Green Extension is an umbrella term used to describe rural advisory services which support the scaling up of sustainable agriculture. This encompasses a range of methods to promote various types of content. What these approaches have in common is a process of socio-ecological learning, i.e., supporting farmers to analyse local problems and opportunities, and test alternative practices under local conditions.
This brochure presents the five-year TAP-AIS project (2019-2024) funded by the European Union under the DeSIRA Initiative and implemented by the Food and Agriculture Organization (FAO) of the United Nations. The project has the main objective to strengthen capacities to innovate in national agricultural innovation systems (AIS) in the context of climate-relevant, productive, and sustainable transformation of agriculture and food systems in Africa, Latin America, Asia and the Pacific.
Over the past few decades, some countries in Asia have been more successful than others in addressing poverty and malnutrition. The key question is what policies, strategies, legislation and institutional arrangements have led to a transformed agricultural sector, effectively contributing to poverty alleviation and addressing malnutrition. The great majority of national policymakers within and outside the Asia-Pacific region are keen to understand the causes of agricultural development and transformation in successful countries in Asia.
In Lao People's Democratic Republic (PDR), agricultural innovation has the potential to improve livelihoods of farmers and rural people, improve food and nutrition security, and allow for sustainable management of natural resources. In order to enable innovation, a well-functioning national Agriculture Innovation System (AIS) should encourage better coordination among the different stakeholders, including national organizations and the private sector.
Cambodia’s development is strongly influenced by growth in the agriculture sector. In this context, the modernization of agriculture has been highly regarded by the government as a long-term strategy to transform traditional labour-based agriculture into technology-based and with that to effectively enhance the country’s further regional integration within the Association of Southeast Asian Nations. In support of this strategic vision, a participatory assessment of the Agricultural Innovation Systems (AIS) was conducted in coordination with the General Department of Agriculture (GDA) and su
A bilateral project between the Swiss Agency for Cooperation and Development (SDC) and the Nepalese government, which ran from 2016 to 2020 and covered 61 municipalities in provinces 1, 3 (Bagmati) and 6 (Karnali), with technical support from the Swiss NGO Helvetas, aimed to promote a multi-stakeholder approach to agricultural services in Nepal.
The agricultural industry is getting more data-centric and requires precise, more advanced data and technologies than before, despite being familiar with agricultural processes. The agriculture industry is being advanced by various information and advanced communication technologies, such as the Internet of Things (IoT). The rapid emergence of these advanced technologies has restructured almost all other industries, as well as advanced agriculture, which has shifted the industry from a statistical approach to a quantitative one.
This report summarizes studies conducted in a framework of TAP-AIS project implemented by FAO’s Research and Extension Unit, and funded by the European Union as a component of the European Union initiative on “Development Smart Innovation through Research in Agriculture” (DeSIRA).
Evaluation provides effective feedback for development plans and programs. In this respect, it is of utmost importance to ensure that the outputs of agricultural extension and education projects are compatible with the ones expected. Therefore, the main purpose of this study was to evaluate agricultural extension model sites approach from actors’ perspectives and to analyze their gaps via the context, input, process, and product (CIPP) evaluation model.