Abstract

Climate change is projected to have an important impact on crop productivity at broad regions of the world. Crop breeders across the globe have continuously been working on development of crop cultivars to adapt to climate change, the detailed information is necessary on when and where the adaptability of current cultivars will be broken and what cultivar traits will be required. Here, we developed a novel hybrid crop modelling approach that coupled a process-based crop model with machine learning and systematically assessed the impacts of climate change on rice productivity for 36 representative cultivars in China. We identified when, where, and what cultivars would be required for rice production to adapt to climate change precisely across China. We showed substantial differences in climate change impacts amongst cultivars. Current cultivars replacement could only alleviate but not offset the potential yield loss due to climate change in the future. Without adaptations and CO2 effect, nearly 67% of single rice and 46% of double rice cultivation areas would require cultivar renewal before 2050. Only two decades of leading time remain in the mid-lower reaches of the Yangtze River. The cultivars with a medium growth cycle, long grain-filling period, high photosynthetic capacity, and less spikelets should be breeding targets to adapt to climate change, although the ideotypic traits could be different for a specific environment and rice type.

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