Application of magnet ionic liquid-based dispersive liquid phase microextraction coupled with HPLC rapid determination three pyrethroid insecticides in food samples

Application of magnet ionic liquid-based dispersive liquid phase microextraction coupled with HPLC rapid determination three pyrethroid insecticides in food samples | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Application of magnet ionic liquid-based dispersive liquid phase microextraction coupled with HPLC rapid determination three pyrethroid insecticides in food samples Lingling Wang, Xiaoxia Chen, Xueying Han, Baozhao Ju This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1833445/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract A simple, green, rapid and efficient magnet ionic liquid (MIL) dispersive liquid–liquid microextraction (DLLME) method coupled with HPLC was successfully developed for determination of three trace pyrethroids (Fenvalerate, beta-cypermethrin and bifenthrin) from water and food sample. The MIL of tri-hexyl-tetradecyl-phosphonium tetra-chlorocobalt (II) [P 6,6,6,14 + ] 2 [CoCl 4 2- ] was explored as the extraction solvent due to its magnetic susceptibility, low UV absorbance and difficult to hydrolyze in aqueous as well as the highest extraction capacity. Important influence factors of extraction efficiency such as the amount of MIL, the pH, ionic strength were optimized. The spiked recoveries of three targets in food samples were in the range of 96.3-103.8%. The limits of detection ranged from 0.75-1.75 ng mL −1 . The results indicated that the developed MIL-DLLME method based on [P 6,6,6,14 + ] 2 [CoCl 4 2- ] as the extraction solution has the advantages of rapid and high efficiency, and can be successfully applied to detect three pyrethroids in real food samples Dispersive liquid-liquid microextraction Magnet ionic liquid Pyrethroids High performance liquid chromatography Figures Figure 1 Figure 2 Figure 3 1. Introduction Pyrethroid insecticides, such as fenvalerate, beta-cypermethrin and bifenthrin are widely used pre-and post-harvest insecticides for fruit, vegetables and agricultural products for the control of pests and diseases(Galadima, et al., 2021 ).They are either sprayed directly on food surfaces or over farmland. Therefore, they persist in food, water and soil after their application(Ccanccapa-Cartagena, Masiá, & Picó, 2017 ; Guo, et al., 2021 ; Xu, Liu, & Yang, 2018 ; Zhu, et al., 2019 ). Pyrethroid insecticides are extensive concerned around the world for their potential health risk of human and aquatic organisms due to their significant neurotoxicity and widespread presenc(Dabrowski, Shadung, & Wepener, 2014 ; Lifeng, et al., 2006 ). Consuming pyrethroids by human brings a series of symptoms as nausea, shakiness, headache, abnormal heartbeat, and vision impairment(Martínez, et al., 2019 ; C. Wang, Chen, Zhang, & Fang, 2009 ). Aquatic organisms of exposing pyrethroids cause motor activity impairment, paralysis and subsequent death(Moraes, Venturini, Cortella, & Rossi, 2013 ; Priya, 2020 ). Therefore, the development of a simple, rapid, and sensitive method for determination of pyrethroid insecticides from food sample is of great importance. However, pyrethroid insecticides are usually present in low concentrations and complex matrices in the vegetables and fruits samples, so sample pretreatment is one of the most important parts of the whole process of analysis. The effective methods for pesticide residues concentration and cleanup extraction techniques prior to determination are often required. Recently, ionic liquids dispersive liquid-liquid micro-extraction (IL-DLLME) has been widely used in analyzing of pyrethroid insecticides because of its simplified, rapid and eco-friendly preconcentration(Abdulra’uf, Lawal, Sirhan, & Tan, 2020 ; Han, Tang, & Row, 2014 ; Hu, et al., 2016 ; Liao, et al., 2019 ). In the IL-DLLME system, ionic liquids (ILs) have been applied as extraction solvents(Kissoudi & Samanidou, 2018 ). The most common way to achieve IL phase separation from the aqueous media is centrifugation, which is time-consuming and tedious (Abdulra’uf, et al., 2020 ).To further simplify the cumbrous centrifugation step and shorten exaction time in phase separation, magnetic ionic liquids (MILs) have been proposed and reported in 2004 by Hayashi (Hayashi & Hamaguchi, 2004 ). MILs are a subclass of ILs that inherit all advantages of ILs. By designing of the MIL structure has yielded magnet active compounds with unique physicochemical properties including high magnetic moments, enhanced hydrophobicity, and the ability to solvate a broad range of molecules(Clark, Nacham, Purslow, Pierson, & Anderson, 2016 ; Yao, et al., 2022 ). Up to date, a few hydrophobic MIL comprised of cation of anion of [FeCl 4 − ],[FeCl 3 Br − ], [MnCl 4 2− ] and [CoCl 4 2− ] have been reported to be used as extraction solvents for trace organic contaminant(Chatzimitakos, Anderson, & Stalikas, 2018 ; Merib, Spudeit, Corazza, Carasek, & Anderson, 2018 ; Trujillo-Rodríguez, et al., 2019 ). Contrasting to several other MIL, the [P 6,6,6,14 + ][CoCl 4 2− ] MIL exhibit many advantages, such as high hydrophobicity, excellent extraction capacity, low UV absorbance, obvious colour and difficult hydrolysis in aqueous media. It has been successfully used in DLLME as extraction solvents for the preconcentration of DNA, biogenic amines and estrogens(Cao, Xu, Xue, Feng, & Zhang, 2019 ; Clark, Yamsek, Nacham, & Anderson, 2015 ; Feng, Xu, Liu, Xue, & Zhang, 2020 ). However, the [P 6,6,6,14 + ][CoCl 4 2− ] MIL has not been comprehensively investigated and applied in other determination system of trace organic contaminant. Therefore, further researches on the MIL using in DLLME methods are of great importance for improvements of existing methods. In this paper, hydrophobic [P 6,6,6,14 + ] 2 [CoCl 4 2− ] MIL was synthesized and used as the extraction solvents. A rapid, effective and eco-friendly MIL-DLLME coupled with HPLC-UV analytical method for the rapid extraction and determination of three trace pyrethroids in food sample was developed. Various factors affecting preconcentration of the analytes were discussed in details. The developed method was successful applied to the simultaneous determination of trace levels of fenvalerate, beta-cypermethrin and bifenthrin in water and food samples. 2. Materials And Methods 2.1. Chemicals and reagents Trihexyl (tetradecyl) phosphonium chloride ([P 6,6,6,14 + ][Cl − ]) were purchased from J&K Chemical Ltd (Beijing, China). Cobalt chloride hexahydrate (CoCl 2 ·6H 2 O) were purchased from Macklin Biochemical Co., Ltd. (Shanghai, China). Fenvalerate (98.5%), beta-cypermethrin(98.8%) and bifenthrin(99.1%) standards were purchased from HEOWNS Biochemical technology Co., Ltd. (Tianjin, China). The stock solution containing the analytes was prepared by dissolving appropriate amount of them in methanol and stored at 4 o C under dark conditions. The working solutions were obtained daily by appropriately diluting the stock solution with deionized water. Analytical grade sodium chloride were purchased from Beijing Chemical Co. (Beijing, China). Deionized water used throughout experiments was purified using a Sartorius Arium 611 system (Sartorius, Göttingen, Germany). Chromatographic grade acetonitrile was purchased from Fisher Corporation (Pittsburgh, PA, USA). HPLC-grade deionised water was obtained from a MilliQ water purification system (MilliQ Water; Molsheim, France). 2.2. Apparatus FTIR spectrum was obtained by 850 FT-IR spectrometer (GANGDONG SCI.&TECH.DEVELOPMENT Co.,Tianjin, China) at a scanning range of 4000 − 400 cm − 1 . The UV-Vis spectroscopy was generated in acetonitrile with a U-3010 UV-Vis Spectrophotometer (PERSEE, Beijing, China). A vortex agitator (Reax Control, Heidolph, Germany) was used for the sample treatment. A PHS-3E acidity meter (INESA Scientific Instruments Co., Ltd, Shanghai, China) was used for pH measurement. 2.3. Synthesis and characterization of MIL MIL of [P 6,6,6,14 + ] 2 [CoCl 4 2− ] was synthesized according to previously published references (Santos, Albo, Rosatella, Afonso, & Irabien, 2014 ). CoCl 2 ·6H 2 O (0.5 equiv.) and [P 6,6,6,14 + ][Cl − ] (1.0 equiv.) were added into dichloromethane. The reaction was performed at 30°C for 24 h by stirring, and then the dichloromethane solution was removed by rotary evaporation. Afterward, the obtained product was dried at 50°C for 12h. The synthesized MIL and precursor were characterized by FTIR spectrum, and UV–Vis spectroscopy. 2.3. Sample preparation Lemon, cucumber and mushroom were purchased from local supermarkets. The spiked sample was prepared by spiking the mixed working solution into 50 mL mushroom sample. The resulting solution was referred to as sample solution, filtered through 0.45 µm filters and then stored at 4 o C. 2.4. MIL-DLLME procedure The MIL-DLLME procedure is illustrated in Scheme 1 . In the extraction procedure, a 5.0 mL aliquot of sample solution containing the analytes was placed in a 10 mL screw cap polypropylene centrifuge tube. The extraction solvent (20 mg [P 6,6,6,14 + ] 2 [CoCl 4 2− ] and 5% NaCl was injected rapidly into the sample solution, and mixture solution was shaken using a vortex agitator for 3 min, a cloudy solution consisting of water and [P 6,6,6,14 + ] 2 [CoCl 4 2− ] was quickly formed. The analytes in aqueous phase were extracted into the fine droplets of [P 6,6,6,14 + ] 2 [CoCl 4 2− ]. Then the analyte enriched [P 6,6,6,14 + ] 2 [CoCl 4 2− ] was isolated from the solution with a magnet positioned at the bottom of the polypropylene tube.The upper aqueous phase was removed with a syringe, the MIL phase was dissolved in 250 µL acetonitrile. The solution was transferred into a sample vial, and 20 µL was injected into the HPLC instrument for chromatographic analysis. 2.5. HPLC analysis HPLC analyses were performed with an Agilent 1100 HPLC system with UV detector. Chromatographic separation of target analytes was performed on a BonChrom-C 18 column (150 mm×4.6 mm, 5 µm) (Agela Technologies Inc.) and the injection volume was 20 µL. A mixture of acetonitrile and water (87:13, v/v) at a flow rate of 1.0 mL min − 1 was used as a mobile phase in isocratic elution mode. The column temperature were set 30°C. The detection wavelength was set at 235 nm. 3. Results and discussion 3.1. Characterisation of MIL The FTIR spectra of the synthesized MIL and precursor was shown in Fig. 1(a). It can be seen that the FTIR spectrum of synthesized [P 6,6,6,14 + ] 2 [CoCl 4 2- ] and precursor [P 6,6,6,14 + ][Cl - ] are almost identical, showing MIL and precursor contained the same cationic structure. As shown in Fig. 1(b), [P 6,6,6,14 + ] 2 [CoCl 4 2- ] exhibited low absorption in UV region which made it a better alternative and sensitive for the determination of analytes coupled in HPLC. Besides [P 6,6,6,14 + ] 2 [CoCl 4 2- ] are immiscible in aqueous phase and it can be quite easily manipulated by an external strong magnetic field. 3.2. Optimization of MIL-DLLME conditions To obtain high extraction efficiency, extraction conditions were optimized using spiked samples (100 ng mL -1 ). The experimental parameters affecting the extraction efficiency were carefully investigated, including amount of extraction solvent, the pH and ionic strength of sample solution, the type and volume of dispersant, as well as extraction time and temperature. All experiments were performed in triplicates (n=3). The extraction recovery and enrichment factor (EF) were calculated based on the following equations: C a and C 0 are the concentration of analyte in the extraction phase and the initial analyte concentration in the sample solution, respectively. V a and V 0 are the volumes of extraction phase and sample solution, respectively 3.2.1. Effect of extraction solvent amount The amount of extraction solvent is an important factor that can influence extraction efficiency. In order to evaluate the influence of extraction solvent amounts on extraction efficiencies of tagets, different amounts of [P 6,6,6,14 + ] 2 [CoCl 4 2- ] (10-30 mg) were tested using the same MIL-DLLME procedure. As shown in Fig.2(a), the recoveries of targets increase with the increase of the volume of [P 6,6,6,14 + ] 2 [CoCl 4 2- ] from 10 to 20 mg, but above 20 mg, the recoveries remained a constant level. The amount of extraction solvent can also determine the enrichment performance because lower amounts generally result in high EFs. Therefore, 20 mg of [P 6,6,6,14 + ] 2 [CoCl 4 2- ] was selected in the following studies because a higher recoveries were obtained and the EFs were acceptable. 3.2.2. Effect of extraction time DLLME is a time-dependent process. Consequently, the effect of the extraction time was examined within the range of 1-10 min. Results (Fig.2(b)) showed that the recoveries of targets increased with increased extraction time. The extraction recoveries were in rang of 96.2–98.4% at 3 min. After 3 min, the recoveries of targets were constant. Therefore, the extraction time for this method was set at 3 min. 3.2.3. Effect of pH In general, the pH of sample solution plays an important role in the extraction process because the pH value of the solution determines the present state of analytes. The effects of pH on the extraction were studied within the pH range of 2-10 using hydrochloric acid and sodium hydroxide, and the results are shown in Fig. 2(c). The recoveries of targets remained over 90% in a range of pH 2-6, but the recoveries decreased at a pH > 8.0. In this study, the pH of natural target analytes solution was close to 6.0, thus, the sample solution was used directly without any pH adjustment. Generally, Hydrophobic are important force in the extraction of MIL. These compounds exist as a neutral form in acid and neutral aqueous solutions, and hydrophobicity interaction was enhanced, which was beneficial to extraction and separation. Under the alkaline conditions, these compounds were decomposed, which result in lower recoverier of targets. 3.2.4. Effect of ionic strength In order to investigate the influence of the ionic strength, different concentrations of NaCl (from 0% to 7%) were added to targets solution, respectively. Results (Fig.2(d)) indicate that the recoveries of targets increase slightly with the increase of NaCl concentration in range of 0-5%. Generally, the salt addition can increase extraction efficiency, could be attributed to the fact that the dissolution of sodium chloride in water increased the viscosity of the solution, which reduced the solubility of the targets in aqueous phase, and facilitates the transfer of the targets from the aqueous phase to non-aqueous phase. However, the recoveries of targets decrease slightly when the concentrations of NaCl was 7%. The results, the salt addition decreases extraction efficiency, could be attributed to the fact that the dissolution of sodium chloride in water increased the viscosity of the solution, which reduced the diffusion rates that targets diffused into extraction solvent. Furthermore, the addition of salt enhanced the solubility of MIL in water. According to theses facts, the subsequent experiments were carried out with 5% (w/v) NaCl. 3.3. Interference studies Fruit, vegetable and juice samples contain considerable amounts of organic matter and inorganic ions. In order to assess the possible analytical applications of the proposed method, the effect of concomitant species on the determination of three pyrethroids in real samples was examined under the optimal conditions as described above. The sample solutions containing 100 ng mL -1 of pyrethroids and the added interfering matter were subjected to the proposed method. The tolerance ratio of each interfering matter was taken as the largest amount yielding an error in the determination of the target analytes not exceeding 5% (Table1). Table 1. Effects of interfering matter on determination of 100.0 ng mL -1 of three pyrethroids. Interference Interference to pyrethroids ratio (w/w) Saccharose, glucose, fructose Ascorbic acid 400 600 Na + , K + , Fe 3+ , Mg 2+ , Ca 2+ 1000 SO 4 2- , PO 4 3 - , NO 3 - , HCO 3 - ,CO 3 2 1000 3.5. Method evaluation 3.5.1 Analytical performances A novel MIL-DLLME based on [P 6,6,6,14 + ] 2 [CoCl 4 2- ] coupled with HPLC for the simultaneous determination of three pyrethroids was developed. Under optimal experimental conditions, a series of experiments were performed to obtain linear ranges, precision, the limit of detection (LOD, S/N=3, S/N: signal-to-noise ratio ) and quantification (LOQ, S/N=10). All the experiments were performed in triplicate. As shown in Table.2, good linearities were observed in the range of 10-1000 ng mL -1 with the correlation coefficients (r 2 ) of 0.9986-0.9995 The LOD and the LOQ were found to be 0.75-1.75 ng mL -1 and 2.5-6.0 ng mL -1 , respectively. The proposed method showed good precision with the intra-day and inter-day RSDs in the range of 1.73-2.19% (n=6) and 3.02–3.89% (n=3), respectively. Table 2. Analytical performance for pyrethroids obtained by MIL-DLLME-HPLC-UV. compound Regression equation LOD (ng mL -1 ) LOQ (ng mL -1 ) r 2 EF Beta-cypermethrin(trans) y=1.1242C+0.9308 1.0 3.5 0.9992 20 Beta-cypermethrin(cis) y=0.7017C-0.7918 1.75 6.0 0.9990 20 Fenvalerate y=1.5455C-4.0931 0.9 3.0 0.9986 20 Bifenthrin y=1.5727C+2.2480 0.75 2.5 0.9995 20 In this procedure, the estimation of uncertainty of the final results and traceability is necessary. According to the Guide to the Expression of Uncertainty in Measurement (GUM). The expanded uncertainty of the target compouds analysis is obtained using the formula (Konieczka & Namieśnik, 2010): Where U is expanded uncertainty, k is coverage factor, for which 3 is usually chosen to obtain a confidence level of approximately 95%, c is average concentration of the analyte, ur (sample) is relative standard uncertainty of sample mass determination, ur (cal) is relative standard uncertainty of calibration step, ur (true) is relative standard uncertainty of recovery determination, ur (rep) is relative standard uncertainty of repeatability, ur (LOD) is relative standard uncertainty of LOD determination and c det is the concentration of the target analyte. Where SD xy is the residual standard deviation, b is the direction coefficient of the calibration curve, p is the number of measurements carried out for given sample, n is the total number of standard samples used for plotting the calibration curve, x sample is the concentration of sample, x m is the mean of all the concentration of a standard solution for which the measurement was made in order to plot a standard curve, x i is the concentration of standard solution. The related parameters were listed in Table 3. The uncertainty of the weight and/or volume of a sample are usually small, so ur (sample) is very often neglected during construction ofthe uncertainty budget(Konieczka & Namieśnik, 2010, L. Wang, et al., 2015) . Table.3 Calculated values of relative standard uncertainty and expanded uncertainty (U, k=2) for the determination of fenvalerate, beta-cypermethrin and bifenthrin in mushroom. Compound Concentration (ng mL -1 ) Relative standard uncertainty U u r(sample) u r(cal) u r(true) u r(rep) u r(LOD) (ng mL -1 ) Beta-cypermethrin(trans) 51.91 0.001 0.0026 0.022 0.012 0.019 3.28 Beta-cypermethrin(cis) 48.52 0.001 0.0025 0.021 0.017 0.036 4.38 Fenvalerate 49.93 0.001 0.0023 0.027 0.024 0.018 4.04 Bifenthrin 49.36 0.001 0.0025 0.025 0.025 0.015 3.80 To evaluate the applicability of the present method, food samples were analyzed. It can be seen (Fig.3) that no significant interference peaks were found at the retention positions of target compounds. To evaluate the precision and accuracy of the proposed method, the spiked samples (50.0, 200.0 ng mL -1 ) were analyzed and the analytical results were showed in Table 4. The recoveries of targets obtained from cucumber, mushroom and lemon samples were in the range of 96.3-103.8%. It can be considered that the current method provides acceptable recoveries and precision for the determination of three pyrethroids in real samples. Table 4. Recoveries of three pyreghroids in cu and mushroom samples. Compound Cucumber Mushroom Lemon Spike (ng mL −1 ) Found (ng mL −1 ) Recovery (%) Spike (ng mL −1 ) Found (ng mL −1 ) Recovery (%) Spike (ng mL −1 ) Found (ng mL −1 ) Recovery (%) Beta-cypermethrin 0 n.d. - 0 n.d. - 0 n.d. - (trans) 50.0 51.37±2.92 102.7 50.0 51.91±3.28 103.8 50.0 51.63± 3.44 103.2 200.0 200.2±2.56 100.1 200.0 202.6±2.08 101.3 200.0 201.8±3.07 100.9 Beta-cypermethrin 0 n.d. - 0 n.d. - 0 n.d. - (cis) 50.0 48.91±3.78 97.8 50.0 48.52±4.38 97.0 50.0 48.66±4.17 97.3 200.0 197.4±3.12 98.7 200.0 192.6±2.88 96.3 200.0 195.7±3.38 97.8 Fenvalerate 0 n.d. - 0 n.d. - 0 n.d. - 50.0 48.67±3.45 97.3 50.0 49.93±4.04 98.7 50.0 49.18±4.12 98.4 200.0 197.1±2.87 98.6 200.0 200.8±3.03 100.4 200.0 198.2±3.73 99.1 Bifenthrin 0 n.d. - 0 n.d. - 0 n.d. - 50.0 49.42±3.78 98.8 50.0 49.36±3.80 97.3 50.0 49.38±3.26 98.8 200.0 197.4±1.98 98.7 200.0 198.6±2.65 99.3 200.0 198.1±2.27 99.0 a n.d. = not detected. 4. Conclusions In this paper, a rapid, efficiently and eco-friendly method of MIL-DLLME based as extractant combined with HPLC was successfully applied to the determination of trace amount of three pyrethroids in food sample. MIL of [P 6,6,6,14 + ] 2 [CoCl 4 2− ] is environment friendly and can be rapid separation from aqueous phase in less than 3 min by an external magnetic field. The proposed method not only operation steps can be simplified but also the pretreatment time can be shortened. The methods showed good linearity and precision. The excellent spiked recoveries of analytes in real samples indicated that the proposed method would be a valuable alternative for the analysis of trace amount of pyrethroid insecticides in the future. Declarations Acknowledgements The authors would like to thank their colleagues and other students who participated in this study. Author Contribution Lingling Wang did the laboratory work by MIL-DLLME-HPLC, wrote the draft of this report, reviewed the fnal version of this report, and supplied all fgures and tables. Dr. Xiaoxia Chen and Dr. Xueying Han for sampling and preparation of food samples. Prof. Dr. Baozhao Ju co-initiated the study, is co-inventor of the assay, and evaluated all data. All authors have read and agreed to the published version of the manuscript. Funding This work was supported by the Natural Fund Guidance Plan of Liaoning Province (2019-ZD-0948). Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. Ethics Approval and Consent to Participate This article does not contain any studies with human participants or animals performed by any of the authors. Competing Interests Xiaoxia Chen, Xueying Han and Baozhao Ju declare that they have no confict of interest regarding the publication of this paper. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1833445","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":120025558,"identity":"71c831ac-6888-452d-83c9-345fbbb5a3c3","order_by":0,"name":"Lingling Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYDACduaGAx8qJHjYmBkbHyRU1BChBajy4IwzNjL87MyHDR6cOUaUlubDvG1pNpL9bGmSD1uYCeswOMzYcJjnzGEeg8M8ZhWJDWwM/O3dCQS1HJxTAdFyI3GHDIPEmbMb8GoxA2o58OYMTMsZNgYDiVwitPC2QbQUJLYxE6flIND7PJLNbGkMRGmxB2kBBjIPPzPzYYmEM8d4CPpFsr358AdgVNqz8R9s/PijokaOv70XvxYMwEOa8lEwCkbBKBgFWAEA9OlOamX+4h8AAAAASUVORK5CYII=","orcid":"","institution":"Liaoning University of Traditional Chinese Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Lingling","middleName":"","lastName":"Wang","suffix":""},{"id":120025560,"identity":"617dc484-81e3-4a5d-b7bb-e359f8e9eec7","order_by":1,"name":"Xiaoxia Chen","email":"","orcid":"","institution":"Liaoning University of Traditional Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xiaoxia","middleName":"","lastName":"Chen","suffix":""},{"id":120025561,"identity":"a47bd00d-d706-4e1f-8fe0-dc27e06b626f","order_by":2,"name":"Xueying Han","email":"","orcid":"","institution":"Liaoning University of Traditional Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Xueying","middleName":"","lastName":"Han","suffix":""},{"id":120025563,"identity":"ce3f1a92-0bb0-4772-b2f0-c276d41841ce","order_by":3,"name":"Baozhao Ju","email":"","orcid":"","institution":"Liaoning University of Traditional Chinese Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Baozhao","middleName":"","lastName":"Ju","suffix":""}],"badges":[],"createdAt":"2022-07-07 04:14:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1833445/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1833445/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":23995807,"identity":"10f01484-3759-4d70-9358-d06eff9128ff","added_by":"auto","created_at":"2022-07-18 16:52:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":115122,"visible":true,"origin":"","legend":"\u003cp\u003e(a) FTIR spectra of MIL and precursor. (b) UV–VIS spectrum of MIL.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1833445/v1/85e439aa2cb3827d5eb1fdb8.png"},{"id":23995263,"identity":"0cf20d36-8d0f-4422-9f47-883e28e888b1","added_by":"auto","created_at":"2022-07-18 16:47:27","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":131011,"visible":true,"origin":"","legend":"\u003cp\u003eOptimization of extraction conditions: (a) effect of amount of the MIL on the extraction efficient of three pyrethroids. (b) effect of extraction time on the desorption efficient of three pyrethroids. (c) effect of pH on the extraction efficient of three pyrethroids and (d) effect of ionic strength on the extraction efficient of three pyrethroids.\u0026nbsp;\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1833445/v1/06d9103ab0579632a86c1cba.png"},{"id":23995261,"identity":"b43063b5-afdc-487f-b20c-cb8c24e0239a","added_by":"auto","created_at":"2022-07-18 16:47:27","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":18487,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cspan class=\"ql-cursor\"\u003e\u003c/span\u003eHPLC–UV Chromatograms of the mushroom samples after pretreatment by MIL-DLLME: the blank mushroom sample (a) and the spiked mushroom sample with 50.0 ng mL\u003csup\u003e-1\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1833445/v1/ee8c87d5df7e8b42fee1061a.png"},{"id":25762009,"identity":"84de1027-0399-4866-9077-b6254d3fe989","added_by":"auto","created_at":"2022-08-28 14:59:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":629351,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1833445/v1/e0baddc5-4adc-442a-bc6c-1ac03561185d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Application of magnet ionic liquid-based dispersive liquid phase microextraction coupled with HPLC rapid determination three pyrethroid insecticides in food samples","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003ePyrethroid insecticides, such as fenvalerate, beta-cypermethrin and bifenthrin are widely used pre-and post-harvest insecticides for fruit, vegetables and agricultural products for the control of pests and diseases(Galadima, et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).They are either sprayed directly on food surfaces or over farmland. Therefore, they persist in food, water and soil after their application(Ccanccapa-Cartagena, Masi\u0026aacute;, \u0026amp; Pic\u0026oacute;, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guo, et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Xu, Liu, \u0026amp; Yang, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Zhu, et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Pyrethroid insecticides are extensive concerned around the world for their potential health risk of human and aquatic organisms due to their significant neurotoxicity and widespread presenc(Dabrowski, Shadung, \u0026amp; Wepener, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Lifeng, et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Consuming pyrethroids by human brings a series of symptoms as nausea, shakiness, headache, abnormal heartbeat, and vision impairment(Mart\u0026iacute;nez, et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; C. Wang, Chen, Zhang, \u0026amp; Fang, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Aquatic organisms of exposing pyrethroids cause motor activity impairment, paralysis and subsequent death(Moraes, Venturini, Cortella, \u0026amp; Rossi, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Priya, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, the development of a simple, rapid, and sensitive method for determination of pyrethroid insecticides from food sample is of great importance. However, pyrethroid insecticides are usually present in low concentrations and complex matrices in the vegetables and fruits samples, so sample pretreatment is one of the most important parts of the whole process of analysis.\u003c/p\u003e \u003cp\u003eThe effective methods for pesticide residues concentration and cleanup extraction techniques prior to determination are often required. Recently, ionic liquids dispersive liquid-liquid micro-extraction (IL-DLLME) has been widely used in analyzing of pyrethroid insecticides because of its simplified, rapid and eco-friendly preconcentration(Abdulra\u0026rsquo;uf, Lawal, Sirhan, \u0026amp; Tan, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Han, Tang, \u0026amp; Row, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hu, et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liao, et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). In the IL-DLLME system, ionic liquids (ILs) have been applied as extraction solvents(Kissoudi \u0026amp; Samanidou, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The most common way to achieve IL phase separation from the aqueous media is centrifugation, which is time-consuming and tedious (Abdulra\u0026rsquo;uf, et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).To further simplify the cumbrous centrifugation step and shorten exaction time in phase separation, magnetic ionic liquids (MILs) have been proposed and reported in 2004 by Hayashi (Hayashi \u0026amp; Hamaguchi, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2004\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMILs are a subclass of ILs that inherit all advantages of ILs. By designing of the MIL structure has yielded magnet active compounds with unique physicochemical properties including high magnetic moments, enhanced hydrophobicity, and the ability to solvate a broad range of molecules(Clark, Nacham, Purslow, Pierson, \u0026amp; Anderson, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yao, et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Up to date, a few hydrophobic MIL comprised of cation of anion of [FeCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e],[FeCl\u003csub\u003e3\u003c/sub\u003eBr\u003csup\u003e\u0026minus;\u003c/sup\u003e], [MnCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] and [CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] have been reported to be used as extraction solvents for trace organic contaminant(Chatzimitakos, Anderson, \u0026amp; Stalikas, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Merib, Spudeit, Corazza, Carasek, \u0026amp; Anderson, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Trujillo-Rodr\u0026iacute;guez, et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Contrasting to several other MIL, the [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e][CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] MIL exhibit many advantages, such as high hydrophobicity, excellent extraction capacity, low UV absorbance, obvious colour and difficult hydrolysis in aqueous media. It has been successfully used in DLLME as extraction solvents for the preconcentration of DNA, biogenic amines and estrogens(Cao, Xu, Xue, Feng, \u0026amp; Zhang, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Clark, Yamsek, Nacham, \u0026amp; Anderson, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Feng, Xu, Liu, Xue, \u0026amp; Zhang, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, the [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e][CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] MIL has not been comprehensively investigated and applied in other determination system of trace organic contaminant. Therefore, further researches on the MIL using in DLLME methods are of great importance for improvements of existing methods.\u003c/p\u003e \u003cp\u003eIn this paper, hydrophobic [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] MIL was synthesized and used as the extraction solvents. A rapid, effective and eco-friendly MIL-DLLME coupled with HPLC-UV analytical method for the rapid extraction and determination of three trace pyrethroids in food sample was developed. Various factors affecting preconcentration of the analytes were discussed in details. The developed method was successful applied to the simultaneous determination of trace levels of fenvalerate, beta-cypermethrin and bifenthrin in water and food samples.\u003c/p\u003e"},{"header":"2. Materials And Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Chemicals and reagents\u003c/h2\u003e \u003cp\u003eTrihexyl (tetradecyl) phosphonium chloride ([P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e][Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e]) were purchased from J\u0026amp;K Chemical Ltd (Beijing, China). Cobalt chloride hexahydrate (CoCl\u003csub\u003e2\u003c/sub\u003e\u0026middot;6H\u003csub\u003e2\u003c/sub\u003eO) were purchased from Macklin Biochemical Co., Ltd. (Shanghai, China). Fenvalerate (98.5%), beta-cypermethrin(98.8%) and bifenthrin(99.1%) standards were purchased from HEOWNS Biochemical technology Co., Ltd. (Tianjin, China).\u003c/p\u003e \u003cp\u003eThe stock solution containing the analytes was prepared by dissolving appropriate amount of them in methanol and stored at 4 \u003csup\u003eo\u003c/sup\u003eC under dark conditions. The working solutions were obtained daily by appropriately diluting the stock solution with deionized water. Analytical grade sodium chloride were purchased from Beijing Chemical Co. (Beijing, China). Deionized water used throughout experiments was purified using a Sartorius Arium 611 system (Sartorius, G\u0026ouml;ttingen, Germany). Chromatographic grade acetonitrile was purchased from Fisher Corporation (Pittsburgh, PA, USA). HPLC-grade deionised water was obtained from a MilliQ water purification system (MilliQ Water; Molsheim, France).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Apparatus\u003c/h2\u003e \u003cp\u003eFTIR spectrum was obtained by 850 FT-IR spectrometer (GANGDONG SCI.\u0026amp;TECH.DEVELOPMENT Co.,Tianjin, China) at a scanning range of 4000\u0026thinsp;\u0026minus;\u0026thinsp;400 cm\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e. The UV-Vis spectroscopy was generated in acetonitrile with a U-3010 UV-Vis Spectrophotometer (PERSEE, Beijing, China). A vortex agitator (Reax Control, Heidolph, Germany) was used for the sample treatment. A PHS-3E acidity meter (INESA Scientific Instruments Co., Ltd, Shanghai, China) was used for pH measurement.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Synthesis and characterization of MIL\u003c/h2\u003e \u003cp\u003eMIL of [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] was synthesized according to previously published references (Santos, Albo, Rosatella, Afonso, \u0026amp; Irabien, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). CoCl\u003csub\u003e2\u003c/sub\u003e\u0026middot;6H\u003csub\u003e2\u003c/sub\u003eO (0.5 equiv.) and [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e][Cl\u003csup\u003e\u0026minus;\u003c/sup\u003e ] (1.0 equiv.) were added into dichloromethane. The reaction was performed at 30\u0026deg;C for 24 h by stirring, and then the dichloromethane solution was removed by rotary evaporation. Afterward, the obtained product was dried at 50\u0026deg;C for 12h. The synthesized MIL and precursor were characterized by FTIR spectrum, and UV\u0026ndash;Vis spectroscopy.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Sample preparation\u003c/h2\u003e \u003cp\u003eLemon, cucumber and mushroom were purchased from local supermarkets. The spiked sample was prepared by spiking the mixed working solution into 50 mL mushroom sample. The resulting solution was referred to as sample solution, filtered through 0.45 \u0026micro;m filters and then stored at 4 \u003csup\u003eo\u003c/sup\u003eC.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.4. MIL-DLLME procedure\u003c/h2\u003e \u003cp\u003eThe MIL-DLLME procedure is illustrated in Scheme \u003cspan refid=\"Sch1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In the extraction procedure, a 5.0 mL aliquot of sample solution containing the analytes was placed in a 10 mL screw cap polypropylene centrifuge tube. The extraction solvent (20 mg [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e \u003csup\u003e2\u0026minus;\u003c/sup\u003e] and 5% NaCl was injected rapidly into the sample solution, and mixture solution was shaken using a vortex agitator for 3 min, a cloudy solution consisting of water and [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e \u003csup\u003e2\u0026minus;\u003c/sup\u003e] was quickly formed. The analytes in aqueous phase were extracted into the fine droplets of [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e \u003csup\u003e2\u0026minus;\u003c/sup\u003e]. Then the analyte enriched [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] was isolated from the solution with a magnet positioned at the bottom of the polypropylene tube.The upper aqueous phase was removed with a syringe, the MIL phase was dissolved in 250 \u0026micro;L acetonitrile. The solution was transferred into a sample vial, and 20 \u0026micro;L was injected into the HPLC instrument for chromatographic analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.5. HPLC analysis\u003c/h2\u003e \u003cp\u003eHPLC analyses were performed with an Agilent 1100 HPLC system with UV detector. Chromatographic separation of target analytes was performed on a BonChrom-C\u003csub\u003e18\u003c/sub\u003e column (150 mm\u0026times;4.6 mm, 5 \u0026micro;m) (Agela Technologies Inc.) and the injection volume was 20 \u0026micro;L. A mixture of acetonitrile and water (87:13, v/v) at a flow rate of 1.0 mL min\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e was used as a mobile phase in isocratic elution mode. The column temperature were set 30\u0026deg;C. The detection wavelength was set at 235 nm.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results and discussion","content":"\u003ch2\u003e\u003cem\u003e3.1. Characterisation of MIL\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe FTIR spectra of the synthesized MIL and precursor was shown in Fig. 1(a).\u0026nbsp;It can be seen that the FTIR spectrum of synthesized\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026nbsp;2-\u003c/sup\u003e]\u0026nbsp;and precursor\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e][Cl\u003csup\u003e-\u003c/sup\u003e] are almost identical, showing MIL and precursor contained the same cationic structure. As shown in Fig. 1(b),\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026nbsp;2-\u003c/sup\u003e]\u0026nbsp;exhibited low absorption in UV region which made it a better alternative and sensitive for the determination of analytes coupled in HPLC. Besides\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e\u0026nbsp;2-\u003c/sup\u003e] are immiscible in aqueous phase and it can be quite easily manipulated by an external strong magnetic field.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.2.\u0026nbsp;\u003c/em\u003e\u003cem\u003eOptimization of MIL-DLLME conditions \u0026nbsp;\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTo obtain high extraction efficiency, extraction conditions were optimized using spiked samples (100 ng mL\u003csup\u003e-1\u003c/sup\u003e). The experimental parameters\u0026nbsp;affecting the extraction efficiency were carefully investigated,\u0026nbsp;including\u0026nbsp;amount of extraction solvent,\u0026nbsp;the pH and\u0026nbsp;ionic strength\u0026nbsp;of sample solution, the type and volume of dispersant,\u0026nbsp;as well as extraction time and temperature. All experiments were performed in triplicates (n=3). The extraction recovery and\u0026nbsp;enrichment factor (EF)\u0026nbsp;were calculated based on\u0026nbsp;the following equations:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eC\u003csub\u003ea\u003c/sub\u003e\u0026nbsp;\u003c/em\u003eand \u003cem\u003eC\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e are the concentration of analyte in the extraction phase and the initial analyte concentration in the sample solution, respectively. \u003cem\u003eV\u003csub\u003ea\u003c/sub\u003e\u003c/em\u003e and \u003cem\u003eV\u003csub\u003e0\u003c/sub\u003e\u003c/em\u003e are the volumes of extraction phase and sample solution, respectively\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.2.1.\u003c/em\u003e\u003cem\u003e\u0026nbsp;Effect of\u0026nbsp;\u003c/em\u003e\u003cem\u003eextraction solvent\u003c/em\u003e\u003cem\u003e\u0026nbsp;amount\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe amount of\u0026nbsp;extraction solvent\u0026nbsp;is an important factor that can influence\u0026nbsp;extraction\u0026nbsp;efficiency. In order to evaluate the influence of extraction solvent\u0026nbsp;amounts\u0026nbsp;on\u0026nbsp;extraction\u0026nbsp;efficiencies of\u0026nbsp;tagets,\u0026nbsp;different\u0026nbsp;amounts\u0026nbsp;of\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e]\u0026nbsp;(10-30\u0026nbsp;mg) were tested using the same MIL-DLLME procedure. As shown in\u0026nbsp;Fig.2(a),\u0026nbsp;the recoveries of\u0026nbsp;targets\u0026nbsp;increase with the increase of the volume of\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e]\u0026nbsp;from 10 to 20 mg, but above 20\u0026nbsp;mg, the recoveries remained a constant level. The amount of\u0026nbsp;extraction solvent\u0026nbsp;can also determine the enrichment performance because lower\u0026nbsp;amounts\u0026nbsp;generally result in high EFs.\u0026nbsp;Therefore, 20 mg of\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e] was selected in the following studies because a higher recoveries were obtained and the EFs were acceptable.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.2.2.\u0026nbsp;\u003c/em\u003e\u003cem\u003eEffect of extraction time\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eDLLME is a time-dependent process. Consequently, the effect of the extraction time was examined within the range of 1-10 min.\u0026nbsp;Results (Fig.2(b)) showed that\u0026nbsp;the recoveries of targets increased with increased extraction time. The extraction recoveries were in rang of 96.2\u0026ndash;98.4%\u0026nbsp;at 3 min. After 3 min, the recoveries of targets were constant. Therefore, the extraction time for this method was set at 3 min.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.2.3. Effect of pH\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eIn general, the pH of sample solution plays an important role in the extraction process because the pH value of the solution determines the present state of analytes. The effects of pH on the extraction were studied within the pH range of 2-10 using hydrochloric acid and sodium hydroxide, and the results are shown in Fig. 2(c). The recoveries of targets remained over 90% in a range of pH 2-6, but the recoveries \u0026nbsp;decreased at a pH \u0026gt; 8.0. In this study, the pH of natural target analytes solution was close to 6.0, thus, the sample solution was used directly without any pH adjustment.\u003c/p\u003e\n\u003cp\u003eGenerally, Hydrophobic are important force in the extraction of MIL. These compounds exist as a neutral form in acid and neutral aqueous solutions, and hydrophobicity interaction was enhanced, which was beneficial to extraction and separation. Under the alkaline conditions, these compounds were decomposed, which result in lower recoverier of targets.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.2.4.\u0026nbsp;\u003c/em\u003e\u003cem\u003eEffect of ionic strength\u003c/em\u003e\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eIn order to investigate the influence of the ionic strength, different concentrations of NaCl (from 0% to 7%) were added to targets solution, respectively. Results (Fig.2(d)) indicate that the recoveries of targets increase slightly with the increase of NaCl concentration in range of 0-5%. Generally, the salt addition can increase extraction efficiency, could be attributed to the fact that the dissolution of sodium chloride in water increased the viscosity of the solution, which reduced the solubility of the targets in aqueous phase, and facilitates the transfer of the targets from the aqueous phase to non-aqueous phase. However, the recoveries of targets decrease slightly when the concentrations of NaCl was 7%. The results, the salt addition decreases extraction efficiency, could be attributed to the fact that the dissolution of sodium chloride in water increased the viscosity of the solution, which reduced the diffusion rates that targets diffused into extraction solvent. Furthermore, the addition of salt enhanced the solubility of MIL in water. According to theses facts, the subsequent experiments were carried out with 5% (w/v) NaCl.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003e3.3.\u003c/em\u003e \u003cem\u003eInterference studies\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eFruit, vegetable and juice samples contain considerable amounts of organic matter and inorganic ions. In order to assess the possible analytical applications of the proposed method, the effect of concomitant species on the determination of three\u0026nbsp;pyrethroids\u0026nbsp;in real samples was examined under the optimal conditions as described above. The sample solutions containing 100 ng mL\u003csup\u003e-1\u003c/sup\u003e of pyrethroids and the added interfering matter were subjected to the proposed method. The tolerance ratio of each interfering matter was taken as the largest amount yielding an error in the determination of the target analytes not exceeding 5% (Table1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u0026nbsp; Effects of interfering matter on determination of 100.0 ng mL\u003csup\u003e-1\u003c/sup\u003e of three pyrethroids.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"45.16728624535316%\"\u003e\n \u003cp\u003eInterference\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54.83271375464684%\"\u003e\n \u003cp\u003eInterference to\u0026nbsp;pyrethroids ratio (w/w)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"45.16728624535316%\"\u003e\n \u003cp\u003eSaccharose, glucose, fructose\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eAscorbic acid\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54.83271375464684%\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003cp\u003e600\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"45.16728624535316%\"\u003e\n \u003cp\u003eNa\u003csup\u003e+\u003c/sup\u003e, K\u003csup\u003e+\u003c/sup\u003e, Fe\u003csup\u003e3+\u003c/sup\u003e, Mg\u003csup\u003e2+\u003c/sup\u003e, Ca\u003csup\u003e2+\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54.83271375464684%\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"45.16728624535316%\"\u003e\n \u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e, PO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e3\u003c/sup\u003e \u003csup\u003e-\u003c/sup\u003e\u003csub\u003e,\u003c/sub\u003e NO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e\u003csup\u003e\u0026nbsp;\u003c/sup\u003e,\u0026nbsp;HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e-\u003c/sup\u003e ,CO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e2\u003c/sup\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"54.83271375464684%\"\u003e\n \u003cp\u003e1000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e3.5. Method evaluation\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e3.5.1 Analytical performances\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eA novel MIL-DLLME based on\u0026nbsp;[P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e]\u0026nbsp;coupled with HPLC for the\u0026nbsp;simultaneous\u0026nbsp;determination of\u0026nbsp;three\u0026nbsp;pyrethroids\u0026nbsp;was developed.\u0026nbsp;Under optimal experimental conditions, a series of experiments were performed to obtain linear ranges, precision, the limit of detection (LOD, S/N=3, S/N: signal-to-noise ratio\u0026nbsp;) and quantification (LOQ, S/N=10). All the experiments were performed in triplicate. As shown in Table.2, good linearities were observed in the range of 10-1000 ng mL\u003csup\u003e-1\u0026nbsp;\u003c/sup\u003ewith the correlation coefficients (r\u003csup\u003e2\u003c/sup\u003e) of 0.9986-0.9995 The LOD and the LOQ were found to be\u0026nbsp;0.75-1.75 ng mL\u003csup\u003e-1\u003c/sup\u003e and 2.5-6.0 ng mL\u003csup\u003e-1\u003c/sup\u003e, respectively. The proposed method\u0026nbsp;showed good precision with the intra-day and inter-day RSDs in the range of 1.73-2.19% (n=6) and 3.02\u0026ndash;3.89% (n=3), respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u0026nbsp;\u003c/strong\u003eAnalytical performance for pyrethroids obtained by MIL-DLLME-HPLC-UV.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.801431127012524%\"\u003e\n \u003cp\u003ecompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.613595706618963%\"\u003e\n \u003cp\u003eRegression equation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003eLOD\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003eLOQ\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003er\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003eEF\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.801431127012524%\"\u003e\n \u003cp\u003eBeta-cypermethrin(trans)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.613595706618963%\"\u003e\n \u003cp\u003ey=1.1242C+0.9308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e0.9992\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.801431127012524%\"\u003e\n \u003cp\u003eBeta-cypermethrin(cis)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.613595706618963%\"\u003e\n \u003cp\u003ey=0.7017C-0.7918\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e1.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e0.9990\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.801431127012524%\"\u003e\n \u003cp\u003eFenvalerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.613595706618963%\"\u003e\n \u003cp\u003ey=1.5455C-4.0931\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e0.9986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"28.801431127012524%\"\u003e\n \u003cp\u003eBifenthrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"23.613595706618963%\"\u003e\n \u003cp\u003ey=1.5727C+2.2480\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"13.595706618962433%\"\u003e\n \u003cp\u003e2.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e0.9995\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.196779964221825%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eIn this procedure, the estimation of uncertainty of the final results and traceability is necessary. According to the Guide to the Expression of Uncertainty in Measurement (GUM). The expanded uncertainty of the target compouds analysis is obtained using the formula (Konieczka \u0026amp; Namieśnik, 2010):\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAikAAABnCAYAAADFXtIrAAARMElEQVR4nO3dMW/i2P7G8cd/3dexGt2FFIhXYGvbXZE0qaLZKp2t3YY0M9ukTLMzjd2sBNK/SDUjtAUN9vaz4RWgFLEzb+XcwhhsYxJCTHDI9yNFuheMbX57gGfOOT62jDFGAAAADfN/+z4BAACAKoQUAADQSIQUAADQSIQUAADQSIQUAADQSIQUAADQSIQUAADQSIQUAADQSIQUAADQSIQUAADQSP/Z9wm8JpZl7fsUAOAgcYcWVCGkPBEfJAAAXgbDPQAAoJEIKRuyLOsN9qJE8ixLlmXJCZJ9n8yeUYtV1KSIemyGOmFzhBSslQR3OjVGxoTqXnxWtO8T2iNqsYqaFFGPzVCn12XbuZh1zeG0zNvrHtjK2+xJWYo8R3cfbtRv7ftM9o9arKImRdRjM9Sp2Z77u1fH7+bOelIiL+3OW/w5gZI1z9fZ5Zftd/fdiJE8yzuAfwVs+D46ZzrZyRdJk+q4z1o0qQ55tI8i2shm9t1u8FyPBYz87/vXr18rtzHGPL9HxexS6BpJxg3jNU/bxq9+6lli3zZuWO8+C6UKXSO5puZD7E/sG1sP/LcI3drrme23cXXcRy2aWIc82kcRbWQz+2o3qMVD8eDHH39c/O8vX74YSeb+/v7J+9noPJ716kfEvm1k+2ZtG/XXP/eMoxrfrv/DvCx0aNzX9mWxidg3dtX7Cl2jJ32TbFr/BtexllocQB3yaB9FtJHN1NZu8JIeCxblQCLJfPv2bev9PXguW7/yUbHxbRl7fYw2/m66UYxdc+PPFzh0H3pPr1vs24Uvjti3jaTF32Zl3eyLt+l1fH4tDqMOebSPItrIZuppN3hJTwkV9/f35pdffqltf2W7u7onmWg0lbpHawYcozvtYjAymYzUPW0rcEpzYrz56GgSKfCc+eOOvCcN8EYaD22dVZx3EgVynNxxJCWB86ousWudnMkejhfjyK3+jUwaZGWM0aBX15Gq69ikGr5MLZpfhzzaRxFtZDMv126wDz///LP++eefne1/dyElvtVUrk7XNMCHMsrKpNvy39pkkWgy6uq0Jx11bblhvPwwDHpSEshpH2vUuVRsjGJfmt094UMdjTVUVyu5Kwk00Ymuz2zZnXa+BJWBprFaR+pqqPGuZ+ZV1bFpNXyJWryGOuTRPopoI5t5qXaDF/X161dZlqX7+3tZlqXv37/v5kBb98E8InT1wJjjDod6bNe4dtWxQ+Nqu27TrExpN+W67tnQuPlJYuvGYhttuxqFrgrdtyt/pf8W6+vYpBo+vRaHWYc82sfq+dBGHrf9dy/24ynR4M8//zSSzG+//VbL/sp21JMSaTyU3LXdKOOdDfVMpzPp0peb617MjjmUq8tdXZAfjTW0l5fTRZ9Hmrqnegs9mb2ByXXfxvJtV2GuO9ds2p/7ymtIHapRlyVqgUPz8eNH/fbbbzvb/w5XnLWV64nMieRddR7MKNsN9ySajCQ/vtGgd6KOXexeTO5mUulDnCRPG79tHXXXn/N4KPvsRC1JiiLd6YGQtnyVvNL6MbVLAjmFeiUKnIfXL1g7j6gm6+r4YjVMAjne/z9aB2m3tdh7HSrRPpYer4X0etvI8nu29B6TSF42p8/xlE1zKX8vO162r/3XCfUyT1zf5N27d3r37l3lc89e0G3rPphHhK6MbNcUlkiJQ+Pa9a9hku7bN3bucufFjPI4NK4fLrtN4+z54jX660pRfLzUxVr1eByaMJ7P2o9D469ZI2ZXl0pXHScsn0OpVoXHn91lvMn7qqrjS9ZwXpN1dTCmhlrsuw6x8f0tz/7Nt4/8Lg65jVRc2pytbTLfTxy6uWUk8tvHJsxftbPTOmEfNo0H9/f3D2773Jix43VSXGPnxlvtcmip9Vh2ccwz9o0tGdsN5x+c9JJoKQ1P+U2zIlYVs/xY9eWA8zHXbL9x+iVi+/Njh66RbOP7rrGzH47QXdlP6NrFcenYN64tY/vzL4dsQafsQx+n7yndPD0H15+/72zfcVgIZtlzVQvelS8V3M62l1XWU8P8e5w/UKyhMaWaVIfm59diR3VIX1SsRbkOcboPScZ1S9vGvnEX7T807vw9lut2kO2jYpvi+67+DL26NrLhZ2V1rZL890n2UC58rASRYsjZXZ2wL1W/id++fSvMo8ov7LbJ6598Ds/ewwHZJKSs7015WOgWg1Hsu6V9xMZ3S18AWagL3cXaL6HvGt+PTejaxnZ9E4e+cec7Cl17+WW7+PHx5z/M6foxcTzfPl6+bvm+XvJfO0+v46M1nNfpsRouapL+n1IdsnN7qVo8vz2ttqXias6FusXx8rlcWyi0DWMOs32Ut6l431WfodfYRjapReU/7Mq9Ibkgs7J9uQZ7rxN2YdugUddADXdBzjEbjcP1NIjPNGo72nxJgkhjnRZuohXfzkrbtNQfHGky32kSjNW5HqiXvabTTvcz6uikL93NpLMPfelupPT6xEhjnem630onJnfakhJNdKSepOjzhabDY7XPb3U6nxA0u40X5+dZx1I4eMGJd0+t4+M1jMYznX3oKdukuobLmmSWdUiP87K1eH57Wm1LkcazbFJlqW6tWOPZ/JLW+Fadk1Zl25AOr32Ut1l931WfodTraiOb1CKdw1e4ZDm+1bR7pFZum+BqOJ/rUrF9NNawNM9vv3XCLpgt55Ns+7oyQso2Wn3dmEvdtje82Vc0VnnBmHanakJcTyf6rCBJ1zw4aklJEsm7mqVfDtFYuuyrlUx0271Uv7VcFyY9Rl+tJJJ3JZ32W1IykY6kYP7N5oZG8aV0N/8e6c6Dj2eNdbqPRZWeUseNapj++CZBOqGvsoalmkhZHaS91eKZ7WmlDsmdZotJlaW6JXeadU/VU6Jg3Fmsv1FuG9IBto+KbQrvu+ozNPeq2sgmtUgmGmkeZJNIXpBI7Y7s2d1iMmzknWvUDefvM9btNFuvJVESeXKuZvI/FI+z9zrh8NTSH3NAyiWpo0ShW33vimXXaX6+TNrdGvq2kWzjhrHxXdf4Ybjcz+LGXOlwhh/Gy/UX7OIwgDsfp86Won5snL2pHq9h9h5zwxwVNczXJHvNa6qDMRW1qKiD6/omna5StW1owjhtO8tJ5Vrdxyuqyybto7xN+X1XfYay7Q6qFvMbv+b/sve3mBcne/k5mc/vy29vu/7K/MLXVie8DoSUClkw2W2Gi41v13UX6Nz4+abbP3Djx9fjuTWkDtXeYl3WfYbeYi22cSh1QtMQUiq8TEgxpp4PdnYlx6ZfQC916fNL2baG1KHaW6zLus/QW6zFNg6tTmgSy5iaZrccmGwCLeUBAGA/mDi7BuEEAID9IqQ8gKACAMD+EFIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVIAAEAjEVJqlASOLMta/jmBkrUbJ4o8R85ie0deVNw68qzi/ixLluPI8aL1+wUA4EAQUmrU6t/IhK4kW35oZG76alVtGHly2m1ddS51bYyMMYrDrobHbXnRcrPewCj2bUmuwmy76zN1h8dqPxSAAAA4AISUmiV3M8k+00lvzQaRJ+d4qG4Y66bfW4SYVm+g0JWGV8XwEd9OJfdU2e5arb4GoStNL/Q5EgAAB4uQUqtEk9FU9tlJdQ+KInnHQ03dUINe9Raa3irObT8eSu5pKfH0TuVKGo5JKQCAw0VIqVMy0Whq6+ykOoAkwZWGsuV/WNfNUhKNNZSrckaR2urYzzpTAAAaj5BSo2Qy0tQ+U3VGSXtZtPb5tNckP7QTjYeS3VF7ZdtYt9PaThsAgEYipNRmHkK6R9VDPclEaUZZMxQUjZVmlCyiJEqnt1Rsn9xpJsnurMYXAAAOBSGlNmnvxsr8kY0kCq6Gku1rMRL0wNBR9PlCU7m67K+Z1wIAwAEgpNRl3fyRyEsvK24dqStpehuvvDQJznUxteVfLy9ZXjt0FHk6HkpuONA2cQgAgE1ZlvWirysjpNRi3hOSm08iSUkUyLnSPLj09MG3peFVbtG2dEG39oXkhjdadIwkkT5fFK8SSpJIgefIOp7JDWMNSCgAgB2yLEvGmK1ea4ypJahYZtszQCryZB0P1z/vhjK5RJEEns4vhkrnvdqy3UtdD5brpSSBo/ZF1axYW7Z7pssPfa27ehkAgDpsGlD+/fdf/fTTT2u3fU7QkQgpAACgZNNw0Wq1dH9/v7OQwnAPAABY2DRYfPr0Sa7rPrjNc4d9CCkAAOBJvn//Lkn64YcfdnqcnYWUJArkOJas3B3zksCRE3BbPAAAXrPff/9dHz9+3PlxdhNSkkATnej6zC4sOBbfau2S8fsWeZYs64E/j/vkAADw6dMn/fXXXy9yrP/sZK+tvvqtSN6xdBbPQ0kS6GrY1eVgJ0d8tt7AyDT03AAAaIJsmOe///3vixxvd3NSorGGucXIos8jTUvriLx2D/a8vPAfAAC79vfff+uPP/5Y/Pb8+uuvktLfw0+fPtV+vJ2FlGg8XC5GFkW60yZLxkfynEDZrJXlEIynwmBLEslz5s85nrJpLuUhG8fL9pUocEr7KB95i+EeY0xj/gAAqMNDV+R8/Pix8Nvz5cuXxWuq5qg09BLkSOPh/L4zSaSo3ZZmXZ22IwXRuomziQJnrNOb5dLwvUEoV65Ck1sCPgnktK/UuYxljFF8KV2cp2Fkub2RMbEuOyO10zXp1b/u6CoXgMp6g0eCAEu8AgDwonZ4CfJUo3NPgXrqKdbtdKariXTSa6WrtFqOgsCTE8x7KKLPGp19KA4HRWMNC0NEiYLzC3XDG/Xny6622h3Zi6fvNLM7SqfqttTrX8odjtMelFZf12cjfWb+KwAAD6pjWfvn9qJIu5o4q54GhRPraWBy8aM3UOh6ujsZ6CabV3u3euVPcjeT3fmQe2CikXxd55NMfKtp91QtpTfl09m11l0/1Do5kyaJWFceAICHZUHloaDx/v17vX//fuXxOgKKtLfF3CKNdbq8oZ6k+HZW2ibRZFQKLvGtpt2jXAhJb+yXznWp2H6lJ0aaVdyFGAAArHrODQbrsJ+QEo2zWwMvtDvd4jbJRCPNrw5KInlBIrU7smd3i8mwkXeuUTec3xE41u20q6NW+lwSeXKuZvI/FI/Tza3bAgAAmmsvIaUio6h1JI0mi8t0ZLUvNJ1eqG1ZstrH0lFLavV12R2lj1nnGnfSOwgrCeRYxxpqqGPLkmW1dT7u6PL6ptBbk0xGmqcYAADQcA26C3KiwDmXSsGiPpE8504fclcPAQCA5mrQDQZb6t9c6vZ8/WXC21u9vPlFJZECz5mvueKIFfYBAHhcg3pSDlQSyGlfSH6o635PChyd61o3u+kuAgDgYBBSdiqSZx1r5seEEgAAnoiQskuRJ+tYxRVzAQDARho0J+XwJHczqbROS5KszriJPGdx/yEAAJAipOzacKzsdkVJ4OlzXBr2SQJdDde9OJLHLFsAwBtFSNmhVv9avj3UcTu9W/PkZKDlfQoTBY6VrgezeEUkb34FUJAoXTF3eCyHbhYAwBtESNmplvo387so3wyKC8sF5xqdpXdyDt3ssbE6sZEJuxpNEiWSbDdk0i0A4E0ipOxJfLu8z1B2S4D4dqiLtiXreKjpbaxWu7PPUwQAYK8IKXvS7uRuA6CZLs4DqeMrNPOelwHXAwEA3jYuQd6bdA2VbM6sGxoNernH3FBmINZZAQC8WYQUAADQSAz3AACARiKkAACARiKkAACARiKkAACARiKkAACARiKkAACARiKkAACARiKkAACARvofdZUZMzhnb2oAAAAASUVORK5CYII=\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere U is expanded uncertainty, k is coverage factor, for which 3 is usually chosen to obtain a confidence level of approximately 95%, c is average concentration of the analyte, ur\u003csub\u003e(sample)\u003c/sub\u003e is relative standard uncertainty of sample mass determination, ur\u003csub\u003e(cal)\u003c/sub\u003e is relative standard uncertainty of calibration step, ur\u003csub\u003e(true)\u0026nbsp;\u003c/sub\u003eis relative standard uncertainty of recovery determination, ur\u003csub\u003e(rep)\u0026nbsp;\u003c/sub\u003eis relative standard uncertainty of repeatability, ur\u003csub\u003e(LOD)\u0026nbsp;\u003c/sub\u003eis relative standard uncertainty of LOD determination and c\u003csub\u003edet\u0026nbsp;\u003c/sub\u003eis the concentration of the target analyte.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\"\u003e\u003c/p\u003e\n\u003cp\u003eWhere SD\u003csub\u003exy\u0026nbsp;\u003c/sub\u003eis the residual standard deviation, b is the direction coefficient of the calibration curve, p is the number of measurements carried out for given sample, n is the total number of standard samples used for plotting the calibration curve, x\u003csub\u003esample\u003c/sub\u003e is the concentration of sample, x\u003csub\u003em\u003c/sub\u003e is the mean of all the concentration of a standard solution for which the measurement was made in order to plot a standard curve, x\u003csub\u003ei\u0026nbsp;\u003c/sub\u003eis the concentration of standard solution. The related parameters were listed in Table 3. The uncertainty of the weight and/or volume of a sample are usually small, so ur\u003csub\u003e(sample)\u0026nbsp;\u003c/sub\u003eis very often neglected during construction ofthe uncertainty budget(Konieczka \u0026amp; Namieśnik, 2010, L. Wang, et al., 2015) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable.3\u0026nbsp;\u003c/strong\u003eCalculated values of relative standard uncertainty and expanded uncertainty (U, k=2) for the determination of fenvalerate, beta-cypermethrin and bifenthrin in mushroom.\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"25.86750788643533%\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"15.930599369085174%\"\u003e\n \u003cp\u003eConcentration\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.410094637223974%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" width=\"35.80441640378549%\"\u003e\n \u003cp\u003eRelative standard uncertainty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.987381703470032%\"\u003e\n \u003cp\u003eU\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"17.83783783783784%\"\u003e\n \u003cp\u003eu\u003csub\u003er(sample)\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.405405405405405%\"\u003e\n \u003cp\u003eu\u003csub\u003er(cal)\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.405405405405405%\"\u003e\n \u003cp\u003eu\u003csub\u003er(true)\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.405405405405405%\"\u003e\n \u003cp\u003eu\u003csub\u003er(rep)\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.405405405405405%\"\u003e\n \u003cp\u003eu\u003csub\u003er(LOD)\u003c/sub\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"20.54054054054054%\"\u003e\n \u003cp\u003e(ng mL\u003csup\u003e-1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.826771653543307%\"\u003e\n \u003cp\u003eBeta-cypermethrin(trans)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.905511811023622%\"\u003e\n \u003cp\u003e51.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.393700787401574%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.0026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.968503937007874%\"\u003e\n \u003cp\u003e3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.826771653543307%\"\u003e\n \u003cp\u003eBeta-cypermethrin(cis)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.905511811023622%\"\u003e\n \u003cp\u003e48.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.393700787401574%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.968503937007874%\"\u003e\n \u003cp\u003e4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.826771653543307%\"\u003e\n \u003cp\u003eFenvalerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.905511811023622%\"\u003e\n \u003cp\u003e49.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.393700787401574%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.0023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.968503937007874%\"\u003e\n \u003cp\u003e4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"25.826771653543307%\"\u003e\n \u003cp\u003eBifenthrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"15.905511811023622%\"\u003e\n \u003cp\u003e49.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"10.393700787401574%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.0025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.976377952755906%\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.968503937007874%\"\u003e\n \u003cp\u003e3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTo evaluate the applicability of the present method, food samples were analyzed. It can be seen (Fig.3) that no significant interference peaks were found at the retention positions of target compounds. To evaluate the precision and accuracy of the proposed method, the spiked samples (50.0, 200.0 ng mL\u003csup\u003e-1\u003c/sup\u003e) were analyzed and the analytical results were showed in Table 4. The recoveries of targets obtained from cucumber, mushroom and lemon samples were in the range of 96.3-103.8%. It can be considered that the current method provides acceptable recoveries and precision for the determination of three pyrethroids in real samples.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;4.\u0026nbsp;\u003c/strong\u003eRecoveries of three pyreghroids in cu and mushroom samples.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"131%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003eCompound\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" style=\"width: 21.4696%;\" width=\"23.711340206185568%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;Cucumber\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 26.9964%;\" width=\"30.927835051546392%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mushroom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 9.8845%;\" width=\"20.61855670103093%\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Lemon\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eSpike\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"8.536585365853659%\"\u003e\n \u003cp\u003eRecovery\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eSpike\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eRecovery\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eSpike\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"12.195121951219512%\"\u003e\n \u003cp\u003eFound\u003c/p\u003e\n \u003cp\u003e(ng mL\u003csup\u003e\u0026minus;1\u003c/sup\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"10.975609756097562%\"\u003e\n \u003cp\u003eRecovery\u003c/p\u003e\n \u003cp\u003e(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003eBeta-cypermethrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e(trans)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e51.37\u0026plusmn;2.92\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e102.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e51.91\u0026plusmn;3.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e103.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e51.63\u0026plusmn;\u0026nbsp;3.44\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e103.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.2\u0026plusmn;2.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e100.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e202.6\u0026plusmn;2.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e101.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e201.8\u0026plusmn;3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e100.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003eBeta-cypermethrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003e(cis)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e48.91\u0026plusmn;3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e48.52\u0026plusmn;4.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e97.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e48.66\u0026plusmn;4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e97.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e197.4\u0026plusmn;3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e192.6\u0026plusmn;2.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e96.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e195.7\u0026plusmn;3.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e97.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003eFenvalerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e48.67\u0026plusmn;3.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e97.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e49.93\u0026plusmn;4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e49.18\u0026plusmn;4.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e197.1\u0026plusmn;2.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e98.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.8\u0026plusmn;3.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e100.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e198.2\u0026plusmn;3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e99.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\n \u003cp\u003eBifenthrin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003en.d.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e49.42\u0026plusmn;3.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e49.36\u0026plusmn;3.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e97.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e50.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e49.38\u0026plusmn;3.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e98.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11.3725%;\" width=\"15.463917525773196%\"\u003e\u0026nbsp;\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.3531%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e197.4\u0026plusmn;1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 7.4399%;\" width=\"7.216494845360825%\"\u003e\n \u003cp\u003e98.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.8217%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e198.6\u0026plusmn;2.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8.0777%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e99.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e200.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 9.2468%;\" width=\"10.309278350515465%\"\u003e\n \u003cp\u003e198.1\u0026plusmn;2.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 7.4399%;\" valign=\"top\" width=\"9.278350515463918%\"\u003e\n \u003cp\u003e99.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003e\u003csup\u003ea\u0026nbsp;\u003c/sup\u003e\u003c/em\u003en.d.\u003cem\u003e=\u003c/em\u003e not detected.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4. Conclusions","content":"\u003cp\u003eIn this paper, a rapid, efficiently and eco-friendly method of MIL-DLLME based as extractant combined with HPLC was successfully applied to the determination of trace amount of three pyrethroids in food sample. MIL of [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e] is environment friendly and can be rapid separation from aqueous phase in less than 3 min by an external magnetic field. The proposed method not only operation steps can be simplified but also the pretreatment time can be shortened. The methods showed good linearity and precision. The excellent spiked recoveries of analytes in real samples indicated that the proposed method would be a valuable alternative for the analysis of trace amount of pyrethroid insecticides in the future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003eThe authors would like to thank their colleagues and other students who participated in this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u0026nbsp;\u003c/strong\u003eLingling Wang did the laboratory work by MIL-DLLME-HPLC, wrote the draft of this report, reviewed the fnal version of this report, and supplied all fgures and tables. Dr. Xiaoxia Chen and Dr. Xueying Han for sampling and preparation of food samples. Prof. Dr. Baozhao Ju co-initiated the study, is co-inventor of the assay, and evaluated all data.\u0026nbsp;All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e This work was supported by the Natural Fund Guidance Plan of Liaoning Province (2019-ZD-0948).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u0026nbsp;\u003c/strong\u003eThis article does not contain any studies with human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e Xiaoxia Chen, Xueying Han and Baozhao Ju declare that they have no confict of interest regarding the publication of this paper.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAbdulra\u0026rsquo;uf, L. 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A polyurethane-based thin film for solid phase microextraction of pyrethroid insecticides. \u003cem\u003eMicrochimica Acta, 186\u003c/em\u003e(9), 596.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dispersive liquid-liquid microextraction, Magnet ionic liquid, Pyrethroids, High performance liquid chromatography","lastPublishedDoi":"10.21203/rs.3.rs-1833445/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1833445/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eA simple, green, rapid and efficient magnet ionic liquid (MIL) dispersive liquid–liquid microextraction (DLLME) method coupled with HPLC was successfully developed for determination of three trace pyrethroids (Fenvalerate, beta-cypermethrin and bifenthrin) from water and food sample. The MIL of tri-hexyl-tetradecyl-phosphonium tetra-chlorocobalt (II) [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e] was explored as the extraction solvent due to its magnetic susceptibility, low UV absorbance and difficult to hydrolyze in aqueous as well as the highest extraction capacity. Important influence factors of extraction efficiency such as the amount of MIL, the pH, ionic strength were optimized. The spiked recoveries of three targets in food samples were in the range of 96.3-103.8%. The limits of detection ranged from 0.75-1.75 ng mL\u003csup\u003e−1\u003c/sup\u003e. The results indicated that the developed MIL-DLLME method based on [P\u003csub\u003e6,6,6,14\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e]\u003csub\u003e2\u003c/sub\u003e[CoCl\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2-\u003c/sup\u003e] as the extraction solution has the advantages of rapid and high efficiency, and can be successfully applied to detect three pyrethroids in real food samples\u003c/p\u003e","manuscriptTitle":"Application of magnet ionic liquid-based dispersive liquid phase microextraction coupled with HPLC rapid determination three pyrethroid insecticides in food samples","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-18 16:47:25","doi":"10.21203/rs.3.rs-1833445/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"73852f8c-121b-4959-8349-afdac7f81bb8","owner":[],"postedDate":"July 18th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-08-28T14:59:17+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-18 16:47:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1833445","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1833445","identity":"rs-1833445","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}