What happens when breeding records move from herd books to tablets? DTreo in Ethiopia’s community-based sheep and goat breeding

Community-based sheep and goat breeding programmes in Ethiopia used to record their data by hand in herd books. This brief, led by ICARDA with ILRI and AbacusBio as co-authors, describes how researchers switched to DTreo, our cloud-based genetic database, and what changed.

The challenge

ICARDA, ILRI and the University of Natural Resources and Life Sciences in Austria (BOKU) started sheep and goat community-based breeding programmes (CBBPs) in Ethiopia in 2010, with Ethiopia’s national research partners.

Breed improvement depends on ranking animals by genetic merit, and that needs good pedigree and performance records. Until recently, those records were kept by hand in herd books. Manual recording is slow and prone to lost data and errors. That reduces the accuracy of animal rankings and rules out more complex evaluation models. As the data grew, entering it by hand became harder, and feedback to communities was delayed.

The partners needed a central, automated system to capture and analyse data and return rankings to communities quickly.

Our approach

ICARDA and Ethiopia’s national research partners worked with AbacusBio to use DTreo, the cloud-based genetic database platform we developed. DTreo captures performance, pedigree, health and environment data. It stores and analyses the data, builds reports and graphics, and can run more complex models to improve the accuracy of genetic evaluations.

The workflow is built for places with poor internet access:

• Capture offline. Trained enumerators record data on tablets in the field and save it offline.
• Send when connected. Once there is a connection, they upload it to the cloud with one click.
• Check and approve. Researchers check and approve the data in the central database.
• Analyse and feed back. Researchers analyse the data and send animal rankings back to the community.

What we found

The system is in use across two countries. The partners developed and tested the database in the Bonga, Horro, Doyogena, Menz, Abergelle and Konso CBBPs in Ethiopia, and in Small East African and Pare goat CBBPs in Tanzania. Nineteen data collectors were trained and equipped with tablets, and started capturing data in 2019. All historic Ethiopian data since 2009 has been uploaded.

Rankings are reaching breeders. Estimated breeding values and animal rankings from the platform go directly to breeder organisations to inform their breeding decisions.

Researchers spend less time travelling. One researcher at Debre Berhan Agricultural Research Center oversees five CBBP sites in Menz. His team used to travel about 160 km every fortnight to monitor data collection and collect copies of the data. He can now monitor and access recent data from all five sites from his office, and create summary reports more easily.

Enumerators find recording easier. Finding farmer and animal information is quicker, and drop-down selections have reduced data entry errors significantly.

Cloud storage protects the records. Floods at the Arba Minch Research Center and conflict in northern Ethiopia damaged herd books and computers. Researchers valued having the data stored securely in the cloud.

What made it work, and what comes next

The authors identified several factors behind the programme’s success:

• an efficient partnership between national and international partners
• committed national researchers, who loaded the historic data onto the system
• strong motivation to use an automated system
• a flexible database that can work with any analytic system
• long-term technical support, capacity development and monitoring

To give a more accurate national picture of small ruminant genetic evaluation, the authors recommend expanding the database to more CBBP sites, including those run by national research institutions, universities and Ethiopia’s biodiversity institute. That would need:

• a national institution to coordinate and own the database system
• all national sheep and goat data moved to the central database

They also recommend adding features to produce breed-level reports, breed-specific prediction equations and animal rankings.

Why it matters

A digital database gives Ethiopian breeders timely feedback and more accurate information, which supports faster genetic improvement. It also creates a lasting record across many breeds. Researchers and policymakers can use it to identify and promote more productive and resilient breeds, and to plan long-term breeding strategies.

Read the full report: DTreo: A digital genetic platform provides accurate and timely data for improved community-based sheep and goat breeding. Getachew, T., Rischkowsky, B., Santos, B., Teviotdale, M., Rekik, M., Mwacharo, J. and Haile, A. 2021. SmaRT Ethiopia Brief. Nairobi, Kenya: ILRI.