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Research progress on pork quality evaluation methods based on non-destructive artificial intelligence technologies
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Lei WANG1, Qing-Kai SHENG2, Hong-Shuai SUN3, Zhen CHEN4, Yan-Jie DONG1, Da CAI1, Shan-Cang ZHAO1, *
Journal of Food Safety & Quality | 2025, 16(14) : 79 - 88
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Journal of Food Safety & Quality | 2025, 16(14): 79-88
• Special Topic: Non-destructive Detection Technology in Food •
Research progress on pork quality evaluation methods based on non-destructive artificial intelligence technologies
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Lei WANG1, Qing-Kai SHENG2, Hong-Shuai SUN3, Zhen CHEN4, Yan-Jie DONG1, Da CAI1, Shan-Cang ZHAO1, *
Affiliations
  • 1 Institute of Quality Standard and Testing Technology for Agro-Products, Shandong Academy of Agricultural Sciences, Ji’nan 250100, China
  • 2 Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Ji’nan 250100, China
  • 3 Weifang Hairuihuachen Testing Technology Co., Ltd., Weifang 261071, China
  • 4 Shandong Futeng Food Co., Ltd., Zaozhuang 277100, China
Published: 2025-07-25 doi: 10.19812/j.cnki.jfsq11-5956/ts.20250224001
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Pork quality is an economically critical trait in swine production, necessitating rapid and accurate evaluation methods to optimize processing efficiency and ensure trade compliance. Recent advancements in artificial intelligence algorithms and sensor technologies have driven the development of non-destructive detection methods based on artificial intelligence, which are now widely applied in the meat industry. Integrating digital image processing with artificial intelligence learning algorithms and multi-sensor data fusion to achieve automated, real-time monitoring of pork quality throughout processing chains represents a pivotal research direction for ensuring meat safety and quality. This article summarized the current key technologies for non-destructive testing of pork quality, including near-infrared spectroscopy, hyperspectral imaging, Raman spectroscopy, fluorescence spectroscopy, terahertz spectroscopy, electronic nose/tongue technology and computer vision systems, elaborated the principles, characteristics and application status of different technologies, and discussed and forecasted the shortcomings and future development directions of different technologies, aiming to provide reference for the application of non-destructive testing technology in pork quality evaluation.

pork quality  /  artificial intelligence  /  non-destructive testing  /  quality evaluation
Lei WANG, Qing-Kai SHENG, Hong-Shuai SUN, Zhen CHEN, Yan-Jie DONG, Da CAI, Shan-Cang ZHAO. Research progress on pork quality evaluation methods based on non-destructive artificial intelligence technologies[J]. Journal of Food Safety & Quality, 2025 , 16 (14) : 79 -88 . DOI: 10.19812/j.cnki.jfsq11-5956/ts.20250224001
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doi: 10.19812/j.cnki.jfsq11-5956/ts.20250224001
  • Receive Date：2025-02-24
  • Online Date：2026-01-07
  • Published：2025-07-25
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  • Received：2025-02-24
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Affiliations
    1 Institute of Quality Standard and Testing Technology for Agro-Products, Shandong Academy of Agricultural Sciences, Ji’nan 250100, China
    2 Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Ji’nan 250100, China
    3 Weifang Hairuihuachen Testing Technology Co., Ltd., Weifang 261071, China
    4 Shandong Futeng Food Co., Ltd., Zaozhuang 277100, China
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表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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