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Raman spectroscopy technique has 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. The book 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 is covered in poultry, oil, beverages, and other selected food…mehr

Produktbeschreibung
Raman spectroscopy technique has 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. The book 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 is covered in poultry, oil, beverages, and other selected food matrices. Its pertinence toward 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 technique a potential approach that is expected to achieve simultaneous and fast detection of multiple analytes in food matrices.
Autorenporträt
Congli Mei is a full professor in Zhejiang University of Water Resources and Electric Power and holds a PhD in Control Science and Engineering from Zhejiang University. His area of research includes the study of soft sensor technology. He also lectures and supervises master degree students; and has to his credit several publications and awards.