- 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.
Since 2004, the Institutional Knowledge Sharing (IKS) Project, managed by CIAT, has focused on scaling up project activities in CGIAR Centers and Programs, with the aim of mainstreaming knowledge sharing (KS) principles and tools. The overall objective is to contribute to organizational development, and improve CGIAR effectiveness by promoting collaborative learning and innovation, and supporting effective use of KS approaches and tools throughout the CGIAR.
Innovation platforms are groups of individuals or stakeholder representatives with different backgrounds and interests. They come together to diagnose problems, identify opportunities, and find ways to achieve their goals. When innovation platforms are set up by development projects, their processes are usually facilitated by the support organization.
This Economic and Sector Work paper, “Enhancing Agricultural Innovation: How to Go Beyond the Strengthening of Research Systems,” was initiated as a result of the international workshop, “Development of Research Systems to Support the Changing Agricultural Sector,” organized by the Agriculture and Rural Development Department of the World Bank in June 2004 in Washington, DC.
The aim of this report is to provide a detailed review of documented social learning processes for climate changeand natural resource managementas described in peer-reviewed literature. Particular focus is on identifying (1) lessons and principles, (2) tools and approaches, (3) evaluation of social learning, as well as (4) concrete examples of impacts that social learning has contributed to.
The present article reviews the results and methodological design of an evaluation at higher education centres in Bolivia, Ghana and India. The ambition of these programmes was to integrate endogenous knowledge and values into education and research programmes. The evaluation provides an example of a mixed methods design that allowed for inclusion and appreciation of perspectives of different stakeholders. An evaluation team has to consider which set of methods is responding to the project context and how the methods complement each other and can be adapted to the case.
This paper examines different practical methods for stakeholders to analyse power dynamics in multi-stakeholders processes (MSPs), taking into account the ambiguous and uncertain nature of complex adaptive systems. It reflects on an action learning programme which focused on 12 cases in Africa and Asia put forward by 6 Dutch development non-governmental organizations (NGOs).
This review seeks to assess the usefulness of innovation systems approaches in the context of the Integrated Agricultural Research for Development (IAR4D) in guiding research agendas, generating knowledge and use in improving food security and nutrition, reducing poverty and generating cash incomes for resource-poor farmers. The report draws on a range of case studies across sub-Saharan Africa to compare and contrast the reasons for success from which lessons can be learned.