Since 1981, IFAD has financed 19 rural development programmes and projects in Rwanda, for a total amount of US$358.04 million, and directly benefiting about 1,540,157 rural households. The IFAD country programme has contributed significantly to improving incomes and food security in rural areas, particularly through watershed development, increased production in marshland and hillsides, development of livestock and export crops, and support for cooperatives and rural enterprises. IFAD also supports the government in mainstreaming climate resilience.
Since 1979, IFAD has invested US$455.09 million in 20 programmes and projects in Kenya (at a total cost of US$980.31 million), in support of the Government’s efforts to reduce rural poverty. In Kenya, IFAD loans provide support to smallholders and value chain actors (such as agrodealers, private extension services, small traders and processors) in the dairy sector, aquaculture, livestock and cereal value chains. In addition, they strengthen the resilience of the natural resource base and improve access to rural financial services.
Geographic information system (GIS) data is often used to map socio-economic data with a spatial component. This data, which is obtained from multiple open-source databases, complements official statistics and generates additional spatial inputs to statistical and econometric analyses. IFAD uses impact assessments using data from face-to-face interviews in order to determine the impact of their projects on strategic goal and objectives. However, the COVID-19 pandemic meant these interviews could no longer take place.
China will be confronted with many challenges in the years to come, including achieving carbon neutrality, ensuring environmental sustainability, protecting vulnerable people, and ensuring a smooth transition from smallholder to modern agriculture. This policy note discusses how China could further advance its food and agricultural development model, making it greener, more sustainable, and more inclusive.
The CDAIS Communication strategy for 2015-2018 aims to contribute to CDAIS project's core objective of making agricultural innovation systems more efficient and sustainable in meeting the demands of farmers, agribusiness and consumers. For more information on CDAIS, see: https://www.fao.org/in-action/tropical-agriculture-platform/cdais-project...
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.
This concept note has been developed within the context of the EU-funded CDAIS project, which is jointly implemented by AGRINATURA-EEIG and the Food and Agriculture Organization of the United Nations (FAO) to support the TAP Action Plan in eight pilot countries in Africa (Angola, Burkina Faso, Ethiopia, Rwanda), Asia (Bangladesh, Laos) and Central America (Guatemala, Honduras) .
CDAIS is a global partnership that aims to strengthen the capacity of countries and key stakeholders to innovate in the context of complex agricultural systems, to improve rural livelihoods. The goal of the Capacity Development for Agricultural Innovation Systems (CDAIS) project is to promote innovation that meets the needs of small farmers, small and medium-sized agribusiness, and consumers.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.