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基于数据非依赖采集和化合物数据库的超高效液相色谱/电喷雾电离-四极杆-轨道阱质谱法对果蔬中448种农药残留进行靶向筛查的定性方法的开发与验证

Development and Validation of a Qualitative Method for Target Screening of 448 Pesticide Residues in Fruits and Vegetables Using UHPLC/ESI Q-Orbitrap Based on Data-Independent Acquisition and Compound Database.

作者信息

Wang Jian, Chow Willis, Chang James, Wong Jon W

机构信息

Canadian Food Inspection Agency, Calgary Laboratory , 3650-36th Street N.W., Calgary, Alberta T2L 2L1, Canada.

ThermoFisher Scientific , 355 River Oaks Parkway, San Jose, California 95134, United States.

出版信息

J Agric Food Chem. 2017 Jan 18;65(2):473-493. doi: 10.1021/acs.jafc.6b05034. Epub 2017 Jan 5.

DOI:10.1021/acs.jafc.6b05034
PMID:28002940
Abstract

A semiautomated qualitative method for target screening of 448 pesticide residues in fruits and vegetables was developed and validated using ultrahigh-performance liquid chromatography coupled with electrospray ionization quadrupole Orbitrap high-resolution mass spectrometry (UHPLC/ESI Q-Orbitrap). The Q-Orbitrap Full MS/dd-MS (data dependent acquisition) was used to acquire product-ion spectra of individual pesticides to build a compound database or an MS library, while its Full MS/DIA (data independent acquisition) was utilized for sample data acquisition from fruit and vegetable matrices fortified with pesticides at 10 and 100 μg/kg for target screening purpose. Accurate mass, retention time and response threshold were three key parameters in a compound database that were used to detect incurred pesticide residues in samples. The concepts and practical aspects of in-spectrum mass correction or solvent background lock-mass correction, retention time alignment and response threshold adjustment are discussed while building a functional and working compound database for target screening. The validated target screening method is capable of screening at least 94% and 99% of 448 pesticides at 10 and 100 μg/kg, respectively, in fruits and vegetables without having to evaluate every compound manually during data processing, which significantly reduced the workload in routine practice.

摘要

开发了一种用于水果和蔬菜中448种农药残留目标筛查的半自动定性方法,并使用超高效液相色谱-电喷雾电离四极杆轨道阱高分辨率质谱(UHPLC/ESI Q-Orbitrap)进行了验证。Q-Orbitrap全扫描/dd-MS(数据依赖型采集)用于获取各农药的产物离子谱,以建立化合物数据库或质谱库,而其全扫描/DIA(数据非依赖型采集)则用于从添加了浓度为10和100 μg/kg农药的水果和蔬菜基质中采集样品数据,用于目标筛查。精确质量、保留时间和响应阈值是化合物数据库中用于检测样品中残留农药的三个关键参数。在构建用于目标筛查的功能正常且可运行的化合物数据库时,讨论了谱内质量校正或溶剂背景锁定质量校正、保留时间校准和响应阈值调整的概念及实际操作。经过验证的目标筛查方法能够分别在水果和蔬菜中筛查出448种农药中的至少94%和99%(添加浓度分别为10和100 μg/kg),在数据处理过程中无需人工评估每一种化合物,这显著减少了日常工作中的工作量。

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