Chinese Journal of Chromatography ›› 2014, Vol. 32 ›› Issue (12): 1390-1399.DOI: 10.3724/SP.J.1123.2014.09005

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Combination of programmable temperature vaporizer-large volume injection gas chromatography-mass spectrometry and automated mass spectral deconvolution and identification system for the determination of 32 pesticides in fruits and vegetables

CAO Zhaoyun1,2, MOU Renxiang1,2, WU Li1,2, LIN Xiaoyan1,2, ZHU Zhiwei1,2, CHEN Mingxue1,2   

  1. 1. Rice Product Quality Inspection and Supervision Center, Ministry of Agriculture, China National Rice Research Institute, Hangzhou 310006, China;
    2. Laboratory of Quality and Safety Risk Assessment for Rice, Ministry of Agriculture, Hangzhou 310006, China
  • Received:2014-09-03 Revised:2014-10-13 Online:2014-12-08 Published:2014-11-28

Abstract:

An analytical method was developed for the simultaneous determination of 32 pesticides including organophosphorus, organochlorine, pyrethroid and carbamate pesticides in fruits and vegetables using gas chromatography-mass spectrometry (GC-MS). The sample was extracted with acetonitrile, and the organic layer was cleaned up with ENVI-Carb and LC-NH2 cartridges. A large volume of 20 μL purified solution was injected into the GC system using programmable temperature vaporizer (PTV). The mass spectrometric detection was operated with full scan mode. The automated mass spectral deconvolution and identfication system (AMDIS) and an isotopic internal standard were used for the qualitative and quantitative determination of the 32 pesticides, respectively. The conditions for PTV-large volume injection were studied. Furthermore, the selectivity and durability of the method were also assessed. Under the optimized conditions, the experimental results showed that all the linearities were good within their test ranges, with correlation coefficients more than 0.995, and the method detection limits of the pesticides were 2.0-5.0 μg/kg. The spiked recoveries (n=6) at three levels in the 0.010-0.50 mg/kg using spinach, snap bean and cucumber samples as blank matrices were in the range of 65.2%-120.3% with the relative standard deviations (RSDs) varying from 4.1% to 22.3%, showing good accuracy of the method. The advantages of the proposed method include high throughput, high sensitivity, reliability, robustness, and the ability to meet the demand of multi-residue pesticide analysis in fruits and vegetables.

Key words: automated mass spectral deconvolution and identification system (AMDIS), fruits, gas chromatography-mass spectrometry (GC-MS), large volume injection, pesticide residues, programmable temperature vaporizer (PTV), vegetables

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