Multi-stakeholder or innovation platforms are increasingly seen as a promising vehicle for agricultural innovation and development. In the field of agricultural research for development (AR4D), such platforms are an important element of a commitment to more intentional, structured and long-term engagement among sector stakeholders.

Capacity development is regarded by CGIAR as an effective vehicle for sustainable development, when embedded within broader CGIAR Research Programs (CRP). This document offers guidelines on how CGIAR and boundary partners (or those partners who take up and adapt research results for the next level of users) can successfully develop and implement strategies which support this process of integration.

Farmers and businesses need to adapt constantly if they are to survive and compete in the rapidly evolving environment associated with the contemporary agricultural sector. Rethinking agricultural research as part of a dynamic system of innovation could help to design ways of creating and sustaining conditions that will support the process of adaptation and innovation. This approach involves developing the working styles and practices of individuals and organizations and the incentives, support structures and policy environments that encourage innovation.

This policy brief consolidates lessons learned from an in-depth literature review on small-scale farmer (SSF) innovation systems and a two-day expert consultation on the same topic, hosted in Geneva by Quaker United Nations Office (QUNO) in May 2015. This review draws together published literature on the evolution of the concept, how on-farm innovation systems function in practice, and the roles of outside actors in supporting them.

The capacity of existing monitoring and decision making tools in generating evidence about the performance of R4D with multi-stakeholder processes, such as innovation platforms (IPs), public private partnerships (PPP), participatory value chain management (PVCM) is very limited. Results of these tools are either contextual and qualitative such as case studies that can not be used by other R4D interventions or quantitative i.e. impact assessments that do not inform what works in R4D.

This paper discusses a range of approaches and benchmarks that can guide future design of value chain impact evaluations. Twenty studies were reviewed to understand the status and direction of value chain impact evaluations. A majority of the studies focus on evaluating the impact of only a few interventions, at several levels within the value chains. Few impact evaluations are based on well-constructed, well-conceived comparison groups. Most of them rely on use of propensity score matching to construct counterfactual groups and estimate treatment effects.

Following the remarkable success of performance testing in the commercial sector, the Agricultural Research Council's Animal Improvement Institute (ARC–AII) initiated a beef cattle performance testing scheme for smallholder farmers in 1996. The scheme, which became known as Kaonafatsho ya Dikgomo (Sotho for animal improvement), has been running well in the Northern and North West Provinces and is set to spread gradually to the rest of the country.

This learning module on Applying innovation system concept in agricultural research for development has been prepared to serve as a tool in achieving the objective of strengthening the capacity of project staff and other researchers and actors who are believed to have a key role to play in ushering in market-led agricultural transformation. This includes national, regional, international and private sector agricultural researchers, university lecturers, and others engaged in biophysical as well as social science research.

This flyer is about the AgriFood chain toolkit, which has been launched in 2013 by the CGIAR programme on Policies, institutions and markets.The AgriFood chain toolkit acts as a clearing house and learning platform – using the power of information and communication technologies to bring together people and resources. 

The aim of this paper is to show the importance of monitoring genetic improvement programmes using the examples of an improvement programme for the Sahiwal breed in Kenya and a progeny testing scheme for Friesian cattle in Kenya. The paper is based on reports by Rege et al. (1992) and Rege and Wakhungu (1992) for the Sahiwal project and Rege (1991a and 1991b) for the progeny testing scheme for Friesian cattle.