化学计量学
拉曼光谱
表面增强拉曼光谱
食品质量
食品安全
计算机科学
分析物
生化工程
生物系统
化学
环境科学
分析化学(期刊)
环境化学
机器学习
食品科学
色谱法
拉曼散射
工程类
物理
生物
光学
作者
Jingjing Wang,Quansheng Chen,Tarun Belwal,Xingyu Lin,Zisheng Luo
标识
DOI:10.1111/1541-4337.12741
摘要
Raman spectroscopy and surface-enhanced Raman spectroscopy (SERS) have been extensively explored in the design of accurate, transparent, and conclusive food safety and quality control assays. Its hyphenation with chemometric algorithms is instrumental in securing safe food campaigns. To provide valuable recommendations and meet the growing demands for food screening, the current study begins with a brief description of the Raman spectroscopy and SERS theory followed by a comprehensive overview of spectral preprocessing, qualitative algorithms, variable selection methods, and quantitative algorithms. The review emphasizes on the importance of food monitoring practices using multivariate regression models. The applicability of the distinct chemometrics modes toward monitoring pesticide, food and illicit additives, heavy metals, pathogens, and its metabolites in Raman spectroscopy and SERS is covered in dairy, poultry, oil, honey, beverages, and other selected food matrices. Its pertinence toward classification and/or discrimination in food quality and safety monitoring and authentication is examined. Finally, it also complies with the limitations, key challenges, and prospects. The chemometrics processing spectra implemented with simpler or no complicated sample pretreatment step make Raman spectroscopy/SERS technique a potential approach that is expected to achieve simultaneous and fast detection of multiple analytes in food matrices.
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