The main objective of this paper is to describe the AgroFE and Agrof-MM projects. This projects aims to develop an agroforestry training system based on a common framework and core content, and to promote training at European level. The knowledge databank is a component of the project training system. It aims to gather and share a set of documents, resources that partners can use and which will have been accessed by learners and the public users.
This material was presented duting the conference: Big Data, a multiscale solution for a sustainable agriculture in Copenhagen Denmark in 2017 and brings an overview of the technological innovations of the French agricultural sector.
In this paper the High Nature Value (HNV) livestock farming systems are defined. These systems are found mainly in marginal areas where physical factors, and in some cases social factors, have prevented intensification of land-use. NV-LINK is a Horizon2020 project that seeks to improve the socio-economic and environmental sustainability of HNV farming in 10 Learning Areas, and more widely across the EU, by promoting innovation.
In an effort to raise incomes and increase resilience of smallholder farmers and their families in Feed the Future1 (FTF) countries, the United States Agency for International Development (USAID) funded the Developing Local Extension Capacity (DLEC) project. This project is led by Digital Green in partnership with the International Food Policy Research Institute (IFPRI), CARE International (CARE) and multiple resource partners.
This document on Good Practices in Extension Research and Evaluation is developed as a hands on reference manual to help young researchers, research students, and field extension functionaries in choosing the right research methods for conducting quality research and evaluation in extension. This manual has been compiled by the resource persons who participated in the Workshop on ‘Good
With the rapid pace of climate change and its impact on food security and livelihoods, climate-smart agriculture is one strategy aiming to help farmers adopt more sustainable farming practices. This study looked at farmers’ adoption of agricultural innovations and the role of social networks in the process.
The ‘ICT based Customer Care Solution for Poor Farmers’ is a case study that highlights Katalyst project’s work in developing low cost ICT solutions for farmers by collaborating with various public and private sector partners. The case study specifically focuses on a missed call based agriculture helpline service that was developed in collaboration with leading agriculture input companies. The service provides agriculture information solutions to smallholder farmers for free. Till date, the service has benefitted approximately 160,000 farmers.
Sustainable agricultural intensification requires the use of multiple agricultural technologies in an integrated manner to enhance productivity while conserving the natural resource base. This study analyses the adoption and impacts of sustainable intensification practices (SIPs) using a dataset from Ghana. A multivariate probit (MVP) model was estimated to assess the adoption of multiple SIPs. Moreover, we used a multivalued semi-parametric treatment effect (MVTE) model to estimate the effects of adopting multiple SIPs on maize productivity.
In developing regions with high levels of poverty and a dependence on climate sensitive agriculture, studies focusing on climate change adaptation, planning, and policy processes, have gained relative importance over the years. This study assesses the impact of farmer perceptions regarding climate change on the use of sustainable agricultural practices as an adaptation strategy in the Chinyanja Triangle, Southern Africa.
This study assessed intermediate results of an investment intended to support climate change adaptation and resilience-building among farmers’ cooperatives in Rwanda. The assessment was based on a purposive sampling survey of farmers’ perspectives conducted in sites in 10 programme intervention districts of the country’s 30 districts.