The IFAD-NUS project, implemented over the course of a decade in two phases, represents the first UN-supported global effort on neglected and underutilized species (NUS). This initiative, deployed and tested a holistic and innovative value chain framework using multi-stakeholder, participatory, inter-disciplinary, pro-poor gender- and nutrition-sensitive approaches.
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.
Growing local and informal markets in Asia and Africa provide both challenges and opportunities for small holders. In developing countries, market failures often lead to suboptimal performance of the value chains and limited and inequitable participation of the poor. In recent years, innovation platforms have been promoted as mechanisms to stimulate and support multistakeholder collaboration in the context of research for development. They are recognized as having the potential to link value chain actors, and enhance communication and collaboration to overcome market failures.
Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.
Invasive species such as Ambrosia (an annual weed) pose a biosecurity risk whose management depends on the knowledge, attitudes and practices of many stakeholders. It can therefore be considered a complex policy and risk governance problem. Complex policy problems are characterised by high uncertainty, multiple dimensions, interactions across different spatial and policy levels, and the involvement of a multitude of actors and organisations. This paper provides a conceptual framework for analysing the multi-level and multi-actor dimensions of Ambrosia management.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.
This chapter proposes a network-based framework to analyze and evaluate participatory and evidence-based policy processes. Four network based performance indicators are derived by incorporating a network model of political belief formation into a political bargaining model of the Baron–Grossmann–Helpman type. The application of our approach to the CAADP reform in Malawi delivers the following results: (i) beyond incentive problems, i.e.
There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.
Relying entirely on survey information and personal exchanges with over 70 scientists from within the CGIAR network, this working paper attempts to achieve a better understanding of the scope of social learning related efforts undertaken in CGIAR and main issues of relevance to more current efforts, such as that planned by the CGIAR program on Climate Change Agriculture and Food Security (CCAFS). A wide range of methods was identified, where groups of people learn in order to jointly arrive at solutions to pressing food security problems.
Here, it is described a new participatory protocol for assessing the climate-smartness of agricultural interventions in smallholder practices. This identifies farm-level indicators (and indices) for the food security and adaptation pillars of CSA. It also supports the participatory scoring of indicators, enabling baseline and future assessments of climate-smartness to be made. The protocol was tested among 72 farmers implementing a variety of CSA interventions in the climate-smart village of Lushoto, Tanzania.