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使用液相色谱与高分辨率质谱联用技术对食品中的污染物和掺假物进行非靶向筛查方法。

Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry.

作者信息

Knolhoff Ann M, Croley Timothy R

机构信息

U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5100 Paint Branch Parkway, College Park, MD 20740, United States.

U.S. Food and Drug Administration, Center for Food Safety and Applied Nutrition, 5100 Paint Branch Parkway, College Park, MD 20740, United States.

出版信息

J Chromatogr A. 2016 Jan 8;1428:86-96. doi: 10.1016/j.chroma.2015.08.059. Epub 2015 Aug 31.

Abstract

The majority of analytical methods for food safety monitor the presence of a specific compound or defined set of compounds. Non-targeted screening methods are complementary to these approaches by detecting and identifying unexpected compounds present in food matrices that may be harmful to public health. However, the development and implementation of generalized non-targeted screening workflows are particularly challenging, especially for food matrices due to inherent sample complexity and diversity and a large analyte concentration range. One approach that can be implemented is liquid chromatography coupled to high-resolution mass spectrometry, which serves to reduce this complexity and is capable of generating molecular formulae for compounds of interest. Current capabilities, strategies, and challenges will be reviewed for sample preparation, mass spectrometry, chromatography, and data processing workflows. Considerations to increase the accuracy and speed of identifying unknown molecular species will also be addressed, including suggestions for achieving sufficient data quality for non-targeted screening applications.

摘要

大多数食品安全分析方法用于监测特定化合物或一组特定化合物的存在。非靶向筛选方法通过检测和识别食品基质中可能对公众健康有害的意外化合物,对这些方法起到补充作用。然而,通用非靶向筛选工作流程的开发和实施极具挑战性,尤其是对于食品基质而言,这是由于其固有的样品复杂性和多样性以及分析物浓度范围较大。一种可以实施的方法是液相色谱与高分辨率质谱联用,这有助于降低这种复杂性,并能够为感兴趣的化合物生成分子式。本文将对样品制备、质谱分析、色谱分析和数据处理工作流程的当前能力、策略和挑战进行综述。还将讨论提高识别未知分子物种准确性和速度的注意事项,包括为非靶向筛选应用获得足够数据质量的建议。

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