An integrative review on the analysis of pesticide multiresidues in sweet pepper samples using the QuEChERS method and chromatographic techniques

Abstract

Since foods are complex matrices that contain pesticides of different classes, multiresidue sample preparation methods such as QuEChERS (Quick, Easy, Cheap, Effective, Rugged, Safe) are used and modified to obtain more accurate and sensitive results. This work was developed through an integrative review in the journal databases Capes, Science Direct, Scielo, and Scientia Chromatographic, from 2011 to 2021, to answer the following question: “What is the most efficient and advantageous sample preparation method for the determination of multiresidue pesticides of interest in sweet pepper samples, when chromatographic techniques are used for detection?” The sweet pepper was chosen because the Pesticide Residue Analysis in Food Program (PARA) suggests that it is the sample with the highest percentage of irregularities related to active ingredients not allowed or above the Maximum Residue Limit (MRL). A total of 391 articles were found, 11 of which met the inclusion criteria established. Several analyses were studied. The organophosphates were the most studied class of pesticide, with seven articles. In addition, there was a predominance of nonpolar analytes (log Kow > 1). The use of different extracting solvents, such as methanol, acetonitrile, ethyl acetate, and acetone, was observed, with acetonitrile presenting the best analytical parameters in most cases. The use of different sorbents such as secondary and primary secondary amine (PSA), ocatadecyllane (C18), graphite carbon (GCB), and carbon black was noted, as well. The authors highlight the difficulties in the analysis when the matrix effect is significant (except for fensulfothion, tensulfothion, flonicamid, and its metabolite TFNA-AM) and the degradation of analytes through the analysis process (flonicamid, captan, folpet, thiophanate methyl and benomyl). Finally, the statistical test Analysis of Variance (ANOVA) was used to identify if there was a significant difference between the different methods used for the same analysis or when the same method used for the different analytes.