Initiative Result:

Three crops in four CGIAR Centers adopt a new breeding data management system to accelerate variety development for smallholder farmers

Breeding today for smallholder farmers in Africa, Asia, and Latin America requires database infrastructure that can handle large amounts of data with quick turnarounds to enable optimal decisions that produce better varieties that fit market demand. Rice, maize, and wheat breeding programs at IRRI, AfricaRice, CIMMYT, and IITA successfully deployed the Enterprise Breeding System, a new data management system that directly digitizes data from planting to harvest for faster and more accurate crop improvement.   

Economic growth in the agricultural sector is more than twice as effective at reducing poverty as growth in other sectors[1], and agriculture is already impacted by climate change faster than we expected[2]. In this straitened setting, breeding today for smallholder farmers in Africa, Asia, and Latin America requires database infrastructure that can handle large amounts of data with fast turnarounds to quickly produce varieties to fit new market demands. 

In 2022, rice, maize, and wheat breeding programs at IRRI, AfricaRice, CIMMYT, and IITA successfully deployed the Enterprise Breeding System (EBS), a data management system fit for collaborative network breeding. As part of its commitment to accessibility, EBS is a license-free, cloud-based system which offers end-to-end support for breeding workflows. All operational data is stored in one single place with no need for access to other systems to execute breeding experiments, therefore enabling both data sharing and collaboration. Using state-of-the-art technology, EBS offers a multi-crop platform that is easy to implement and maintain.  

“…we have one primary objective which focuses on implementing improved data management, experimental designs, and breeding methods to accelerate genetic gain and improved breeding efficiency. Therefore, implementing EBS is one of the top priorities for [the] AGG project [Accelerating Genetic Gains in Maize and Wheat for Improved Livelihoods]” – Yoseph Beyene, Regional Maize Breeding Coordinator – Africa, and Maize Breeder – Eastern Africa

A detailed change management plan supported the adoption of the system at each Center. A Service Desk under one centralized platform offered the same level of services whenever needed across all regions of the globe to resolve blockers in daily use of the system. This Service Desk processed more than 1,000 tickets with a 95% satisfaction rating in 2022. For the first time in the CGIAR, we also took a systematic KPI-driven approach to adoption, tracking a common set of adoption indicators monthly and used the metrics to adaptively respond when usage stalled. A comprehensive training program was also implemented that comprised 118 separate trainings of various sizes hosted by all four Centers, with 263 women and 365 men trained to use the system. 

Adoption progress at the four Centers has been impressive, with more and more breeding teams using the system in their daily routines. Since April 2022, c. 2.5 million plot data points have been recorded in the system with c. 350,000 new germplasm records. This is current data, digitized in real-time for direct use by breeders and their staff, unleashing breeder time and putting predictive breeding within reach.  

With the foundation provided by working software and a comprehensive adoption support process, we are ready to expand to CGIAR legumes at IITA and begin outreach to potential NARES who may be interested to adopt the system in 2023. The system is becoming a cornerstone of the long-term strategy for sustainable data management in Genetic Innovations and has been recognized as a flagship product by CGIAR’s Digital and Data Group. As a system that was born within the CGIAR in response to breeding program needs, the EBS team practices an iterative user-driven design process guiding its development. As the CGIAR breeding strategy evolves, the EBS software, its supporting team, and its ways of working will ensure that Breeding Resources can adaptively respond in the coming years to support the breeding networks taking shape under Genetic Innovations in their information management needs.   

References:
  1. Enterprise Breeding System release notes 5.0   
  2. Enterprise Breeding System release notes 4.0 

 

Header image:In-person training at AfricaRice, M’béStation, October 2022. Photo by CGIAR.

CGIAR Centers

CGIAR Centers contributing to this result: CIMMYT, IRRI, AfricaRice, IITA.

Partners

This result was made possible by our valued partners: Cornell University, Integrated Breeding Platform, Weber and Fritz Consulting, Diversity Arrays Technology, the Breeding API project.