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KMID : 1024620210410040563
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Food Science of Animal Resources
2021 Volume.41 No. 4 p.563 ~ p.588
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A Review on Meat Quality Evaluation Methods Based on Non-Destructive Computer Vision and Artificial Intelligence Technologies
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Shi Yinyan
Wang Xiaochan
Borhan Md Saidul
Young Jennifer
Newman David
Berg Eric
Sun Xin
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Abstract
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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, realtime inspection and quality control in meat production. In the near future, with evergrowing application requirements and research developments, it is a trend to integrate such systems to provide effective solutions for various grain quality evaluation applications.
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KEYWORD
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meat quality, non-destructive detection, key technology, grading assessment, industrial application
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