Targeting plant breeders, ag researchers, and agri-tech stakeholders focused on data-driven, climate-resilient crop improvement. The goal is to define practical use cases that showcase predictive models and build a solid proof of concept. Seeking partners to test and refine models using metabolomic, genomic, or environmental data to speed up trait prediction and early genotype selection. Collaborations will strengthen applicability in real breeding contexts towards practical tools for breeding programs, sustainable agriculture, and development of crops better adapted to environmental stresses.

Predictive models have been developed and tested using available datasets. The next steps are to finalize the models and further validate their predictive performance in order to establish a robust proof of concept and assess their applicability in breeding programs.