Method validation and quantification of 188 pesticides in animal liver using QuEChERS and GC-MS/MS

The pesticide residues in animal products are the main research focus in the present scenario since they pose a severe health hazard to humans and also loss for the livestock industry. The goal of the current work was to create a method and screen animal liver from Karnataka, India for pesticide residues (n = 188) using gas chromatography triple quadrupole mass spectrometry. We found strong linearity (r2 = 0.999) from 50 to 800 ppb for the pesticides standard mixture. The lowest limit of detection (LOD) of 0.067 ppb was found for pebulate compound, followed for endosulfan ether was 0.07 ppb, and we found highest LOD for dichlofluanid (0.986 ppb). Coming to the limit of quantification, lowest was found for pebulate (0.202 ppb), followed by endosulfan ether (0.212 ppb), and the highest was obtained in dichlofluanid (2.989ppb). The average recovery ranged from 84 to 122% and 81 to 105%, at 100 and 400 ppb, respectively. In the initial study, we analyzed 31 liver samples that were sent to our Veterinary Forensic Science Laboratory between February 2022 and October 2023 and pesticide residues have been quantified in 9 samples from domestic as well as wild animals. A total of eighteen pesticides from the organonitrogen compounds (n = 8), organochlorine (n = 7), organophosphorus (n = 2), and pyrethroids (n = 1) categories were found and none were quantified higher than the maximum residue limits set by different national and interna- tional regulatory bodies except for beta benzene hexachloride and chlorpyrifos. It can be concluded that our developed method using a QuEChERS extraction or cleanup method and triple quadrupole mass spectrometry can be applied to the regular monitoring of the majority of multi-residue pesticides in less time and thereby control management can be initiated. (c) 2024 Socie<acute accent>te<acute accent> Franc,aise de Toxicologie Analytique. Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.