Multi-Residue Determination of Pesticides in Farmed Aquatic Animal Products Using Gas Chromatography-Tandem Mass Spectrometry
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, ResidueIntroduction
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.
MRM transition and optimized parameters of GC-MS/MS for 51 target compounds
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).
Accuracy and precision at three testing levels in fishery products, shrimp and manila clam
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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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.