Little is known about effective ways to operationalize agricultural innovation processes. The authors of this article use the MasAgro program in Mexico (which aims to increase maize and wheat productivity, profitability and sustainability), and the experiences of middle level ‘hub managers’, to understand how innovation processes occur in heterogeneous and changing contexts. Their research shows how a program, that initially had a relatively narrow technology focus, evolved towards an innovation system approach.

This paper uses the Mexican Sustainable Modernisation of Traditional Agriculture (Ma-sAgro) programme as a case study to analyse the challenges to operationalizing agricultural innovation systems. The authors outline the relationship between Mexico ́s extension approaches and global trends in technological change. They then analyse how MasAgro ́s innovatio nnetworks are operationalized. Thirdly, is identified ways to efficiently target in innovation networks, using a case-study from the state of Chiapas. Finally, the paper draw lessons from MasAgro ́s innovation systems.

There is great untapped potential for farm mechanization to support rural development initiatives in low- and middle-income countries. As technology transfer of large machinery from high-income countries was ineffective during the 1980s and 90s, mechanization options were developed appropriate to resource poor farmers cultivating small and scattered plots. More recently, projects that aim to increase the adoption of farm machinery have tended to target service providers rather than individual farmers.

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.

Finance is a key lever for turning agriculture from a potential source of environmental harm and social inequity to a driver of conservation and social inclusiveness. Private and public sector funding for farmers to combat climate change and protect and restore nature (‘Paying for Nature’) is rapidly increasing. Yet this new funding may not reach its aims without drastically improving farm-level reward mechanisms.