An Agricultural Big Data-Driven Supply Chain Risk Management and Decision Support System

With the rapid development of the global agricultural industry, supply chain management is facing increasingly complex challenges. The agricultural supply chain involves multiple links, covering the whole process from production to sales, and is affected by a variety of factors such as natural disasters, market fluctuations and logistics delays. How to effectively identify, predict and manage these risks has become an important issue to improve the stability and efficiency of the agricultural supply chain. This paper systematically analyzes the current situation and challenges of risk management in agricultural supply chain, deeply discusses the application mode of agricultural big data in risk identification, analysis and decision-making, and clarifies the technology trend and future direction of intelligent development. With the further integration of agricultural science and technology and information technology, the risk management of agricultural products supply chain will become more intelligent and efficient. By promoting the in-depth application of big data, artificial intelligence and blockchain technologies, and strengthening the collaboration and innovation of the whole industry, it is expected to realize the comprehensive optimization of agricultural supply chain and help the sustainable development of global agriculture.