This article highlights the potential for AI and machine learning to revolutionize the medicinal plant supply chain in India by enabling AI-driven quality assessment and traceability at the farm gate. By applying AI-powered tools to assess plant quality early in the supply chain, inefficiencies are reduced, quality is improved, and end-to-end traceability is enhanced from farm to consumer benefiting stakeholders across agriculture, logistics, and healthcare sectors. These technological advancements were discussed by experts from the National Medicinal Plant Board (NMPB) and the Institute of Teaching and Research in Ayurveda (ITRA) at a recent seminar.
In the Agriculture & Food sector, the AI-driven assessment of medicinal plants directly improves crop quality and reduces post-harvest losses. For Logistics & Supply Chain, AI creates a more efficient and transparent system, reducing transportation costs and ensuring product integrity throughout the supply chain.
Businesses involved in the medicinal plant supply chain can leverage AI-powered solutions to automate quality control, improve traceability, and reduce losses due to spoilage or adulteration. Implementing AI vision systems at farm gates could streamline the assessment process, reduce the need for manual inspection, and provide real-time data on product quality. This translates into improved efficiency, reduced operational costs, and enhanced product reliability.