Oracle Partners with Wild Bio to Advance AI-Assisted Crop Breeding

en.Wedoany.com Reported - On September 24, Oracle and UK agricultural technology company Wild Bioscience (Wild Bio) announced a partnership. Wild Bio will use Oracle Cloud and Oracle IoT technology to support crop field research, aggregating data collected from trial sites into a unified cloud environment and analyzing crop performance through AI, providing a data foundation for subsequent breeding trait selection and field validation. The collaboration focuses on trait research covering crop stress resistance, resource use efficiency, yield, and carbon fixation capacity.

Wild Bio's breeding platform is based on plant evolutionary genomics. It uses AI to analyze wild plant genomes, identifying adaptive genetic traits formed over long-term evolution, and then introduces selected candidate traits into modern crop varieties for validation. Research goals include improving crop productivity under environmental stresses such as high temperatures and drought, while also selecting varieties with higher carbon dioxide removal potential.

The collaboration extends Wild Bio's existing AI breeding pipeline further into the field data collection stage. Oracle IoT will be used to capture crop growth and environmental data from trial plots, while Oracle Cloud will handle data aggregation, storage, and computation. The research team will then use AI to compare the performance of different varieties and traits under real agricultural conditions, feeding the results back into the next round of trait selection.

Wild Bio has now entered the field trial stage to validate the actual impact of candidate traits on crop yield, resource use efficiency, climate adaptability, and carbon removal capacity. The company plans to use this collaboration to continue expanding the scale of field research and to refine the data loop from genomic analysis, trait selection, and crop cultivation to field validation.

Wild Bio is a seed and genetics technology company focused on improving crops using evolutionary genomics, AI, and precision breeding. The collaboration has not disclosed investment amounts, specific crop varieties, field trial areas, or commercialization timelines. At this stage, the core work remains focused on breeding trait validation and the development of field data systems.