“Raman plus X” dual-modal spectroscopy technology for food analysis: A review

IF 12 1区 农林科学 Q1 FOOD SCIENCE & TECHNOLOGY
Lixin Ma, Xiaonan Yang, Shanshan Xue, Ruiyun Zhou, Chen Wang, Zhiming Guo, Yansong Wang, Jianrong Cai
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引用次数: 0

Abstract

Raman spectroscopy, a nondestructive optical technique that provides detailed chemical information, has attracted growing interest in the food industry. Complementary spectroscopic methods, such as near-infrared (NIR) spectroscopy, nuclear magnetic resonance (NMR), terahertz (THz) spectroscopy, laser-induced breakdown spectroscopy (LIBS), and fluorescence spectroscopy (Flu), enhance Raman spectroscopy's capabilities in various applications. The integration of Raman with these techniques, termed “Raman plus X,” has shown significant potential in agri-food analysis. This review highlights the latest advances and applications of dual-modal spectroscopy methods combining Raman spectroscopy with NIR, NMR, THz, LIBS, and Flu in food analysis. Key applications include detecting harmful contaminants, evaluating food quality, identifying adulteration, and characterizing structure. The synergistic use of Raman-based dual-modal spectroscopy provides more comprehensive information and improves modeling accuracy compared to single techniques. The review also explores the role of data fusion in multisource spectral analysis and discusses challenges and prospects of “Raman plus X,” including the development of integrated hardware and advanced data fusion algorithms. These advancements aim to streamline multisource data analysis, offering valuable insights to select appropriate analytical methods for practical applications in the food industry.

食品分析用“拉曼加X”双峰光谱技术综述。
拉曼光谱是一种提供详细化学信息的非破坏性光学技术,在食品工业中引起了越来越多的兴趣。互补的光谱方法,如近红外(NIR)光谱、核磁共振(NMR)、太赫兹(THz)光谱、激光诱导击穿光谱(LIBS)和荧光光谱(Flu),增强了拉曼光谱在各种应用中的能力。将拉曼与这些技术相结合,称为“拉曼加X”,在农业食品分析中显示出巨大的潜力。本文综述了拉曼光谱与近红外、核磁共振、太赫兹、LIBS、流感等双峰光谱技术在食品分析中的最新进展及应用。主要应用包括检测有害污染物,评估食品质量,识别掺假和表征结构。与单一技术相比,基于拉曼的双峰光谱的协同使用提供了更全面的信息,提高了建模精度。该综述还探讨了数据融合在多源光谱分析中的作用,并讨论了“拉曼加X”的挑战和前景,包括集成硬件和先进数据融合算法的发展。这些进步旨在简化多源数据分析,为食品工业的实际应用选择适当的分析方法提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
26.20
自引率
2.70%
发文量
182
期刊介绍: Comprehensive Reviews in Food Science and Food Safety (CRFSFS) is an online peer-reviewed journal established in 2002. It aims to provide scientists with unique and comprehensive reviews covering various aspects of food science and technology. CRFSFS publishes in-depth reviews addressing the chemical, microbiological, physical, sensory, and nutritional properties of foods, as well as food processing, engineering, analytical methods, and packaging. Manuscripts should contribute new insights and recommendations to the scientific knowledge on the topic. The journal prioritizes recent developments and encourages critical assessment of experimental design and interpretation of results. Topics related to food safety, such as preventive controls, ingredient contaminants, storage, food authenticity, and adulteration, are considered. Reviews on food hazards must demonstrate validity and reliability in real food systems, not just in model systems. Additionally, reviews on nutritional properties should provide a realistic perspective on how foods influence health, considering processing and storage effects on bioactivity. The journal also accepts reviews on consumer behavior, risk assessment, food regulations, and post-harvest physiology. Authors are encouraged to consult the Editor in Chief before submission to ensure topic suitability. Systematic reviews and meta-analyses on analytical and sensory methods, quality control, and food safety approaches are welcomed, with authors advised to follow IFIS Good review practice guidelines.
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