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.

machine vision technology  /  Chinese medicinal herbs  /  industrial chain  /  artificial intelligence+  /  opportunities and challenges