Citation: CAO Zhaoyun, MOU Renxiang, WU Li, LIN Xiaoyan, ZHU Zhiwei, CHEN Mingxue. 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[J]. Chinese Journal of Chromatography, ;2014, 32(12): 1390-1399. doi: 10.3724/SP.J.1123.2014.09005 shu

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 Zhaoyun ^1,2 ,
MOU Renxiang ^1,2 ,
WU Li ^1,2 ,
LIN Xiaoyan ^1,2 ,
ZHU Zhiwei ^1,2 ,
CHEN Mingxue ^1,2,,

1.
1. Rice Product Quality Inspection and Supervision Center, Ministry of Agriculture, China National Rice Research Institute, Hangzhou 310006, China;

Corresponding author: CHEN Mingxue,
Received Date: 3 September 2014
Available Online: 13 October 2014
Fund Project: 国家粮油作物产品质量安全风险评估项目(GJFP2014006). (GJFP2014006)

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.
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