龙葵
质谱法
杀虫剂
化学
色谱法
环境化学
园艺
生物
农学
作者
Ayrton M.S. Santos,Raquel Cintra de Faria,Igor Pereira,Leomir A. S. de Lima,Carla Monteiro Leal,A. Nascimento,Rosineide C. Simas,Nerilson M. Lima,Boniek G. Vaz
标识
DOI:10.1016/j.jfca.2022.104467
摘要
• Method for determination of pesticide residues in tomatoes was developed using PSI-MS. • PSI-MS has been successfully applied to pesticide quantification in tomato varieties. • The quantification method by PSI-MS offers an excellent LOD, LOQ and recovery values. • Application of PSI-MS combined with PCA to differentiate the metabolites from tomato varieties. • PSI-MS is a rapid and efficient technique for analyzing pesticides in foodstuffs. The determination of pesticide residues in tomatoes is usually performed by GC–MS and LC–MS, which provide high analytical performance but require several steps of sample preparation. Thus, this work employed a simpler and faster technique, the Paper Spray Ionization Mass Spectrometry (PSI-MS), combined with Principal Component Analysis (PCA) to differentiate the tomatoes varieties and for quantification of pesticides residues. It was determined a metabolic profiling by PSI-MS and the samples were grouped according to the variety using PCA. A quantitative method was developed for sensitive and accurate quantitative analysis of the fungicide cyazofamid by PSI(+)-MS using fruit peels of two varieties of tomatoes. The method showed a calibration curve with R 2 > 0.99, and low limits of detection (LOD) and quantification (LOQ) of 10 ng.mL −1 and 25 ng.mL −1 , respectively. The intra-day and inter-day recoveries percentage were in a range of 93.87–109.32 % and 99.54–100.81 % for variety Sweet Heaven, respectively. Similar results were obtained for variety BS II0012 with a satisfactory average recovery ranged from 89 % to 108 %, within the standards established by the regulatory agency. The results obtained reinforce the potential of PSI-MS as a rapid and simple analytical tool for determination of pesticide residue in agricultural products.
科研通智能强力驱动
Strongly Powered by AbleSci AI