Year 1 activities were mainly on establishment of the project team at the global and country levels. A Partnership Agreement between AGRINATURA-EEIG and FAO was formalized and signed, and practical coordination mechanisms established. A Specific Power of Attorney between AGRINATURA-EEIG members within CDAIS was created, agreed and signed by all members, serving as the consortium agreement among members.
This PROLINNOVA report to the 3rd GFAR Programme-Committee meeting is composed of two parts.
The past 1 entitles ‘ PROLINNOVA genesis and growth’ describes historical background and
PROLINOVA in general while the part 2 entitles ‘2007 accomplishments’ narrates specific
accomplishments of PROLINNOVA during the period January-November 2007 . Further, the annex 1
lists contact addresses.
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
Development education, it combines various methodologies of education to promoting knowledge, so that agriculture sector needs development education to revive productivity through agriculture. ICT (Information communication technology) help to provide knowledge to the door step of farmers.
This study introduces a framework for managing information flow in innovation systems. An organisation's capacity to receive information, to share it with others and to learn from it is assumed to be the key factor that shapes the flow patterns and, hence, the performance of the innovation system concerned. The framework is applied to characterise the information structure underlying the agricultural innovation system of Azerbaijan and to develop an information strategy for the system to accelerate the information flow.
This decision guide is intended to help extension professionals and their organizations make informed decisions about which extension method and approach to use for providing information, technologies and services to rural producers and to facilitate interactions and knowledge flow. Expected users include field-based rural advisors, extension managers and programme planners.
The first part of the working document on the global strategy brings together the ideas of some 40 experts involved in gender and participatory research who took part in the workshop ‘Repositioning Participatory Research and Gender Analysis in Times of Change’ in Cali, Colombia (June 16–18, 2010).The workshop participants firmly believe that gender responsive participatory research (GRPR) offers some of the most powerful and useful approaches for achieving sustainable development, including alleviating poverty, improving well being, achieving sustainable levels of natural resource use, and
During May 2010 the International Centre for Tropical Agriculture (CIAT) hosted two events related to knowledge management (KM): The Knowledge Share Fair for Latin America and the Caribbean, funded by the Food and Agriculture Organization of the United Nations (FAO), and a regional meeting of the Knowledge Management for Development (KM4Dev) community. The Fair was attended by 200 professionals from more than 70 organizations and 18 countries and showcased more than 40 experiences related to KM in agriculture, development and food security.
ICT-driven digital tools to support smallholder farmers are arguably inevitable for agricultural development, and they are gradually evolving with promising outlook. Yet, the development and delivery of these tools to target users are often fraught with non-trivial, and sometimes unanticipated, contextual realities that can make or mar their adoption and sustainability. This article unfolds the experiential learnings from a digital innovation project focusing on surveillance and control of a major banana disease in East Africa which is being piloted in Rwanda.
The Colombian Ministry of Agriculture Colombia, an international research center and a national farmers’ organization developed a data-driven agricultural program that: (i) compiles information from multiple sources; (ii) interprets that data; and (iii) presents the knowledge to farmers through the local advisory services. Data was collected from multiple sources, including small-scale farmers. Machine learning algorithms combined with expert opinion defined how variation in weather, soils and management practices interact and affect maize yield of small-scale farmers.