- 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.
Ethiopia is a home for diverse livestock including small ruminants and has the largest population of livestock in Africa. Livestock is kept for export earnings, food security, economic growth, poverty reduction and employment opportunities. Small ruminants are an important resource for livelihood and food security improvement serving as sources of food, income, risk mitigation, property security, monetary saving, investment, and providing other social and cultural benefits.
As calls for bolstering environmental services on croplands have grown more insistent during the past two decades, the search for ways to foster sustainable, reduced input agriculture has become more urgent. In this context authors re-examine by means of a meta-analysis the argument, first proposed by Robert McC. Netting, that small scale, mixed crop – livestock farming, a common livelihood among poor rural peoples, encourages environmentally sustainable agricultural practices.
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.
Small-scale farmers in the Brazilian Amazon collectively hold tenure over more than 12 million ha of permanent forest reserves, as required by the Forest Code. The trade-off between forest conservation and other land uses entails opportunity costs for them and for the country, which have not been sufficiently studied. We assessed the potential income generated by multiple use forest management for farmers and compared it to the income potentially derived from six other agricultural land uses.
Small millets, a group of highly nutritious food, have taken a back seat in the Indian agriculture landscape in recent years, due to government policies and failings in the value chain. In this commentary, the unusual decline of small millets in comparison to its substitutes, and the repercussions thereof, were first presented as context. Thereafter, based on analysis of data from literature, survey, and stakeholder contributions, a cluster map for the Indian small millets value chain was designed, and its competitive state presented.
Conflicts of interests have been hypothesized when agricultural advisory services are connected to agri-input businesses. However, these have not been examined using large sets of advisory service and grower data. We provide quantitative insights into dependencies between service, crop production, sustainability and the level of agri-input business-linkage of extension workers. This study analyzed 34,000+ prescription forms (recommendations) issued to growers in China, as well as grower interview data.
Coffee production is the main economic activity for smallholder farmers in Rwanda; it is also a major export crop. However, Rwandan coffee production has been facing structural changes with a significant decline in production. Considering the importance of the coffee sector to rural livelihoods and its potential role in export earnings, there is a need to ensure that small-scale coffee farmers efficiently use scarce resources in their production activities.
The study first identified fully efficient farmers and then estimated technical efficiency of inefficient farmers, identifying their determinants by applying a Zero Inefficiency Stochastic Frontier Model (ZISFM) on a sample of 300 rice farmers from central-northern Thailand. Next, the study developed scenarios of potential production increase and resource conservation if technical inefficiency was eliminated. Results revealed that 13% of the sampled farmers were fully efficient, thereby justifying the use of our approach.