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Article Abstract
A rapid and high-throughput method using both GC-MS/MS and UPLC-Q-Orbitrap systems was applied for pesticide multi-residues analysis in food samples. Strategies based on QuEChERs extraction, intelligent data mining tools with in-house/online database, and in-silico fragment prediction system were introduced to screen and identify target/untargeted features. Full-scan combined with data-independent-acquisition modes was evaluated in real sample in an attempt to improve and facilitate the pesticide screening process, of which the results showed that FS-vDIA provided equal detection rate (100%) and far less false positive results than FS-AIF did. The proposed methodology was evaluated in analysis of pesticide multi-residues in several proficiency test samples provided by EURL, and exhibited a high detection rate (>90%) of various pesticide residues with satisfactory recoveries (70-130%) without reporting false positive results. The method was also applied in China's national surveys from 2016 to 2019, and results showed its high performance in pesticide analysis in different food matrices.
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| http://dx.doi.org/10.1016/j.foodchem.2020.126576 | DOI Listing |
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