Following their first formation in Indonesia over 25 years ago, Farmer Field Schools (FFS) have served as a “proof of concept” of how transformative learning can help governments, donors and development stakeholders achieve development objectives. The FFS approach, which has now been used in more than 90 countries by more than 12 million small farmers (FAO, 2016), not only creates a space in which the practical needs of smallholders to solve production-related issues can be addressed but also fosters personal and community-level transformation through empowerment.
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.
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
This book discusses innovation problems and opportunities for family farming in the different regions of the American continent, as well as the role of hemispheric, regional and national agrifood research systems. Likewise, it provides a description of the main innovation actions and projects promoted by IICA, and the main success cases over recent years.
Le rapport est construit en trois parties : • la première partie traite de l’adaptation des agricultures familiales aux changements climatiques et des conditions de l’adaptation ; • la seconde partie aborde la place de l’adaptation des agricultures familiales dans les politiques publiques ; • la troisième partie propose un certain nombre de recommandations en vue d’une meilleure intégration de cette question dans les politiques publiques. Une présentation des trois études de cas-pays est par ailleurs proposée en annexe.
El informe está estructurado en tres partes:
• la primera parte trata de la adaptación de la agricultura familiar a los cambios climáticos y de las condiciones de la adaptación; • la segunda parte aborda el lugar que ocupa la adaptación de la agricultura familiar en las políticas públicas;
• la tercera parte propone algunas recomendaciones para una mejor integración de este tema en las políticas públicas.
Una presentación de los tres estudios de caso-países figura también en anexo.
Agricultural information is transferred through social interactions; therefore, ties to agricultural informants and network structures within farmers’ local neighborhoods determine their information-gathering abilities. This paper uses a spatial autoregressive model that takes account of spatial autocorrelation to examine such network connections, including friendship networks and advice networks, upon farmers’ knowledge-gathering abilities during formal agricultural training.
Applied Research and Innovation Systems in Agriculture (ARISA) was implemented by CSIRO in collaboration with Indonesian partners. This multi-year program seeks to strengthen collaboration between public research organisations and agribusinesses in order to incubate and deliver technology and business solutions appropriate to smallholder farmers. The geographic focus of the program was Eastern Indonesia.
We look at the trade-off between smallholder cocoa intensification and the ecosystem in Indonesia and investigate the determinants of environmental efficiency in cocoa production. In our analysis, we apply a distance output function that includes cocoa production and the abundance of native rainforest plants as outputs. Our data set, based on a household and environment survey conducted in 2015, allows us to analyze 208 cocoa producers with both measured and self-reported data. We find that the intensification of cocoa farms results in higher ecosystem degradation.