This document intends to provide an analysis of the outcomes of the application of the TAP Common Framework in the eight countries of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. The TAP Common Framework (TAP CF) was developed at the global level as an initial activity of the CDAIS project in order to guide capacity development (CD) and strengthening of Agricultural Innovation Systems (AIS). The project then tested this framework in eight pilot countries (Guatemala, Honduras, Burkina Faso, Angola, Rwanda, Ethiopia, Lao PDR, Bangladesh).
This flyer described the collaboration between FAO and Agrinatura and in particular two main areas of activities:
1) Joint implementation of the EU-funded Capacity Development for Agricultural Innovation Systems (CDAIS) project from 2015 to 2019, in eight countries: Angola, Bangladesh, Burkina Faso, Ethiopia, Guatemala, Honduras, Lao People’s Democratic Republic, Rwanda;
The publication is a part of the FAO work to assist the member countries in reforming their national Extension and Advisory Services (EAS). It highlights the main elements and provides concrete guidelines for the policy makers to make EAS demand-driven, i.e. responsive to diverse needs and demands of rural producers, including the most vulnerable groups, women and youth etc.
This study focuses on Smart Farming Innovations (SFI) of the Philippines. It is motivated by the 5th-agenda of the current Philippine President to increase agricultural and rural enterprise productivity. The study presents a strategy to lead research, development, and market of organic foods as medicine and build social entrepreneurs in using SFI.
Agricultural transformation and development are critical to the livelihoods of more than a billion small-scale farmers and other rural people in developing countries. Extension and advisory services play an important role in such transformation and can assist farmers with advice and information, brokering and facilitating innovations and relationships, and dealing with risks and disasters.
Policy brief No. 2. The majority of the world’s poor are smallholder farmers in developing countries. These smallhol- ders face several obstacles that limit their produc- tivity and profits, such that their incomes remain low. Institutional changes in the agricultural value chains are required to reduce poverty rates among smallholder farmers, and to stimulate agricultural growth.
Farm workers in developing countries often belong to the poorest of the poor. They typically face low wages, informal working arrangements, and inadequate social protection. Written employment contracts with clearly defined rights and obligations could possibly help, but it is not clear how such contracts could be introduced and promoted in traditional peasant environments. To address this question, we develop and implement a randomized controlled trial with farmers in Côte d’Ivoire.
Poverty is prevalent in the small-farm sector of many developing countries. A large literature suggests that contract farming —a preharvest agreement between farmers and buyers— can facilitate smallholder market participation, improve household welfare, and promote rural development. These findings have influenced the development policy debate, but the external validity of the extant evidence is limited. Available studies typically focus on a single contract scheme or on a small geographical area in one country.
Mobiliser les approches issues de l’Intelligence Artificielle (IA) en Santé Animale (SA) permet d’aborder des problèmes de forte complexité logique ou algorithmique tels que rencontrés en épidémiologie quantitative et prédictive, en médecine de précision, ou dans l’étude des relations hôtes × pathogènes.
In the existing literature, the effects of contract farming on household welfare were examined with mixed results. Most studies looked at single contract types. This paper contributes to the literature by comparing two types of contracts – simple marketing contracts and resource- providing contracts – in the Ghanaian oil palm sector. We investigate the effects of both contracts on farm income, as well as spillovers on other household income sources. We use survey data collected with an innovative sampling design and a control function approach to address possible issues of endogeneity.