Simultaneous determination of organophosphorus pesticides in fruits and vegetables using atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry

Accepted Manuscript Simultaneous determination of organophosphorus pesticides in fruits and vegetables using atmospheric pressure gas chromatography quadrupole-time-offlight mass spectrometry Zhipeng Cheng, Fengshou Dong, Jun Xu, Xingang Liu, Xiaohu Wu, Zenglong Chen, Xinglu Pan, Jay Gan, Yongquan Zheng PII: DOI: Reference:

S0308-8146(17)30552-6 http://dx.doi.org/10.1016/j.foodchem.2017.03.157 FOCH 20861

To appear in:

Food Chemistry

Received Date: Revised Date: Accepted Date:

9 August 2016 19 February 2017 29 March 2017

Please cite this article as: Cheng, Z., Dong, F., Xu, J., Liu, X., Wu, X., Chen, Z., Pan, X., Gan, J., Zheng, Y., Simultaneous determination of organophosphorus pesticides in fruits and vegetables using atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry, Food Chemistry (2017), doi: http://dx.doi.org/ 10.1016/j.foodchem.2017.03.157

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Simultaneous determination of organophosphorus pesticides in fruits and vegetables

using

atmospheric

pressure

gas

chromatography

quadrupole-time-of-flight mass spectrometry Zhipeng Cheng , Fengshou Dong ab*, Jun Xu , Xingang Liu , Xiaohu Wu , Zenglong Chen , a

a

a

b

a

a

a

a

Xinglu Pan , Jay Gan , Yongquan Zheng

a

State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of

Plant Protection, Chinese Academy of Agricultural Sciences, Beijing, 100193, P. R. China b

Department of Environmental Science, University of California, Riverside, CA,

925521, USA

Abbreviations: APGC-QTOF-MS, Atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry; OPPs, organophosphorus pesticides; C18, octadecylsilane; PSA, primary secondary amine; GCB, graphitized carbon black; ME, matrix effects; SSE, signal suppression/enhancement;

Corresponding Author Tel:+86-10-62815938;

fax:+86-10-62815938.

[email protected] (F. Dong).

1

E-mail

address:

ABSTRACT This paper describes the application of atmospheric pressure gas chromatography quadrupole-time-of-flight mass spectrometry for the simultaneous determination of organophosphorus pesticides in apple, pear, tomato, cucumber and cabbage. Soft ionization with APGC source was compared with traditional electron impact ionization (EI). The sensitivity of APGC for all the analytes was enhanced by 1.0-8.2 times. The ionization modes with APGC source was studied by comparing the charge-transfer and proton-transfer conditions. The optimized QuEChERs method was used to pretreat the samples. The calibration curves were found linear from 10-1000 µg/L, obtaining correlation coefficients higher than 0.9845. Satisfactory mean recovery values, in the range of 70.0-115.9%, and satisfactory precision, with all RSDr <19.7% and all RSDR values <19.5% at the three fortified concentration levels for all the fifteen OPPs. The results demonstrate the potential of APGC-QTOF-MS for routine quantitative analysis of organophosphorus pesticide in fruits and vegetables.

KEYWORDS: organophosphorus pesticides, APGC-QTOF-MS, soft ionization, fruits, vegetables

2

1. INTRODUCTION To increase the productivity of the harvest, organophosphorus pesticides (OPPs) have been widely used in fruits and vegetables to control pests. This often results in the presence of trace pesticide residue in fruits and vegetables, which are harmful to human health because of their potential mutagenicity properties (Karalliedde, Wheeler, Maclehose, & Murray, 2000; Wang, Qiao, Ma, Zhao, & Xu, 2013; L. Wu, Song, Hu, Zhang, Yu, Yu, et al., 2015). Therefore, there is an increasing demand to develop an accurate and sensitive analytical method for simultaneous determination of trace levels of OPPs to facilitate the risk assessment. Due to the low concentration of the analytes and the complex matrix of the samples, a preliminary sample preconcentration and separation technique are required. Thus, different extraction and cleanup processes for pesticides analysis such as solid phase extraction method (SPE) (Yang, Luo, Li, & Liu, 2016), dynamic microwave-assisted extraction (DMAE) (Lijie Wu, Hu, Li, Song, Yu, Zhang, et al., 2016), optimized QuEChERS (quick, easy, cheap, effective, rugged and safe) extraction method (Rizzetti, Kemmerich, Martins, Prestes, Adaime, & Zanella, 2016; Zhao, Hu, Wang, Zhao, & Yang, 2015) have been used for preparation in fruits and vegetables. The outstanding QuEChERS method have been widely used for monitoring pesticides (Jia, Wang, Wang, Yin, Liu, & Liu, 2012; Kretschmann, Cedergreen, & Christensen, 2016; Wei, Tao, Chen, Xie, Pan, Liu, et al., 2015; Zhong, Wang, Dong, & Hu, 2015), synthetic musk (Saraiva, Cavalheiro, Lanceleur, & Monperrus, 2016), veterinary drug (Leon, Pastor, & Yusa, 2016; Martínez-Domínguez, Romero-González, & Frenich, 2016; Stubbings & Bigwood, 2009; Wei, et al., 2015; Zhang, Liu, Li, Zhang, 3

Cao, Su, et al., 2016), and organic contaminants (Baduel, Mueller, Tsai, & Ramos, 2015; Chatterjee, Utture, Banerjee, Shabeer, Kamble, Mathew, et al., 2016; Morrison, Sieve, Ratajczak, Bringolf, & Belden, 2016; Vavrouš, Vápenka, Sosnovcová, Kejlová, Vrbík, & Jírová, 2016). After sample preparation, the determination of OPPs in different sample matrices was usually carried out by using gas chromatography mass spectrometry (GC-MS) (B. Chen, Wu, Wu, Jin, Xie, Feng, et al., 2016; Shamsipur, Yazdanfar, & Ghambarian, 2016), gas chromatography flame photometric

detector (GC-FPD) (Du,

Ren,

& Beckett,

2004)

and

gas

chromatography coupled to electron capture (GC-ECD) (Jardim, Mello, Goes, Frota, & Caldas, 2014). However, determination of pesticide residues by these techniques which often leads to false positives can be complicated by the interference of matrix components co-eluted with the analytes of interest and the unwanted matrix effect obtained by these techniques typically causes a loss of accuracy and sensitivity. Atmospheric pressure gas chromatography (APGC) is a soft ionization technique which generates high relative and absolute abundance molecular ions and protonated molecules resulting in less fragmentation of the analytes than conventional electron ionization (EI), thus, enhancing sensitivity and selectivity (Cheng, Dong, Xu, Liu, Wu, Chen, et al., 2016; Hernando, Agüera, Fernández-Alba, Piedra, & Contreras, 2001; Sales, Portoles, Sancho, Abad, Abalos, Saulo, et al., 2016). The technique can produce highly abundant precursor ions that can reduce matrix interferences effectively. The molecular ion, protonated molecular ion or mixed ions are usually present under charge-transfer or proton-transfer conditions. The capability of APGC

4

has been demonstrated in some fields including food analysis (Organtini, Haimovici, Jobst, Reiner, Ladak, Stevens, et al., 2015) and environmental pollutants (Domeno, Canellas, Alfaro, Rodriguez-Lafuente, & Nerin, 2012; Organtini, et al., 2015; van Bavel, Geng, Cherta, Nácher-Mestre, Portolés, Ábalos, et al., 2015). However, there are few performance evaluation reports for determination of OPPs by using APGC-QTOF-MS (Pintado-Herrera, González-Mazo, & Lara-Martín, 2014). Therefore, it is necessary to make more effort to dig the potential characteristic of APGC for the simultaneous determination of OPPs in fruits and vegetables. The main objective of this study was to evaluate the performance of APGC-QTOF-MS by comparing the difference between EI and APGC ionization mode and to evaluate sample preparation based on QuEChERS method. An efficient and effective method for the simultaneous determination of fifteen frequently-used OPPs in fruits and vegetables using APGC-QTOF-MS was developed and the fitness of the method was validated by the analysis of some authentic environmental samples for pesticides residues. 2. MATERIALS AND METHODS

2.1. Chemicals and Reagents Standard solutions of parathion (100 mg/L), phosphoric acid (100 mg/L), parathion-methyl (100 mg/L), fenthion (100 mg/L), triazophos (100 mg/L), diazinon (100 mg/L), dimethoate (100 mg/L), pirimiphos-methyl (100 mg/L), fenitrothion (100 mg/L), malathion (100 mg/L), phosalone (100 mg/L), quinalphos (100 mg/L), chlorpyrifos (100 mg/L), tolclofos-methyl (100 mg/L) were obtained from

5

Agro-Environment Protection Institute, Ministry of Agriculture (Beijing, China). Analytical grade acetone for pesticide residue analysis was purchased from Sinopharm Chemical Reagent Co., Ltd (Beijing, China), acetonitrile for extraction of pesticides was obtained from Beijing chemical works (Beijing, China). Anhydrous magnesium sulfate (MgSO4) was purchased from Xilong Chemical Co., Ltd (Beijing, China) and sodium chloride (NaCl) was obtained from Sinopharm Chemical Reagent Co., Ltd (Beijing, China). Chromatography grade hexane was obtained from Thermo Fisher Scientific Corporation (Shanghai, China). Ultra-pure water was collected from a Milli-Q system (Bedford, MA, USA). Bondesil octadecylsilane (C18, 40 µm), primary secondary amine (PSA, 40 µm) and graphitized carbon black (GCB, 40 µm) sorbents were purchased from Bonna-Agela Technologies (Tianjin, China). Nylon syringe filters (0.22 µm; Tengda, Tianjin, China) were used to filter the concentrated extracts. 2.2. APGC-QTOF-MS Instrumentation All measurements of the fifteen OPPs were performed by an Agilent 7890A GC system (Agilent Technologies, Santa Clara, CA) equipped with a 7693 autosampler (CTC Analytics, Zwingen, Switzerland) coupled to a Q-TOF (Xevo G2-S, Waters Corporation, Manchester, UK), combined with a

APGC source. A HP-5MS (Agilent

Technologies) analytical column of 30 m × 0.250 mm inner diameter and 0.25 µm of film thickness was used. The GC oven temperature program for the gas chromatography was as follows: initial temperature of 80 ℃ held for 1 min, ramped at 20 ℃ min-1 to 200 ℃ and held for 1 min, then increased ramp by 10 ℃ min-1

6

to 300 ℃ and held for 2 min, resulting in a total run time of 20 min. Helium (purity>99.999%) was used as carrier gas at 1.5 ml/min. API positive polarity and sensitivity mode were selected for MS ionization. The Xevo G2-S QTOF was operated at a scan time of 0.2 s and the mass range was considered as m/z 50-650. For mass spectrometry (MSE, where E represents collision energy which involves the rapid alternation between two conditions of energy), two acquisition functions were used in applying different collision energies: a low energy (6 eV) function and a high energy function which in the case of a collision energy ramp (20 to 40 eV), thus providing the accurate mass of precursor ion, in addition to accurate mass fragment ions for further confirmatory purposes. The corona voltage was 2.2 KV, the cone gas was set at 150 l/h and an ion source of 100 ℃. Perfluorotributylamine (PFTBA) was utilized for daily MS calibration. The instrument was operated at proton-transfer conditions that adding water into the ionization source as a modifier. The oven temperature program and analytical column of GC analysis are the same with the APGC-QTOF-MS analysis. Splitless injections of 1 µL sample were carried out at 280 ℃. 2.3. Recommended Sample Treatment The extraction procedure was carried out following the QuEChERS method. Approximately, 500 g of the sample matrices (apple, pear, tomato, cucumber and cabbage) were chopped and homogenized before the preliminary test. 10 g of the thoroughly homogenized samples were weighed into a 50 mL polypropylene centrifuge tube with a screw cap and 10 mL acetonitrile were added to the tube. The

7

tube was shaken vigorously for 10 min with a vortex mixer. Next, a total of 1 g of NaCl and 4 g of anhydrous MgSO4 were added and shaken vigorously for 5 min. The tubes were centrifuged for 5 min at a relative centrifugal force (RCF) of 2811 × g, then 1.5 mL upper layer solvent was transferred into a 2 ml centrifuge tube which contained an amount of cleaning agent containing 80 mg C18 and 150 mg MgSO4 for apple and cucumber samples, 40 mg PSA and 150 mg MgSO4 for pear and tomato samples, 40 mg C18 and 150 mg MgSO4 for cabbage samples. Then 2 mL centrifuge tubes were vortexed for 1 min and centrifuged for 5 min at RCF 2400 × g. Then 900 µL the upper layer solvent was transferred into a 5 mL tube and nitrogen blow to dryness by using sample concentrator. The analytes were redissolved in 900 µL hexane and filtered using a 0.22 µm Nylon syringe for APGC-QTOF-MS injection. 2.4. Method Validation To evaluate the performance of the validated method, the method was developed in terms of specificity, linearity, limits of detection (LOD), limit of quantification (LOQ) and precision, stability. Standard stock solution (5 mg L-1) of the mixture of the fifteen organophosphorus pesticides was prepared in chromatography grade hexane. Five different sample matrixes with fifteen organophosphorus pesticides of the mixture were spiked at three levels (50, 100 and 500 µg L-1) and analyzed together with control samples. In addition, there was no laboratory contamination in the control samples. The pure solvent calibration standards were used to evaluate the matrix effects (ME). %ME is the %difference in the best-fit slope of the matrix-matched calibration standard vs. the best-fit slope from pure solvent standard

8

(Koesukwiwat, Lehotay, Miao, & Leepipatpiboon, 2010). The matrix-induced signal suppression/enhancement (SSE) was determined by slope ratio of matrix-matched calibration curve/pure solvent calibration curve. The linearity of the method was evaluate by linear regression of standard solution and matrix-matched calibration curves. The matrix-dependent LOQs and LODs of the method were determined by the corresponding chromatogram of the lowest calibration standard used in the matrix-matched calibration. The LODs of fifteen organophosphorus pesticides were confirmed based on the lowest concentration of the spiked levels with a signal-to-noise (S/N) ratio of 3:1, whereas the LOQs of fifteen organophosphorus pesticides were confirmed based on the lowest concentration of the spiked levels with a signal-to-noise (S/N) ratio of 10:1. The accuracy, precision and reproducibility of the method were conducted by the recovery of the five samples and by the relative standard deviations (RSD). The EU SANTE/11945/2015 guidance document stipulates average recovery in the range of 70 – 120% with RSD less or equal 20% per each spiking level as the acceptance criteria for validation of pesticide residue methods. The recovery and reproducibility experiments were carried out for each sample matrix in five replicates (intra-day precision) each at three spiking levels on three different days (inter-day precision). The stability of the method for simultaneous determination of OPPs in fruits and vegetables was determined in the solvent and in the matrices. All the samples used in the stability test were stored at -20 ℃ until use. 3. RESULTS AND DISCUSSION

9

3.1. Optimization of ionization modes with APGC The ionization reaction, depending on the analytes of interest, can occur by two processes: charge-transfer conditions (under dry conditions) and proton-transfer conditions (in the presence of a protic solvent in the source). Molecular ions, protonated molecule or both were provided by the different ionization mechanisms in APGC source (Tania Portolés, Mol, Sancho, & Hernández, 2014). The relative abundance of the analytes for the protonated molecule depends on the ionization conditions, especially the amount of protic solvent in the source. All the analytes were selected to evaluate the behavior of the ionization modes under both ionization conditions. Under proton-transfer conditions, only parathion-methyl, diazinon, pirimiphos-methyl, fenitrothion, phosalone and quinalphos showed an abundant formation of [M+H]+ when using water as a modifier. For other compounds, the M+. ion was observed in the APGC source under the proton-transfer conditions. As an example, quinalphos and tolclofos-methyl were evaluated with APGC ionization modes for the formation of M+. and [M+H]+ (Fig. 1). For quinalphos, it can be clearly seen that both M+. and [M+H]+ were present in the APGC spectrum under charge-transfer and proton-transfer conditions. Obviously, when adding water as a modifier, the formation of [M+H]+ was favored and it finally became the base peak of the APGC spectrum in most cases. Conversely, in the spectrum of tolclofos-methyl, no presence of [M+H]+ was observed in the proton-transfer conditions and M+. showed in both charge-transfer and proton-transfer conditions. For most compounds, higher response values can be obtained under proton-transfer conditions. Thus, the

10

best option to perform the experiment would be to use water as a modifier to facilitate the formation of the protonated molecule. An explanation of this phenomenon was the presence of water or proton donor in the ionization source, which promote the formation of the protonated molecule instead of the molecular ion. Moreover, the proton transfer behavior could be explained because the nitrogen plasma reacts with water or proton donor in the ionization source, and indirectly transfers protons to the analytes (T Portolés, Sancho, Hernández, Newton, & Hancock, 2010). 3.2. Comparison of ionization behavior High relative and absolute abundance molecular ions or protonated molecules ions generated by soft ionization technique resulting in less fragmentation of the analytes. When using GC-EI-MS, the relative abundance of molecular ion was approximately 5%, and the highest mass was m/z=118 (Fig 2A). The molecular ion m/z=298 was fragmented into several fragments. As showed in the spectra of quinalphos with APGC source, no excess fragments were observed. The M+. and [M+H]+ showed the high abundance and the ion [M+H]+ occurred as the base peak (Fig 2B). The different ionization modes for GC-EI-MS and APGC have influence on the sensitivity of the analytes. The sensitivity determined by signal-to-noise ratio increased by approximately 1.8 times. The sensitivity of other compounds increased in the range of 1.0-8.2 times (Fig S1). This phenomenon can be explained that the high absolute abundance of molecular ions generated by the soft ionization of APGC source improved the sensitivity of the analytes to conduct the process of qualitative and quantification analysis. More importantly, the selection of higher abundance

11

molecular fragments with APGC mode always tends to have a more accurate qualitative and quantitative effects except for sensitivity. In the light of obtained results, it is of great value to conduct future work in the search of the abilities of APGC. 3.3. Fragmentation behavior of OPPs For mass spectrometry (MSE), two acquisition functions (function 1 and 2) which were obtained by a collision ramp were applied. MSE involves the rapid alternation between two conditions of energy, thus providing the accurate mass of precursor ion and accurate mass fragment ions for further confirmatory purposes. Low collision energy (function 1) was used to prevent fragmentation and high collision energy (function 2) was benefit to obtain fragments. However, for qualitative purposes, it is beneficial to obtain fragment ions, ideally without compromising the relative abundance of molecular ions or protonated ions (Tania Portolés, Mol, Sancho, & Hernández, 2014). In this way, the full scan data with molecular or protonated ion and fragments were obtained in a single run. The obtained molecular ions and fragments from acquisition functions have a significant impact on the qualitative and quantitative analysis. MassFragment software was useful to suggest probable structures of fragment ions coming from the protonated molecule and to evaluate whether they were in accordance with the compound being evaluated. As an example of diazinon, spectrum of different functions of diazinon was displayed to evaluate the function of MSE and the chromatograms of fragment ions were showed (Fig 3). [M+H]+ ion (m/z 305.2055) was predominantly generated which was acted as an

12

important qualitative and quantification characteristic ion for diazinon in the low energy function. In the high energy function, three new typical fragments (m/z 135.0732, 153.1481, 169.1305) were formed with chromatographic peaks at the same retention time. m/z 169.1305 (C4H10O3PS) and m/z 135.0732 (C8H11N2) were produced from the break-up of C-O bond. m/z 153.1481 (C4H10O2PS) was formed by losing oxygen atom by the break-up of O-P bond (Fig 3). 3.4. Optimization of Clean-up Sorbents To obtain satisfactory cleanup effects for QuEChERS pretreatment, the cleanup effect of different sorbents such as primary secondary amine (PSA), octadecylsilane (C18) and graphitized carbon black (GCB) were investigated for optimizing the pretreatment method. 20 mg C18 + 150 mg MgSO4, 40 mg C18 + 150 mg MgSO4, 80 mg C18 + 150 mg MgSO4, 20 mg PSA + 150 mg MgSO4, 40 mg PSA + 150 mg MgSO4, 80 mg PSA + 150 mg MgSO4, 20 mg GCB + 150 mg MgSO4, 40 mg GCB + 150 mg MgSO4 and 80 mg GCB + 150 mg MgSO4 were respectively used in this study to evaluate the effect on the recovery rate in apple, pear, tomato, cucumber and cabbage samples. To the best of our knowledge, C18 has the ability to extract nonpolar and medium-polar compounds from the polar samples (X. Chen, Xu, Liu, Tao, Pan, Zheng, et al., 2014). PSA has a weak anion exchange function and is applied to remove various polar organic acids, polar pigments, some sugars and fatty acid from non-polar samples. As for GCB, it is mainly used to remove hydrophobic interaction-based compounds (Hu, Liu, Dong, Xu, Li, Xu, et al., 2015). Results show that, without the cleanup by C18, PSA and GCB, the extracted sample color were

13

deeper than that with sorbent. As shown in Fig. 4, the recovery and RSD were both satisfactory when the 80 mg C18 + 150 mg MgSO4 sorbent was used in apple and cucumber matrix and 40 mg PSA + 150 mg MgSO4 sorbent was used in pear and tomato matrix and 40 mg C18 + 150 mg MgSO4 was used to clean up the cabbage samples. 3.5. Method Validation 3.5.1. LODs, LOQs and linearity The linearity of the method was evaluated by the different calibration curves (apple, pear, tomato, cucumber and cabbage) with the concentration ranging from 10 to 1000 µg/L (10, 50, 100, 200, 500 and 1000 µg/L). The calibration curves with good linearity and the coefficients of correlation (R2) of all the standard curves and matrix-matched curves are summarized (Table 1). Excellent linearities were observed for all the OPPs (R2 ≥ 0.9845 in all cases). The estimated LODs of the fifteen OPPs were between 0.13 and 7.1 µg/kg, and the LOQs were between 0.43 and 23.66 µg/kg. 3.5.2. Accuracy and stability. A spiked recovery assay was conducted to evaluate the performance of the method. The precision of the method was determined by the repeatability (RSDr) and reproducibility (RSDR). The RSDr was obtained by analyzing the spiked samples for the same day and the RSDR for three distinct days. Satisfactory mean recovery values, in the range of 70.0-115.9%, and satisfactory precision, with all RSDr <19.5% and all RSDR values <19.7% at the three fortified concentration levels for all the fifteen OPPs

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(Table S1). 3.6. Application to real samples The real samples was analyzed to evaluate the effectiveness and applicability of the proposed method for measuring trace levels of OPPs. The applicability of the proposed method was also assessed for the analysis of 30 real samples including 6 apples, 6 pears, 6 tomatoes, 6 cucumbers and 6 cabbages from the market in Beijing (China), the concentration of all the compounds were below the LOD.4. Conclusions This work presents the evaluation and excellent performance of GC-QTOF-MS with APGC soft ionization source for the simultaneous determination of fifteen organophosphorus pesticides in apple, pear, tomato, cucumber and cabbage. The soft ionization is beneficial for generating molecular ions or protonated molecular ion with different ionization modes and high resolution QTOF-MS offers accurate mass and fragment ions in a high performance method for the analysis of OPPs. Comparing with GC-EI-MS, the sensitivity of the method is improved (1.0-8.2 times) when using APGC-QTOF-MS. With proton-transfer conditions, parathion-methyl, diazinon, pirimiphos-methyl, fenitrothion, phosalone and quinalphos showed an abundant formation of [M+H]+ when using water as a modifier. For parathion, phosphoric acid 1, phosphoric acid 2, fenthion, triazophos, dimethoate, malathion, chlorpyrifos and tolclofos-methyl, the M+. ion was observed in the APGC source under the proton-transfer conditions. The estimated LODs of the fifteen OPPs were between 0.13 and 7.1 µg/kg and mean recovery values were in the range of 70.0-115.9%. This study not only presents the benefits of APGC-QTOF-MS but also provides an

15

effective method for the simultaneous determination and screening of target OPPs in fruits and vegetables. Further application and evaluation of APGC-QTOF-MS need to be investigated for the screening of environment and food samples. Notes The authors declare no competing financial interest. ACKNOWLEDGEMENTS This work was financially supported by the National Natural Science Foundation of China (31471798).

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Vavrouš, A., Vápenka, L., Sosnovcová, J., Kejlová, K., Vrbík, K., & Jírová, D. (2016). Method for analysis of 68 organic contaminants in food contact paper using gas and liquid chromatography coupled with tandem mass spectrometry. Food Control, 60, 221-229. Wang, X., Qiao, X., Ma, Y., Zhao, T., & Xu, Z. (2013). Simultaneous determination of nine trace organophosphorous pesticide residues in fruit samples using molecularly imprinted matrix solid-phase dispersion followed by gas chromatography. Journal of Agricultural and Food Chemistry, 61(16), 3821-3827. Wei, H., Tao, Y., Chen, D., Xie, S., Pan, Y., Liu, Z., Huang, L., & Yuan, Z. (2015). Development and validation of a multi-residue screening method for veterinary drugs, their metabolites and pesticides in meat using liquid chromatography-tandem mass spectrometry. Food Additives & Contaminants: Part A, 32(5), 686-701. Wu, L., Hu, M., Li, Z., Song, Y., Yu, C., Zhang, H., Yu, A., Ma, Q., & Wang, Z. (2016). Dynamic microwave-assisted extraction combined with continuous-flow microextraction for determination of pesticides in vegetables. Food chemistry, 192, 596-602. Wu, L., Song, Y., Hu, M., Zhang, H., Yu, A., Yu, C., Ma, Q., & Wang, Z. (2015). Application of magnetic solvent bar liquid-phase microextraction for determination of organophosphorus pesticides in fruit juice samples by gas chromatography mass spectrometry. Food Chemistry, 176, 197-204. Yang, X., Luo, J., Li, S., & Liu, C. (2016). Evaluation of nine pesticide residues in three minor tropical fruits from southern China. Food Control, 60, 677-682. Zhang, Y., Liu, X., Li, X., Zhang, J., Cao, Y., Su, M., Shi, Z., & Sun, H. (2016). Rapid screening and quantification of multi-class multi-residue veterinary drugs in royal jelly by ultra performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Food Control, 60, 667-676. Zhao, F., Hu, C., Wang, H., Zhao, L., & Yang, Z. (2015). Development of a MAb-based immunoassay for the simultaneous determination of O, O-diethyl and O, O-dimethyl organophosphorus pesticides in vegetable and fruit samples pretreated with QuEChERS. Analytical and bioanalytical chemistry, 407(30), 8959-8970. Zhong, M., Wang, T., Dong, B., & Hu, J. (2015). QuEChERS-based study on residue determination and dissipation of three herbicides in corn fields using HPLC-MS/MS. Toxicological and Environmental Chemistry, 1-10.

Figures caption Fig 1. Full scan spectra obtained under charge-transfer conditions (a1, b1) and proton-transfer conditions (a2, b2) for quinalphos and tolclofos-methyl. Fig 2. Extracted ion chromatograms and mass spectra of quinalphos using GC-EI-MS (A) and APGC-QTOF-MS (B). Fig 3. Accurate mass spectrum and chemical structures proposed for the most abundant fragment 19

ions (left) and APGC-QTOF-MS extracted-ion chromatograms (right) for diazinon. Fig 4. Purification effect of different sorbents and different amount (20 mg C18, 40 mg C18, 80 mg C18, 20 mg PSA, 40 mg PSA, 80mg PSA, 20 mg GCB, 40 mg GCB, 80 mg GCB) on the pesticides in apple, pear, cucumber, tomato and cabbage samples at the concentrations of 50 µg/kg (n=5).

20

Table 1. Retention time (min), accurate mass (Da), characteristic fragment ions, matrix-matched calibration and solvent calibration curve (0.01-1 mg/L), coefficients (r2), slope ratio (matrix/hexane) and sensitivity of fifteen OPPs. compounds

Rt (min)

Accurate mass (Da)

m/z 1

m/z 2

m/z 3

Matrix

Calibration curve

r2

Slope ratio

(matrix/

hexane) parathion

phosphoric acid 1

phosphoric acid 2

parathion-methyl

10.53

8.88

9.49

9.67

292.1094

300.1465

300.1465

264.0741

236.0327

174.1071

174.1071

155.0053

123.0590

132.0864

132.0864

127.0429

94.0621

127.0436

127.0436

109.0291

LOD

LOQ

(µg/kg)

(µg/kg)

Hexane

y=100.11x+2470.9

0.9858

--

--

--

Apple

y = 49.5x + 509.06

0.9997

0.49

0.27

0.90

Pear

y = 47.95x - 224.06

0.9982

0.48

0.33

1.10

Tomato

y = 48.475x + 437.41

0.9993

0.48

0.24

0.80

Cucumber

y = 56.469x + 1036.9

0.9990

0.56

0.25

0.83

Cabbage

y = 47.24x + 380.21

0.9993

0.47

0.36

1.20

Hexane

y=12.866x-77.37

0.9995

--

--

--

Apple

y = 4.6791x - 26.262

0.9988

0.36

5.3

17.66

Pear

y = 4.4019x + 6.9786

0.9980

0.34

4.2

14.00

Tomato

y = 5.019x - 34.232

0.9991

0.39

4.5

15.00

Cucumber

y = 5.5444x - 14.117

0.9958

0.43

6.0

20.00

Cabbage

y = 3.9587x + 46.585

0.9989

0.31

7.1

23.66

Hexane

y=44.785x-313.75

0.9992

--

--

--

Apple

y = 14.532x + 38.305

0.9992

0.32

0.52

1.73

Pear

y = 13.928x - 17.414

0.9990

0.31

0.98

3.27

Tomato

y = 16.599x - 143.56

0.9944

0.37

2.59

8.63

Cucumber

y = 18.617x + 205.74

0.9990

0.42

3.75

12.50

Cabbage

y = 13.139x + 211.09

0.9996

0.29

2.34

7.80

Hexane

y=46.329x+379.61

0.9995

--

--

--

Apple

y = 13.167x + 164.09

0.9994

0.28

3.19

10.63

Pear

y = 13.535x - 101.05

0.9969

0.29

2.45

8.17

Tomato

y = 15.812x + 11.618

0.9994

0.34

1.11

3.70

fenthion

triazophos

diazinon

dimethoate

10.47

13.27

9.05

8.31

278.0824

314.1407

305.2055

230.0560

169.0480

162.0998

169.1305

125.0077

127.0411

105.0908

119.0864

153.1481

143.0223

135.0732

Cucumber

y = 19.332x - 149.35

0.9992

0.42

1.74

5.80

Cabbage

y = 12.622x + 59.223

0.9953

0.27

1.94

6.47

Hexane

y=93.229x+2574.2

0.9980

--

--

--

Apple

y = 9.5955x + 35.221

0.9999

0.10

4.54

15.13

Pear

y = 10.038x - 127.37

0.9981

0.11

3.66

12.20

Tomato

y = 9.4575x - 7.3207

0.9997

0.10

4.54

15.13

Cucumber

y = 10.989x + 77.132

0.9985

0.12

4.69

15.63

Cabbage

y = 9.2291x + 26.469

0.9981

0.10

5.00

16.67

Hexane

y=120.44x-547.26

0.9999

--

--

--

Apple

y = 46.326x - 102.34

0.9974

0.38

1.12

3.73

Pear

y = 44.21x - 411.07

0.9929

0.37

1.78

5.93

Tomato

y = 52.595x - 493.9

0.9947

0.44

0.71

2.37

Cucumber

y = 60.17x - 23.292

0.9969

0.50

2.20

7.33

Cabbage

y = 44.232x + 680.34

0.9937

0.37

1.58

5.27

Hexane

y=137.94x+2356.7

0.9952

--

--

--

Apple

y = 73.043x + 810

0.9990

0.53

0.19

0.63

Pear

y = 64.083x + 1693.1

0.9958

0.46

0.23

0.77

Tomato

y = 74.95x + 504.1

0.9999

0.54

0.20

0.67

Cucumber

y = 84.314x + 1297.9

0.9984

0.61

0.26

0.87

Cabbage

y = 70.841x + 1047.6

0.9987

0.51

0.13

0.43

Hexane

y=8.5431x+76.807

0.9993

--

--

--

Apple

y = 2.8406x - 56.776

0.9986

0.33

3.85

12.83

Pear

y = 2.9682x - 96.932

0.9845

0.35

4.42

14.73

Tomato

y = 3.0777x - 86.194

0.9969

0.36

3.95

13.17

Cucumber

y = 3.7908x - 19.89

0.9984

0.44

4.69

15.63

y = 2.5739x + 30.063

0.9973

0.30

4.29

14.30

Cabbage

pirimiphos-methyl

fenitrothion

malathion

phosalone

quinalphos

10.14

10.14

10.29

15.25

11.30

306.1742

278.0883

331.1159

368.0758

299.1291

164.1529

127.0419

143.0228

182.0399

163.0679

125.0081

108.0780

109.0275

125.0082

99.0284

138.0401

147.0872

129.0742

Hexane

y=37.862x-341.46

0.9984

--

--

--

Apple

y = 13.502x + 194.11

0.9992

0.36

0.39

1.30

Pear

y = 13.208x - 120.59

0.9931

0.35

0.81

2.70

Tomato

y = 14.827x + 14.716

0.9993

0.39

1.33

4.43

Cucumber

y = 15.898x + 214.01

0.9967

0.42

1.19

3.97

Cabbage

y = 13.097x + 3.2585

0.9992

0.35

0.96

3.20

Hexane

y=47.238x-301.68

0.9996

--

--

--

Apple

y = 14.91x + 110.53

0.9987

0.32

1.63

5.43

Pear

y = 14.732x - 171.91

0.9909

0.31

1.39

4.63

Tomato

y = 16.54x - 0.5495

0.9993

0.35

2.14

7.13

Cucumber

y = 18.254x + 175.57

0.9964

0.39

3.66

12.20

Cabbage

y = 14.789x - 25.796

0.9965

0.31

2.50

8.33

Hexane

y=8.2911x-54.525

0.9999

--

--

--

Apple

y = 3.4522x + 81.744

0.9996

0.42

3.85

12.83

Pear

y = 3.0265x + 127.61

0.9963

0.36

4.16

13.87

Tomato

y = 3.6874x + 43.659

0.9992

0.44

3.57

11.90

Cucumber

y = 4.3012x + 60.263

0.9964

0.52

4.55

15.17

Cabbage

y = 3.5817x + 60.174

0.9972

0.43

5.00

16.67

Hexane

y=10.595x-276.89

0.9982

--

--

--

Apple

y = 3.4888x + 8.858

0.9974

0.33

3.49

11.63

Pear

y = 3.3534x - 15.742

0.9962

0.32

4.29

14.30

Tomato

y = 4.3281x - 63.797

0.9972

0.41

4.05

13.50

Cucumber

y = 4.7715x - 43.266

0.9931

0.45

4.05

13.50

Cabbage

y = 3.3059x - 16.397

0.9977

0.31

3.19

10.63

Hexane

y=28.358x-141.19

0.9995

--

--

--

Apple

y = 9.9568x + 141.14

0.9961

0.35

3.75

12.50

chlorpyrifos

tolclofos-methyl

10.51

9.76

352.0096

301.0304

257.9519

250.0178

165.9642

175.0098

138.9471

125.0090

Pear

y = 8.8735x + 91.41

0.9997

0.31

5.17

17.23

Tomato

y = 11.595x - 97.706

0.9938

0.41

3.33

11.10

Cucumber

y = 13.022x + 67.057

0.9982

0.46

2.59

8.63

Cabbage

y = 9.1917x + 118.55

0.9987

0.32

4.29

14.30

Hexane

y=9.1124x+33.362

0.9994

--

--

--

Apple

y = 4.2262x + 84.695

0.9978

0.46

2.05

6.83

Pear

y = 3.592x + 33.646

0.9998

0.39

1.92

6.40

Tomato

y = 3.8919x + 63.494

0.9987

0.43

1.39

4.63

Cucumber

y = 4.7101x + 85.258

0.9981

0.52

1.18

3.93

Cabbage

y = 3.7554x + 17.494

0.9973

0.41

1.42

4.73

Hexane

y=16.736x-47.63

0.9998

--

--

--

Apple

y = 5.4595x + 184.59

0.9975

0.33

5.55

18.50

Pear

y = 5.6893x - 25.928

0.9986

0.34

4.28

14.27

Tomato

y = 6.3665x + 26.707

0.9999

0.38

3.00

10.00

Cucumber

y = 7.5902x + 70.94

0.9955

0.45

3.95

13.17

Cabbage

y = 5.3678x + 216.61

0.9899

0.32

4.69

15.63