石焱芳,王 征.气相色谱-负化学离子源质谱法测定白菜中6种痕量农药残留[J].食品安全质量检测学报,2019,10(24):8509-8514
气相色谱-负化学离子源质谱法测定白菜中6种痕量农药残留
Determination of 6 trace pesticides in Chinese cabbage by gas chromatography-negative chemical ionization–mass spectrometry
投稿时间:2019-08-07  修订日期:2019-10-06
DOI:
中文关键词:  气相色谱-负化学离子源质谱法  农药残留  白菜  痕量
英文关键词:gas chromatography-negative chemical ionization-mass spectrometry  pesticide residue  Chinese cabbage  trace
基金项目:
作者单位
石焱芳 泉州医学高等专科学校 
王 征 福建省产品质量检验研究院 
AuthorInstitution
SHI Yan-Fang Quanzhou Medical College 
WANG Zheng Fujian Inspection and Research Institute for Product Quality 
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中文摘要:
      目的 建立一种气相色谱-负化学离子源质谱法(gas chromatography-negative chemical ionization-mass spectrometry, GC-NCI/MS)测定白菜中6种痕量农药残留的分析方法。方法 采用乙腈超声提取, Carb/氨丙基固相萃取柱净化, 酮麝香为内标物, 进行气相色谱–负化学离子源质谱分析检测。结果 6种农药残留在相应线性浓度范围内线性良好, 回归系数r2≥0.999, 不同浓度区间加标平均回收率在89.2%~111.5%, 相对标准偏差(relative standard deviation, RSD)为0.6%~12.7%。五氯硝基苯、百菌清、甲基对硫磷、α-硫丹、β-硫丹、硫丹硫酸酯6种农药残留检出下限分别为0.013、0.06、0.06、0.024、0.012、0.01 ng/mL。结论 该方法回收率高, 分离效果好, 灵敏度高, 检出下限低, 快速方便, 适用于实际蔬菜样品中多农药残留的痕量分析。
英文摘要:
      Objective To establish a method for the determination of 6 trace pesticides in Chinese cabbage by gas chromatography-negative chemical ionization-mass spectrometry (GC-NCI-MS). Methods Samples were ultrasonic extracted with acetonitrile, cleaned up on a carb/aminopropyl column, the internal standard used was musk ketone, then detected with gas chromatography–negative chemical ionization-mass spectrometry. Results The linearity of 6 pesticide residues is good in the corresponding linear concentration range. Within the relative range correlation coefficient r2≥0.999, the average recovery rates of 6 pesticides varied from 89.2% to 111.5%, with the relative standard deviations of 0.6%–12.7%.The detection limits of this method for nitrobenzene, chlorothalonil, methyl parathion, α-endosulfan, β-endosulfan and endosulfan sulfate were 0.013, 0.06, 0.06, 0.024, 0.012 and 0.01 ng/mL. Conclusion The established method has high accuracy and reproducibility, and the limit of detection is relatively low, which can meet the detection requirements of residues in vegetables.
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