This report discusses general innovation issues and how they are affecting economic growth. It emphasizes how the advances in ICT, biotechnology and other fields of science are changing the innovation landscape and what are the implications for CD.

This report reviews recent trends in agricultural innovation systems (AIS) and discusses the impact of a wide range of policies on the creation and diffusion of innovation in the agricultural and agrifood sector. It suggests a framework for analysing the role of governments in fostering increased innovation, with a view to helping to identify practical actions that governments could take to improve productivity growth, sustainable use of resources, and resilience to future market developments in national and global agriculture and agri-food systems.

The Challenge of Capacity Development: Working Towards Good Practice draws on four decades of documented experience provided by both bilateral and multilateral donors, as well as academic specialists, to help policy makers and practitioners think through effective approaches to capacity development and what challenges remain in the drive to boost country capacity. The analysis is underpinned by a conceptual framework which guides practitioners to view capacity development at three interrelated levels: individual, organisational and enabling environment levels.

This conference proceedings from the OECD Conference on Agricultural Knowledge Systems (AKS), held in Paris, on 15-17 June 2011, discusses a large range of experiences and approaches to AKS  explores how to foster development and adoption of innovation to meet global food security and climate change challenges. The conference considered developments in institutional frameworks, public and private roles and partnerships, regulatory frameworks conducive to innovation, the adoption of innovations and technology transfers, and the responsiveness of AKS to broader policy objectives.

This chapter outlines the role of a well-functioning agricultural innovation system in ensuring good use of public funds, and higher responsiveness to the needs of ‘innovation consumers’ through improved collaboration between public and private participants, including across national borders. A well-functioning agricultural innovation system is key to improving the economic, environmental and social performance of the food and agriculture sector.

This chapter analyses the functioning of the Brazilian agricultural innovation system. It discusses the role of the different actors and describes governance mechanisms to define priorities and evaluate performance. It analyses trends in agricultural R&D expenditure and sources of funding, the role of intellectual property protection in fostering knowledge markets, and outlines mechanisms used to facilitate knowledge transfers, including collaboration at the national level and the adoption of innovation at the farm or firm level.

Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting.

The three system CGIAR research programs on Integrated Systems for the Humid Tropics, Dryland Systems and Aquatic Agricultural Systems have included “capacity to innovate” as an intermediate development outcome in their respective theories of change. The wording of the intermediate development outcome is “increased systems capacity to innovate and contribute to improved livelihoods of low-income agricultural communities.” This note captures the CGIAR's collective thinking about this intermediate development outcome from a systems perspective to clarify it and inspire other programs.

This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.

This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.