摘要
目的建立自动QuEChERS结合气相色谱-串联质谱法(gas chromatography-tandem mass spectrometry,GC-MS/MS)快速测定花生油中172种农药残留的分析方法。方法花生油样品加水后,加入15 mL乙腈提取,放入自动QuEChERS前处理设备,以N-丙基乙二胺(primary secondary amine,PSA)和十八烷基硅烷键合硅胶(C18)为填料进行净化。HP-5MS UI气相色谱柱分离,在多重反应监测(multiple reaction monitoring,MRM)模式下进行测定,采用基质匹配外标法进行定量。结果172种农药的相关系数(r^(2))均大于0.995,线性关系良好,检出限为1~5μg/kg,定量限为2~10μg/kg在10、50和100μg/kg 3个添加水平下,平均回收率在70.1%~112.8%、72.6%~114.3%、71.8%~114.9%范围内,相对标准偏差(relative standard deviation,RSD)均小于15.0%(n=6)。结论该方法操作简单,灵敏高效,能够满足花生油中多种农药残留检测的需求,也可以为复杂基质的自动化前处理提供参考。
Objective To establish a rapid method for the determination of 172 kinds of pesticide residues in peanut oil by gas chromatography-tandem mass spectrometry(GC-MS/MS)combined with automatic QuEChERS.Methods The peanut oils samples were added with water,then extracted with 15 mL acetonitrile.The solution was purified by primary secondary amine(PSA)and C18 with puting into the automatic QuEChERS pretreatment equipment.Pesticides were separated by an HP-5 MS UI gas chromatographic column,determined on multiple reaction monitoring(MRM)mode and quantified by matrix matching external standard method.Results All pesticides had a good linearity with the correlation coefficients(r^(2))greater than 0.995.The limits of detection and the limits of quantitation were 1-5μg/kg and 2-10μg/kg,respectively.At 3 kinds of spiked levels of 10,50 and 100μg/kg,the average recoveries of 172 kinds of pesticides were 70.1%-112.8%,72.6%-114.3%,and 71.8%-114.9%,respectively,the relative standard deviations(RSDs)were less than 15%(n=6).Conclusion This method is simple,sensitive and efficient.It can meet the needs of the determination of a variety of pesticide residues in peanut oil.At the same time,it provides a reference for automatic pretreatment of complex matrixes.
作者
蒋康丽
扈斌
吴兴强
崔宗岩
谢瑜杰
范春林
王明林
陈辉
连玉晶
吕美玲
王雯雯
JIANG Kang-Li;HU Bin;WU Xing-Qiang;CUI Zong-Yan;XIE Yu-Jie;FAN Chun-Lin;WANG Ming-Lin;CHEN Hui;LIAN Yu-Jing;LV Mei-Ling;WANG Wen-Wen(College of Food Science and Engineering,Shandong Agricultural University,Taian 271018,China;Agricultural Product Safety Research Center,Chinese Academy of Inspection and Quarantine,Beijing 100176,China;Technology Center of Qinhuangdao Customs,Qinhuangdao 066004,China;Agilent Technologies(China)Co.,Ltd.,Beijing 100102,China)
出处
《食品安全质量检测学报》
CAS
北大核心
2021年第17期6857-6864,共8页
Journal of Food Safety and Quality
基金
国家重点研发计划项目(2017YFF0211304)
中国检科院基本科研业务费项目(2020JK009)。