抄録
Facing multiple pressures such as continuous global population growth, limited arable land resources, and intensified climate change, agricultural production is undergoing a critical stage of transformation and upgrading. As the core driving force of next-generation information technology, artificial intelligence (AI) is profoundly reshaping crop genetic improvement and efficient production systems. This paper systematically reviews the major application progress of AI technology in crop variety improvement and yield enhancement, including key areas such as genomic selection, high-throughput phenotyping, gene editing–assisted breeding, precision agricultural management, intelligent pest and disease identification and control, and crop yield prediction. By comprehensively analyzing the mechanisms through which AI enhances breeding efficiency, optimizes field management, and maximizes resource utilization, this study reveals the scientific value and economic potential of AI in accelerating genetic improvement and promoting sustainable agricultural development. Furthermore, it discusses the challenges faced by AI applications in agriculture, including data heterogeneity, algorithm interpretability, cross-scale model integration, and ethical governance, and proposes future directions and research priorities. The paper aims to provide a systematic reference for agricultural technological innovation, promote the deep integration of AI with modern agriculture, and advance global food security and green agricultural development.
