Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review

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.

Keywords:

• Raman spectroscopy
• chemometrics
• muscle foods
• adulteration

Author contributions

Haiyang Ma: Data curation and writing-original draft. Jiajun Guo: Data curation, Monitored. Giushan Liu: Funding acquisition, Investigation, Guided the framework, Writing-review & editing. Delang Xie, Bingbing Zhang: Supervised the content. Xiaojun Li, Qian Zhang, Qingqing Cao: Supervised the content. Xiaoxue Li, Fang Ma, Yang Li: Data curation, Supervision. Guoling Wan, Yan Li, Di Wu, PingMa: Software, Supervision. Mei Guo, Junjie Yin: Validation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was financially supported by the Natural Science Foundation of Ningxia Hui Autonomous Region in 2022 [Grant No. 2022AAC03019], the leading Talent Project of Science and Technology Innovation in Ningxia Hui Autonomous Region in 2020 [Grant No. 2020GKLRLX05], the Science and Technology Planning Project of Yinchuan, Ningxia Province in 2022 [2022ZDNY05], and the National Natural Science Foundation of China in 2017 [Grant No. 31760435].