Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Veterinary Medicine, China Agricultural University, Beijing 100193, China; email:
NHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing 100022, China.
Annu Rev Food Sci Technol. 2019 Mar 25;10:429-455. doi: 10.1146/annurev-food-032818-121233. Epub 2019 Jan 17.
Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry-based technologies, including gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis-mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry-based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.
在食品安全和完整性领域,非靶向性的化学危害分析方法非常可取,以确保人类健康。非靶向代谢组学和化学数据库筛选这两种不同的分析策略可用于筛选食品基质中的未知污染物。为了检测化合物以及随后的成分化和候选离子的解释,需要足够的质量和色谱分辨率。基于分析化学的技术,包括气相色谱-质谱联用 (GC-MS)、液相色谱-质谱联用 (LC-MS)、核磁共振 (NMR) 和毛细管电泳-质谱联用 (CE-MS),结合化学计量学分析,可用于生成感兴趣化合物的分子公式。化学数据库的构建在非靶向检测中起着至关重要的作用。本文综述了当前用于分析复杂食品基质的样品制备、基于分析化学的技术以及数据分析,以及非靶向检测方法的局限性和挑战。样品制备和分析平台的改进可能会提高食品真实性、质量和安全性的相关性。