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 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.
While the Agricultural Science and Technology Indicators (ASTI) initiative provides data and analysis of domestic public and private spending on agricultural research and development for a wide range of developing countries, the literature pays little attention, if any, to foreign assistance to agricultural, fishing and forestry research and agricultural extension. The objective of the present study is to fill this gap.
The central question in increasing productivity and generating incomes in African agriculture is how to move from technology generation to innovations that respond to constraints of agricultural production along the value chains. This question was considered in the context of subsistence agriculture, smallholder production systems, inefficient marketing and investments by the private sector, a preponderance of public interventions, and inadequate policies.
This chapter is a part of the book Integrated Agricultural Research for Development: from Concept to Practice. It focuses on the development and implementation of action plans for innovation platforms (IPs). The chapter introduces the constitution of committees, IP operationalisation, the case of IP functioning in the Democratic Republic of Congo, and post-formation issues for IPs.
This study explores the properties of innovation systems and their contribution to increased eco-efficiency in agriculture. Using aggregate data and econometric methods, the eco-efficiency of 79 countries was computed and a range of factors relating to research, extension, business and policy was examined. Despite data limitations, the analysis produced significant results.
This study explores the properties of innovation systems and their contribution to increased eco-efficiency in agriculture. Using aggregate data and econometric methods, the eco-efficiency of 79 countries was computed and a range of factors relating to research, extension, business and policy was examined. Despite data limitations, the analysis produced some interesting insights. For instance public research spending has a positive significant effect for emerging economies, while no statistically significant effect was found for foreign aid for research.
Extension and advisory services (EAS) play a key role in facilitating innovation for sustainable agricultural development. To strengthen this role, appropriate investment and conducive policies are needed in EAS, guided by evidence. It is therefore essential to examine EAS characteristics and performance in the context of modern, pluralistic and increasingly digital EAS systems. In response to this need, the Food and Agriculture Organization of the United Nations (FAO) has developed guidelines and instruments for the systematic assessment of national EAS systems.
Extension and advisory services (EAS) play a key role in facilitating innovation processes, empowering marginalized groups through capacity development, and linking farmers with markets. Advisory services are increasingly provided by a range of actors and funded from diverse sources. With the broadened scope of EAS and the growing complexity of the system, the quantitative performance indicators used in the past (e.g. related to investment, staffing or productivity) are not adequate anymore to understand whether the system is well-functioning.
The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.