This paper presents the processes, general guidelines lessons and experiences pertaining to “good practices” for organizing and forming Agricultural Innovation Platforms in the Lake Kivu Pilot Learning Site, covering three countries (Uganda, Rwanda and Democratic Republic of Congo) with widely differing social political environments to address agricultural development challenges.
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.
This paper examines how the different institutional innovations arising from various permutations of linkages and interactions of ARD organizations (national, international advanced agricultural research centres and universities) influenced the different outcomes in addressing identified ARD problems.
On 15 November 2012, as part of the IFAD East and Southern Africa regional meeting in Addis Ababa, ILRI was asked to convene and facilitate a 1 hour session on ways that CGIAR and IFAD could collaborate. The session drew on contributions from different CGIAR centres; it involved speakers from ILRI, IWMI and ICARDA. It provided a very good, but short, opportunity to make connections between some CGIAR staff and IFAD and project staff; several individual follow up conversations were triggered.
The presentation (www.slideshare.net/ILRI/cgiar-and-ifad-sharing-and-scaling-up-innovations) reflected on current collaboration experiences between IFAD and the CGIAR, it introduced the ‘renewed’ research for development focus of the CGIAR and its multi-center Research Programs and it explored ideas for future collaboration.
- 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 chapter is a part of the book Integrated Agricultural Research for Development: from Concept to Practice.