农业
转化式学习
多学科方法
生物技术
气候变化
人口
全球人口
可持续农业
持续性
业务
可持续发展
世界人口
环境资源管理
工作(物理)
工程类
作物
环境规划
全球挑战
遗传(遗传算法)
计算机科学
特质
农林复合经营
风险分析(工程)
粮食安全
作者
Zhao Wang,Dandan Yang,Cao Xu
摘要
Global agriculture faces unprecedented challenges from climate change and population growth, creating an urgent demand for the rapid development of resilient and high-yielding crop varieties. Although conventional breeding has achieved substantial progress in crop improvement, it is increasingly constrained by bottlenecks in genetic diversity, efficiency, and the uncertainty of trait inheritance under complex environments. Recent advances in integrative biotechnology offer transformative opportunities to reconfigure crop improvement into a predictive and design-driven process. This review synthesizes these advances into an integrated, multidisciplinary framework for precise breeding of climate-resilient crops, emphasizing the need to move beyond descriptive data accumulation toward mechanistic integration and beyond single-trait modification toward systems-level design. By integrating genome-phenome-environment insights with artificial intelligence-powered predictive modeling, we envision the rise of precise breeding frameworks capable of rapidly delivering climate-resilient, high-yielding crops. Such approaches are critical to fortifying agricultural systems, mitigating climate vulnerability, and securing a sustainable food future.
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