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Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review.
Ma, Haiyang; Guo, Jiajun; Liu, Guishan; Xie, Delang; Zhang, Bingbing; Li, Xiaojun; Zhang, Qian; Cao, Qingqing; Li, Xiaoxue; Ma, Fang; Li, Yang; Wan, Guoling; Li, Yan; Wu, Di; Ma, Ping; Guo, Mei; Yin, Junjie.
Afiliação
  • Ma H; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Guo J; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Liu G; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Xie D; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Zhang B; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Li X; School of Electronic and Electrical Engineering, Ningxia University, Yinchuan, China.
  • Zhang Q; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Cao Q; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Li X; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Ma F; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Li Y; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Wan G; College of Food Science and Engineering, Ocean University of China, Qingdao, China.
  • Li Y; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Wu D; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Ma P; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Guo M; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
  • Yin J; School of Food Science and Engineering, Ningxia University, Yinchuan, Ningxia, China.
Crit Rev Food Sci Nutr ; : 1-23, 2024 Mar 24.
Article em En | MEDLINE | ID: mdl-38523442
ABSTRACT
Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Crit Rev Food Sci Nutr Assunto da revista: CIENCIAS DA NUTRICAO Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China
Texto completo
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Revista: Crit Rev Food Sci Nutr Assunto da revista: CIENCIAS DA NUTRICAO Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China