This paper was presented at the Farmer First Revisited: 20 Years On conference at IDS, University of Sussex, UK, December 2007. Its focus is the challenge of strengthening agricultural innovation systems. The paper prefaces this discussion by reflecting on an apparent paradox. While agricultural innovation has never been better studied and understood, many of our ideas about innovation have failed to fundamentally change the institutional and policy setting of public and private investment intended to promote innovation for development.

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.

Despite increasing interest and support for multi-stakeholder partnerships, empirical applications of participatory evaluation approaches to enhance learning from partnerships are either uncommon or undocumented. This paper draws lessons on the use of participatory self-reflective approaches that facilitate structured learning on processes and outcomes of partnerships. Such practice is important to building partnerships, because it helps partners understand how they can develop more collaborative and responsive ways of managing partnerships.

The UNDP Capacity Assessment Methodology User‘s Guide gives UNDP and other development practitioners a detailed step-by-step guide to conducting a capacity assessment using the UNDP Capacity Assessment Methodology, which consists of the UNDP Capacity Assessment Framework, a three-step process and supporting tools. 

Innovation systems can be defined in a variety of ways: they can be national, regional, sectoral, or technological. They all involve the creation, diffusion, and use of knowledge. Systems consist of components, relationships among these, and their characteristics or attributes. The focus of this paper is on the analytical and methodological issues arising from various system concepts. There are three issues that stand out as problematic. First, what is the appropriate level of analysis for the purpose at hand?

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 report is concerned with the ‘who?’ ‘what?’ and ‘how?’ of pro-poor extension. It builds on the analytical framework proposed in the Inception Report of the same study (Christoplos, Farrington and Kidd, 2001), taking it forward by fleshing out the analysis with empirical information gathered from several countries during the course of the study (from primary data in Bolivia, Colombia, Nicaragua, Uganda and Vietnam, and from secondary sources in a range of other countries, including India), and drawing conclusions on the scope for action by governments and donors in a range of contexts.

This chapter deals with capacity development (CD), which has been a core issue in international development cooperation policies and practices for decades. The first section outlines what CD entails, why is it important and why at the same time it is so difficult to grasp. A distinction is made between capacity at the individual, organisational/institutional and societal level. The unequal relationship between donors and recipients, which has often led to unsatisfactory progress and results in CD, is briefly discussed.

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. 

This paper introduces the Multilevel Stakeholder Influence Mapping (MSIM) tool, which aims to assist analysts in the study of power dynamics across levels within climate adaptation regimes. The tool is adapted from the Stakeholder Influence-Mapping tool (2005) of the International Institute for Environment and Development (IIED). MSIM is a simple visual tool to examine and display the relative power/influence that different individuals and groups have over a focal issue—in this case, climate change adaptation of smallholder farmers.