人工智能重塑粮食产业价值链

Core Viewpoint - Artificial intelligence (AI) is transforming the food industry by shifting from extensive management to precise management, significantly reducing food loss and waste, which represents a substantial hidden cost in the industry [1][2]. Group 1: AI in Food Industry Management - AI acts as a "calculating master" in reducing food loss and waste, with significant potential for savings in the food supply chain [1][2]. - In the procurement phase, AI visual recognition systems enhance sampling efficiency and fairness, minimizing losses caused by delays and misjudgments [2]. - AI-driven sensors and IoT in storage facilities enable continuous monitoring and analysis of grain conditions, providing automatic alerts and controlling environmental systems to protect grain quality [2]. Group 2: AI in Agricultural Production - AI is pivotal in the agricultural sector, facilitating precision farming through accurate fertilization, irrigation, and pest diagnosis, which reduces chemical usage and conserves water [3]. - AI can predict crop yields months in advance by analyzing weather data, historical yields, and real-time crop images, thus supporting informed decision-making [3]. - The integration of AI with blockchain technology creates a traceable quality assurance system from farm to table, enhancing food safety and brand trust [3]. Group 3: AI as an Innovation Engine - AI is driving the food industry from initial processing to full-value utilization, uncovering hidden values in by-products and enhancing industry resilience [4]. - By optimizing processes, AI converts by-products like rice bran and soybean residue into high-value products, alleviating feed resource shortages and increasing profitability [4]. - AI supports food innovation, leading to the development of new products such as soybean ice cream, thereby extending the industry chain and improving risk management [4]. Group 4: AI and Industry Ecosystem - AI is reshaping the industry ecosystem, giving rise to new business models and collaborative supply chains [5]. - Fully automated "dark factories" controlled by robots and AI systems enable continuous production, significantly enhancing efficiency and product quality [5]. - The combination of AI and big data facilitates integrated platforms that connect various stakeholders in the food supply chain, addressing issues of fragmentation and information flow [5]. Group 5: Challenges and Future Directions - Despite the potential of AI in the food sector, challenges such as inconsistent agricultural data standards, high costs, and talent shortages remain [5]. - There is a need for national policy implementation, collaborative efforts, and the development of low-cost, modular AI solutions to enhance industry adoption [5]. - Establishing a comprehensive data collection system and fostering interdisciplinary talent development are essential for AI to effectively empower the food industry [5].