). GC–MS/MS is a selective and sensitive technique that is acceptable for the simultaneous detection of volatile and thermostable pesticide residues in food commodities of animal origin (Raina, 2011). The analytical methods used for the determination of pesticide residues in animal products and food samples (n=60) had a detection rate of 41.7% (Nasiri et al., 2016; Zhao et al., 2016). However, there is a paucity of information on analytical methods used for multipesticides in fish using GC-MS/MS (Sapozhnikova & Lehotay, 2013). There are currently no analytical methods for the simultaneous determination of 51 compounds in aquatic animal products.

Pesticide residue analysis in aquatic animal product samples is challenging due to the low concentrations and a wide range of pesticides in a complex matrix (Chan et al., 2012). Therefore, it is necessary to develop rapid, reliable, and effective analytical methods for the simultaneous determination of multiple pesticide compounds (Nasiri et al., 2016). Based on our previous study, we focused on 51 pesticides (including thermostable and strong volatile organochlorines, organophosphorus, and pyrethroids) having the potential to contaminate aquatic animal products. An analytical method was developed and validated for the determination of pesticides in fish (flatfish and eel), shrimp, and Manila clam. The proposed method was applied to aquatic animal samples collected from retail markets.


Materials and Methods
Reagents and chemicals

All pesticide standards were of high purity (>90%) and were purchased from Dr. Ehrenstofer (Augsburg, Germany) and Sigma-Aldrich (Buchs, Switzerland). HPLC grade ethyl acetate, methanol, acetone, and n-hexane were purchased from Merck Inc. (Darmstadt, Germany). Anhydrous magnesium sulfate (MgSO4), sodium chloride, and octadecylsilane (C18) were purchased from Sigma-Aldrich and Waters (Milford, MA, USA), respectively. A filter of 0.22- μm polytetrafluoroethylene (PTFE) was acquired from Teknokroma (Barcelona, Spain).

The stock solution of individual analyte (approximately 1000 μg/mL) was prepared in a 50-mL volumetric flask using acetonitrile, methanol, acetone, and n-hexane as solvents. For working standard mixtures, a range of final target concentrations was prepared in acetone from the above stock solution by serial dilution. All stock solutions were stored at -20°C in amber glass bottles to prevent photolysis.

Sample preparation

Aquatic animal product samples were purchased from local markets in Korea. The de-skinned fillets (over 500 g) were homogenized and then stored at -20°C. The blank samples were tested to ensure that it did not contain any of the target pesticides before use as a negative control. The aquatic animal samples (over 500 g) were prepared for analysis using matrix-matched calibration and monitoring. The homogenized samples (2 g) of aquatic animal samples were transferred into a 50 mL centrifuge tube. Thereafter, 10 mL of ethyl acetate was added to each sample, shaken vigorously by hand for 30 s. This was followed by the addition of 500 mg of NaCl and 1g of anhydrous MgSO4 to each sample, which was then vortexed for 5 min. After vortexing, the extracts were put into a freezer at -20°C for 15 min and then centrifuged at 4500 × g at a temperature of 4°C for 10 min. The supernatant was transferred into a 50 mL centrifuge tube. The organic phase was evaporated under nitrogen stream at 50°C and diluted in 10 mL of acetonitrile, after which C18 (200 mg), PSA (200 mg), and anhydrous magnesium sulfate (500 mg) were added. The mixture was shaken for 5 min and centrifuged at 4500 × g, 4°C for 10 min. The supernatant was trans- ferred into a 15-mL centrifuge tube and evaporated using nitrogen stream at 50°C and reconstituted with 1mL of 20% acetone in hexane. Finally, the extracts were filtered through a 0.22-μm PTFE syringe filter. The final extracts (5 μL) were injected into the GC-MS/MS system for further analysis.

GC-MS/MS analysis

An Agilent 7890 GC system coupled with an Agilent 7010 GC/MS Triple Quadrupole (Agilent Technologies, Santa Clara, CA, USA) and a Rxi®-5Sil MS (0.25mm i.d. × 30 m, 0.50 μm film thickness) capillary column was used for the GC-MS/MS analysis. Electron impact ionization (EI) mass spectra was obtained at 70 eV and monitored from 100 to 600 m/z for full scan mode analysis. The working parameters were as follows: injector temperature was set at 280°C and the carrier gas (He) at 1.0 mL/min. The optimized GC oven temperature was initially 70°C (held for 3 mins), increased to 180°C at a rate of 20°C/min, and then finally to 300°C at 5°C/min (held for 7 mins). The mass selective detector transfer line was set at 280°C and the ion source at 230°C. The injection mode was splitless, and the injection volume was 1μ L. Data collection was performed in the multiple reaction monitoring (MRM) mode, and the optimized MRM parameters are listed in Table 1.

Table 1. 
MRM transition and optimized parameters of GC-MS/MS for 51 target compounds
Compounds Formula Retention time
(min)
Molecular weight
(g/mol)
Precursor ion
(m/z)
Product ion
(m/z)
Collision energy
(eV)
Aldrin C12H8Cl6 15.9 364.9 263a) 193 40
263 191 40
255 220 15
Allethrin C19H26O3 17.1 302.4 136 93.0 20
123 81.0 10
123 79.9 20
alpha-HCH C6H6Cl6 12.1 290.8 219 183 85
217 181 85
181 145 15
beta-HCH C6H6Cl6 12.7 290.8 219 183 10
219 147 30
181 145 10
Carbophenothion C11H16ClO2PS3 21.1 342.9 344 159 85
342 199 85
342 157 85
Chlordane_cis C10H6Cl8 18.2 409.8 375 266 20
373 266 20
373 264 20
Chlordane_trans C10H6Cl8 17.7 409.8 375 266 20
373 266 20
373 264 20
Chlorpropham C10H12ClNO2 11.6 213.7 213 171 10
213 127 85
171 127 15
Chlorpyrifos C9H11Cl3NO3PS 15.7 350.6 314 258 20
199 171 15
197 169 15
Chlorpyrifos_methyl C7H7Cl3NO3PS 14.4 322.5 286 271 20
286 93.0 20
- - -
delta-HCH C6H6Cl6 13.6 290.8 219 147 30
181 146 10
181 145 10
Deltamethrin C22H19Br2NO3 31.4 505.2 255 174 5
253 174 5
253 93.0 15
Dicofol C14H9Cl5O 16.2 370.5 250 139 15
139 111 15
139 75.0 35
Dieldrin C12H8Cl6O 18.1 380.9 277 241 10
277 206 20
263 193 20
Endosulfan_alpha C9H6Cl6O3S 18.2 406.9 241 206 20
239 204 20
207 172 20
dosulfan_beta C9H6Cl6O3S 20.0 406.9 241 206 15
207 172 15
205 170 15
Endosulfan_sulfate C9H6Cl6O3S 20.2 406.9 274 237 25
272 237 20
239 204 15
Endrin C12H8Cl6O 19.0 380.9 263 193 40
263 191 35
245 173 30
Endrin keton C12H8Cl6O 22.9 380.9 317 281 10
317 245 20
317 101 15
EPN C14H14NO4PS 23.2 323.3 169 141 5
169 77.0 20
157 77.0 30
Etofenprox C25H28O3 28.9 376.5 163 135 10
163 107 20
163 77.0 30
Fenpropathrin C22H23NO3 23.5 349.4 265 210 10
265 89 40
209 116 15
Fipronil C12H4Cl2F6N4OS 16.8 437.1 367 255 30
367 213 30
351 255 15
Fipronil sulfone C12H4Cl2F6N4O2S 18.7 453.1 383 255 30
383 241 15
255 228 15
Flusilazole C16H15F2N3Si 19.0 315.4 233 165 20
233 152 20
233 91.0 30
gamma-HCH C6H6Cl6 13.0 290.8 219 183 10
219 147 30
181 145 10
Heptachlor C10H5Cl7 14.8 373.3 274 237 20
272 237 20
237 119 40
Heptachlor_epoxide_a C10H5Cl7O 17.0 389.3 355 265 15
353 263 15
237 143 25
Heptachlor_epoxide_b C10H5Cl7O 17.1 389.3 253 183 30
217 181 30
183 119 30
Hexachlorbenzene C6Cl6 12.3 284.8 284 249 25
284 214 40
- - -
Indoxacarb C22H17ClF3N3O7 31.1 527.8 218 203 20
203 134 20
203 106 30
Kresoxim_methyl C18H19NO4 19.1 313.3 131 130 15
131 89.0 35
116 89.0 15
Mecarbam C10H20NO5PS2 17.1 329.4 159 131 20
131 86.0 15
131 74.0 10
Metolachlor C15H22ClNO2 15.7 283.8 238 162 10
162 133 15
162 117 40
MGK_264 C17H25NO2 16.4 275.4 164 98.0 10
164 93.0 10
164 80.0 30
Nonachlor cis C10H5Cl9 20.2 444.2 409 300 15
407 300 30
407 298 30
Nonachlor_trans C10H5Cl9 18.3 444.2 409 300 25
407 300 15
- - -
Oxychlordane C10H4Cl8O 17.0 423.7 187 123 20
187 87.0 35
187 84.9 35
Parathion C10H14NO5PS 15.9 291.3 291 109 20
291 80.9 30
186 140 5
Pentachloroaniline C6H2Cl5N 14.1 265.3 265 194 10
265 192 5
- - -
Permethrin_cis C21H20Cl2O3 26.8 391.3 183 168 20
183 155 10
183 154 20
Prochloraz C15H16Cl3N3O2 26.9 376.7 308 70.0 15
180 138 10
180 69.0 20
Procymidone C13H11Cl2NO2 17.3 284.1 285 96.0 5
283 96.0 5
283 68.0 20
Propargite C19H26O4S 22.1 350.5 135 107 20
135 94.9 20
135 77.1 30
Propyzamide C12H11Cl2NO 13.1 256.1 175 147 15
173 145 20
173 109 35
Tefluthrin C17H14ClF7O2 13.4 418.7 197 141 10
177 137 20
177 127 20
Tetraconazole C13H11Cl2F4N3O 16.0 372.1 336 218 20
336 204 40
336 164 30
Tolclofos_methyl C9H11Cl2O3PS 14.6 301.1 265 250 15
265 220 25
265 93.0 30
Trichloronate C10H12Cl3O2PS 16.2 333.6 299 271 20
297 269 20
297 223 20
Trifluralin C13H16F3N3O4 11.6 335.3 306 264 10
306 160 20
264 160 10
Vinclozolin C12H9Cl2NO3 14.5 286.1 285 212 10
187 124 20
a)The bold text expressed as quantification ion.

Method validation

The method was validated according to the Codex guideline (CAC/GL 71, 2009). The blank samples (flatfish, eel, shrimp, and Manila clam) were tested to ensure that they did not contain any interferences and/or target compounds. The measured parameters were the linearity, limits of detection (LOD), limits of quantification (LOQ), accuracy, and precision. The validation study was carried out using tissue samples previously checked to be free of residual pesticides. The LOD was calculated at a signal-to-noise ratio (S/N) of 3, whereas the LOQ value was calculated using an S/N ratio of 10. The linearity was tested using matrix-matched calibrations (blank, 10, 20, 50, 100, 150 μg/kg) that were prepared by adding the appropriate amount (200 μL) of standard mixtures in the solvent into the fish and shrimp samples. The accuracy and precision (expressed as recovery and relative standard deviation, respectively) were determined by analyzing all samples spiked at 10, 20, and 100 μg/kg. The accuracy and precision were validated based on three target concentrations (10, 20, and 100 μg/kg). The accuracy and precision were determined at the three levels in the blank samples in five replicate analyses.


Results and Discussion
Optimization of GC-MS/MS conditions

GC-MS/MS is a valuable approach for the determination of highly hydrophobic and volatile organochlorine pesticides (Hernández et al., 2013; Chatterjee et al., 2016; FSIS, 2018). In the current study, GC-amenable pesticides (organophosphorus, pyrethroids, carbamates insecticides, herbicides, and fungicides) were selected based on their potential use and contamination in fishery products and the aquaculture industry. GC-MS/MS based analytical methods have been preferred for the determination of pesticide residues in fish due to their high sensitivity and selectivity with low interferences (Munaretto et al., 2013; Sapozhnikova & Lehotay, 2013; Manuelmolina-Ruiz et al., 2014; Sahu & Nelapati, 2018; Colazzo et al., 2019).

The precursor ions, product ions, and collision energies were optimized for the best intensity of target compounds (Table 1). Based on a full scan spectrum, precursor ions were selected; then, the collision energy was adjusted to generate the product ions. MRM transitions with the highest intensities with related collision energies as well as retention times for all the pesticides were selected for quantification. The most abundant precursor ion with the highest m/z value was designated as the quantification ion, whereas the least intense product ion was designated as the qualifier ion. Due to the co-eluting sample interfering with the analytes, two precursor or additional product ions were used as qualifiers to prevent possible false-positives.

Optimization of extraction and purification

The QuEChERS (quick, easy, cheap, effective, rugged, and safe) approach was applied to this method because of its versatility (de Oliveira et al., 2019). The analytical method was developed and validated using GC-MS/MS based on QuEChERS. The optimization of purification was carried out using a salting-out solvent extraction step and a d-SPE clean-up step to remove matrix components (e.g., fatty acid). For the extraction step, salts that are easily electrolyzed in an aqueous solution were used as reagents to achieve separation of the ethyl acetate of nonpolar pesticides in an organic solvent (Sapozhnikova, 2014; Cao et al., 2015; FSIS, 2018). For the purification step, MgSO4, PSA, and C18 were used. MgSO4 was used for moisture removal (Perović et al., 2018). PSA provided polar adsorption and weak anion exchange, which removed polar compounds such as organic acids, fatty acids, carbohydrates, and sugars, whereas the C18 hydrocarbon chains eliminated fatty acids and nonpolar interfering substances (Sapozhnikova & Lehotay, 2013; Shin et al., 2018; Kim et al., 2020). Based on previous studies, the combination of MgSO4 (500mg), C18 (200 mg), and PSA (200 mg) was adopted for multi-pesticide detection in fishery products.

Method validation

Specificity was evaluated through the analysis of the four different fishery product samples against a reagent blank. No interference was observed at the same retention time as the analyte. The validation process was performed by determining the linearity, LOD, LOQ, accuracy, and precision based on the CODEX guidelines (CODEX,2014). The chromatograms of the target compounds are shown in Figure 1. The linearity (expressed as correlation coefficients, r2) of the matrix calibration curves was >0.98 for all target compounds. Our results showed good linearity and allowed for the coverage of all target compounds. The LOD a nd LOQ w ere ≤3 a nd ≤ 1 0μg/kg, respectively. T he accuracy (expressed as recovery, %) and precision (expressed as RSD, %) of the target compounds were evaluated in spiked blank samples at three concentrations (10, 20, and 100 μg/kg). The overall recoveries for all the target compounds ranged from 62.4% to 120%. The precision was observed at 20.7% (Table 2). Three compounds (i.e., chlorothalonil, iprodione, and terbufos) were excluded before the start of method validation because of their inconsistent recoveries and/or unsatisfactory linearity of the calibrations. Some pesticides cannot be appropriately assessed using the buffered QuEChERS method (Lehotay et al., 2005; Cho et al., 2016).

Table 2. 
Accuracy and precision at three testing levels in fishery products, shrimp and manila clam
Compounds Target testing level(μg/kg) Flatfish (n=5) Eel (n=5) Shrimp (n=5) manila clam (n=5)
Recovery (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%) Recovery (%) RSD (%)
Aldrin 10 108 4.8 86.7 8.1 99.1 8.4 88.4 14.8
20 102 6.2 95 5.2 104 13.8 96.7 8.6
100 100 2.5 95.1 5 102 10.2 92.5 18.1
Allethrin 10 108 6.3 92.1 17.2 106 16.6 110 16.9
20 103 10.2 91.4 14.5 100 19.2 110 9.8
100 88.1 11 90.9 12.3 96.8 15.7 98.4 6
Carbophenothion 10 109 4.2 86.5 7.8 94.5 11.1 73.5 11.6
20 104 6.1 94.5 6.2 105 7.5 86.2 5.5
100 102 1.6 95.4 4.1 106 8.7 86.9 13.4
Chlordane-cis 10 108 1.4 85.6 5.2 100 9.5 97.3 6.7
20 102 4.3 94.4 4.2 104 4.7 97.3 6.8
100 98.2 2.5 96.9 3.7 104 6 98.9 12.3
Chlordane-trans 10 110 2.7 89.6 5.1 98.8 7.9 72.7 12.2
20 102 4.4 95 4.1 102 5.7 92.1 6.9
100 100 2.1 95.5 4 105 6.8 104 9.3
Chlorpropham 10 117 11.6 88.9 8.7 99 11.6 80.7 15.2
20 105 13.3 88.5 8.7 95.4 14 90.4 11
100 107 4.3 86 6.7 92.5 12.4 96.8 16.4
Chlorpyrifos 10 118 6.6 92.3 5.5 94.9 11 93.1 13
20 108 6.6 97 5.9 104 6.2 102 8.1
100 103 2 94.8 4.1 103 9.8 103 15.2
Chlorpyrifos methyl 10 115 9 88.3 7.3 99 12 94.2 13.9
20 106 11.1 93.1 8.4 98.8 8.4 96.5 9.2
100 103 4.1 91.9 4.8 102 19.4 92.8 13
Deltamethrin 10 112 7.5 90.7 9.6 92.2 20.1 103 19.3
20 103 6.9 93.9 7.4 107 12.1 108 14.3
100 101 4.4 93.2 3.9 119 13.8 109 6.6
Dicofol 10 120 4.3 94.9 8.3 91 9 102 8.3
20 116 4.7 94.2 7.3 97.3 5.9 108 5.7
100 113 2.7 97.7 3.2 94.3 7.3 118 14.3
Dieldrin 10 104 4.4 88.6 7.4 103 7.1 79.8 19.1
20 100 6.2 93.7 4.3 104 4.4 89.9 8.9
100 98.9 2.7 95.7 4.6 104 6.4 100 9.8
Endosulfan α 10 109 2.8 91 5.9 108 16.5 95.7 6.9
20 104 5.3 98.2 4.3 107 4.6 98.3 3.5
100 103 2.7 96.1 3 112 16.4 97.1 13.9
Endosulfan β 10 106 2.1 87.3 5.6 100 6 96.5 6.9
20 101 4.1 96.4 3.7 103 4.4 97.6 3.9
100 98.8 2.4 98.5 4.3 104 5.7 98.8 11.1
Endosulfan sulfate 10 107 4.2 83.9 7.8 101 6.2 89.1 7.3
20 100 5.2 94.9 3.9 103 3.8 93.6 2
100 102 2 98.5 3.9 103 4.8 92.4 6.6
Endrin 10 105 2.7 84.3 5.6 100 6.4 75.2 9.3
20 100 4.5 95.8 3.4 104 3.7 94.7 7.9
100 97.7 2 98.6 4.8 105 4.5 107 13
Endrin keton 10 106 1.8 90.4 4.9 100 6.3 79.5 2.3
20 102 3.3 95.3 3.7 104 3.9 76.1 5.8
100 102 1.8 96.2 4.4 105 5.4 78.3 14
EPN 10 102 2.6 89 4.6 98.3 9.8 107 3.1
20 97.6 5.4 89.1 4.2 104 6.6 98.1 2.6
100 103 1.1 91.5 4.3 109 8.1 94.3 4.7
Etofenprox 10 114 5.3 84.2 8.1 92.7 9.6 119 6.1
20 107 5.8 95.9 7.1 101 5.5 117 5
100 101 3.4 97.3 4.6 105 8.1 109 8.2
Fenpropathrin 10 108 3.8 89 6.4 96.1 10.4 86.3 5.8
20 101 4.9 96 5.3 105 7 95.4 5.5
100 99.2 1.7 94.8 4.5 107 8.6 102 6.3
Fipronil 10 110 2 93.7 7.3 95.8 17.4 105 4.1
20 101 4.6 96.3 6.6 100 11 100 3.5
100 101 3.7 95.6 4 101 16.8 91.6 5.3
Fipronil sulfone 10 106 2.8 86.9 5.7 117 12.8 100 4
20 100 3.9 94.5 4.3 80.7 14.6 95.2 4.4
100 98 3.4 96.2 3.6 83.3 12.5 89.3 5.5
Flusilazole 10 106 2.8 87.7 6.2 108 13 99.1 5.3
20 101 5 97.7 4.3 91.6 15.7 100 4
100 97 1.6 96.6 3.4 94.3 14.7 95.5 5.8
alpha-HCH 10 112 9.6 81.2 7 103 14.1 78.6 17.4
20 105 11.8 91.1 6.2 116 12.6 94.7 11.5
100 106 5.2 88.6 8.5 93.5 19.9 86 19.3
bata-HCH 10 110 3.4 79.8 8.2 104 6.5 84.8 13.2
20 97.5 7.4 91.1 4.6 107 7.9 99.1 7.4
100 86.5 3.9 95.4 3.9 112 12.9 109 14.6
delta-HCH 10 109 4 86.5 6.2 103 6.6 81.4 8.6
20 104 4.3 93.6 5.3 100 6.7 93.9 5.6
100 101 1.8 96.7 4.5 106 14.9 106 12.8
gamma-HCH 10 113 6.8 86.8 5.7 106 9.2 83.4 17.1
20 105 7.6 92.5 5.5 107 16.1 83.5 11.3
100 105 3.3 91.3 5.1 98 12.2 81.6 12.7
Heptachlor 10 112 5.3 82.9 7 104 8.6 76.5 17.8
20 104 8.2 92 6.1 105 15.6 79.7 10.1
100 104 2.3 93.2 5.3 99 12.4 71.7 13.5
Heptachlor epoxide a 10 109 2.7 90.5 6.8 101 7.3 97.4 7.1
20 101 5.3 95.2 4.2 103 6.5 96.4 6.9
100 100 1.7 95.3 3.9 105 5.4 96 13.4
Heptachlor epoxide b 10 112 5.4 93.8 16.8 86.6 8 89.8 17.4
20 98.6 7.6 96.8 9.1 100 6.3 102 15.8
100 100 4.1 92.4 2.7 106 5.9 100 15.2
Hexachlorbenzene 10 111 7.4 118 7.8 100 17 75.1 11.5
20 95.4 7.3 104 7.5 103 16.1 90.6 15.1
100 96.2 1.8 107 1.8 105 17.8 74.5 14.9
Indoxacarb 10 105 5.6 83.5 9.9 96.7 8.9 100 8.6
20 100 3.5 95.8 5.5 99.3 4.8 98.6 4.5
100 96.4 3.1 98.4 2.9 98.2 9.6 96.5 6.4
Kresoxim methyl 10 110 2 78.5 5.6 95.9 9.4 96.7 4.7
20 103 4.4 94.6 4.6 105 4.7 103 3
100 97.3 2.1 100 4.2 105 7.8 107 8.2
Mecarbam 10 113 4 86.6 6.4 99.2 15 98.9 7.8
20 106 5.5 93.7 6.5 104 9.6 101 3.2
100 103 2.8 92.9 4.1 102 13.4 108 10.8
Metolachlor 10 108 2.7 87.1 5.7 95.9 10.7 80.4 9.5
20 102 4.9 96.6 4.5 102 5.8 94.8 4.5
100 96.8 1.3 95.9 4.5 101 9.7 102 12.1
MGK-264 10 117 3.8 83.7 6.8 96.9 9.8 100 8.2
20 104 4.6 96.4 5.1 103 6.2 103 4.3
100 101 1.4 97 3.8 103 9.3 104 12.6
Nonachlor cis 10 110 3.6 89.3 6.1 101 7.7 88.7 6.1
20 105 4.5 96.2 4 105 5.6 92.3 4.1
100 102 1.8 98 4 105 5.4 98.5 6.6
Nonachlor trans 10 117 2.4 81.6 7.7 97.5 8.1 81.2 10.7
20 117 3.4 95.6 3.7 103 5.5 92.6 7
100 115 2.8 102 4.6 106 6.2 104 11.6
Oxychlordane 10 110 3.2 85.9 4.4 101 6.7 98.9 7.1
20 102 4.6 95.8 3 104 6.8 96.5 5.6
100 100 1.9 96.2 3.8 103 6.6 97.1 14.1
Parathion 10 108 3.7 90.5 5.8 98.1 12.6 77.8 9.2
20 100 6.6 91.1 5.1 101 8 88.7 6.5
100 104 3 89.6 4.7 105 13.3 99.3 13.9
Pentachloroaniline 10 111 6.7 86 9.9 97.8 9.8 87.9 14.1
20 103 8.5 94.8 8 100 7.7 98.3 10
100 103 3.1 95.3 5 104 14.7 104 18.7
Permethrin cis 10 103 3.1 87.7 5.7 92 9.1 115 8.4
20 105 6.2 94.2 6.8 102 7.2 111 8.5
100 104 2.1 95.7 4.2 106 8.7 110 10.3
Prochloraz 10 112 7.8 94.1 7.5 92.7 16.5 109 4.6
20 107 6.8 93.5 8 103 7.3 100 5.6
100 106 2.2 94.1 5.6 106 12.2 79.9 15.4
Procymidone 10 109 3.9 88.3 5.8 98.9 9.9 88.2 8.3
20 103 5.6 96.2 5 103 5.8 98.1 5.3
100 101 1.8 95.4 3.8 102 8.8 103 9.8
Propargite 10 110 1.8 81.5 6.8 94.8 8.3 85.3 6.4
20 106 4.1 98 4.6 106 4.5 100 2.5
100 95.2 1.9 98.3 3.6 104 4.9 107 6.6
Propyzamide 10 115 7.4 87.4 7.9 96.4 11.4 76.4 11.2
20 107 9 93.3 8.5 97.4 8.1 93.4 5.2
100 103 3.8 93.1 4.6 97.2 10.1 109 14.1
Tefluthrin 10 115 8.1 83 7.9 96.5 10.8 86.9 18.1
20 104 12.7 92 8.1 101 9.5 98.5 9.8
100 103 4.1 91.1 6 101 13.6 92.4 14.6
Tetraconazole 10 107 3 87.8 6.5 95 12.6 97.4 4.3
20 101 3.6 94.3 4.8 101 6 98.3 4.7
100 97 2.1 96.6 3.2 102 11.4 92.2 6.9
Tolclofos methyl 10 115 7.1 87.7 7.4 98.1 11.2 86.4 14.6
20 105 9.5 94.2 7.8 101 7.6 93.1 7.5
100 103 2.7 92.4 4.8 105 16.1 93.1 12.1
Trichloronate 10 111 2.8 84.6 7.2 95 10.4 94.9 9.8
20 103 5.5 95.8 5.2 104 6.4 95.8 7.4
100 99.1 2.1 96.2 4.7 103 10.1 98.3 13.3
Trifluralin 10 104 11.3 87.3 6.9 100 6.5 79.1 18.6
20 95.8 15.8 84.7 7.9 108 7.6 81 13.1
100 104 6.2 79.9 8.6 82.6 16.7 73.6 12.9
Vinclozolin 10 111 6.3 88.3 7.3 96.9 9.9 62.4 16.6
20 105 7.6 95 7 99.4 5.9 89.8 7
100 103 2.6 94.9 4.5 100 9.2 116 17.9


Fig. 1. 
GC-MS/MS Chromatogram of a spiked sample with 51 pesticides at 10 μg/kg.

Application and real sample monitoring

The applicability of the method was evaluated through the analysis of the target pesticides in 79 fishery product samples purchased from the local markets in Korea. Trifluralin was detected in one sample (1%) at a concentration of 67μg/kg in the Manila clam, while its residue in flatfish was below LOQ. Trifluralin is frequently detected in aquatic animal samples. The residue of trifluralin was reported to be above 1μg /kg in shrimp produced in Asian countries (Chan et al., 2012). Trifluralin residues (35−204 μg/kg) were detected in 11 pangasius fillet imported from Vietnam in 2011 (Chan et al., 2013). Previous studies have revealed that the trifluralin residues in Manila clam and flatfish (<LOQ) indicated the presence of pesticide runoff into the aquaculture environment (Shin et al., 2011). Trifluralin has been reported to mostly appear in runoff water in agricultural fields (Antoniouds, 2012). Furthermore, trifluralin residues in shrimp are associated with its use in the control of fungi and parasites in aquaculture farms and the surrounding environment. Further studies are needed to more clearly interpret the pesticide residues found in aquatic animal species.

The aquaculture industry has been overwhelmed by a wide range of parasitic and bacterial diseases affecting cultured species (Bondad-Reantaso et al., 2005). In order to prevent or treat these diseases, several chemicals have been used in high-density aquatic farms (Kang et al., 2018). Moreover, non-compliant samples in farmed aquatic animals are increasing due to the unintended and overuse of chemical compounds (Park et al., 2020). Further investigations are required to assess the dietary exposure to ethoxyquin residues and their health risks associated with the dietary intake of the farmed aquatic animals (Choi et al., 2020).


Conclusions

In this study, a multi-residue pesticide analysis method was developed and optimized for 51 pesticides in fishery products based on the QuEChERS approach combined with GC-MS/MS. The developed method was both selective and sensitive. The method was successfully tested on 79 fishery product samples purchased from the local markets in Korea, proving to be suitable for routine multiresidue analyses of target pesticides for monitoring purposes. Trifluralin was detected in one sample (1%). The proposed method was successfully validated and applied for the identification and confirmation of pesticides in fishery products. These findings indicate that these compounds do not need to be as persistent as pesticides to accumulate in fishery products. Additionally, more extensive monitoring studies are needed to understand the potential of these compounds to bioaccumulate and assess their runoff from river water into aquaculture farms.


Acknowledgments

This study was supported by a grant from Chungnam National University and Ministry of Food and Drug Safety of Korea [grant numbers 17161MFDS651, 19161MFDS 581] in 2017 and 2019.

Conflict of Interest

The authors declare that they have no conflict of interest.


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Author Information and Contributions

Dasom Shin, Department of Bio-Environmental Chemistry, College of Agriculture and Life Sciences, Chungnam National University, Master student, https://orcid.org/0000-0001-5623-9342

Joohye Kim, Pesticide and Veterinary Drug Residues Division, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Researcher, https://orcid.org/0000-0002-4081-2404

Hui-Seung Kang, Pesticide and Veterinary Drug Residues Division, National Institute of Food and Drug Safety Evaluation, Ministry of Food and Drug Safety, Doctor of Philosophy, https://orcid.org/0000-0003-2207-5559

Chi-Hwan Lim, Department of Bio-Environmental Chemistry, College of Agriculture and Life Sciences, Chungnam National University, Professor, http://orcid.org/0000-0001-9713-781X

Experimental work: D. S. and J.K., drafting and writing of the manuscript: D.S., revising of manuscript: H.-S. K., reviewing of the manuscript: H.-S. K. and C.-H. L.