In times of market liberalization and structural adjustment, the agricultural sectors of developing countries face profound changes. To seize new market opportunities, farmers need to innovate. In order to innovate, farmers need new technologies and information on how to access and manage them, as well as better support services for the delivery of inputs and knowledge, and better infrastructure for delivering produce to the market.
The TOWS Matrix is derived from the SWOT Analysis model. The SWOT analysis is based on two factors; internal factors (Strengths and Weakness) and external factors (Opportunities and Threats). For an organisation to function at the best of its potential, these tools should be utilised at the beginning of the year. This article shows how important these tools are important in an organisation.
Este folleto describe brevemente el proyecto "Desarrollo de Capacidades para los Sistemas de Innovación Agrícola en El Salvador", implementado por la FAO en conjunto con el Centro Nacional de Tecnología Agropecuaria y Forestal “Enrique Álvarez Córdova” (CENTA), del Ministerio de Agricultura y Ganadería (
The concept of technology adoption (along with its companions, diffusion and scaling) is commonly used to design development interventions, to frame impact evaluations and to inform decision-making about new investments in development-oriented agricultural research. However, adoption simplifies and mischaracterises what happens during processes of technological change. In all but the very simplest cases, it is likely to be inadequate to capture the complex reconfiguration of social and technical components of a technological practice or system.
Este trabajo describe la experiencia de cinco años de trabajo con cooperativas, asociaciones y comunidades Mapuche. Este trabajo describe las estratégias empleadas por los productores para desarrollar canales de comercialización que así lograron aprovechar los buenos precios de la lana para capitalizarse.
Este estudio de caso cuenta historias inspiradoras de cambio derivadas del proyecto propuesto por el acuerdo de colaboración entre el CIP y el FIDA y permitió recuperar 171 testimonios en los tres países, de los cuales los propios productores protagonistas priorizaron 24 casos que para ellos reflejaban mejor lo que había significado el proyecto. De estos 24 casos, se seleccionaron cinco historias, de las cuales tres son de Bolivia (sus historias recibieron puntajes más altos), seguidas de una de Perú y otra de Ecuador. Tres de ellas corresponden a mujeres y dos a varones.
This study aims at inspiring the success of further agricultural innovation policies. Findings fromthis study will provide useful inputs for researchers, governments, the private sector, donors, and other stakeholders to improve policy-maker engagement processes for innovations to ensure appropriate development and dissemination of innovation and maximise their socioeconomic impacts on the wider population.
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.
Coffee production is the main economic activity for smallholder farmers in Rwanda; it is also a major export crop. However, Rwandan coffee production has been facing structural changes with a significant decline in production. Considering the importance of the coffee sector to rural livelihoods and its potential role in export earnings, there is a need to ensure that small-scale coffee farmers efficiently use scarce resources in their production activities.
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.