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 articles in the dossier present different approaches to supporting farmer-led research, ranging from partnerships between small-scale farmer organisations and research institutions, to alliances of farmer groups, nongovernmental organisations and researchers, to constellations in which farmer organisations directly contract researchers. The articles highlight some innovations that have emerged from these processes and – more important still – show new ways of organising research so that it strengthens innovative capacities at grassroots level.

Research, extension, and advisory services are some of the most knowledge-intensive elements of agricultural innovation systems. They are also among the heaviest users of information communication technologies (ICTs). This module introduces ICT developments in the wider innovation and knowledge systems as well as explores drivers of ICT use in research and extension.

This article used thematic content analysis to assess the influence of IPs on the governance of the parboiled rice value chain. The findings reveal that local rice value chains are characterized by unequal access to resources and asymmetry of power, which generates inequalities within groups. Although their influence is less discernible, IPs have contributed to greater visibility for some emerging stakeholders and rebalanced stakeholders in terms of influence in value chains

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 paper presents the common framework on CD for AIS developed by TAP and points to the relevance of meta-learning and the importance of “functional capacities”, if higher education institutions and their graduates are to become active players in the agricultural innovation system. The Framework was developed through an inclusive, participatory and multi-stakeholders approach with contributions by TAP Partners, including FARA and the Global Conference on Higher Education and Research in Agriculture.

in the context of the EU-funded JOLISAA (JOint Learning in Innovation Systems in African Agriculture) project, four local innovation processes involving smallholders in Benin were selected for in-depth assessment: innovation in hwedo agrofishing, integrated soil fertility management (ISFM), rice parboiling and soy value chains. Stakeholders directly involved in the innovation process were interviewed.

 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.

Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.