抄録
Climate change, characterized by frequent extreme weather events, rising temperatures, and abnormal spatiotemporal distribution of precipitation, has become a major challenge to global agricultural sustainability, significantly affecting crop yield, quality, and stability. Enhancing crop adaptability to climate change is therefore a core issue for ensuring food security and ecological resilience. In recent years, big data technologies, with their advantages in multi-source data integration, rapid computation, and intelligent analysis, have provided new theoretical frameworks and practical approaches for agricultural adaptability research. This study systematically analyzes the key mechanisms by which climate change impacts crop growth, evaluates typical applications of big data in environmental monitoring, adaptive prediction model construction, disaster risk assessment, and precision management, and highlights research progress in data acquisition, algorithm optimization, and interdisciplinary integration. Meanwhile, it identifies persistent bottlenecks such as insufficient data standardization, poor regional applicability, and inadequate policy coordination. Looking ahead, building open and shared data platforms, developing high-precision crop–climate coupled models, and advancing the application of intelligent decision-support systems are essential to fully leverage the strategic value of big data in enhancing crop climate adaptability and promoting sustainable agricultural production.
