Ion mobility spectrometry coupled with chemometrics for the rapid identification of six pesticide residues in rice samples

Abstract

Rice, as a staple food for nearly half of the world's population, has raised significant concerns regarding its safety. Pesticide residues represent one of the major factors threatening the quality and safety of rice. This work used isoprothiolane, propanil, fenitrothion, carbendazim, flutolanil, and pirimiphos-methyl as examples to explore the feasibility of using ion mobility spectrometry (IMS) for the rapid and simultaneous identification of multiple pesticide residues in rice. Rice samples were preprocessed via QuEChERS method to obtain matrix solutions. Analysis of the IMS data of the solvent and matrix standard solutions revealed that the six pesticides were present in positive and negative ionization detection modes. Additionally, the peak times of propanil and fenitrothion were similar, which poses significant challenges for qualitative identification and indicates that the selected pesticides are representative. After feature extraction of the IMS data and evaluation of various algorithms, support vector machine (SVM) models were separately developed on the basis of single ionization mode data and the fusion of positive and negative ionization modes data. The former achieved an identification accuracy rate of over 90%, whereas the latter improved the identification accuracy rate for similar pesticide residues to 100%. Compared with the time spent on sample pretreatment, the time required for data acquisition can be negligible. Therefore, it is advisable to collect IMS data in different ionization modes simultaneously, providing multidimensional information for data fusion. This study provides an efficient and reliable method for the rapid screening of multiple pesticide residues with highly similar spectra in rice, demonstrating significant practical application value.