ArticleFrontiers in plant science2026
A crop recommendation using improved expert-guided constraint aware differential evolution and CatBoost surrogate learning.
Article in Frontiers in plant science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Planning for sustainable crops, among other things, depends on smart decision-support systems capable of managing multi-criteria interactions and different environmental conditions. This study presents a multi-criterion, scenario-aware crop recommendation system developed by coupling Improved ECA-DE (Expert-guided Constraint-Aware Differential Evolution) optimization with CatBoost (Categorical Boosting) surrogate learning. The system assesses the suitability of crops using a range of agro-environmental factors, such as soil type, soil pH, temperature, humidity, water requirement, crop duration, and water source under three scenarios: balanced, drought, and short-season conditions. Improved ECA-DE is used for the determination of criterion weights, and the CatBoost model approximates expert-based suitability scores very effectively. The prediction performance of the proposed method was very high, with coefficient of determination (
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