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.

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.

The development of effective agricultural monitoring networks is essential to track, anticipate and manage changes in the social, economic and environmental aspects of agriculture. The authors welcome the perspective of Lindenmayer and Likens (J. Environ. Monit., 2011, 13, 1559) as published in the Journal of Environmental Monitoring on their earlier paper, “Monitoring the World's Agriculture” (Sachs et al., Nature, 2010, 466, 558–560).

The organization of the Nutrition Innovation Labs represents a novel model for focusing U.S.- supported research on food and nutrition issues in developing countries. Their aims are to discover how policy and program interventions can most effectively achieve large-scale improvements in maternal and child nutrition, particularly by leveraging agriculture and build human and institutional capacity for applied policy analysis, research and program implementation. 

The Feed the Future Innovation Lab for Collaborative Research on Grain Legumes (Legume Innovation Lab; LIL), supports ten multi-disciplinary collaborative research and institutional capacity strengthening subcontracted projects working in 13 Feed the Future countries in Africa and Central America and the Caribbean involving scientists at 10 US universities, 3 USDA/ARS research centers, and 23 developing country national agriculture research systems and universities.

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.