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高效液相色谱法测定中药材氨基甲酸酯类农药残留
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  • 英文篇名:Determination of N-Methyl Carbamate Pesticides in Traditional Chinese Herbal Medicines by HPLC
  • 作者:郭新颖 ; 顾俊 ; 陈峰 ; 史玉坤 ; 杨梅桂 ; 戴志英 ; 杨清华 ; 谢超
  • 英文作者:GUO Xin-ying;GU Jun;CHEN Feng;SHI Yu-kun;YANG Mei-gui;DAI Zhi-ying;YANG Qing-hua;XIE Chao;Nantong Center for Disease Control and Prevention;
  • 关键词:中药材 ; 氨基甲酸酯农药 ; 高效液相色谱 ; 农药残留
  • 英文关键词:Chinese herbal medicine;;carbamate pesticides;;HPLC;;pesticide residues
  • 中文刊名:NYZZ
  • 英文刊名:Agrochemicals
  • 机构:南通市疾病预防控制中心;
  • 出版日期:2019-05-10
  • 出版单位:农药
  • 年:2019
  • 期:v.58
  • 基金:南通市卫生和计划生育委员会科研课题专项(WKZL2018084)
  • 语种:中文;
  • 页:NYZZ201905014
  • 页数:3
  • CN:05
  • ISSN:21-1210/TQ
  • 分类号:45-47
摘要
[目的]建立测定中药材中N-甲基氨基甲酸酯类农药残留量的高效液相色谱-柱后衍生-荧光检测分析方法。[方法]样品经乙腈-水超声提取,经无水硫酸钠-PSA柱吸附净化,用液相色谱法进行定量测定。[结果]6种N-甲基氨基甲酸酯类农药标准曲线线性关系良好,相关系数r为0.996~0.999,检出限为0.01~0.02 mg/kg,在3个加标水平下,6种农药的平均回收率为83.3%~107.5%,相对标准偏差为2.5%~11.3%。[结论]该方法准确、快速、净化效果好,可满足农药残留的检测要求。
        [Aims] The aims were to establish a method for determination of N-methyl carbamate pesticide residues in Chinese herbal medicine by HPLC-post column derivatization-fluorescence detection. [Methods] The samples were extracted with acetonitrile-water, purified with anhydrous sodium sulfate-PSA, and quantified by HPLC. [Results] The linear relationship for six kinds of N-methyl carbamate pesticide was good, the correlation coefficient was 0.996-0.999,the limit of detection was 0.01-0.02 mg/kg, the average recoveries of the 6 pesticides at the 3 spiked levels were83.3-107.5%, the relative standard deviation was 2.5-11.3%. [Conclusions] The method is accurate, rapid, and has good purification effect, which can meet the requirements of pesticide residue detection.
引文
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    [2]黄霞,刘芳,聂立,等.高效液相色谱法测定牛奶中速灭威、克百威、异丙威农药残留[J].中国酿造, 2017(1):168-170.
    [3]李少军,付格红,窦延光.高效液相色谱仪检测食用林产品中10种氨基甲酸酯农药残留方法的优化[J].食品安全导刊, 2016(24):93-94.
    [4]魏茹霞.茶叶中多种农药残留的液相色谱-串联质谱法测定分析[J].科技展望, 2017, 27(1):79-178.
    [5]刘姣,刘雪峰,樊宝娟,等. GC-MS法测定18种药材中的农药残留量[J].西北药学杂志, 2017, 32(1):9-13.
    [6]方翠芬,李文庭,陈碧莲,等. GC-MS/MS法同时测定枸杞子中23种农药残留量[J].药物分析杂志, 2016(11):2009-2015.

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