The ultimate aim of this research is to contribute towards a viable theoretical framework of agro-based technology transfer. This study uses case study methodology involving an agro-based government research institution and six private firms in Malaysia. This research reveals that the development of new technology did not lead to technology transfer until business opportunity is properly recognised. The business opportunity must be recognised first; then, the process of technology transfer will follow.
According to transition science, system innovation requires experimentation and social learning to explore the potential of innovations for sustainable development. However, the transition science literature does not elaborate much on the learning processes involved. Senge's Field of Change provides a more detailed approach to the role of learning and action in innovation. We linked the Field of Change to transition management literature in order to explore social learning in an agricultural innovation experiment in the Netherlands called the ‘New Mixed Farm’.
This paper uses the Mexican Sustainable Modernisation of Traditional Agriculture (Ma-sAgro) programme as a case study to analyse the challenges to operationalizing agricultural innovation systems. The authors outline the relationship between Mexico ́s extension approaches and global trends in technological change. They then analyse how MasAgro ́s innovatio nnetworks are operationalized. Thirdly, is identified ways to efficiently target in innovation networks, using a case-study from the state of Chiapas. Finally, the paper draw lessons from MasAgro ́s innovation systems.
Agricultural value chains can be understood as the systems of people, organizations and activities needed to create process and deliver agricultural products from producers to consumers. Over time and due to huge changes that have happened in the surroundings, agricultural value chains have become very integrated and complex. Small farmers can prosper by joining in modern higher-level agricultural value chains, but there are numerous obstacles, as well.
This paper applies the framework for pro-poor analysis to welfare changes from a CGE-microsimulation model to analyze what are the better or worse models for agriculture modernization, and to estimate the contribution of growth and redistribution to changes in poverty in DRC. The findings indicate that labor-using technological change generates absolute and relative pro-poor effects whereas capital-using technological change leads to immiserizing growth.
Agricultural innovations are seen as a key avenue to improve nutrition and health in smallholder farm households. But details of these agriculture-nutrition-health linkages are not yet well understood. While there is a broad literature on the adoption of agricultural technologies, most studies primarily focus on impacts in terms of productivity and income. Nutrition and health impacts have rarely been analyzed. In this article, we argue that future impact studies should include nutrition and health dimensions more explicitly.
In Sub-Sahara Africa, adoption rates of improved crop varieties remain relatively low, which is partly due to farmers’ limited access to information. In smallholder settings, information often spreads through informal networks. Better understanding of such networks could potentially help to spur innovation and farmers’ exposure to new technologies. This study uses survey data from Tanzania to analyze social networks and their role for the spread of information about improved varieties of maize and sorghum.
Fair Trade is a labeling initiative aimed at improving the lives of the poor in developing countries by offering better terms to producers and helping them to organize. Although Fair Trade-certified products still comprise a small share of the market—for example, Fair Trade-certified coffee exports were 1.8 percent of global coffee exports in 2009—growth has been very rapid over the past decade. Whether Fair Trade can achieve its intended goals has been hotly debated in academic and policy circles.
For millennia, humans have modified plant genes in order to develop crops best suited for food, fiber, feed, and energy production. Conventional plant breeding remains inherently random and slow, constrained by the availability of desirable traits in closely related plant species. In contrast, agricultural biotechnology employs the modern tools of genetic engineering to reduce uncertainty and breeding time and to transfer traits from more distantly related plants.
The CGIAR research program on livestock and fish aims to sustainably increase the productivity of small-scale livestock and fish systems so as to increase the availability and affordability of meat, milk and fish for poor consumers across the developing world. The purpose of this document is to lay out a Monitoring, Evaluation and Learning (MEL) Framework for the program. The Framework provides a concise narrative of why the M&E system is important, how it operates, what kinds of data it will collect and who is responsible for data collection and analysis.