Early applications of the innovation systems framework to developing-country agriculture suggest opportunities for more intensive and extensive analysis. There is ample scope for empirical studies to make greater use of the theoretical content available in the literature, and to employ more diverse methodologies, both qualitative and quantitative. Further, there is room to improve the relevance of empirical studies to the analysis of public policies that support science, technology, and innovation, as well as to policies that promote poverty reduction and economic growth.

This paper explores the application of the innovation systems framework to the design and construction of national agricultural innovation indicators. Optimally, these indicators could be used to gauge and benchmark national performance in developing more responsive, dynamic, and innovative agricultural sectors in developing countries.

Ethiopian agriculture is changing as new actors, relationships, and policies influence the ways in which small-scale, resource-poor farmers access and use information and knowledge in their agricultural production decisions. Although these changes suggest new opportunities for smallholders, too little is known about how changes will ultimately improve the wellbeing of smallholders in Ethiopia. The authors of this paper examine whether these changes are improving the ability of smallholders to innovate and thus improve their own welfare.

The article provides a conceptual framework and discusses research methods for analyzing pluralistic agricultural advisory services. The framework can also assist policy-makers in identifying reform options. It addresses the following question: Which forms of providing and financing agricultural advisory services work best in which situation? The framework ‘disentangles’ agricultural advisory services by distinguishing between (1) governance structures, (2) capacity, (3) management, and (4) advisory methods.

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.

A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.

Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.

A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.