Non-Destructive Techniques for the Analysis and Evaluation of Meat Quality and Safety: A Review

• Published in: Foods Vol. 11; no. 22; p. 3713
• Main Authors: Wu, Xiaohong, Liang, Xinyue, Wang, Yixuan, Wu, Bin, Sun, Jun
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 18.11.2022; MDPI
• Subjects: Accuracy; Chemical composition; Dietary minerals; Discriminant analysis; Electronic noses; Food; Food adulteration and inspection; Food research; Food safety; Food science; Forecasts and trends; hyperspectral imaging; Imaging techniques; Interdisciplinary subjects; Machine vision; Meat; Meat products; Meat quality; Methods; near-infrared spectroscopy; non-destructive detection; Nondestructive testing; Nutritive value; Proteins; Quality; Quality assessment; Quantitative analysis; Raman spectroscopy; Review; Safety; Spectrum analysis; China; meat quality; non-destructive detection; near-infrared spectroscopy; Raman spectroscopy; hyperspectral imaging
• ISSN: 2304-8158; 2304-8158
• DOI: 10.3390/foods11223713

With the continuous development of economy and the change in consumption concept, the demand for meat, a nutritious food, has been dramatically increasing. Meat quality is tightly related to human life and health, and it is commonly measured by sensory attribute, chemical composition, physical and chemical property, nutritional value, and safety quality. This paper surveys four types of emerging non-destructive detection techniques for meat quality estimation, including spectroscopic technique, imaging technique, machine vision, and electronic nose. The theoretical basis and applications of each technique are summarized, and their characteristics and specific application scope are compared horizontally, and the possible development direction is discussed. This review clearly shows that non-destructive detection has the advantages of fast, accurate, and non-invasive, and it is the current research hotspot on meat quality evaluation. In the future, how to integrate a variety of non-destructive detection techniques to achieve comprehensive analysis and assessment of meat quality and safety will be a mainstream trend.