Screening of 485 Pesticide Residues in Fruits and Vegetables by Liquid Chromatography-Quadrupole-Time-of-Flight Mass Spectrometry Based on TOF Accurate Mass Database and QTOF Spectrum Library. (23rd November 2019)

• Record Type: Journal Article
• Authors: Pang, Guo-Fang; Fan, Chun-Lin; Chang, Qiao-Ying; Li, Jian-Xun; Kang, Jian; Lu, Mei-Ling
• Is Part Of: Journal of AOAC International. Volume 101:Number 4(2018)
• Page Start: 1156
• Page End: 1182
• Publication Date: 2019-11-23
• Subjects: Agricultural chemistry -- Periodicals; Food -- Analysis -- Periodicals; 543
• DOI: 10.5740/jaoacint.17-0125
• Languages: English
• ISSNs: 1060-3271

Abstract

Abstract: This paper uses the LC-quadrupole-time-of-flight MS technique to evaluate the behavioral characteristics of MS of 485 pesticides under different conditions and has developed an accurate mass database and spectra library. A high-throughput screening and confirmation method has been developed for the 485 pesticides in fruits and vegetables. Through the optimization of parameters such as accurate mass number, time of retention window, ionization forms, etc., the method has improved the accuracy of pesticide screening, thus avoiding the occurrence of false-positive and false-negative results. The method features a full scan of fragments, with 80% of pesticide qualitative points over 10, which helps increase pesticide qualitative accuracy. The abundant differences of fragment categories help realize the effective separation and qualitative identification of isomer pesticides. Four different fruits and vegetables—apples, grapes, celery, and tomatoes—were chosen to evaluate the efficiency of the method at three fortification levels of 5, 10, and 20 μg/kg, and satisfactory results were obtained. With this method, a national survey of pesticide residues was conducted between 2012 and 2015 for 12 551 samples of 146 different fruits and vegetables collected from 638 sampling points in 284 counties across 31 provincial capitals/cities directly under the central government, which provided scientific data backup for ensuring pesticide residue safety of the fruits and vegetables consumed daily by the public. Meanwhile, the big data statistical analysis of the new technique also further proves it to be of high speed, high throughput, high accuracy, high reliability, and high informatization.