Une évaluation approfondie du système de vulgarisation agricole tunisien montre que des paquets technologiques améliorés destinés au système de production agricole mixte élevage-orge en Tunisie semi-aride permettent d’économiser jusqu’à 40 % des coûts d’alimentation du bétail, mais ne sont pas largement adoptés. Les faibles taux d’adoption sont typiques pour de nombreuses technologies approuvées dans les pays en voie de développement.
Breeding programs for local breeds kept by small farmers in developing countries are a major challenge. Animal recording of pedigree and performance under conditions of subsistence livestock farming is remain difficult or next to impossible. This means that standard genetic evaluations, as well as selection and planning of mating based on estimates of the animals' genotypes, cannot be done at any level in the population of the target breed or genetic group.
The final report outlines key outputs and outcomes of the implemented activities between 7 April 2015 and 6 April 2019 including review of the seed sector in Afghanistan; development of legal, managerial and technical documents for Public-Private-Producers Partnership (PPPP) model in seed sector, revitalization of seed testing laboratories, capacity building of stakeholders and awareness raising among stakeholders. The project was initiated in 2015 with a brainstorming workshop to create awareness about the PPPP concept among stakeholders and document their suggestions.
Face à la dégradation des ressources naturelles liée à la surexploitation, à la croissance démographique et au changement climatique, les services nationaux de vulgarisation en Tunisie nécessitent une révision de leurs priorités et une réforme de leurs modes de prestation de services.
This report brings a review about the CTA activities in 2018 based on three intervention areas. One is promoting youth entrepreneurship and creating employment for young people, particularly through the use of information and communication technologies (ICTs). The second, digitalisation, cuts across all intervention areas and focuses on the application of digital technologies to transform business models and provide new revenue throughout agricultural value chains.
This report aims to o estimate the current use of machinery in rice and bananas value chains; To establish determinants of mechanization in rice and bananas along the entire value chains; and estimate the effects of the determinants on mechanization levels. This study therefore seeks to identify factors that influence
mechanization levels for rice and bananas value chains. The findings from this study will help provide technical and policy recommendations for the improvement of not only the rice and banana value chains but the entire agriculture sector
This paper presents a case study of the Honey Bee Network’s decentralized model for collecting, verifying and disseminating grassroots innovations and provides a roadmap for its replication in Africa. The Honey Bee Network brings together governmental and non‐governmental institutions, members of academia, scholars and a large number of volunteers.
This report is a summary of the several activities pursued within the Program of Accompanying Research for Agricultural Innovation (PARI) to contribute to sustainable agricultural growth, food and nutrition security in Africa and India. The Institute of Agricultural Engineering, Tropics and Subtropics worked in the identification of technological innovations and further intervention in the dairy value chain, offering a potential solution for cooling milk from the earliest stage of milk production and
The objective of the study was to identify a viable trade-off between low data requirements and useful household-specific prioritizations of advisory messages. At three sites in Ethiopia, Kenya, and Tanzania independently, we collected experimental preference rankings from smallholder farmers for receiving information about different agricultural and livelihood practices. At each site, was identified socio-economic household variables that improved model-based predictions of individual farmers’ information preferences.
It has long been recognized that investment is needed to build capacity in Science Technology and Innovation (STI) particularly in low and medium income (LMI) countries. Yet there is little understanding as to how to do this.