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.

Innovations generally arise out of a network of actors and relationships and network structure determines how effective networks are at fostering innovation. This paper (Part II) presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia. The prototype method used is based on social network analysis methodology. This paper concludes with a final section to identify lessons learnt and makes recommendations for future research.

The CGIAR Research Program on Integrated System for the Humid Tropics, or Humidtropics, works towards transforming the lives of the rural poor in several action sites in Asia, Africa and Tropical America. In doing so, different technologies and innovations were implemented and while at first the capacity development was going on almost intuitively, as an integrated part of the implementation process, it has soon become clear that such groundbreaking activities and ideas require a more organized and supervised approach.

Farmers in Asia like to grow cassava because the crop will tolerate long dry periods and poor soils, and will produce reasonable yields with little inputs. Most farmers realize, however, that cassava production on slopes can cause severe erosion, while production without fertilizer inputs may lead to a decline in soil productivity. Research has shown that cassava yields can be maintained for many years with adequate application of fertilizers, and that there are various ways to reduce erosion.

Coordinated formal efforts to generate technologies for enhancing agricultural development in Ethiopia was mainly rooted in formal research and development institutions up to very recently. A number of improved technologies have been generated wlth the efforts made so far and the superiority of some of the technologies over the traditional practices has already been proved, at least for the major commodities.

As global populations continue to increase, agricultural productivity will be challenged to keep pace without overtaxing important environmental resources. A dynamic and integrated approach will be required to solve global food insecurity and position agriculture on a trajectory toward sustainability. Genetically modified (GM) crops enhanced through modern biotechnology represent an important set of tools that can promote sustainable agriculture and improve food security.

Rapid appraisal of agricultural innovation systems (RAAIS) is a participatory, diagnostic tool for integrated analysis of complex agricultural problems. RAAIS facilitates interaction between different groups of stakeholders in collecting and analysing data. The poster briefs what RAAIS is, when to use it, what is available and where it has been used.

The presentation is for the ILRI Innovation Platform (IP) Training Workshop. At the end of this session participants will be able to: Capture basic concepts in IP monitoring and evaluation; Comprehend why it is important to monitor and evaluate IPs; Contribute to fine-tuning of Africa RISING IP monitoring and evaluation framework; Identify IP TG members championing the M&E work at the research sites.

Empirical studies on agricultural technology adoption generally divide a population into adopters and nonadopters, and analyse the reasons for adoption or nonadoption at a point in time. In reality, technology adoption is not a one-off static decision, rather it involves a dynamic process in which information gathering, learning and experience play pivotal roles, particularly in the early stage of adoption. A conceptual framework for an adoption pathway is suggested in which farmers move from learning to adoption, to continuous or discontinuous use over time.