[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5851/kosfa.2021.e25

A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies

Shi, Yinyan (Department of Agricultural and Biosystems Engineering, North Dakota State University)
Wang, Xiaochan (College of Engineering, Nanjing Agricultural University)
Borhan, Md Saidul (Department of Agricultural and Biosystems Engineering, North Dakota State University)
Young, Jennifer (Department of Animal Sciences, North Dakota State University)
Newman, David (Department of Animal Science, Arkansas State University)
Berg, Eric (Department of Animal Sciences, North Dakota State University)
Sun, Xin (Department of Agricultural and Biosystems Engineering, North Dakota State University)

Publication Information

Food Science of Animal Resources / v.41, no.4, 2021 , pp. 563-588 More about this Journal

Abstract

Increasing meat demand in terms of both quality and quantity in conjunction with feeding a growing population has resulted in regulatory agencies imposing stringent guidelines on meat quality and safety. Objective and accurate rapid non-destructive detection methods and evaluation techniques based on artificial intelligence have become the research hotspot in recent years and have been widely applied in the meat industry. Therefore, this review surveyed the key technologies of non-destructive detection for meat quality, mainly including ultrasonic technology, machine (computer) vision technology, near-infrared spectroscopy technology, hyperspectral technology, Raman spectra technology, and electronic nose/tongue. The technical characteristics and evaluation methods were compared and analyzed; the practical applications of non-destructive detection technologies in meat quality assessment were explored; and the current challenges and future research directions were discussed. The literature presented in this review clearly demonstrate that previous research on non-destructive technologies are of great significance to ensure consumers' urgent demand for high-quality meat by promoting automatic, real-time inspection and quality control in meat production. In the near future, with ever-growing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.

Keywords

meat quality; non-destructive detection; key technology; grading assessment; industrial application;

Citations & Related Records

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