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.

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 develops a quantitative, graph-theoretic method for analysing systems of institutions. With an application to the agricultural innovation system of Azerbaijan, the method is illustrated in detail. An assessment of existing institutional linkages in the system suggests that efforts should be placed on the development of intermediary institutions to facilitate quick and effective flow of knowledge between the public and the private components of the system.

This paper is an attempt to take stock of the authors' work. In Section 2, the authors reflect upon the emergence and fairly rapid diffusion of the concept ‘national system of innovation’ as well as related concepts. In Section 3,  they describe how the Aalborg-version of the concept evolved by a combination of ideas that moved from production structure towards including all elements and relationships contributing to innovation and competence building.

The paper explores the implications of rural livelihood diversity for agricultural innovation policies. It summarises literature on the nature of rural poverty, with particular emphasis on the relative roles of farm and non-farm income. It also reviews the various roles, direct and indirect, that agricultural innovation can play in rural poverty reduction. Finally, it uses an agricultural knowledge and information systems (AKIS) perspective to argue for a differentiated approach to targeting agricultural innovations, based on an analysis of rural assets.

In times of market liberalization and structural adjustment, the agricultural sectors of developing countries face profound changes. To seize new market opportunities, farmers need to innovate. In order to innovate, farmers need new technologies and information on how to access and manage them, as well as better support services for the delivery of inputs and knowledge, and better infrastructure for delivering produce to the market.

There is increasing evidence that public organizations dedicated exclusively to research and development (R&D) in agribusiness need systematic management tools to incorporate the uncertainties and complexities of technological and nontechnological factors of external environments in its long-term strategic plans. The major issues are: What will be the agribusiness science and technology (S&T) needs be in the future? How to prepare in order to meet these needs?