xSeedScore
Machine learning-based decision-support solution for predictive plant breeding and trait optimization
DescriptionOverview of the initiative and its approach.
Computomics xSeedScore is a machine learning-based decision-support solution designed to accelerate plant breeding and trait optimization for agriculture. xSeedScore enables breeders to predict crop performance, select optimal crosses, and develop climate-resilient varieties, supporting food security and sustainable production. The solution integrates genotypic, phenotypic, and environmental data to deliver actionable insights for breeders and researchers.
TechnologyTechnology used by the initiative.
xSeedScore applies machine learning and bioinformatics analyses to integrate genomic, phenotypic and environmental data for predictive evaluation of plant breeding candidates. The solution is provided through computational analytics delivered by Computomics to support breeding decision-making.
TargetUsers, groups, or communities targeted by the initiative.
The main users are seed companies, plant breeders and research organisations engaged in crop breeding, variety development and genomic analysis.
Business modelHow the initiative delivers and sustains its value.
xSeedScore is offered as a subscription-based software-as-a-service (SaaS) platform, with fee-for-service consulting and data analytics. Data-driven insights may be monetized for research and commercial partners. Pricing is tailored to breeding program scale and data requirements.
ImpactThe observed or intended effects of the initiative.
xSeedScore aims to enable breeders to identify up to 10 times more outstanding candidates for commercial pipelines, to reduce time to market by up to 6 years, and double prediction accuracy compared to standard methods. The solution can support climate-smart breeding, reduce resource-intensive field trials, and promote biodiversity by enabling the development of diverse crop varieties adapted to specific climates. .
PartnersOrganizations and stakeholders involved in the initiative.
2Blades Foundation; Hudson River Biotechnology; EIT Food; Beck’s Hybrids; AB InBev; University of California, Davis
Four BettersThe FAO Four Betters supported by the initiative.
Better environment
Better production
