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.
In developing regions with high levels of poverty and a dependence on climate sensitive agriculture, studies focusing on climate change adaptation, planning, and policy processes, have gained relative importance over the years. This study assesses the impact of farmer perceptions regarding climate change on the use of sustainable agricultural practices as an adaptation strategy in the Chinyanja Triangle, Southern Africa.
This article addresses the impact of Integrated Agricultural Research for Development (IAR4D) on food security among smallholder farmers in three countries of southern Africa (Zimbabwe, Mozambique and Malawi). Southern Africa has suffered continued hunger despite a myriad of technological interventions that have been introduced in agriculture to address issues of food security, as well as poverty alleviation.
Climate variability and change threaten and impact negatively on biodiversity, agricultural sustainability, ecosystems, and economic and social structures – factors that are all vital for human resilience and wellbeing. To cope with these challenges, embracing sustainability in food production is therefore essential. Practising sustainable agriculture is one way of ensuring sustainability in pro-poor farming communities in low-income countries.
This study aims to contribute to literature on climate smart agriculture (CSA) scaling by identifying institutional and policy strategies that can help effect scaling of CSA practices in developing regions particularly SSA region. Increased adoption rates are more likely to enhance the overall impact of CSA innovations on productivity, food security, livelihoods and overall sustainability of agriculture. Furthermore, the study seeks to highlight and suggest possible approaches/strategies that the research and development community can adopt in taking CSA to scale.