摘要
建立了超高压液相色谱-高分辨质谱同时筛查蓝莓中90种农药残留的方法。采用改良的QuEChERS方法提取目标物残留,超高压液相色谱-四极杆/离子回旋轨道阱高分辨质谱正负离子模式全扫描-数据依赖性碎片离子采集,代表性基质匹配标准工作曲线定量。结果显示:改良的QuEChERS净化填料中,PSA和C_(18)净化粉的用量均在150 mg时净化效果最好;方法检出限和定量限分别为0.1~18.7μg/kg和0.2~20.2μg/kg,90种农药在0.005~0.1 mg/kg范围内,线性关系良好,决定系数R^(2)≥0.992;在0.01、0.05和0.1 mg/kg浓度水平进行基质添加回收实验,回收率50.1%~130.9%,相对标准偏差为1.0%~14.9%。在对实际样品的筛查中,检测到5种农药残留显示了方法的实际应用效能。本方法前处理简便、目标分析物覆盖范围广、在筛查定量基础上可同时完成高精度定性分析,可有效用于蓝莓中常用农药残留的监测。
A method for simultaneous screening of 90 pesticide residues in blueberries by ultra-high pressure liquid chromatography high resolution mass spectrometry was developed.Target residues in blueberries were extracted by an improved QuEChERS protocol.Ultra-high pressure liquid chromatography coupled to quadrupole/orbitrap high-resolution mass spectrometry was employed for screening analysis with full mass scanning trigged data dependent fragment ion acquisition in positive and negative mode.The analytes were quantified by representative matrix-matched standard curve.The results showed that the optimized ratio of PSA vs C_(18)was 1:1 with amount of 150 mg respectively in the improved QuEChERS protocol.The limits of detection and limits of quantitation of the method were 0.1~18.7μg/kg and 0.2~20.2μg/kg as well.The linearities for 90 pesticides were fitted by regression calculation at the range of 0.005~0.1 mg/kg with determination coefficient R^(2)≥0.992.With calibration of the representative matrix-matched standard curve,recoveries were calculated ranging from 50.1%to 130.9%and relative standard deviations were varied in the scope of 1.0%~14.9%at the three spiking levels of 0.01,0.05 and 0.1 mg/kg.Five pesticides were detected in the real-life blueberry samples purchased in the market,evidencing the applicability of the developed method.The proposed approach is applicable for routine pesticide monitoring in blueberries with simple sample preparation,broad analyte coverage and powerful capability of quantification and qualification.
作者
邵影
张鸿伟
高瑞刚
韩芳
杨帆
林超
李明哲
聂晨
张晓梅
赵雪
SHAO Ying;ZHANG Hongwei;GAO Ruigang;HAN Fang;YANG Fan;LIN Chao;LI Mingzhe;NIE Chen;ZHANG Xiaomei;ZHAO Xue(Ocean University of China,College of Food Science and Engineering,Qingdao 266100,China;Technology Center of Qingdao Customs District,Qingdao 266109,China;Technology Center of Hefei Customs District,Hefei 230022,China)
出处
《食品工业科技》
CAS
北大核心
2023年第5期230-240,共11页
Science and Technology of Food Industry
基金
青岛市民生科技计划项目(18-6-1-107-nsh)
青岛海关科研项目(QK202017)。
关键词
蓝莓
农药残留
高分辨质谱
筛查
基质效应
blueberry
pesticide
high resolution mass spectrometry
screening
matrix effect
