Innovation is an important challenge for European agriculture, but little is known about the performance of the Agricultural Knowledge and Innovation Systems (AKIS). This report contributes towards this knowledge, as it reports on experiences from different countries and regions. The systems are very different between countries, regions and sectors.

These proceedings include all the papers presented during the AISA workshop either as oral papers or as posters. It also includes the edited text resulting from the Living Keynote process, an innovation in itself.
The AISA workshop was held on 29-31 May 2013 in Nairobi, Kenya, as part of an international week devoted to Agricultural innovation in Africa. The AISA workshop focused on active social learning among participants, developed a collective "living keynote" about the following issues:

Argentine agriculture has undergone significant transformations over the past three decades. After a long period of stagnant production and productivity, starting in the early 1970s, a number of independent but interconnected events fostered a new technological cycle that induced rapid growth in cereals and oilseeds production. Zero tillage and the introduction of genetically modified soybean varieties were key elements of this change. Argentina reached a leading position across agricultural commodity markets.

This background note for the development of an AIS Investment Sourcebook provides a menu of tools and guidance to invest in agricultural innovation in different contexts. The content is drawn on tested good practice examples and innovative approaches with emphasis on lessons learned, benefits and impacts, implementation issues, and replicability

The paper aims to identify barriers to the development of Learning and Innovation Networks for sustainable agriculture (LINSA). In such networks, social learning processes take place, and knowledge about sustainable agriculture is co-produced by connecting between the different frames and social worlds of the stakeholders with the help of boundary objects. Studying such processes at the interface between different knowledge spheres of research, policy and practice requires a specific methodology.

The role of civil society in influencing public opinion towards more democratic and developmental approaches is now well-recognised in diverse fields such as health, education, livelihoods, issues relating to disadvantaged social groups and the environment. Yet, science and technology in India is predominantly seen as the preserve of the state, and more recently the market. In the linear model of innovation, civil society is seen at best as having a role in extension or the delivery of technology produced elsewhere.

The Andhra Pradesh sorghum coalition illustrates the valued added by working in coalition. By combining different perspectives to give rise to new, synthesised ideas, the member organisations worked at a faster pace and achieved their objectives more successfully and sustainably than they could have done if working separately. The methodology of their research was designed collaboratively. As a result, scientists carried out repeat experiments on poultry, at the request of poultry farmers and feed manufacturers, which greatly increased their confidence in the evidence.

Drawing on a systematic review of over 500 documents, this study finds that, although FFS (farm field schools) projects have changed practices and raised yields in pilot projects, they have not been effective when taken to scale. The FFS approach requires a degree of facilitation and skilled facilitators, which are difficult to sustain beyond the life of the pilot programmes. FFS typically promotes better use of pesticides, which requires hands-on experience to encourage adoption. As a result, diffusion is unlikely and has rarely occurred in practice.

The increasing complexity of technology development and adoption is rapidly changing the effectiveness of scientific and technological policies. Complex technologies are developed and disseminated by networks of agents. The impact of these networks depends on the assets they command, their learning routines, the socio-economic environment in which they operate and their history.