This book aims to identify the characteristics of innovative farmers and suggests policy strategies to encourage agricultural innovations. The analysis shows that agricultural innovations are taking place in Turkey and various public and private stakeholders contribute to the development and adoption of innovation in agriculture. Agricultural enterprises and cooperatives, clusters of innovation, non-governmental organizations, research institutes, government, and international institutions play an important part in the collaborative effort to create and disseminate innovation.
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.
This brief explores the definition of Agricultural Knowledge and Information System (AKIS) and the inventory of AKIS in Europe.
Innovation is an important challenge for European agriculture, but little is known about the performance of the Agricultural Knowledge and Innovation Systems (AKIS). This report contributes towards this knowledge, as it reports on experiences from different countries and regions. The systems are very different between countries, regions and sectors.
This paper offers a perspective on the Agricultural Knowledge and Innovation System. The first chapter gives an introduction to the subject and explains the role of SCAR and of the Strategic Working Group AKIS. The second chapter investigates the AKIS and their role in innovation, including the policy context of the European Innovation Partnership “Agricultural productivity and sustainability”. Chapter 3 discusses the relation in a globalised world between Agricultural Research (AR) and Agricultural Research for Development (ARD).
This paper relates the European Innovation Partnerships (EIP) to be implemented by Operational Groups (OGs) in Basilicata. New relationships and regeneration produced a “bio-economic Cluster”, creating “smart” specialization and a system linking research, innovation and the enterprise world. The Cluster consolidated competence and knowledge in small and medium enterprises, including agriculture and forest farms and encouraged the dissemination and implementation of innovative products and processes.
The government of Ethiopia gives great attention to agriculture and rural development for the country’s economy development. Dairy development is one of the components of agricultural development. To improve dairy production in certain locality, dairy producers should able to access and use appropriate knowledge for the particular problem at the right time. This research was conducted to assess agricultural knowledge management system and its challenges and opportunities of knowledge management processes in Bure district.
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.
Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected.
Science and technology (S&T) are major contributors to food security, poverty reduction, and economic growth, as has been proven in Asia since the early-1970s through the Green Revolution in agriculture. Continuing to secure such gains, however, is becoming an increasingly complex undertaking. More than ever, quantitative data are vital for measuring, monitoring, and benchmarking the performance of agricultural S&T systems, including their inputs and outcomes.