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 framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming system's capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle processes of agricultural practices, farm demographics, governance and risk management.
Learn about the Women’s Empowerment Farmer Business Schools (WE-FBS) implemented in Kenya through FAO’s Flexible Multi-Partner Mechanism (FMM). The approach prompts men and women to reflect critically on their roles, resources, and activities in farming, and to develop strategies that are needed to maximize their commercial potential.
Genetic improvement on local breeds kept by small farmers in developing countries is challenging. Even though good pedigree and performance recording is crucial and an important component of breeding programs, it remain difficult or next to impossible under conditions of subsistence livestock farming. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
Powerpoint presentation on Global Partnership on Developing Innovation Capacities in Agriculture.
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.
Mountain agricultural systems (MASs) are multifunctional and multidimensional sociocultural systems. They are constantly influenced by many factors whose intensity and impacts are unpredictable. The recent Hindu Kush–Himalayan Assessment Report highlighted the need to integrate mountain perspectives into governance decisions on sustaining resources in the Hindu Kush–Himalayan region, emphasizing the importance of sustainable MASs.
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.
This guide is the second in a series of documents designed to support agencies implementing participatory agroenterprise development program operating within defined geographical areas.