• • Hyperspectral imaging combined with machine learning enables non-destructive discrimination of ginseng age (林下参参龄) and kudzu root (粉葛) cultivation years, with PCA-based spectral feature extraction achieving classification accuracy critical for premium pricing and authenticity verification in the herbal market.
• • Improved SSD algorithms achieve lightweight Panax notoginseng disease detection, reducing model size while maintaining detection precision—essential for deployment on edge devices in remote mountainous cultivation regions where computational resources are constrained.
• • YOLO-V5l and ResNet50 architectures demonstrate effective farmland pest detection, with the dual-model approach enabling real-time identification and classification, directly impacting yield loss reduction in TCMM cultivation where pest outbreaks can cause 20-30% crop damage.
• • UAV-based multi-temporal remote sensing using RGB imagery enables Polygonatum odoratum (玉竹) GLI index monitoring and plant counting in sunflower and maize at seedling stages, providing scalable field phenotyping that replaces labor-intensive manual scouting across large TCMM plantations.