国家近期提出“人工智能＋”战略，机器视觉技术（machine vision technology，MVT）作为人工智能的“眼睛”，在多个领域展现出广泛的应用潜力。系统综述了MVT在中药材全产业链中的应用现状。通过采集常规视觉图像与多源光谱视觉图像，并结合传统机器学习与深度学习算法，MVT已广泛用于中药材种子质量评价与分选、种植环境适宜性分析与区划、植株生长监测与田间管理、采收决策、产地初加工控制及产品质量评价等关键环节，显著提升了生产过程的智能化水平和质量管控能力。然而，当前MVT在中药材产业中的应用仍存在技术碎片化、数据孤岛化、模型实验室化及成本高昂化等突出问题。基于“人工智能＋”战略的引导，进一步提出应推动构建覆盖全产业链的智能体系统、建立共建共享的数据资源生态、研发轻量化自适应算法模型及创新普惠性商业模式等发展策略，以推动MVT在中药材产业中的深度融合与规模化应用，为实现全链条智能化与高质量发展提供技术支撑。

China has recently proposed the “artificial intelligence +” strategy. Machine vision technology (MVT), which serves as the visual perception interface for artificial intelligence, has demonstrated broad application potential across multiple domains. This review provides a systematic overview of MVT applications throughout the entire industrial chain of Chinese medicinal herbs. By acquiring conventional visual images and multi-source spectral images, and by integrating both traditional machine learning and deep learning algorithms, MVT has been widely implemented in critical processes including seed quality evaluation and sorting, suitability analysis and regional zoning of cultivation environments, plant growth monitoring and field management, harvesting decision-making, primary processing control at the place of origin, and product quality assessment. These applications have significantly enhanced the intelligence level of production processes and the capability for quality control. Nevertheless, prominent challenges remain, such as technological fragmentation, data silos, lab-bound models, and high implementation costs. Guided by the “artificial intelligence +” strategy, this paper further proposes strategic directions including establishing intelligent agent systems covering the entire industrial chain, creating collaborative data resource ecosystems, developing lightweight adaptive algorithm models, and innovating inclusive business models. These measures aim to promote deep integration and large-scale application of MVT in the Chinese medicinal herb industry, thereby providing technical support for intelligent, high-quality development of the entire value chain.

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国家工信部重大任务专项“中药绿色智能制造技术”（2240STCZB2613）；北京中医药大学基本科研业务费（揭榜挂帅）项目（2023-JYB-JBZD-060）