Although advanced breeding informatics software for breeding data management and analytics have been developed on a global scale, adoption rates in public sector breeding programs remains low. As a result, many programs lack access to historical data sets while others don’t have the resources to build the long-term reliable data sets essential to informed breeding decisions.
We partner with our Centers of Innovation to implement breeding informatics software that enables breeders to maximize response to selection and the value of their varieties. We work to understand where breeders are at today and where they want to go. Our goal: support the adoption of informatic systems that can organize and analyze large data sets in ways that work for the unique needs of individual national programs. Breeders everywhere must make rapid scientific decisions, and the right data at the right time can make all the difference. Thus, we strive to adopt and adapt intuitive breeding decision support tools that can help breeders make choices about varieties that address the needs of farmers and their communities.
“Our priority is to get the right information to the right people at the right time, in the right form to help them make informed decisions”Kelly RobbinsBreeding informatics lead
Working with CIWA to develop analytical pipelines and decision support tools for regional multi-year, multi-location genetic evaluations.
Malawi & Uganda
New breeding programs for cowpea, finger millet and sorghum offer opportunities to deploy the Breeding Management System and design optimal breeding schemes.
Leveraging the BrAPI standard to rapidly deploy customized applications to increase the utility of BrAPI compliant data management systems
Research from our experts
- Applying quantitative genetics theory and simulation to identify potential improvements with existing breeding program designs
- Understanding data needs and adapting software programs to the unique needs of breeding programs
- Deploying appropriate breeding and genomic data management solutions and provide training to users
- Scalable growth models for time-series multispectral images (Robbins, Gore)
- Simulation of sugar kelp (Saccharina latissima) breeding guided by practices to prioritize accelerated research gains (Robbins)
- Population Genetics of Sugar Kelp Throughout the Northeastern United States Using Genome-Wide Markers (Robbins)
- Strategies for effective use of genomic information in crop breeding programs serving Africa and South Asia (Robbins)
- The Genomic Open-source Breeding Informatics Initiative (GOBii) is a large-scale public-sector project working to apply high-density genotypic information to the breeding of staple crops.
- CGIAR Excellence in Breeding works to accelerate the modernization of crop breeding programs with guidance, resources, shared platforms and technologies.
- The Breeding API (BrAPI) project is an effort to enable interoperability among plant breeding databases. Check out all the servers in the world that are BrAPI compliant and the data management systems that have been deployed.