Ideotype optimization with Crop Modelling: CERES-Rice

This dataset supports the study on rice ideotype optimization using the CERES-Rice model integrated with AI-driven sensitivity analysis and genetic algorithm optimization. It includes the input files, environmental scenarios (weather and soil data), and the output results from 1,884 virtual rice cultivars. Each cultivar is evaluated across four contrasting environments to analyze performance based on grain yield and water use efficiency. The dataset is structured to allow reproduction of the full analysis pipeline, including outputs and the final ideotype comparison with field cultivars.