Development and Validation of a Multiresidue Method for Simultaneous Analysis of 451 Multiclass Pesticides in Fodder Crops.
Sonu Kumar Mahawer, Sachin C Ekatpure, Narendra Kulkarni, Kaushik Banerjee
Journal of AOAC International
Abstract
Fodder crops are widely used as main ingredients of animal feed products. To combat pest infestations, farmers often apply pesticides on farms, the residual content of which may accumulate at or beyond toxic levels in/on the green fodder at the stage of harvest. To safeguard animals and humans (through ecological food chains) from these residual pesticides, both domestic and commercial programs are necessary to monitor the levels of pesticide residues in food and feed. The existing methods exhibit constraints regarding scope, selectivity, and sensitivity. These limitations warrant a high-throughput multiresidue method for monitoring and risk assessment of multiclass pesticides in fodder crops. The study aimed to develop and validate a multiresidue method for the simultaneous analysis of 451 multiclass pesticides, their isomers, and metabolites of toxicological concern in three widely used fodder crops, namely sorghum, maize, and lucerne. Well-homogenized samples of sorghum, maize, and lucerne (10 g) were extracted with acetonitrile (10 mL). An aliquot of the extract was cleaned by dispersive solid-phase extraction (dSPE) with graphitized carbon black (GCB, 7.5 mg/mL). The method performance was evaluated for a mixture of multiclass pesticides at 10 and 20 µg/kg using liquid and gas chromatography with tandem mass spectrometry (LC-MS/MS and GC-MS/MS). The GC-MS/MS and LC-MS/MS techniques allowed analyses of the test pesticides within chromatographic run times of 17 and 20 min, respectively. The method's performance using matrix-matched calibration was satisfactory for all compounds (recoveries 70-120%, repeatability-RSD, <20%) at 10 and 20 µg/kg in three studied matrixes. The method successfully determined the residues of all tested compounds in each fodder matrix. It demonstrates satisfactory selectivity, accuracy, and repeatability. Given all of these, it is recommended for regulatory and commercial testing pur