The Agriculture Technology Program for Turkmenistan (AgTech), funded by USAID and implemented by Weidemann Associates, Inc., aims to increase and develop private enterprises, and improve productivity of private, small and household farms. The project has two key components: the improvement of genetics, education and organization as a means of increasing the incomes of private agribusiness involved in livestock; skills building for private producers, processors and marketers of fruits and vegetables.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
This review aims to identify key issues and opportunities needed to bring current Agricultural Education and Training (AET) systems up to the needed capacity. This paper first looks at the opportunities identified in the preliminary research. Next the paper looks at some of the many pitfalls learned from previous AET work that should be avoided moving forward. Lastly the paper gives a brief explanation for some of the key areas that the preliminary research identified as requiring further research and study in a modern day context.
Social learning in multi-actor innovation networks is increasingly considered an important precondition for addressing sustainability in regional development contexts. Social learning is seen as a means for enabling stakeholders to take advantage of the diversity in perspectives, interests and values for generating more sustainable practices and policies. Although more and more research is done on the meaning and manifestations of social learning, particularly in the context of natural resource management, little is known about the social dynamics in the process of social learning.
The increasing complexity of technology development and adoption is rapidly changing the effectiveness of scientific and technological policies. Complex technologies are developed and disseminated by networks of agents. The impact of these networks depends on the assets they command, their learning routines, the socio-economic environment in which they operate and their history.
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?
This paper argues that impact assessment research has not made more of a difference because the measurement of the economic impact has poor diagnostic power. In particular it fails to provide research managers with critical institutional lessons concerning ways of improving research and innovation as a process. Paper's contention is that the linear input-output assumptions of economic assessment need to be complemented by an analytical framework that recognizes systems of reflexive, learning interactions and their location in, and relationship with, their institutional context.
Grant funds specifically targeted to smallholder farmers to facilitate innovation are a promising agricultural policy instrument. They stimulate smallholders to experiment with improved practices, and to engage with research, extension and business development services providers. However, evidence on impact and effectiveness of these grants is scarce. Partly, because attribution of changes in practices and performance to the grant alone is challenging, and the grant is often invested in innovation processes that benefitted from other support in the past.