| 總結: | This research targets the development and validation of the best efficient method for sample extraction of pesticide analytes and LC-MS/MS (Agilent G6490A) instrumentation for selected samples of freshly obtained fruits and vegetables. However, the instrument underwent auto-tuning and Mass-Hunter optimization initially, using 1000 μg/kg standard solution of pesticides mixture to obtain product ions, collision energies, and retention times of the respective analytes. Then, the best mobile phase was first selected comparatively among the nine analyzed setups using responses of the default instrumental settings. Subsequently, multivariate optimization was carried out on the main factors of the instrument, screened (Plackett-Burman) and optimized (Box-Behnken) using response surface methodology (RSM) for the design of experiment (DOE) generated by Minitab-17 statistical software. However, the total chromatographic peak area (TCPA) resulted from the multiple reactions monitoring (MRM) scan analysis of 100 μg/kg standard solution of analytes was used for the optimization. After that, a comparative analysis was attempted between the optimized and unoptimized instrumental settings. Similarly, some important parameters in the sample preparation methodologies were also selected for multivariate optimization using the RSM designs. These occurred after the selection of acetonitrile (ACN) and 1-hexyl-3-methylimidazolium hexafluorophosphate ([C6MIM][PF6]) ionic liquid-based respectively for extraction and cleanup purposes. Subsequently, individual optimization studies were carried out on the QuEChERS-dSPE, and QuEChERS-IL-DLLME technical factors using Milli-Q-water (analytical sample) consistently spiked with 200 μL of 100 μg/kg multi-pesticides mixture. Eventually, the optimized factors of the two methods above were combined (QuEChERS-dSPE-IL-DLLME) and comparative studies were conducted with their respective unoptimized conditional methods. Consequently, the optimized QuEChERSdSPE-IL-DLLME method was selected and validated (SANTE/11813/2017) for the determination of multi-pesticide residues in fruit and vegetable samples. Resultingly, the precision was expressed based on the laboratory repeatability (RSDr %) (≤ 20%), as well as the accuracy range for the relative (82 – 138%) and absolute (84–101%) recoveries, were satisfactory. The overall matrix effects were very week (≤ -80%). The range of LOD (0.01 - 0.54 μg/kg) and LOQ (0.03 - 1.79 μg/kg) were acceptable. Also, linearity (5– 400 μg/kg) of the evaluated results and regression coefficient (R2) were > 0.99. Conclusively, this developed method could potentially be more reliable and suitable for routine determination of multiple pesticide residues in vegetables and fruits.
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