Spectroscopic techniques combined with chemometrics for rapid detection of food adulteration: Applications, perspectives, and challenges.

Journal: Food research international (Ottawa, Ont.)
Published Date:

Abstract

Food adulteration is an important threat to food safety and can be difficult to detect. Some analytical methods are complex and difficult to meet the needs of large numbers of samples. In this study, we introduced the application of six spectroscopic techniques (NIR, FTIR, HSI, Raman, UV-Vis, and FS) and chemometric methods in common food adulteration (powdered food, meat, honey, drink, edible oil, and dairy product) over the last three years. We introduced the consequences of food adulteration, the principles, advantages, and limitations of spectroscopic techniques, spectral data preprocessing and key wavelength selection methods, chemometrics methods, dataset division methods, and evaluation methods for models. Moreover, it provided a perspective for the future application of spectroscopic techniques in food adulteration. The results showed that linear chemometric methods were still the main method used by many researchers, which may limit the application potential of spectroscopic techniques. Therefore, deep learning-based chemometrics methods and their interpretability should be further explored in food adulteration. Secondly, data fusion and ensemble models based on multiple spectroscopic techniques and chemometrics can further improve the accuracy of the models. Future research should select appropriate spectroscopic techniques based on food type and spectroscopic principles, and consider portable technical solutions wherever possible to improve the application scenarios of spectroscopic techniques.

Authors

  • Shijie Shi
    College of Agriculture, Yangtze University, Hubei, China; MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River, Yangtze University, China. Electronic address: shi.shijie@yangtzeu.edu.cn.
  • Kaidi Zhang
    Department of Nephrology, The First Hospital of Hebei Medical University, Shijiazhuang City, China.
  • Nina Tian
    College of Agriculture, Yangtze University, Hubei, China.
  • Zhaoqiang Jin
    College of Agriculture, Yangtze University, Hubei, China; MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River, Yangtze University, China.
  • Ke Liu
    State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102, P.R. China.
  • Liying Huang
    College of Food Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
  • Xiaohai Tian
    College of Agriculture, Yangtze University, Hubei, China; MARA Key Laboratory of Sustainable Crop Production in the Middle Reaches of the Yangtze River, Yangtze University, China.
  • Cougui Cao
    College of Plant Science & Technology, Huazhong Agricultural University, Hubei, China; Shuangshui Shuanglü Institute, Huazhong Agricultural University, Wuhan, Hubei, China.
  • Yunbo Zhang
    Laboratory of Industrial Biotechnology of Department of Education, Jiangnan University, Wuxi 214122, Jiangsu, China.
  • Yang Jiang
    Department of Ophthalmology Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences Beijing People's Republic of China.