The intelligent transformation of agricultural product supply chains represents a critical solution to persistent challenges including information fragmentation across traditional stages, high logistical expenses, and quality traceability difficulties. This transformation holds substantial importance for enhancing operational efficiency, safeguarding quality standards, and advancing agricultural modernization. This study systematically examines the fundamental concepts, reviews technological progress across various supply chain stages, and proposes future development directions.

Detailed examination of key technological advances reveals significant innovations across production, processing, storage, transportation, distribution, and retail segments. In the production stage, integrated deployment of the Internet of Things (IoT), Artificial Intelligence (AI), and blockchain technologies enables precision decision-making and effective pest and disease management. Processing operations benefit from intelligent sorting systems and novel cleaning and sterilization techniques that elevate product quality. Storage efficiency improves through IoT-enabled environmental monitoring combined with AI-optimized inventory management. Transportation focuses on cold chain technology innovations and intelligent scheduling systems to enhance delivery timeliness. Retail applications leverage big data analytics and AI to drive targeted marketing strategies and inventory optimization, while comprehensive end-to-end traceability ensures data transparency throughout the entire chain.

Looking ahead, accelerated development of unmanned operations and shared information platforms will be essential. Technology-enabled approaches can strengthen supply chain resilience, while refined management practices will boost international competitiveness. At the industry level, deeper low-carbon transformation is needed through adoption of clean energy sources, sustainable packaging solutions, and intelligent logistics systems aligned with carbon peak and carbon neutrality objectives. Current technological deployment continues to face obstacles including data governance gaps and insufficient standardization. Policy guidance establishing technical regulations, increased research investment, and strengthened cross-disciplinary collaborative innovation are necessary to drive intelligent upgrades. These efforts will ultimately support sustainable agricultural development and contribute to global food security.