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作 者:胡明友[1] 邵国建 王晔 任泽宇 徐玲珍 HU Ming-you;SHAO Guo-jian;WANG Ye;REN Ze-yu;XU Ling-zhen(Huzhou Municipal Center for Disease Control and Prevention,Huzhou,Zhejiang 313000,China)
机构地区:[1]湖州市疾病预防控制中心,浙江湖州313000
出 处:《中国卫生检验杂志》2022年第18期2211-2214,共4页Chinese Journal of Health Laboratory Technology
摘 要:目的建立高效、灵敏的测定蔬菜和水果中22种农药残留的检测方法。方法GC-MSMS结合QuEChERS前处理方法,应用(LVI-PTV)程序升温大体积进样技术,优化了进样溶剂种类等参数,加入环氧七氯内标以进行质量控制,并确定最佳提取条件;采用GC-MSMS进行分析,采用专用的大体积进样衬管,这使进样体积高达10μl,利用程序升温汽化,以提高对农药残留的检测灵敏度。结果使用特殊的进样技术,进样体积为10μl时,对农药残留的检测相比传统不分流进样,平均灵敏度提高了5倍;22种农药残留在0.005 mg/kg~0.20 mg/kg,线性相关系数都在0.999以上、精密度<5.0%(n=6),低浓度(0.005 mg/kg)、中浓度(0.020 mg/kg)、高浓度(0.10 mg/kg)的回收率分别为71.6%~94.1%、73.6%~104.0%、82.3%~99.8%,各组分检出限在0.00044 mg/kg~0.0083 mg/kg。结论本方法是一种非常灵敏、高效的检测方法,能够满足日常样品的检测要求。Objective To establish an efficient and sensitive method for the determination of 22 pesticide residues in vegetables and fruits.Methods Gas chromatography-mass spectrometry(GC-MSMS)was coupled with QuEChERS pretreatment method,technique of programmed temperature large volume solvent injection(LVI-PTV)was used,the parameters such as the type of injection solvent were optimized,and the internal standard Epoxy Heptachlor was added for quality control;GC-MSMS was used for the analysis,and a special large-volume injection liner was used.This makes the injection sample volume up to 10μl,and the temperature programmed vaporization was used to improve the detection sensitivity of pesticide residues.Results When the injection volume was 10μl,the average sensitivity of the detection of agricultural residues was increased by about 5 times compared with the traditional non-split injection.In the range of 0.005 mg/kg-0.20 mg/kg,the linear correlation coefficient(r)was above 0.999 and the precision was<5.0%(n=6).The recoveries of low concentration(0.005 mg/kg),medium concentration(0.020 mg/kg)and high concentration(0.10 mg/kg)were 71.6%-94.1%,73.6%-104.0%and 82.3%-99.8%,respectively.The detection limit of each component was 0.00044 mg/kg-0.0083 mg/kg.Conclusion This method is very sensitive and efficient,and can meet the requirements of the daily samples detection.
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