This paper presents the processes, general guidelines lessons and experiences pertaining to “good practices” for organizing and forming Agricultural Innovation Platforms in the Lake Kivu Pilot Learning Site, covering three countries (Uganda, Rwanda and Democratic Republic of Congo) with widely differing social political environments to address agricultural development challenges.

This paper examines how the different institutional innovations arising from various permutations of linkages and interactions of ARD organizations (national, international advanced agricultural research centres and universities) influenced the different outcomes in addressing identified ARD problems.

The central question in increasing productivity and generating incomes in African agriculture is how to move from technology generation to innovations that respond to constraints of agricultural production along the value chains. This question was considered in the context of subsistence agriculture, smallholder production systems, inefficient marketing and investments by the private sector, a preponderance of public interventions, and inadequate policies.

The overall objective of this research was to undertake a rapid milk value chain analysis toward identifying innovation opportunitiesto boost the milk production in Rwanda. The identified opportunities include boosting milk production through improved cattle breeds and animal nutrition, introduction of small and medium scale processors, development of business hub models around MCCs, consumer sensitization and school programs to boost milk demand

This report make an analysis of Sorghum value chain in Uganda. Based on that, innovation opportunities in Uganda that can influence expansion of sorghum Value Chain and enhance socio-economic gains of all the actors are identified. Some of the identified opportunities among others include increasing farm level production through enacting supportive policy and providing support to organizations in seed production and distribution, introduction of small scale sorghum processing, and increasing their capacity as well as that of the existing processing entities

This report aims to analyse the value chain of Organic Pinneaples in Uganda and to identify innovation opportunities in order to increase the market share of the product

In this paper its argued that when flexibly applied and adapted to capture dynamics typical in systems innovation projects, the Log Frame Approach (LFA) ( and logical frameworks have considerable utility to support evaluation for both learning and accountability, and for identifying and addressing institutional logics, which leads to system innovation.

Primary Innovation is a five year collaborative initiative demonstrating and evaluating co-innovation, a systemic approach to innovation addressing complex problems, in five ‘innovation projects’ (active case studies) in different agricultural industries. In defining the elements of co-innovation, Primary Innovation has emphasised nine principles which guide activity in the innovation projects.

This paper describes a process for stimulating this engagement to develop a shared understanding of systemic problems, challenge prevalent institutional logics, and identify individual and collective actions that change agents might undertake to stimulate system innovation. To achieve this the process included (i) multiple actors from the agricultural innovation systems, (ii) steps to prompt reflexivity to challenge underlying institutional logics, (iii) an iterative process of practical experimentation to challenge current practices, and (iv) actions to encourage generative collaboration.

This study identifies systemic problems in the New Zealand Agricultural Innovation System (AIS) that affect the ability of participants in the agricultural sectors to co-develop technologies. We integrate structural and functional streams of innovation system enquiry, gathering data through 30 semi-structured interviews with individuals in Government, industry and research. Interviews explored perceptions of the influence of actors, interactions, institutions, infrastructure, and market structure on the effectiveness of AIS functions.