Social structure, especially in the form of social networks, affects the adoption of agricultural technologies. In light of an increasing focus on new demand-driven agricultural extension approaches that leverage social networks as an opportunity, too little is known about (a) which network characteristics matter? and (b) how do specific network characteristics matter? This paper investigates the impact of social networks in relation to smallholder dairy production technology adoption in Ethiopia.
Ethiopia has a diverse agro-ecology and sufficient surface and ground water resources, suitable for growing various temperate and tropical fruits. Although various tropical and temperate fruits are grown in the lowland/midland and highland agro-ecologies, the area coverage is very limited. For example, banana export increased from less than 5,000 tons in 1961 to 60,000 tons in 1972, but in 2003 declined to about 1,300 tons worth less than USD 350,000.
ICARDA scientists along with CGIAR LIVESTOCK developed a cloud-based genetic database platform to boost breed improvement programs in community-based livestock breeding programs in Ethiopia.
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
Breeding programs for local breeds kept by small farmers in developing countries are a major challenge. Animal recording of pedigree and performance under conditions of subsistence livestock farming is remain difficult or next to impossible. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
- Lack of automated data capture systems affects timely feedback and accuracy of information for breeding decisions.
- CGIAR researchers and national research partners have adopted a digital genetic database, Dtreo, that is enhancing genetic improvement by providing timely and accurate animal ranking information to communities.
- Dtreo is a digital genetic database that is flexible and easy to use, that allows users to capture and save data offline. Data is uploaded to the database once an internet connection has been established.
Digital platform enhances genetic progress in community-based sheep and goat breeding programs in Ethiopia:
- Up-to-date information on estimated breeding values and animal rankings is directly channeled to breeder organizations and used for selection decisions.
- The digital platform motivated use of more complicated evaluation models which improve accuracy of breeding values considerably.
- When upscaled, this will help create a permanent multi-country source of information.
The IPMS project proposes to ‘contribute to improved agricultural productivity and production through market-oriented agricultural development, as a means for achieving improved and sustainable livelihoods for the rural population’ in Ethiopia. To accomplish this goal the project supports development and (action) research on innovative technologies, processes and institutional arrangements in three focus areas i.e.
Ethiopian needs to achieve accelerated agricultural development along a sustainable commercialization path to alleviate poverty and ensure overall national development. In this regard, sustainable commercial of smallholder dairying provides a viable and growing opportunity; with deliberate, appropriate and sustained policy support. A recent empirical analysis concludes however, that Ethiopian smallholder dairy sub-sector has not been able to take-off despite decades of development interventions.