Abstract
In the context of the agricultural transformation towards precision and intelligence, optimizing nitrogen management in rice fields to improve production efficiency and resource utilization has become an important research topic. This paper proposes and investigates an intelligent nitrogen management solution based on a regional agricultural big data platform. By integrating multi-source data such as soil properties, climatic conditions, fertilization history, and irrigation management, combined with artificial intelligence (AI) technologies, a customized nitrogen management strategy suitable for large-scale rice fields is developed. The research includes: (1) analyzing the system architecture and core technologies of the agricultural big data platform, explaining the methods of data collection, cleaning, fusion, and processing; (2) constructing an AI-based nitrogen demand prediction model and precision fertilization strategies; (3) exploring the synergistic effect of organic fertilizers and irrigation management in improving nitrogen use efficiency and proposing optimization pathways; (4) developing an AI-assisted decision-making system to achieve dynamic optimization of rice field resources. Case analysis verifies that the platform significantly improves nitrogen use efficiency and rice field productivity, demonstrating its potential to enhance regional agricultural resource utilization and achieve sustainable development. This paper provides scientific technological support for nitrogen management in rice fields and offers an important reference for the development of smart agriculture.
