Representative matrices for use in matrix-matched calibration in gas chromatography-mass spectrometry for the analysis of pesticide residues in different types of food-medicine plants

Abstract

Matrix-matching calibration is a method for minimizing or eliminating the matrix effect in pesticide residue analysis. However, when the matrix effect cannot be ignored, a matrix-matching calibration must be established for each single plant, which is time-consuming and laborious. To increase laboratory productivity and simplify analysis procedures, we proposed a strategy for the determination of multiple pesticide residues from different food-medicine plants using a single matrix-matching calibration. Herein, the matrix effects of 30 organophosphorus pesticides, 15 triazine pesticides and 12 pyrethroid pesticides in 11 food-medicine plants as determined by GC-MS/MS were investigated. Performance characteristics of the established method were validated according to SANTE/11813/2017 guidelines set by the European Commission. To better verify the influences of plants varieties and the physicochemical characteristics of pesticides on matrix effects, hierarchical cluster analysis was employed. There was little difference between plants with the same medicinal parts in the same family, indicating that these types of samples were more likely to be classified into the same category. The results show that matrices can be grouped into different clusters when analyzing different pesticide types. Any type of plant can be chosen from its cluster as a representative matrix to generate a matrix-matching solution, simplifying analysis without sacrificing accuracy. The establishment of the method aims to provide new research ideas for future analysis of pesticide residues in complex matrices.