Toward a general framework for AI-enabled prediction in crop improvement

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Carlos Messina, Julian Garcia-Abadillo, Owen Powell, Shunichiro Tomura, Alina Zare, Baskar Ganapathysubramanian, Mark Cooper

Published: 01 Jul 2025, Last Modified: 09 Nov 2025Theoretical and Applied GeneticsEveryoneRevisionsCC BY-SA 4.0
Abstract: A theoretical framework for AI and ensembled prediction for crop improvement is introduced and demonstrated using the logistic map. Symbolic/sub-symbolic AI-based prediction can increase predictive skill with increase in system complexity.