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基于表面增强拉曼光谱的食品中农药残留快速现场痕量检测

Rapid field trace detection of pesticide residue in food based on surface-enhanced Raman spectroscopy.

作者信息

Zhang De, Liang Pei, Chen Wenwen, Tang Zhexiang, Li Chen, Xiao Kunyue, Jin Shangzhong, Ni Dejiang, Yu Zhi

机构信息

College of Horticulture & Forestry Sciences, Key Laboratory of Horticultural Plant Biology, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China.

College of Optical and Electronic Technology, China Jiliang University, Hangzhou, 310018, China.

出版信息

Mikrochim Acta. 2021 Oct 7;188(11):370. doi: 10.1007/s00604-021-05025-3.

Abstract

Surface-enhanced Raman spectroscopy is an alternative detection tool for monitoring food security. However, there is still a lack of a conclusion of SERS detection with respect to pesticides and real sample analysis, and the summary of intelligent algorithms in SERS is also a blank. In this review, a comprehensive report of pesticides detection using SERS technology is given. The SERS detection characteristics of different types of pesticides and the influence of substrate on inspection are discussed and compared by the typical ways of classification. The key points, including the progress in real sample analysis and Raman data processing methods with intelligent algorithm, are highlighted. Lastly, major challenges and future research trends of SERS analysis of pesticide residue are also addressed. SERS has been proven to be a powerful technique for rapid test of residue pesticides in complex food matrices, but there still is a tremendous development space for future research.

摘要

表面增强拉曼光谱是一种用于监测食品安全的替代检测工具。然而,关于农药的表面增强拉曼光谱检测及实际样品分析仍缺乏定论,表面增强拉曼光谱中智能算法的总结也是一片空白。在这篇综述中,给出了使用表面增强拉曼光谱技术进行农药检测的综合报告。通过典型的分类方式,讨论并比较了不同类型农药的表面增强拉曼光谱检测特性以及基底对检测的影响。重点突出了实际样品分析的进展以及采用智能算法的拉曼数据处理方法。最后,还探讨了农药残留表面增强拉曼光谱分析的主要挑战和未来研究趋势。表面增强拉曼光谱已被证明是一种用于快速检测复杂食品基质中残留农药的强大技术,但未来研究仍有巨大的发展空间。

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