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 Farmer Field School (FFS) approach has been very successful and witnessed a strong expansion in many areas beyond crop production. Notwithstanding this success, the adoption of FFS in national extension often remains problematic and FFS activities have often been implemented in the margin of national institutions with strong reliance on donor funding. The creation of an enabling environment for institutional support is essential for expanding the effort, improving quality, and strengthening impact and continuity of the FFSs.

The importance of agriculture to Mongolia’s economy, and to its rural economy in particular, makes sustainable agricultural development a national priority. The transition from collective socialism to a market economy in the 1990s nearly caused the collapse of the entire agriculture sector. Since privatization, the number of livestock animals, mainly sheep and goats, has increased dramatically, reaching 45.1 million in 2012. This growth in both livestock and crop production was enabled by several factors. Yet investment in research and extension remains very low.

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.

Following their first formation in Indonesia over 25 years ago, Farmer Field Schools (FFS) have served as a “proof of concept” of how transformative learning can help governments, donors and development stakeholders achieve development objectives. The FFS approach, which has now been used in more than 90 countries by more than 12 million small farmers (FAO, 2016), not only creates a space in which the practical needs of smallholders to solve production-related issues can be addressed but also fosters personal and community-level transformation through empowerment.

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.

 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.