The agrarian system Analysis and Diagnosis is used for this study, the goal of which was to provide a corpus of basic knowledge and elements of reflection necessary for the understanding the Niayes farming systems dynamics in Senegal, West Africa. Such holistic work has never been done before for this small region that provides the majority of vegetables in the area, thanks to its microclimate and access to fresh water in an arid country.
Indicator-based tools are widely used for the assessment of farm sustainability, but analysts still face methodological and conceptual issues, including data availability, the complexity of the concept of sustainability and the heterogeneity of agricultural systems. This study contributes to this debate through the illustration of a procedure for farm sustainability assessment focussed on the case study of the South Milan Agricultural Park, Italy. The application is based on a set of environmental, social and economic indicators retrieved from the literature review.
Smallholder farmers in East Africa need information and knowledge on appropriate climate-smart agriculture (CSA) practices, technologies, and institutional innovations in order to effectively adapt to changing climatic conditions and cope with climate variability. This paper assesses farmer adoption of climate-smart agricultural practices and innovation after being exposed to Farms of the Future Approach (FotF). First; we explore and assess the various CSA technologies and practices; including institutional innovations farmers are adopting.
Past studies showing that barriers to farmers’ adaptation behaviors are focused on their socio-economic factors and resource availability. Meanwhile, psychological and social considerations are sparingly mentioned, especially for the related studies in developing countries. This study investigates the impact of psychological factors and social appraisal on farmers’ behavioral intention to adopt adaptation measures for the aforementioned reason, due to climate change and not to anthropogenic climate change.
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.
This concept note has been developed within the context of the EU-funded CDAIS project, which is jointly implemented by AGRINATURA-EEIG and the Food and Agriculture Organization of the United Nations (FAO) to support the TAP Action Plan in eight pilot countries in Africa (Angola, Burkina Faso, Ethiopia, Rwanda), Asia (Bangladesh, Laos) and Central America (Guatemala, Honduras) .
This training manual was prepared under the EU-funded project Capacity Development for Agricultural Innovation Systems (CDAIS), a global partnership (Agrinatura, FAO and 8 pilot countries) that aims to strengthen the capacity of countries and key stakeholders to innovate in complex agricultural systems, thereby achieving improved rural livelihoods.
CDAIS is a global partnership that aims to strengthen the capacity of countries and key stakeholders to innovate in the context of complex agricultural systems, to improve rural livelihoods. The goal of the Capacity Development for Agricultural Innovation Systems (CDAIS) project is to promote innovation that meets the needs of small farmers, small and medium-sized agribusiness, and consumers.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.