抄録
With the intensifying impact of global climate change on agricultural production, drought-resistant breeding of maize, a vital food crop, has become a key area of international research. Long breeding cycles, high costs, and low efficiency constrain traditional breeding methods. The introduction of artificial intelligence (AI) has brought transformative breakthroughs to maize drought resistance breeding. This paper systematically reviews the primary applications of AI in this field, including genomic data analysis, high-throughput phenotypic data collection, construction of drought-resistance gene networks, and AI-driven strategies in marker-assisted breeding. By integrating multi-omics data and intelligent algorithms, AI significantly enhances the precision of gene selection and drought phenotype analysis. AI demonstrates broad potential in identifying gene-editing targets for drought resistance, phenotypic identification, and metabolic pathway analysis, providing strong support for precision breeding. This paper aims to summarize the latest advancements in AI technology in maize drought resistance breeding, analyze current challenges, and explore future directions for technological integration and innovation, offering new insights and strategies for maize drought resistance breeding.
