A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition.

Journal: Molecules (Basel, Switzerland)
Published Date: Feb 1, 2021

Abstract

Near-infrared spectroscopy (NIRS) combined with pattern recognition technique has become an important type of non-destructive discriminant method. This review first introduces the basic structure of the qualitative analysis process based on near-infrared spectroscopy. Then, the main pretreatment methods of NIRS data processing are investigated. Principles and recent developments of traditional pattern recognition methods based on NIRS are introduced, including some shallow learning machines and clustering analysis methods. Moreover, the newly developed deep learning methods and their applications of food quality analysis are surveyed, including convolutional neural network (CNN), one-dimensional CNN, and two-dimensional CNN. Finally, several applications of these pattern recognition techniques based on NIRS are compared. The deficiencies of the existing pattern recognition methods and future research directions are also reviewed.

Authors

  • Jian Zeng
    Longgang District Central Hospital of Shenzhen Shenzhen China.
  • Yuan Guo
    Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.
  • Yanqing Han
    Xi'an Jiaotong University City College, Xi'an, China.
  • Zhanming Li
    School of Grain Science and Technology, Jiangsu University of Science and Technology, Zhenjiang 212004, Jiangsu, PR China; College of Life Sciences, China Jiliang University, Hangzhou 310018, PR China. Electronic address: lizhanming@cjlu.edu.cn.
  • Zhixin Yang
    State Key Laboratory of Internet of Things for Smart City, Faculty of Science and Technology, University of Macau, Macau, China.
  • Qinqin Chai
    College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.
  • Wu Wang
    College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350108, China.
  • Yuyu Zhang
    Beijing Key Laboratory of Flavor Chemistry, Beijing Technology and Business University (BTBU), Beijing 100048, China.
  • Caili Fu
    College of Biological Sciences and Engineering & Key Laboratory for Analytic Science of Food Safety and Biology (MOE & Fujian Province), Department of Chemistry, Fuzhou University, Fuzhou, 350116, PR China. Electronic address: caili_fu@hotmail.com.

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