Abstract:

Significance The intelligent transformation of agricultural product supply chains is an essential solution to the challenges faced by traditional supply chains, such as information asymmetry, high logistics costs, and difficulties in quality traceability. This transformation also serves as a vital pathway to modernize agriculture and enhance industrial competitiveness. By integrating technologies such as the Internet of Things (IoT), big data, and artificial intelligence (AI), intelligent supply chains facilitate precise production and processing, efficient logistics distribution, and transparent quality supervision. As a result, they improve circulation efficiency, ensure product safety, increase farmers' incomes, and promote sustainable agricultural development. Furthermore, in light of global shifts in agricultural trade, this transformation bolsters the international competitiveness of China's agricultural products and propels the agricultural industrial chain toward higher value-added segments. This paper systematically examines the conceptual framework, technological applications, and future trends of intelligent supply chains, aiming to provide a theoretical foundation for industry practices and insights for policymaking and technological innovation. Progress In the production phase, IoT and remote sensing technologies enable real-time monitoring of crop growth conditions, including soil moisture, temperature, and pest infestation, facilitating precision irrigation, fertilization, and pest management. Big data analysis, coupled with AI algorithms, helps in predicting crop yields, optimizing resource allocation, and minimizing waste. Additionally, AI-driven smart pest control systems can dynamically adjust pesticide application, reducing chemical usage and environmental impact. The processing stage leverages advanced technologies for efficient sorting, grading, cleaning, and packaging. Computer vision and hyperspectral imaging technologies enhance the sorting efficiency and quality inspection of agricultural products, ensuring only high-quality products proceed to the next stage. Novel cleaning techniques, such as ultrasonic and nanobubble cleaning, effectively remove surface contaminants and reduce microbial loads without compromising product quality. Moreover, AI-integrated systems optimize processing lines, reducing downtime and enhancing overall throughput. Warehousing employs IoT sensors to monitor environmental conditions like temperature, humidity, and gas concentrations, ensuring optimal storage conditions for diverse agricultural products. AI algorithms predict inventory demand, optimizing stock levels to minimize waste and maximize freshness. Robotics and automation in warehouses improve picking, packing, and palletizing efficiency, reducing labor costs and enhancing accuracy. The transportation sector focuses on cold chain innovations to maintain product quality during transit. IoT-enabled temperature-controlled containers and AI-driven scheduling systems ensure timely and efficient delivery. Additionally, the integration of blockchain technology provides immutable records of product handling and conditions, enhancing transparency and trust. The adoption of new energy vehicles, such as electric and hydrogen-powered trucks, further reduces carbon footprints and operating costs. In the distribution and sales stages, big data analytics optimize delivery routes, reducing transportation time and costs. AI-powered demand forecasting enables precise inventory management, minimizing stockouts and excess inventories. Moreover, AI and machine learning algorithms personalize marketing efforts, improving customer engagement and satisfaction. Blockchain technology ensures product authenticity and traceability, enhancing consumer trust. Conclusions and Prospects As technological advancements and societal demands continue to evolve, the intelligent transformation of agricultural product supply chains has become increasingly urgent. Future development should prioritize unmanned operations to alleviate labor shortages and enhance product quality and safety. Establishing information-sharing platforms and implementing refined management practices will be crucial for optimizing resource allocation, improving operational efficiency, and enhancing international competitiveness. Additionally, aligning with the "dual-carbon" strategy by promoting clean energy adoption, optimizing transportation methods, and advocating for sustainable packaging will drive the supply chain toward greater sustainability. However, the application of emerging technologies in agricultural supply chains faces challenges such as data governance, technical adaptability, and standardization. Addressing these issues requires policy guidance, technological innovation, and cross-disciplinary collaboration. By overcoming these challenges, the comprehensive intelligent upgrade of agricultural product supply chains can be achieved, ultimately contributing to the modernization and sustainable development of the agricultural sector.

Key words: agricultural products, intelligent supply chain, IoT, AI, blockchain