Research Progress of Electronic Nose and Near-Infrared Spectroscopy in Meat Adulteration Detection

Author:

Sun Xu12,Wang Songlin1,Jia Wenshen2

Affiliation:

1. College of Mechanical Engineering and Automation, Liaoning University of Technology, Jinzhou 121001, China

2. Institute of Quality Standards and Testing Technology, Beijing Municipal Academy of Agriculture and Forestry, Beijing 100097, China

Abstract

China is a large consumer of meat and meat products. People’s daily diets include a variety of meat, but meat food adulteration problems are common. This paper discusses the research progress of the electronic nose and near-infrared spectroscopy in the field of meat adulteration detection. Through the study of dozens of related papers in recent years, it has been found that the use of the electronic nose and near-infrared spectroscopy for meat detection has the advantages of speed, a nondestructive nature, high sensitivity, strong quantitative analysis, high automation, a wide applicability, an improved product quality, and cost reduction over the traditional detection, but it may be limited in detecting the adulteration of a specific meat, and there are issues with the life and stability of the sensors of the electronic nose in the process of detection, along with the problems of the high requirements for the modeling of the data of near-infrared spectroscopy. This paper takes adulterated meat as the research object and briefly summarizes the detection principles of the electronic nose and near-infrared spectroscopy, as well as the types of sensors applied in the electronic nose. The research progress of the electronic nose and near-infrared detection technology in meat adulteration assessment is reviewed, the advantages and disadvantages of the two in practical application are analyzed, the classification of pattern recognition methods and their applications in meat identification are described, and the feasibility and practical significance of the joint application of the two in meat adulteration detection are envisioned. Meanwhile, the challenges faced by the two in meat detection are pointed out.

Funder

Key Research and Development Projects of Hebei Province

Innovative Entrepreneurial Team Project of Anhui Institute of Innovation for Industrial Technology

Capacity Building Project of Beijing Academy of Agriculture and Forestry Sciences

National Natural Science Foundation of China

Surface Project of Liaoning Provincial Department of Education

Publisher

MDPI AG

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