El objetivo de esa tesis es identificar, caracterizar, analizar y definir los modelos de toma de decisiones en los modelos de organización productiva del Noreste de la Provincia de La Pampa (Departamentos Chapaleufú, Trenel y Maracó), como aporte para la mejora de la gestión del Sistema de Extensión Rural y Transferencia de Tecnología del Instituto Nacional de Tecnología Agropecuaria
The objective of TAF’s projects was either to strengthen companies’ core operations by delivering consulting expertise to enable them to grow, and hence contribute to food security through increased production and food availability, or to facilitate the implementation of new business models that extend their reach to poor consumers, producers or employees through ‘inclusive business’ initiatives
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.
Looking at local learning capacity and systems of relations can help to understand the potential to develop innovation within a specific context. This work contributes to the definition of new actors who are developing innovation for sustainability in rural areas. The study focuses on the knowledge systems of farmers who are applying alternative breeding strategies: it uses a network approach to explore the knowledge system in which individual farmers are embedded in order to understand their specific relational features.
In this paper, was analyzed farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. Was used a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results.
Building on previous research, the purpose of this study was to describe the needs of the extension agents, in the Riyadh Region of Saudi Arabia, for training on Organic Agriculture (OA). This knowledge will be used to develop organic educational programs for extension agents. The specific objectives were to:
This presentation sets out a future research agenda for research on agricultural extension and advisory services, under influence of sustainability transitions and disruptive technologies such as digital agriculture technology, and synthetic foods. For a recording of the presentation see: https://www.youtube.com/watch?v=03V7zSD63pw
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 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.
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.