Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting.
This paper takes the viewpoint of a social scientist and looks at agricultural scientists' pathways for science impact. Awareness of these pathways is increasingly becoming part and parcel of the professionalism of the agricultural scientist, now that the pressure is on to mobilize smallholders and their productive resources for (global) food security and for reducing persistent rural poverty. Significant new thinking about pathways is emerging and it is useful to present some of this, even if it is not cut-and-dried.
The article provides a conceptual framework and discusses research methods for analyzing pluralistic agricultural advisory services. The framework can also assist policy-makers in identifying reform options. It addresses the following question: Which forms of providing and financing agricultural advisory services work best in which situation? The framework ‘disentangles’ agricultural advisory services by distinguishing between (1) governance structures, (2) capacity, (3) management, and (4) advisory methods.
This report presents the main results of the EU-funded IN-SIGHT project ‘Strengthening Innovation Processes for Growth and Development’. The authors sketched out a conceptual framework and knowledge base for a more effective European policy on innovation in agriculture and rural areas. Both conceptual framework and knowledge base are consistent with the new European agenda for agricultural and rural policy and sensitive to the diversity of the European agricultural and rural systems.
This presentation was realized for the GFAR workshop on "Adoption of ICT Enabled Information Systems for Agricultural Development and Rural Viability" (at IAALD-AFITA-WCCA World Congress, 2008). It presents lessons learned through linking research to extension, including examples from projects in Nigeria, Colombia, Uganda ,Costa Rica, Egypt and Bhutan.
En este artículo se realiza un análisis crítico teórico-práctico de los conceptos de innovación, extensionismo y transferencia de tecnología. A partir de los mismos, de sus fundamentos metodológicos y limitaciones, se presentan algunas alternativas al modelo lineal de transferencia de tecnología (TdT). Se discute acerca de una propuesta alternativa de innovación, en la cual el desarrollo de alianzas efectivas y la comprensión y síntesis de visiones compartidas resulta clave para enfrentar desafíos y problemas del entorno, cada vez más complejo y cambiante.
Este documento describe la iniciative de ;a Secretaría de Fomento Agropecuario del Estado de Coahuila que crea a solicitud expresa de los productores rurales, el programa de extensionismo agropecuario y rural, con el propósito de llevar al campo un sistema integral de asistencia técnica, soportado en la tecnología que generan las instituciones de investigación, y con el respaldo de técnicos altamente capacitados, comprometidos con el desarrollo rural sustentable. Dentro de los principales objetivos del programa, está en el caso de cultivos, elevar los rendimientos y mejorar su calidad, y pa
In this paper, a novel method to collect symptoms of the disease, as observed by the farmers, using a mobile phone application has been presented. A cumulative composite risk index (CCRI) obtained from more than one existing disease forecast models is validated from the actual late blight queries received from the farmers. The main contribution of the paper is a protocol that combines the symptoms based diagnostic approach along with the plant disease forecasting models resulting in detection of Potato late blight with higher accuracy.