MS

Journal Pre-proofs Upgrading analytical methodology through comparative study for screening of 267 pesticides/metabolites in five representative matrices using UPLCMS/MS Tae-Woong Na, Md. Musfiqur Rahman, Sung-Woo Kim, Md. Ershadul Haque, Jong-Bang Eun, Jae-Han Shim PII: DOI: Reference:

S1570-0232(19)31563-6 https://doi.org/10.1016/j.jchromb.2020.122021 CHROMB 122021

To appear in:

Journal of Chromatography B

Received Date: Revised Date: Accepted Date:

22 October 2019 2 February 2020 3 February 2020

Please cite this article as: T-W. Na, Md. Musfiqur Rahman, S-W. Kim, Md. Ershadul Haque, J-B. Eun, J-H. Shim, Upgrading analytical methodology through comparative study for screening of 267 pesticides/metabolites in five representative matrices using UPLC-MS/MS, Journal of Chromatography B (2020), doi: https://doi.org/ 10.1016/j.jchromb.2020.122021

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Research Article Upgrading analytical methodology through comparative study for screening of 267 pesticides/metabolites in five representative matrices using UPLC-MS/MS Tae-Woong Naa †, Md. Musfiqur Rahmanb † *, Sung-Woo Kimc, Md. Ershadul Haqued, JongBang Eune, and Jae-Han Shimb* aNational

Agricultural Products Quality Management Service (NAQS), 141, Yongjeon-ro,

Gimcheon-si, Gyeongsangbuk-do, Republic of Korea bNatural

Products Chemistry Laboratory, Chonnam National University, Yongbong-ro 77,

Buk-gu, Gwangju 500-757, Republic of Korea. cJeollanamdo

Agricultural Research and Extension Services, Environment-Friendly

Agricultural Research Institute, 1508, Senam-ro, Sanpo-myeon, Naju-si, Jeollanamdo, 58213, Republic of Korea. dDepartment

of Statistics, University of Dhaka, Dhaka-1000, Bangladesh

eDepartment

of Food Science and Technology and BK 21 plus Program, Graduate School of

Chonnam National University. Yongbong-ro 77, Buk-gu, Gwangju 500-757, Republic of Korea.

*Corresponding authors: Tel.: +82-62-530-2135; fax: +82-62-530-0219. E-mail address: [email protected] (J-H. Shim) and Tel.: +82-10-5687-3687; fax: +82-62-530-0219. E-mail address: [email protected]; [email protected] (Md. Musfiqur Rahman)

† The first two authors contributed equally to this study.

RESEARCH HIGHLIGHTS - A total of 267 pesticides/metabolites/plant activators/growth regulators were analyzed to compare the traditional MFDS#83 method with the QuEChERS EN method using UPLCMS/MS - Five representative matrices (mandarin, pepper, potato, rice, and soybean) were selected with regard to pH, pigments, starch, and fat along with high consumption rate. - QuEChERS EN method provided better results than the MFDS#83 method for all matrices except mandarin - QuEChERS EN method can be an upgraded replacement for the MFDS#83 method for pepper, potato, rice, soybean, or similar types of matrices for quick screening - A further modification of the QuEChERS EN version is required for acidic/low pH matrices like mandarin.

GRAPHICAL ABSTRACT

ABSTRACT A comparative study was conducted to replace the traditional screening method (MFDS#83) with the Quick, Easy, Cheap, Effective, Rugged and Safe (QuEChERS) EN method for the determination of 267 pesticides/metabolites/plant activators/growth regulators in five representative crop matrices (mandarin, pepper, potato, rice, and soybean). In the traditional method, samples were extracted with acetonitrile and salt, and purified with a solid-phase extraction cartridge. In the QuEChERS method, the sample extraction was carried out using acetonitrile and a mixture of salts, and purification was performed using dispersive solid phase extraction. The limit of quantification (LOQ) for the MFDS#83 method was 0.0004 mg/kg, whereas for the QuEChERS EN method, the LOQ varied from 0.002–0.006 mg/kg for all analytes in various matrices. A six-point matrix-matched calibration curve was prepared for all analytes in five matrices for both methods. Both the MFDS#83 and QuEChERS EN methods provided excellent linearity, with the coefficients of determination (R2) ≥ 0.99 for most of the compounds. In both cases, the method was validated in terms of recovery and repeatability after the fortification of two different concentrations with three replicates for each of the concentrations. The QuEChERS EN method provided better recovery than the MFDS#83 method for all matrices except mandarin.

Keywords: pesticides; multi-residue; QuEChERS; traditional method; UPLC-MS/MS.

1. Introduction The continued use of pesticides has the benefit of increasing production in agro-food industries; however, it also negatively affects the environment, crops, and livestock [1, 2]. Primarily, the pesticide is exposed by application to crops and resulting residues that are not absorbed by the crops but are washed in air or rainwater and flow into the soil or river [3]. Therefore, this residue can be delivered to the crops via soil or water, finally resulting in bioaccumulation in the livestock through contaminated feed [4]. In addition, these pesticides can be decomposed by light, moisture, or temperature according to their properties, and some degraded metabolites can be formed as toxic sulfoxide or sulfone. The toxic metabolites are absorbed and taken up by the food chain and environmental circulation [5-7]. These processes suggest that the management of pesticide is now an important issue for both the local and international community [8]. To monitor pesticides routinely, it is urgent to establish effective sample preparation and detection methods, which include single-residue methods (SRM) for analyzing individual compounds and multi-residue methods for simultaneous analysis of various compounds [9]. Although SRM have the advantage of being more reliable in terms of precision and reproducibility, the main drawback of these methods is their limited application to specific pesticide and specific crops, [9, 10]. In contrast, simultaneous multi-residue methods have the advantage of analyzing various compounds at the same time, although the precision and reproducibility of specific compounds are slightly reduced. These methods are applicable to various crop matrices over a wide range of pesticides [11-16]. Therefore, to monitor

pesticide residue during the production and distribution stages, and develop an approach that has versatility under different international conditions, the multi-residue method is more suitable than the SRM, and the development and verification of these methods are essential [6, 17, 18]. In recent years, more rapid, simple, and precise methods of analysis have become prominent. The most popular analytical method in this regard is a method called the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) method. The QuEChERS method was first introduced by Anastassiades in 2003 to effectively remove matrix co-extracts and successfully transfer polar pesticides to the solvent layer in the shortest possible time using magnesium sulfate (MgSO4). The purification was carried out by dispersive solid-phase extraction (d-SPE) instead of time-consuming solid-phase extraction [19]. The possible outcome of the method was the analysis of a wide range of pesticides to various plant matrices [19-21]. The main advantages of QuEChERS was its possibility of modification to suit the characteristics of the analyte, matrices, and amount of sample or solvent. Because of these advantages, two major modifications of QuEChERS were observed for pH-dependent analytes: one is an acetate-buffered version introduced by Lehotay in 2005, which is the official AOAC method, and the other is a citrate-buffered version introduced in 2007 as a final modified version, which became the official EU method called QuEChERS EN [20, 22]. Furthermore, the method is still being modified for analysis of a wide range of pesticides in various matrices [23-27]. In the Republic of Korea, multi-class pesticides were analyzed using the multi-residue methods named MFDS#83 (Ministry of Food and Drug Safety#83) from the Korean Food Code. The method involved acetonitrile and salts (sodium chloride,) for extraction, and purification was carried out using an aminopropyl cartridge. Finally, analysis was conducted via liquid chromatography (LC) and gas chromatography (GC), coupled with a traditional detector. However, the method required mass spectrometric confirmation for avoiding false

positive/negative results. This was the only validation method before the QuEChERS method was introduced [12]. The method has been used since its initial introduction in 2000 as a representative liquid extraction method without any modification. The method was modeled by the California Department Food and Agriculture (CDFA) and published by the United States Food and Drug Administration (FDA). The CDFA method was based on the Mills (1963) method, introduced as the first multi-class pesticide multi-residue method, which was considered a precise method established through long-term experiments and results [28-31]. The method has been verified through modification and supplementation over a period of time; thus, it can be applied to various crops and is known to be suitable for quantification. However, the method lacks research on the simultaneous analysis of more than 200 pesticides. In addition, it is well-known that the cleanup process is omitted or simplified, and is affected by the matrix. Therefore, many studies on the applicability to various crops should be conducted and verified. In this study, we compared the latest official version of the QuEChERS EN method and traditional multi-residue method (MFDS#83), which has been proven to be an effective method. Thus, the purpose of this study was to investigate whether the QuEChERS EN method can be a replacement of the existing traditional method and determine the ability of both methods to simultaneously analyze more than 200 pesticides.

2. Experimental 2.1. Chemicals and standards A total of 267 pesticide/metabolite/plant activator/growth regulator standards were included in this study, from which 256 were parent compounds, while the others were isomers and metabolites. The pesticides were classified as insecticide (88), fungicide (76), herbicide (72), acaricide (11), nematicide (2), plant activator (2), and plant growth regulator (5). The pesticide standards were purchased from AccuStandard, Inc. (New Haven, CT, USA), Wako

Pure Chemical Industries, Ltd. (Osaka, Japan), Dr. Ehrenstorfer GmbH (Augsburg, Germany), Chem Service, Inc. (West Chester, USA), and LG Life Sciences, Ltd. (Seoul, Korea). Analytical grade reagents and solvents were used for extraction, purification, and detection. Acetonitrile, methanol, and dichloromethane were purchased from Burdick & Jackson (Muskegon, USA). Aminopropyl (NH2) SPE cartridge (1 g, 6 mL) was obtained from Waters (Massachusetts, USA). An A-QTM EN QuEChERS kits (4.0 g MgSO4, 1.0 g NaCl, 1.0 g Trisodium Citrate Dihydrate, 0.5 g Disodium hydrogen citrates sesquihydrate, Lot No., 150513-E10) was supplied by KRIAT (Daejeon, Republic of Korea). A syringe filter MN, 0.2 µm– 15 mm was purchased from CHROMAFIL (Duren, Germany). Sodium chloride and formic acid (< 98%) were purchased from Junsei Chemical Co. Ltd. (Tokyo, Japan). Ammonium formate (> 99%) was supplied by Kanto Chemical Co. (Tokyo, Japan).

2. 2. Preparation of standard stock solution and calibration Standard stock solution for each of the analytes was individually prepared at the level of 1000 mg/L. For the mixed standard solution, 200 μL of each standard solution was aliquoted into a 20-mL volumetric flask and evaporated under nitrogen stream to prepare 20 mL of a mixed standard solution at a level of 10 mg/L. All the prepared standard solutions were sealed in amber vials and stored at −20 °C for freezing. To prepare the calibration curve, the mixed standard solution was diluted with acetonitrile at concentrations of 0.002, 0.005, 0.01, 0.02, 0.05, and 0.1 mg/kg. The calibration curve was constructed based on the peak area of the chromatogram. Matrix-matched standards of the QuEChERS method and the MFDS#83 method were prepared by using a blank extract and diluted in a ratio of 4 : 1 (blank extract : standard mixture).

2.3. UPLC-MS/MS

A Waters AQUITY H-Class ultra-performance liquid chromatography (UPLC) (Waters, Hertfordshire, UK) system was coupled with a triple quadrupole mass spectrometer (AB SCIEX QTRAP 4500, SCIEX, Redwood, CA, USA) for instrumental analysis. The separation was achieved using a CAPCELL CORE-C18 column (100 × 2.1 mm, 2.7 μm). The mobile phase consisted of (A) water and (B) methanol, containing 0.1% (v/v) formic acid and 5-mM ammonium formate flowing in gradient mode. The mobile phase gradient was started at 95% A for 1 min with the flow rate of 0.3 mL/min, decreased to 45% A at 1.5 min and to 40% A at 5 min. The phase gradient continued to drop to 10% A with the flow rate increasing to 0.4 mL/min and dropped to 2% A at 12.1 min, remaining the same until at 15 min. At that time, initial condition was reinstated at 15.1 min, remaining constant until at 20 min. The injection volume was 2 μL with a flow rate of 0.3 mL/min, and the total run time was 20 min for each injection. The column temperature was set at 35 °C. The conditions of mass spectrometry (MS) for some pesticides are published; however, because the product and precursor ions are varied owing to the instrument brand and analysis conditions, the MS conditions were optimized and established for 267 target analytes. The instrument was operated using electrospray ionization in the positive and negative modes. The curtain gas was 25 psi, ion spray voltages were 5500 V for positive and −4500 V for negative mode, and the temperature was 500 °C. The Q1 mass scan of each component was performed to confirm the precursor ion and intensity. Then, a scan for the product ion was performed and the changes in the DP (declustering potential), EP (entrance potential), CE (collision energy), and CXP (collision cell exit potential) were noted. The most suitable MS/MS product ion spectra were selected through the chromatogram. The intensity, selectivity, and sensitivity of the ion were measured for the obtained spectrum, and the quantifier and qualifier were determined. The optimized MRM conditions are shown in Table 1.

2.4. Selection of experimental samples Five types of crops, which can represent the characteristics of each taxon, were selected in this study. Rice represents high starch; soybean represents oil seeds,; potato represents roots/tubers, which contain much water; pepper represents fruiting vegetables, which also contain large amounts of water; and mandarin represents fruits, with high acid and water content. All samples were purchased from an organic agricultural farm and stored after being crushed separately with dry ice at −40 °C (soybean and rice were crushed without dry ice).

2.5. Sample preparation 2.5.1. MFDS#83 method protocol A 50-g representative chopped sample was homogenized with 100 mL of acetonitrile for 5 min and filtered with Whatman 6 filter paper. The filtrate was transferred to a 500-mL separatory funnel, and 15 g of NaCl was added. The sample mixture was then shaken for 5 min with a mechanical shaker and kept 1 h for separation. From the upper layer, 20 mL was transferred to a 100-mL separatory funnel and partitioned with 20 mL of n-hexane saturated with acetonitrile. The lower acetonitrile layer was collected, and the upper n-hexane layer was re-extracted with 20 mL of acetonitrile saturated with n-hexane. Both the acetonitrile layers were combined and evaporated for purification. The extract was re-dissolved in a 4-mL mixture of MeOH:DCM (1:99 v/v) and loaded to a 500mg amino cartridge, which was previously conditioned with 6 mL of DCM. The cartridge was then eluted with 6 mL of MeOH:DCM (1:99 v/v) mixture and evaporated. The purified extract was then reconstituted with 2 mL of acetonitrile and filtered with a membrane filter.

2.5.2. QuEChERS EN method protocol

From the homogenized sample, 10 g (5 g for rice and soybean) was added to a 50-mL Teflon centrifuge tube to which 10 mL of acetonitrile (15 mL for soybean) was added and shaken for 1 min. Then, 4.0 g of MgSO4, 1.0 g of NaCl, 1.0 g of trisodium citrate dihydrate, and 0.5 g of disodium hydrogen citrate sesquihydrate was added and shaken again for 1 min. The tube was thereafter centrifuged for 5 min at 4000 rpm. Afterwards, 1.0 mL of the supernatant was transferred to a 2 mL micro-centrifuge tube to which 150 mg of MgSO4, and 25 mg of PSA (primary secondary amine) were added as purification sorbent and vortexed for 20 s. The micro-centrifuge tube was then centrifuged for 5 min at 4000 rpm. The purified supernatant was filtered through a 0.2-µm syringe filter and transferred to a 2-mL vial for UPLC-MS/MS analysis.

2.6. Method validation Method was validated through the standard parameters of the SANTE guidelines, such as limit of quantification, linearity, selectivity, specificity, accuracy, and precision [32]. Limit of quantification (LOQ) represents the lowest concentration or mass of the analyte that provided signal 10 times higher than the noise level. Linearity was assessed from the coefficient of determination (R2) after constructing a six-point calibration curve using concentration vs area. Selectivity is the identical retention time of the standard peak, and the peak recovered after fortification of the same standard to the blank sample. Specificity is the absence of interference or interference ≤ 30% of the LOQ at the standard retention time in the blank samples. Accuracy is the average recovery of the fortified standard from the blank samples with three replicates. Precision was measured from the relative standard deviation derived from the three-replicate analysis.

2.7. Statistical Analysis

The recovery and RSD value of 267 pesticides extracted from two different methods (MFDS#83 and QuEChERS EN) in five matrices (mandarin, pepper, potato, rice, and soybean) at two different concentration level (10 × LOQ, 50 × LOQ) were analyzed and compared. The acceptable range of the recovery values and the %RSD values were considered as 70-130% and 0-30 respectively. Data analysis and entry were accomplished by the use of statistical package SPSS. The data were analyzed in two sections. The first section of the analysis was made up of a non-parametric binomial test for comparing two methods (MFDS#83 and QuEChERS EN) and also for comparing two concentration levels (10 × LOQ, 50 × LOQ), the second section was made up of a non-parametric chi-square test for comparing the matrices (Mandarin, pepper, Potato, Rice, and Soybean). The null hypotheses of interest were (i) MFDS#83 and QuEChERS EN methods were equally likely to fulfill the requirement (value at acceptable range) (ii) 10 × LOQ and 50 × LOQ concentrations levels were equally likely to fulfill the requirement, and (iii) All five matrices (mandarin, pepper, potato, rice, and soybean) were equally likely to fulfill the requirement. In hypothesis testing, the null hypothesis will be rejected at 5% level of significance if p-value of that test is less than 0.05. Rejection of null hypothesis in (i), (ii) and (iii) indicates significant differences in the proportions fulfill the requirement.

3. Results and discussion 3.1. Method validation Linearity at the level of 0.002–0.1 mg/kg was verified with the established analytical conditions of UPLC-MS/MS for both methods. Excellent linearity was observed for the matrixmatched calibration curve constructed with the extract of QuEChERS EN, showing coefficients of determination (R2) ≥ 0.99 for all compounds except three. Meanwhile, good linearity was also observed from the matrix-matched calibration extracted from MFDS#83 with coefficients

of determination (R2) ≥ 0.99 for most of the compounds except ten. In both methods, a lower linearity was observed for a few compounds with a determination of coefficient (R2) ≥ 0.97. The limit of quantification was calculated using a S/N ratio based on the detection limit. This value was dependent on the dilution ratio of the dilution method used. The limit of quantification for all the analytes in the five representative matrices following the MFDS#83 method was 0.0004 mg/kg. On the other hand, the quantitative limits of the QuEChERS EN method were set to 0.002 mg/kg for potato, citrus and pepper, 0.004 mg/kg for brown rice, and 0.006 mg/kg for soybean. The LOQ of the MFDS#83 method was approximately ten times lower than that of the QuEChERS EN method because of the concentration process (evaporation step) involved in the traditional method. For the recovery test, five representative agricultural products were prepared and spikes at 10 times LOQ and 50 times LOQ. According to the project guideline the recovery and RSD tolerances were estimated at the 70%–130% and ≤ 30% levels, respectively. A table with the recoveries at 10 × LOQ is provided as supplementary information.

3.2. Statistical interpretation The MFDS#83 and QuEChERS EN method were compared in terms of recovery and the null hypothesis is rejected as the observed p-value was 0.029. This result indicates the proportion of two methods differs significantly and QuEChERS EN method predominant (51.7%) in terms of pesticides at an acceptable range. The p-value for the concentration levels 10 × LOQ and 50 × LOQ was observed as 0.795 in the MFDS#83 method and was 0.737 in the QuEChERS EN method consequently the null hypothesis of equality of proportion couldn’t be rejected in both the methods. Therefore the two concentration levels were equally likely to fulfill the requirement within the MFDS#83 and QuEChERS EN methods. The p-value for testing the equality of proportion among the five matrices was 0.535 in the MFDS#83 method but it was

0.001 in the QuEChERS EN method. Therefore five matrices were equally likely to fulfill the requirement within the MFDS#83 methods. In contrast, five matrices differ significantly in fulfilling the requirement (value at an acceptable range) within the QuEChERS EN method. In QuEChERS EN method Rice was predominant (21.6%) in terms of the acceptable range. In the case of RSD, the MFDS#83 and QuEChERS EN method were compared and the null hypothesis is rejected as the observed p-value was 0.000. This result indicates the proportion of two methods differs significantly and QuEChERS EN method predominant (52.5%) in terms of pesticides at an acceptable range. The p-value for the concentration levels 10 × LOQ and 50 × LOQ was observed as 0.934 in the MFDS#83 method and was 0.829 in the QuEChERS EN method consequently the null hypothesis of equality of proportion couldn’t be rejected in both the methods. Therefore the two concentration levels were equally likely to fulfill the requirement within the MFDS#83 and QuEChERS EN methods. Similarly, the p-value for testing the equality of proportion among the five matrices was 0.295 in the MFDS#83 method and was 0.986 in the QuEChERS EN method consequently the null hypothesis of equality of proportion couldn’t be rejected in both the methods. Therefore the five matrices were equally likely to fulfill the requirement within the MFDS#83 and QuEChERS EN methods.

3.3. Comparative study of MFDS#83 and QuEChERS EN methods The recovery and repeatability percentages of 267 compounds in the MFDS#83 and QuEChERS EN methods are shown in Fig. 1. In the MFDS#83 method, the number of compounds that satisfy the guidelines of 70–130% recovery and RSD of 30% or less at the 10 × LOQ level were 191–216, where the highest number of compounds was found in the potato matrix, followed by pepper, mandarin rice, and soybean. At 50 × LOQ, 191–220 compounds were recovered in the order of potato, mandarin, pepper, rice, and soybean.

On the other hand, in QuEChERS EN method, at the 10 × LOQ level, 189–247 compounds satisfied the guidelines (recovery 70–130% and RSD 30% or less). The highest recovery rate was found for rice, followed by soybean, potato, pepper, and mandarin. Only 189 compounds were recovered for mandarin, which were somewhat lower than those for other crops. At 50 × LOQ, 179–241 compounds were recovered, in which the highest number of compounds were recovered from potato, followed by soybean, rice, pepper, and mandarin.

3.4. Comparison in terms of recovery percentage The 267 compounds and the compounds that satisfy the guidelines in terms of recovery rate and RSD at the levels of 10 × LOQ and 50 × LOQ in both methods are shown in Fig. 2. To observe the difference based on the fortified concentrations, the recovery percent for each concentration was compared. As shown in the figure, at the 10 × LOQ level, the QuEChERS EN method showed better results than the MFDS#83 method by 4.87% for pepper, 5.62% for potato, 13.86% for rice, and 16.48% for soybean. However, MFDS#83 showed better results by 7.86% for mandarin than the QuEChERS EN method at the same concentration level. On the other hand, at 50 × LOQ level, the QuEChERS EN method showed 1.12% better results for pepper, 7.87% for potato, 10.11% for rice, and 17.98% for soybean, but for mandarin, the extraction efficiency in terms of number of compounds was 13.86% lower than that of the MFDS#83 method. The results at the 10 × LOQ and 50 × LOQ levels were slightly different because of the different spiking concentrations. Therefore, the number of compounds that satisfy the guidelines at both concentration levels were compared. The results showed that the QuEChERS EN method was 3.00% better for potato, 11.60% for rice, and 11.60% for soybean. For mandarin, the MFDS#83 method showed 14.4% better results, and the results for pepper were similar in both methods. As opposed to these two matrices, potato, rice, and soybean showed good results in the QuEChERS EN method for all comparison results.

3.5. Traditional to modern methodology Although the QuEChERS EN method showed no significant difference with the MFDS#83 method in the recovery test, it showed comparatively better results in the method validation test. The recovery results showed that none of the compounds met the guidelines. At the low level (10 × LOQ level), the QuEChERS EN method showed better results compared with the MFDS#83 method except mandarin, which might be due to the low pH of mandarin influencing recovery during the QuEChERS EN method. Five representative matrices were selected in this study with regard to pH, fat, pigment, and starch with high consumption on a regular basis. Monitoring methods are primarily used as qualitative method and fastness is important in analyzing the field sample. The QuEChERS EN method involves a lower amount of toxic solvent consumption, no use of a glass apparatus, and no time-consuming cartridge purification, like the traditional MFDS#83 method does. Therefore, it is expected that QuEChERS EN method can be practically applied for multi-residue analysis.

4. Conclusions To upgrade the multi-residue analytical method, the QuEChERS EN method and traditional MFDS#83 method were compared for the screening of 267 pesticides/metabolites/plant activators/growth regulators in five representative matrices using UPLC-MS/MS. The matrices (mandarin, pepper, potato, rice, and soybean) were selected in terms of pH, pigments, starch, and fat along with high consumption rate. Both methods provided good linearity and low LOQ for most of the analytes. The QuEChERS EN method provided better results in terms of recovery and repeatability than the MFDS#83 method for all matrices except mandarin. As a quick screening method, the QuEChERS EN method can be an upgraded replacement of the MFDS#83 method for pepper, potato, rice, and soybean, or similar types of matrices. Further

modification of the QuEChERS EN version is needed for acidic/low pH matrices, such as mandarin. Conflict of interest The authors declare no conflict of interest.

Acknowledgments This study was supported by a grant of Ministry of Food and Drug Safety (MFDS) (Project no. 15162MFDS071), Republic of Korea.

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using GC-MS/MS, Gyeongsang National University, doctoral thesis, 2013. [18] National Agricultural Products Quality Management Service, hazardous substances analysis method for agricultural products: Korea Food and Drug Safety notice 2013-138 (amendment, 2013.4.5) [19] M. Anastassiades, S.J. Lehotay, D. Štajnbaher, F.J. Schenck, Fast and Easy Multiresidue Method Employing Acetonitrile Extraction/Partitioning and "Dispersive Solid-Phase Extraction" for the Determination of Pesticide Residues in Produce, J. AOAC Int. 86 (2003) 412~431. [20] S.J. Lehotay, M. Hiemstra, P. van Bodegraven, Validation of Fast and Easy Method for the Determination of Residues from 229 Pesticides in Fruits and Vegetables Using Gas and Liquid Chromatography and Mass Spectrometric Detection, J. AOAC Int. 88 (2005) 595~614. [21] P. Payá, M. Anastassiades, D. Mark, I. Sigalova, B. Tasdelen, J. Oliva, A. Barba, Analysis of pesticide residues using the Quick Easy Cheap Effective Rugged and Safe (QuEChERS) pesticide multiresidue method in combination with gas and liquid chromatography and tandem mass spectrometric detection. Anal. Bioanal. Chem. 389 (2007) 1697~1714. [22] QuEChERS: A Mini-multiresidue method for the analysis of pesticide residues in low-fat products.(www.Quechers.com, 2009) [23] S.J. Lehotay, K.A. Son, H. Kwon, U. Koesukwiwat, W. Fu, K. Mastovska, E. Hoh, N. Leepipatpiboon, Comparison of QuEChERS sample preparation methods for the analysis of pesticide residues in fruits and vegetables, J. Chromatogr. A 1217 (2010) 2548~2560. [24] K. Mastovska, K.J. Dorweiler, S.J. Lehotay, W.J. Segscheid, K.A. Szpylka, Pesticide Multiresidue Analysis in Cereal Grains Using Modified QuEChERS Method Combined with Automated Direct Sample Introduction GC-TOFMS and UPLC-MS/MS Techniques, J. Agric. Food Chem. 58 (2010) 5959~5972. [25] U. Koesukwiwat, S.J. Lehotay, K. Mastovska, K.J. Dorweiler, N. Leepipatpiboon,

Extension of the QuEChERS Method for Pesticide Residues in Cereals to Flaxseeds, Peanuts, and Doughs, J. Agric. Food Chem. 58 (2010) 5950~5958. [26] F.J. Schenck, J.E. Hobbs, Evaluation of the Quick, Easy, Cheap, Effective, Rugged, and Safe (QuEChERS) Approach to Pesticide Residue Analysis, Bull. Environ. Contam. Toxicol. 73 (2004) 24~30. [27] U. Koesukwiwat, K. Sanguankaew, N. Leepipatpiboon, Rapid determination of phenoxy acid residues in rice by modified QuEChERS extraction and liquid chromatography–.tandem mass spectrometry. Anal. Chim. Acta 626 (2008) 10~20. [28] Multi-residue pesticide screens, California Department of Food and Agriculture, Division of Inspection Services, Chemistry Laboratory Services Branch, Pesticide Residue Program. Joe T, 1988 [29] M. Luke, J.E. Froberg, H.T. Masumoto, Extraction and cleanup of organochlorine, organophophate, organonitrogen and hydrocarbon pesticides in produce for determination by gas-liquid chromatography. J. Assoc. Off. Anal. Chem. 58 (1975) 1020~1026. [30] P.A. Mills, J.H. Omley, R.A. Guither, Rapid method for chlorinated pesticide residues in nonfatty foods. J. Assoc. Off. Anal. Chem. 46 (1963) 186~191. [31] S.M. Lee, M.L. Papathakis, H.M.C. Feng, G.F. Hunter, J.E. Carr, Multipesticide residue method for fruits and vegetables: California Department of Food and Agriculture. Fresenjus Journal of Analytical Chemists, 339, 1991, 376~383 [32] Directorate General for Health and Food Safety. Guidance document on analytical quality control and method validation procedures for pesticide residues and analysis in food and feed, Doc. no. SANTE/11813/2017. European Commission, Brussels, 2007.

240

225

216

214 210

191

<<50 50 % % 50 <<70 50 70 % % 70 <130 70 < 130%% > 130 % 130 % < RSD > 30 % 30 % < RSD

175 55 42

38

46

45

Number of pesticides

Number of pesticides

200

50

220

216

210

25

214

211

200

191

<<50 50%% 50 < <70 70%% 70 <130 70 < 130%% > 130 % 130 % < RSD > 30 % 30 % < RSD

55

50

45

44

45 35

25 16

11 4

6

4

5

0 Mandarin

0

Pepper

2

3 1

2

7

10

8

8

7

3

2

Potato

Rice

Soybean

4

1

0

Mandarin

4

Pepper

48

27

0

0

3

Mandarin

16 15 4 3

Pepper

2

Soybean

15

12 3 2

Potato

6

2 0

Rice

239

238

<<50 50 % % 50 70% % 50 < <70 70 < <130 70 130%% > 130 % 130 % < RSD%><30RSD % 30

200 179

150 59

50 27

22 11

Rice

3

217

% 50 % <<50 50<<70 % 70 % 50 70 <130 % 70 < 130 % > 130 % 130 RSD%><30 % 30 % < RSD

189

25

4 4

241

235

231

Number of pesticides

Number of pesticides

50

Potato

250

247

250

200

3

1

(b)

(a)

227

2

25

25

20

12

14

10 13

3 2

0

Soybean

0

4 1

2

Mandarin

Pepper

(c)

3

Potato

0

11 13

11 1 3

Rice

2 2

Soybean

(d)

Fig. 1. Recovery and repeatability percentage of 267 pesticides in five representative matrices (a) MFDS#83 method at 10×LOQ level; (b) MFDS#83 method at 50×LOQ level; (c) QuEChERS EN at 10×LOQ level; and (d) QuEChERS EN at 50×LOQ level

Fig. 2. Average percent recovery of 267 compounds at the (A) 10×LOQ level; (B) 50×LOQ level.

Table 1. Optimized MRM conditions of 256 (267) pesticides for multi-residue pesticide analysis using LC-MS/MS Compound

Activity

RT

Q1

Q3

DP

EP

CE

CXP

Abamectin B1a

Insecticide

Acephate

Insecticide

Acetamiprid

Insecticide

Acibenzolar-Smethyl Alachlor

Plant activator Herbicide

Aldicarb

Insecticide

Ametoctradin

Fungicide

Amisulbrom

Fungicide

Amitraz

Insecticide

Atrazine

Herbicide

Azimsulfuron

Herbicide

Azinphosmethyl Azoxystrobin

Insecticide

Bendiocarb

Insecticide

Benfuracarb

Insecticide

Benfuresate

Herbicide

BensulfuronMethyl BenthiavalicarbIsopropyl Benzobicyclon

Herbicide Fungicide

Benzoximate

Acaricide

13.23 13.23 2.85 2.85 3.63 3.63 7.31 7.31 8.52 8.52 4.09 4.09 10.00 10.00 10.87 10.87 12.58 12.58 5.61 5.61 5.77 5.77 6.54 6.54 6.95 6.95 4.57 4.57 11.05 11.05 6.07 6.07 6.40 6.40 7.80 7.80 7.82 7.82 10.29

890.50 890.53 183.97 183.97 223.10 223.10 211.10 211.10 270.12 270.12 212.98 208.10 276.20 276.20 465.83 465.83 294.11 294.11 216.12 216.12 425.00 425.00 318.04 318.04 404.10 404.10 224.20 224.20 411.20 411.20 274.15 274.15 410.90 410.90 382.10 382.10 447.00 447.00 364.06

305.00 113.10 143.00 95.00 126.00 99.10 140.00 136.10 238.00 162.10 116.00 116.00 149.20 176.20 227.00 148.10 163.20 122.20 174.00 103.90 182.10 156.10 132.10 160.00 372.10 344.10 167.20 109.20 195.10 102.10 163.10 77.10 149.00 119.10 180.10 116.20 257.10 229.10 198.90

60 56 46 46 86 86 50 91 41 41 56 41 66 66 76 76 61 61 36 36 71 71 51 51 76 76 71 71 86 86 61 61 76 76 86 86 61 61 6

10 10 10 10 10 10 10 10 10 10 10 10 5 5 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 10

35 73 11 29 29 49 31 39 13 27 15 11 49 49 29 63 21 41 23 39 23 45 21 19 19 31 13 23 31 41 25 101 27 53 39 29 37 51 11

8 10 8 8 11 11 8 11 10 6 4 8 4 4 10 10 11 11 8 8 11 11 10 11 15 13 11 11 11 11 10 12 11 11 11 11 4 4 8

Fungicide

Herbicide

10.29

364.06

105.00

6

10

37

10

Table 1. Continued Compound

Activity

RT

Q1

Q3

DP

EP

CE

CXP

Bifenazate

Acaricide

Bitertanol

Fungicide

Boscalid

Fungicide

Bromacil

Herbicide

Buprofezin

Insecticide

Cadusafos

Insecticide

Cafenstrole

Herbicide

Carbaryl

Insecticide

8.15 8.15 9.97 9.97 7.34 7.34 4.60 4.60 11.16 11.16 10.21 10.21 7.95 7.95 4.87 4.87 3.35 3.35 3.35 3.35 4.58 4.58 4.97 4.97 9.32 9.32 9.44 9.44 6.37 6.37 12.64 12.64 11.88 11.88 4.85 4.85 8.32 8.32 4.18 4.18

301.00 301.00 338.28 338.28 343.00 343.00 261.07 261.07 306.20 306.20 271.10 271.10 351.20 351.20 202.10 202.10 192.10 192.10 192.01 192.01 222.10 222.10 236.17 236.17 412.00 412.00 334.10 334.10 482.04 482.04 539.91 539.91 349.93 349.93 358.00 358.00 395.20 395.20 414.16 414.16

198.10 170.10 269.20 70.00 307.00 140.00 205.00 188.20 201.30 116.20 159.10 97.10 100.20 72.10 145.10 127.10 160.10 132.00 160.10 132.10 165.10 123.00 143.10 86.90 345.80 365.90 139.10 103.10 283.90 450.90 382.90 158.20 97.00 198.00 141.00 167.10 175.10 147.20 182.90 83.00

71 71 71 71 111 116 66 66 66 66 71 71 71 71 71 71 91 91 60 60 70 70 66 66 91 91 76 76 6 6 86 86 71 71 81 81 71 71 111 111

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

15 27 13 47 27 27 21 41 17 21 19 49 19 39 16 39 27 41 25 41 17 29 21 35 27 21 29 57 21 25 29 25 53 25 23 25 21 61 21 59

13 11 8 6 17 13 10 10 11 11 11 11 11 11 10 10 13 11 6 12 9 9 10 10 13 15 11 11 10 18 14 6 8 8 11 11 11 11 8 8

Carbendazim Fungicide Benomyl Carbofuran

Insecticide

Carboxin

Fungicide

CarfentrazoneEthyl Carpropamide

Herbicide Fungicide

Chlorantraniliprole Insecticide Chlorfluazuron

Insecticide

Chlorpyrifos

Insecticide

Chlorsulfuron

Herbicide

Chromafenozide

Insecticide

Cinosulfuron

Herbicide

Table 1. Continued Compound

Activity

Clethodim

RT

Q1

Q3

DP

EP

CE

CXP

Herbicide

10.87 10.87 Clofentezine Acaricide 10.38 10.38 Clomazone Herbicide 6.49 6.49 Clothianidin Insecticide 3.54 3.54 Cyazofamid Fungicide 8.64 8.64 Cyclosulfamuron Herbicide 8.26 8.26 10.15 Cyflufenamid Fungicide 10.15 Cyhalofop-butyl Herbicide 10.58 10.58 Cymoxanil Fungicide 3.82 3.82 Cyproconazole Fungicide 8.01,8.68 (I,II)a 8.01,8.68

360.10 360.10 303.00 303.00 240.10 240.10 250.10 250.10 325.10 325.10 422.00 422.00 413.08 413.08 358.11 358.11 199.02 199.02 292.10 292.10

164.00 77.00 138.10 102.10 125.10 89.00 169.10 132.10 107.90 261.00 260.80 217.90 295.10 203.00 256.00 120.00 128.00 83.00 70.14 125.17

76 76 71 71 81 81 66 66 71 71 71 71 71 71 76 76 51 51 81 81

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

27 99 19 55 25 61 17 17 19 15 23 33 21 49 17 35 13 35 33 41

13 11 11 11 11 11 21 21 11 13 13 13 12 8 10 10 10 8 11 11

Cyprodinil

Fungicide

226.10 226.10 167.03 167.03 231.03 231.03 385.00 385.00 305.20 305.20 350.00 350.00 220.87 220.87 268.00 268.00 406.00 406.00 311.00 311.00

93.00 77.10 85.00 125.00 89.00 61.00 329.00 278.00 169.20 153.20 332.90 127.00 109.00 79.10 226.00 180.00 251.00 337.00 158.10 141.10

96 96 56 56 16 16 46 46 86 86 31 31 66 66 71 66 81 126 76 76

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

41 63 23 23 13 41 33 43 27 29 9 21 23 50 15 23 23 23 19 45

8 8 8 10 8 6 14 12 11 11 12 12 8 8 15 14 19 19 11 11

8.79 8.79 Cyromazine Insecticide 1.58 1.58 Demeton-SInsecticide 4.66 methyl 4.66 Diafenthiuron Insecticide 12.41 12.41 9.72 Diazinon Insecticide 9.72 Dichlofluanid Fungicide 7.95 7.95 4.51 Dichlorvos Insecticide 4.51 6.86 Diethofencarb Fungicide 6.85 Difenoconazole Fungicide 10.25 10.25 8.86 Diflubenzuron Insecticide 8.86 aCyproconazole including two peaks

Table 1. Continued Compound

Activity

Dimepiperate

Herbicide

Dimethametryn

Herbicide

Dimethenamide

Herbicide

Dimethoate

Insecticide

Dimethomorph Fungicide (E) Dimethomorph (Z) Dimethylvinphos Insecticide Diniconazole

Fungicide

Diphenamid

Herbicide

Dithiopyr

Herbicide

Diuron

Herbicide

Dymron

Herbicide

Edifenphos

Fungicide

Emamectine B1a Insecticide Emamectine B1b EPN

Insecticide

Esprocarb

Herbicide

Ethaboxam

Fungicide

Ethiofencarb

Insecticide

Ethofenprox

Insecticide

RT

Q1

Q3

DP

EP

CE

CXP

10.49 10.49 8.38 8.38 7.10 7.10 3.68 3.68 7.04 7.04 7.54 7.54 7.95 7.94 10.04 10.04 6.13 6.13 10.95 10.95 5.84 5.84 7.74 7.74 9.39 9.39 10.89 10.89 10.48 10.48 10.62 10.62 11.26 11.26 5.16 5.16 5.09 5.09 13.68 13.68

264.13 264.13 256.20 256.20 276.10 276.10 229.98 229.98 388.10 388.10 388.11 388.11 330.96 330.96 326.10 326.10 240.20 240.20 402.10 402.10 233.10 233.10 269.10 269.10 311.10 311.10 886.90 886.90 872.80 872.80 324.10 324.10 266.20 266.20 321.02 321.02 226.10 226.10 394.30 394.30

146.10 119.10 186.10 71.00 244.10 168.30 199.00 125.00 301.10 165.20 301.10 165.20 127.00 169.90 70.00 158.70 134.20 165.10 354.00 271.90 72.10 160.10 151.10 119.10 111.10 109.10 82.20 158.30 82.20 158.30 296.00 156.90 91.10 65.10 183.10 200.20 106.90 164.10 177.20 135.20

6 6 91 91 76 76 46 46 101 101 101 101 66 66 21 21 91 91 96 96 86 86 86 86 86 86 131 131 126 126 16 16 81 81 86 86 61 61 71 71

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

13 23 25 43 19 31 13 27 25 45 25 45 15 47 61 37 27 55 23 39 35 35 17 25 29 41 119 49 119 51 19 29 33 79 31 35 21 11 21 33

6 10 11 11 13 11 8 10 11 11 11 11 10 8 6 18 11 11 13 13 11 11 11 11 11 11 11 11 11 11 12 14 11 11 8 8 9 10 11 11

Table 1. Continued Compound

Activity

Ethoprophos

Insecticide

Ethoxyquin

Fungicide

Ethoxysulfuron

Herbicide

Etoxazole

Acaricide

Etrimfos

Insecticide

Famoxadone

Fungicide

Fenamidone

Fungicide

Fenamiphos

Nematicide

Fenarimol

Fungicide

Fenazaquin

Acaricide

Fenbuconazole

Fungicide

Fenobucarb

Insecticide

Fenothiocarb

Acaricide

Fenoxanil

Fungicide

Fenoxaprop-PEthyl Fenoxycarb

Herbicide Insecticide

Fenpyroximate

Acaricide

Fenthion

Insecticide

Fentrazamide

Herbicide

Ferimzone (z)

Fungicide

RT

Q1

Q3

DP

EP

CE

CXP

8.35 8.35 6.14 6.14 7.79 7.79 12.15 12.15 9.58 9.58 9.83 9.83 7.24 7.24 8.83 8.83 8.28 8.28 12.67 12.67 8.67 8.67 6.66 6.66 9.06 9.06 6.95 6.95 11.00 11.00 9.06 9.06 12.42 12.42 9.66 9.66 9.48 9.48 6.26 6.26

243.00 243.00 218.21 218.21 399.00 399.00 360.20 360.20 293.10 293.10 392.16 392.16 312.10 312.10 304.20 304.20 331.00 331.00 307.20 307.20 337.20 337.20 208.10 208.10 254.08 254.08 329.10 329.10 362.00 362.00 302.20 302.20 422.00 422.00 279.10 279.10 350.19 350.19 255.20 255.20

130.90 96.90 160.20 174.20 260.90 217.90 141.10 63.00 265.00 125.10 331.20 238.10 236.00 92.00 217.00 202.00 268.00 81.00 161.20 147.10 125.10 70.00 95.20 152.00 72.00 160.00 156.10 172.20 288.10 121.00 116.20 256.20 366.00 135.00 247.10 169.20 154.10 83.00 132.00 124.20

66 66 81 81 76 76 96 96 86 86 36 36 61 61 56 56 101 106 91 91 96 96 67 67 56 56 156 156 86 86 76 76 66 56 86 86 61 61 86 86

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

27 43 43 39 21 33 43 129 21 33 13 25 19 37 29 45 27 27 19 59 41 35 19 11 33 13 43 49 23 37 15 17 23 41 17 23 17 35 27 27

10 10 10 10 13 13 11 11 13 11 10 10 10 8 8 8 13 13 11 11 11 11 10 10 8 8 13 11 13 11 11 13 21 13 13 11 10 10 17 17

Table 1. Continued Compound

Activity

Flonicamid TFNA

Insecticide

TFNG Fluacrypyrim

Acaricide

Flubendiamide

Insecticide

Flucetosulfuron (Er) Flucetosulfuron (Th) Fludioxonil

Fungicide

Flufenacet

Herbicide

Flufenoxuron

Insecticide

Flumioxazin

Herbicide

Fluopicolide

Fungicide

Fluopyram

Fungicide

Fluquinconazole

Fungicide

Flusilazole

Fungicide

Flutolanil

Fungicide

Herbicide

Forchlorfenuron Plant growth regulator Fosthiazate Insecticide Furathiocarb

Insecticide

Gibberellic acid

Plant growth regulator

RT

Q1

Q3

DP

EP

CE

CXP

3.34 3.34 3.21 3.21 3.27 3.27 10.55 10.55 9.39 9.39 6.59 6.59 6.79 6.79 7.27 7.27 8.46 8.46 12.18 12.18 6.34 6.34 7.68 7.68 8.20 8.20 8.17 8.17 8.84 8.84 7.62 7.62 5.77 5.77 5.14 5.14 11.16 11.16 3.59 3.59

229.95 229.95 192.02 192.02 248.98 248.98 427.00 427.00 408.10 683.03 488.16 488.16 488.16 488.16 266.09 266.09 364.10 364.10 489.00 489.00 355.00 355.00 383.00 383.00 397.02 397.02 375.90 375.90 316.10 316.10 324.00 324.00 248.10 248.10 284.10 284.10 383.20 383.20 364.15 364.15

203.10 148.00 148.00 98.10 203.10 148.10 145.10 205.10 274.10 408.00 156.00 273.10 156.00 273.10 229.00 158.00 152.20 194.30 158.10 141.10 327.10 299.10 173.00 109.00 208.00 173.00 307.10 108.00 247.10 165.20 262.00 242.00 129.00 155.10 228.10 104.20 195.20 252.10 239.10 311.00

86 86 21 21 86 86 71 71 45 45 56 56 56 56 1 1 71 71 91 91 45 45 91 91 81 81 91 91 101 101 81 86 81 81 76 76 81 81 56 56

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

23 39 31 45 31 39 33 17 23 15 23 35 23 35 15 45 25 17 27 71 30 36 35 91 29 35 33 69 23 39 23 23 21 19 15 29 23 17 21 19

13 11 6 11 13 13 11 13 10 10 6 10 6 10 8 8 11 11 11 11 8 8 10 12 8 8 13 11 13 11 11 11 11 11 11 11 11 11 8 14

Table 1. Continued Compound HalosulfuronMethyl Haloxyfop

Activity Herbicide Herbicide

Haloxyfop-PMethyl Hexaconazole

Fungicide

Hexaflumuron

Insecticide

Hexazinone

Herbicide

Hexythiazox

Acaricide

Imazalil

Fungicide

Imazosulfuron

Herbicide

Imibenconazole

Fungicide

Imicyafos

Nematicide

Imidacloprid

Insecticide

Inabenfide Iprobenfos

Plant growth regulator Fungicide

Iprovalicarb

Fungicide

Isoprocarb

Insecticide

Isoprothiolane

Fungicide

Isopyrazam

Fungicide

Kresoximmethyl Linuron

Fungicide Herbicide

RT

Q1

Q3

DP

EP

CE

CXP

8.37 8.37 9.32 9.32 10.52 10.52 9.63 9.63 10.82 10.82 4.59 4.59 11.76 11.76 4.58 4.58 7.43 7.43 11.35 11.35 4.18 4.18 3.50 3.50 6.92 6.92 9.10 9.10 8.24 8.24 5.49 5.49 7.71 7.71 10.30 10.30 9.38 9.38 6.91 6.91

435.00 435.00 362.08 362.08 376.00 376.00 314.10 314.10 461.00 461.00 253.23 253.23 353.10 353.10 297.05 297.05 412.90 412.90 411.00 411.00 305.10 305.10 256.00 256.00 339.14 339.14 288.97 288.97 321.20 321.20 194.20 194.20 291.10 291.10 360.20 360.20 314.16 314.16 249.00 249.00

182.10 139.00 316.00 287.90 315.90 287.90 70.00 159.10 158.20 141.10 171.10 71.10 228.00 168.10 158.90 255.10 153.10 257.90 125.00 171.00 201.10 235.20 209.00 175.00 320.90 80.00 205.00 91.00 119.10 203.20 95.20 137.10 231.10 189.10 244.20 320.30 116.00 131.10 160.00 182.10

76 76 76 76 96 96 96 96 91 91 71 71 76 76 41 41 76 76 88 88 51 51 65 65 81 81 61 61 66 66 71 71 71 71 56 56 56 56 75 75

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

31 59 23 35 21 29 39 43 25 59 23 45 23 37 27 23 19 33 50 28 31 25 21 25 23 67 15 12 35 15 19 13 15 27 33 29 23 33 23 19

11 11 10 12 13 13 11 11 11 11 10 10 15 13 8 10 11 13 11 11 4 4 14 14 12 6 8 8 11 13 11 11 13 11 4 4 10 12 11 11

Table 1. Continued Compound

Activity

Lufenuron

Insecticide

Malathion

Insecticide

Mandipropamid

Fungicide

Mefenacet

Herbicide

Mepanipyrim

Fungicide

Mepronil

Fungicide

Metalaxyl

Fungicide

Metamifop

Herbicide

Metazosulfuron

Herbicide

Metconazole

Fungicide

Methabenzthiazuro n Methidathion

Herbicide Insecticide

Methiocarb

Insecticide

Methomyl

Insecticide

Methoxyfenozide

Insecticide

Metobromuron

Herbicide

Metolachlor

Herbicide

Metolcarb

Insecticide

Metrafenone

Fungicide

Metribuzin

Herbicide

Table 1. Continued

RT

Q1

Q3

DP

EP

CE

CXP

11.70 11.70 7.75 7.75 7.57 7.57 7.98 7.98 8.35 8.35 7.67 7.67 5.67 5.67 11.07 11.07 7.25 7.25 9.73 9.73 5.55 5.55 6.29 6.29 7.02 7.02 3.33 3.33 7.83 7.83 5.48 5.48 8.59 8.59 4.30 4.30 10.23 10.23 4.64 4.64

510.90 510.90 331.00 331.00 411.80 411.80 299.10 299.10 224.00 224.00 270.20 270.20 280.20 280.20 441.10 441.10 476.10 476.10 320.20 320.20 222.10 222.10 303.10 303.10 226.20 226.20 163.10 163.10 369.30 369.30 259.00 259.00 284.16 284.16 166.03 166.03 409.04 409.04 215.06 215.06

158.20 141.20 127.00 99.10 328.10 125.00 148.20 120.20 106.00 77.00 119.10 91.20 220.20 160.20 288.00 180.20 182.20 295.10 70.00 125.00 165.20 150.10 85.10 145.10 169.20 121.00 88.10 106.20 149.20 133.10 170.00 148.10 252.00 176.20 109.00 94.00 209.10 227.00 187.10 59.80

60 60 71 71 76 76 81 81 96 96 91 91 76 76 101 101 41 41 91 91 76 76 76 76 71 71 61 61 66 66 66 66 31 31 46 46 66 66 61 61

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 9 9 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

27 67 17 31 21 47 19 35 35 35 31 53 17 31 23 27 31 25 43 61 23 45 27 15 13 23 13 13 21 31 23 21 19 33 15 41 23 29 23 71

8 8 11 11 13 11 11 11 11 11 11 11 11 11 13 11 4 4 11 11 11 11 11 13 11 11 10 10 11 11 8 8 10 8 8 8 10 10 8 6

Compound

Activity

Mevinphos

Insecticide

Milbemectin A3

Acaricide

Milbemectin A4 Molinate

Herbicide

Monocrotophos Insecticide Myclobutanil

Fungicide

Napropamide

Herbicide

Nereistoxin

Insecticide

Nicosulfuron

Herbicide

Novaluron

Insecticide

Nuarimol

Fungicide

Ofurace

Fungicide

Omethoate

Insecticide

Oxadiazon

Herbicide

Oxadixyl

Fungicide

OxamyI

Insecticide

Oxaziclomefon

Herbicide

Paclobutrazole Penconazole

Plant growth regulator Fungicide

Pencycuron

Fungicide

Table 1. Continued

RT

Q1

Q3

DP

EP

CE

CXP

3.86 3.86 12.93 12.93 13.37 13.37 7.69 7.69 3.37 3.37 7.71 7.71 8.46 8.46 0.82 0.82 10.23 10.23 10.97 10.97 6.90 6.90 4.55 4.55 3.08 3.08 11.48 11.48 4.09 4.09 3.23 3.23 11.02 11.02 7.44 7.44 9.12 9.12 10.16 10.16

224.99 224.99 511.29 511.29 525.36 525.36 188.20 188.20 224.10 224.10 289.20 289.20 272.20 272.20 150.00 150.00 411.08 411.08 493.10 493.10 315.00 315.00 282.10 282.10 214.14 214.14 345.10 362.10 279.20 279.20 237.03 237.03 376.00 376.00 294.18 294.18 284.10 284.10 329.00 329.00

192.90 127.00 95.10 105.10 91.00 55.10 126.20 55.10 127.10 109.10 70.00 125.10 171.20 129.20 105.00 61.00 209.10 228.90 158.10 141.10 252.00 81.00 254.10 160.20 125.00 109.10 303.00 220.00 219.20 133.20 72.00 90.10 190.10 133.10 70.00 125.10 159.10 70.10 125.00 99.00

56 56 86 86 86 86 71 71 66 66 86 86 86 86 41 41 71 71 86 86 101 101 86 86 66 66 61 61 76 76 6 6 86 86 46 46 81 81 86 86

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

9 19 47 89 109 93 17 35 21 41 27 41 23 21 21 33 19 23 27 69 31 31 17 31 31 39 20 31 15 27 27 11 21 47 47 45 39 27 33 83

8 10 10 12 12 12 11 11 11 11 11 11 13 11 10 6 8 10 11 11 13 13 13 11 10 10 11 11 13 11 6 8 11 11 6 11 11 11 11 15

Compound

Activity

Pendimethalin

Herbicide

Penoxsulam

Herbicide

Penthiopyrad

Fungicide

Pentoxazone

Herbicide

Phenthoate

Insecticide

Phorate

Insecticide

Phosalone

Insecticide

Phosphamidone Insecticide Phoxim

Insecticide

Picoxystrobin

Fungicide

Piperophos

Herbicide

Pirimicarb

Insecticide

Pirimiphosmethyl Probenazole

Insecticide

Prochloraz

Fungicide

Profenofos

Insecticide

Prometryn

Herbicide

Propamocarb

Fungicide

Propanil

Herbicide

Propaquizafop

Herbicide

Table 1. Continued

Plant activator

RT

Q1

Q3

DP

EP

CE

CXP

11.97 11.97 4.94 4.94 9.33 9.33 11.16 11.16 9.35 9.35 10.08 10.08 10.02 10.02 4.10 4.10 10.11 10.11 9.22 9.22 10.44 10.44 4.47 4.47 10.04 10.04 4.33 4.33 9.51 9.51 10.89 10.89 7.26 7.26 2.98 2.98 6.89 6.89 11.32 11.32

282.16 282.16 484.05 484.05 360.13 360.13 354.05 354.05 321.03 321.03 261.04 261.04 368.10 368.10 300.10 300.10 299.10 299.10 368.09 368.09 354.10 354.10 239.20 239.20 306.20 306.20 224.01 224.01 376.05 376.05 373.00 373.00 242.14 242.14 189.20 189.20 218.10 218.10 444.12 444.12

212.10 194.10 195.10 194.50 276.00 255.90 286.00 186.00 79.00 135.00 75.00 46.90 182.10 75.20 127.10 174.20 129.00 76.90 205.10 145.00 255.00 171.00 72.10 182.20 164.20 108.20 41.10 39.00 308.00 265.90 302.70 128.00 158.00 200.10 102.20 74.00 162.10 127.10 100.10 56.00

31 31 56 56 76 76 86 86 66 66 46 46 81 81 86 86 71 71 56 56 91 91 73 73 96 96 61 61 36 36 86 86 56 56 76 76 86 86 81 81

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

15 23 37 41 19 27 17 35 57 27 13 45 21 95 25 19 17 45 13 29 19 29 34 21 29 39 27 57 17 23 23 59 31 25 23 35 19 37 33 51

8 8 8 8 10 10 10 8 6 10 8 6 13 11 11 11 11 11 8 6 15 13 10 9 11 11 4 4 12 10 13 11 8 8 11 11 11 11 10 10

Compound

Activity

Propiconazole

Fungicide

Propoxur

Insecticide

Pymetrozin

Insecticide

Pyraclofos

Insecticide

Pyraclostrobin

Fungicide

Pyrazolynate

Herbicide

Pyrazophos

Fungicide

Pyrethrin

Insecticide

Pyribenzoxim

Herbicide

Pyributicarb

Herbicide

Pyridaben

Insecticide

Pyridaphenthion Insecticide Pyrifluquinazon

Insecticide

Pyriftalid

Herbicide

Pyrimethanil

Fungicide

Pyrimidifen

Insecticide

Pyriminobacmethyl (E) Pyriminobacmethyl (Z) Pyrimisulfan Pyriproxyfen Table 1. Continued

Herbicide

Herbicide Insecticide

RT

Q1

Q3

DP

EP

CE

CXP

9.48 9.48 4.53 4.53 3.05 3.05 9.95 9.95 9.96 9.96 10.19 10.19 10.16 10.16 12.27 12.27 11.50 11.50 11.76 11.76 12.76 12.76 7.94 7.94 7.75 7.75 6.65 6.65 6.56 6.56 11.05 11.05 6.63 6.63 7.54 7.54 6.11 6.11 11.84 11.84

342.07 342.07 210.20 210.20 218.20 218.20 361.10 361.10 388.00 388.00 439.10 439.10 374.00 374.00 329.28 329.28 610.20 610.20 331.10 331.10 365.00 365.00 341.04 341.04 465.10 465.10 319.17 319.17 200.20 200.20 378.10 378.10 362.10 362.10 362.13 362.13 420.10 420.10 322.00 322.00

158.90 69.00 111.10 93.10 105.10 79.20 111.10 138.10 194.00 163.00 173.10 155.00 222.20 194.20 161.20 105.20 413.10 180.20 181.10 108.00 147.00 309.00 189.10 205.10 423.10 107.20 139.20 83.10 107.20 82.10 184.20 150.20 330.10 75.10 330.20 284.10 370.00 388.10 96.00 185.00

66 66 66 66 81 81 101 101 46 51 91 91 96 96 66 66 61 61 70 70 96 91 61 61 61 61 96 96 96 96 96 96 76 66 66 76 36 36 56 51

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 11 11 10 10 10 10 10 10 10 10 10 10 8 8 10 10

33 39 19 33 27 55 85 55 19 29 25 25 27 43 17 43 23 47 21 40 31 31 29 29 27 45 41 65 31 35 31 45 19 109 21 33 23 21 21 29

14 8 11 11 11 11 11 11 14 14 11 11 11 11 10 10 15 11 10 10 11 11 8 8 8 8 10 10 11 11 11 11 13 12 10 13 6 6 13 14

Compound

Activity

Pyroquilon

Fungicide

Quinalphos

Insecticide

Quinmerac

Herbicide

Quinoclamine

Herbicide

Quizalofopethyl Salflufenacil

Herbicide

Sethoxydim

Herbicide

Silafluofen

Insecticide

Simeconazole

Fungicide

Simetryn

Herbicide

Spinetoram (J) Spinetoram (L) SpinosynA

Herbicide

Insecticide

Insecticide SpinosynD Spirodiclofen

Insecticide

Spiromesifen

Insecticide

Sulfoxaflor

Insecticide

Tebuconazole

Fungicide

Tebufenozide

Insecticide

Tebufenpyrad

Acaricide

Table 1. Continued

RT

Q1

Q3

DP

EP

CE

CXP

4.42 4.42 9.31 9.31 3.83 3.83 4.40 4.40 11.01 11.01 6.65 6.65 11.28 11.28 14.33 14.33 8.31 8.31 4.84 4.84 9.95 9.95 10.55 10.55 9.24 9.24 9.85 9.85 12.38 12.38 11.98 11.98 3.73 3.73 9.28 9.28 8.98 8.98 11.18 11.18

174.10 174.10 299.14 299.14 222.10 222.10 208.10 208.10 373.13 373.13 501.10 501.10 328.20 328.20 426.15 426.15 294.20 294.20 214.06 214.06 748.52 748.52 760.49 760.49 732.50 732.50 746.50 746.50 411.20 411.20 371.20 371.20 278.08 278.08 308.00 308.00 353.10 353.10 334.20 334.20

132.00 117.10 97.10 163.10 204.00 141.10 105.10 77.10 299.20 163.10 349.00 198.00 282.30 178.10 287.00 168.00 70.00 72.90 124.10 68.00 98.10 142.20 98.20 142.20 142.30 99.10 142.20 99.20 71.10 313.10 273.20 255.20 174.00 153.90 70.00 125.00 133.10 297.10 145.20 117.20

101 101 76 76 71 71 101 101 101 101 46 46 81 81 30 30 41 41 71 71 101 101 106 106 116 116 116 116 55 55 65 65 61 61 96 96 71 66 116 116

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

31 41 51 33 19 43 33 51 25 59 35 59 17 25 15 49 53 49 25 49 101 45 91 43 39 67 39 65 25 17 19 29 11 37 41 41 25 25 37 51

11 11 10 10 11 11 11 11 10 10 6 6 11 13 10 8 8 6 12 6 12 10 12 10 11 11 11 11 4 8 6 6 8 12 11 11 11 11 11 11

Compound

Activity

Tebupirimfos

Insecticide

Teflubenzuron

Insecticide

Terbuthylazine

Herbicide

Terbutryn

Herbicide

Tetraconazole

Fungicide

Thenylchlor

Herbicide

Thiabendazole

Fungicide

Thiacloprid

Insecticide

Thiamethoxam Insecticide Thiazopyr

Herbicide

Thidiazuron

Plant growth regulator Thifensufuron- Herbicide Methyl Thiobencarb Herbicide Thiodicarb

Insecticide

Thiophanatemethyl Tiadinil

Fungicide

Tolclofosmethyl Tolyfluanid

Fungicide

Triadimefon

Fungicide

Triazophos

Insecticide

Table 1. Continued

Fungicide

Fungicide

RT

Q1

Q3

DP

EP

CE

CXP

11.44 11.44 11.40 11.40 7.15 7.15 7.40 7.40 8.42 8.42 8.42 8.42 3.50 3.50 3.77 3.77 3.34 3.34 9.53 9.53 4.53 4.53 4.34 4.34 10.11 10.11 5.02 5.02 4.47 4.47 7.83 7.83 10.21 10.21 9.44 9.44 7.70 7.70 8.15 8.15

319.12 319.12 381.10 381.10 230.10 230.10 242.13 242.13 372.00 372.00 324.09 324.09 202.10 202.10 253.10 253.10 292.00 292.00 397.06 397.06 221.10 221.10 388.00 388.00 258.10 258.10 355.10 355.10 343.10 343.10 268.10 270.10 301.02 301.02 363.97 363.97 294.10 294.10 314.10 314.10

277.00 153.10 158.20 141.10 174.20 104.00 186.10 91.00 159.00 70.00 127.10 97.00 175.10 131.10 126.10 186.10 211.20 181.20 377.00 335.00 102.00 128.00 167.10 204.90 125.00 89.30 88.10 108.10 151.10 226.20 101.10 101.10 124.90 175.00 238.00 137.00 197.20 225.00 162.20 119.20

56 56 66 66 86 86 36 36 76 81 46 46 96 96 81 121 66 66 56 56 81 81 81 81 81 81 71 71 81 81 61 61 81 81 51 51 91 91 81 81

10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10

19 37 23 57 21 43 25 35 47 37 19 59 33 43 27 19 17 27 31 39 19 25 21 33 27 67 23 21 25 15 27 27 21 33 19 37 19 19 27 47

10 8 13 11 13 11 8 8 11 15 6 8 13 11 17 16 11 11 12 14 11 11 11 13 11 11 11 11 11 11 8 8 12 14 8 12 11 11 11 11

Compound

Activity

Tricyclazole

Fungicide

Trifloxystrobin

Fungicide

Triflumizole

Fungicide

Triflumuron

Insecticide

Uniconazole

Fungicide

Vamidothion

Insecticide

Bentazone (-)

Herbicide

RT

Q1

Q3

DP

EP

CE

CXP

3.94 3.94 10.72 10.72 10.44 10.44 9.98 9.98 7.62 7.62 3.59 3.59 4.44 4.44

189.99 189.99 409.00 409.00 346.07 346.07 359.10 359.10 292.11 292.11 287.91 287.91 238.90 238.90

163.10 136.00 186.00 206.00 278.00 73.00 156.10 139.10 70.00 125.10 146.10 118.00 196.90 174.90

46 46 51 46 26 26 91 91 46 46 66 66 -5 -5

10 10 10 10 10 10 10 10 5 5 10 10 -10 -10

31 39 23 21 15 23 23 45 41 39 19 35 -26 -26

6 6 14 14 8 11 13 11 4 4 11 11 -13 -13

Author statement Tae-Woong Na & Md. Musfiqur Rahman.: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation. Sung-Woo Kim: Visualization, Investigation. Jae-Han Shim: Supervision. Md. Ershadul Haque: Statistical Analysis and Interpretation: Jong-Bang Eun: Writing- Reviewing and Editing,

Conflict of interest The authors declare no conflict of interest.

Declaration of interests ☐ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.