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| 基于人工智能的无损检测技术在猪肉品质评价中应用研究进展 |
| Research progress on pork quality evaluation Methods Based on Artificial Intelligence Technologies |
| 投稿时间：2025-02-24 修订日期：2025-06-25 |
| DOI： |
| 中文关键词: 猪肉品质 人工智能 无损检测；品质评价 |
| 英文关键词:pork quality Artificial intelligence Non-destructive testing quality evaluation |
| 基金项目:枣庄市自主创新及成果转化计划项目（2024GH03）、山东省重大科技创新工程项目(2023CXGC0214) |
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| 中文摘要: |
| 猪肉品质是猪的重要经济性状,快速准确开展猪肉品质评价,对于猪肉加工和贸易至关重要。近年来,随着人工智能算法与传感器技术的协同突破,基于人工智能的猪肉品质无损检测技术已成为近年来的研究热点,并在肉类行业得到了广泛应用。开展数字图像处理技术与人工智能学习算法相结合,多传感器数据相融合技术研究,实现猪肉产品加工全程质量的自动化、实时检测,是未来肉品质量安全无损检测的重要研究方向。本文综述了当前主要的猪肉品质无损检测关键技术，包括近红外光谱、高光谱成像、拉曼光谱、荧光光谱技术、太赫兹光谱、电子鼻/电子舌技术和计算机视觉系统,阐述了不同技术的原理、特点和应用现状,并对不同技术存在的不足和未来的发展方向进行了讨论和展望,旨在为无损检测技术在猪肉品质评价中的应用提供参考。 |
| 英文摘要: |
| 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 (AI) 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 review summarized key non-destructive technologies for pork quality assessment: Near-infrared spectroscopy, Hyperspectral imaging, Raman spectroscopy, Fluorescence spectroscopy, Terahertz spectroscopy, Electronic nose/tongue technology, Computer vision systems. It elucidated the operational principles, technical characteristics, and application status of these methodologies while critically analyzing their limitations and future developmental trajectories. This synthesis aims to provide a reference for advancing non-destructive technologies in pork quality evaluation. |
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