Abstract
In modern agricultural technology development, precision fertilization based on big data and artificial intelligence (AI) has become a critical strategy for enhancing rice production efficiency and achieving sustainable agriculture. This paper systematically analyzes the dynamic nitrogen demand of rice at various growth stages, proposing a data-driven precision fertilization model through real-time monitoring to optimize nitrogen application strategies and improve nitrogen use efficiency. By integrating soil sensors, the Internet of Things, and remote sensing technology, nitrogen demand can be monitored in real-time and undergo intelligent decision-making via AI algorithms, reducing nitrogen waste and minimizing environmental pollution. Additionally, the paper explores the potential of gene editing technology to enhance rice nitrogen use efficiency. Through multiple case studies, this paper demonstrates the practical applications of big data and AI technologies in rice nitrogen management, aiming to explore how technological innovations can advance intelligent nitrogen management and sustainable agricultural production.
