Des facteurs structurels expliquent l’insécurité alimentaire en éthiopie : forte croissance démographique, faible productivité des parcelles agricoles, cultures majoritairement pluviales, réseau de communication quasi inexistant, etc. Malgré des moyens et des marges de productivité importants, les politiques agricoles n’ont pas permis de réduire les besoins en aide alimentaire de la population. Explications dans ce dossier.
“I see mindset shifts being promoted by CDAIS says Gemechu Nemie, director of the Ethiopian Animal Feed Industry Association (EAFIA) and a key member of the livestock feed safety and quality innovation niche. And this is the sort of change that the CDAIS project is beginning to engender, as partners start to implement approaches that better promote innovation in agriculture, by inspiring small and simple personal revolutions… Ethiopia is one of eight CDAIS pilot countries, and within each, several ‘niches’ or ‘innovation partnerships’ have been selected.
This study identifies, characterizes, evaluates, and validates promising agricultural innovations on wheat and faba bean crops along their value chains. It particularly addresses the following four research questions: ▪What constrains are likely to adversely influence efficiency, productivity, marketability, and market performance of wheat and faba bean in Ethiopia? What is the level and sources of efficiency and productivity of smallholder wheat and faba bean producers? Which innovations are promising to enhance productivity and profitability of wheat and faba bean along the value chains?
The study is an attempt to identify the type and channels of acquiring agricultural information by farmers; and whether this information helps them in their decisions to adopt new and improved technologies, which can then be translated into higher yield. A unique two-period panel data sets that come from surveys conducted in 2011 and 2013 by the Central Statistical Agency in collaboration with Ethiopian Strategic Support Program were used to evaluate Agricultural Growth Program (AGP)
The objective of this paper is twofold. First, using a three rounds panel data of 7110 households, was investigate the adoption decisions and the complementarities among the four labor-intensive technologies (agricultural extension service, irrigation, soil conservation and planting seeds in a row) and a comprehensive use of four modern inputs (improved seed variates, inorganic fertilizer, pesticides, organic fertilizer) which have been frequently adopted by smallholder farmers.
This report is divided in 3 studies that acess the status of the agricultural innovation in Ethiopia.
This brief describes the activies carried out by the project: South-South knowledge transfer strategies for scaling up pro-poor bamboo livelihoods, income generation and employment creation, and environmental management in Africa. The project, funded by the European Union and IFAD and implemented by the International Bamboo and Rattan Organisation (INBAR), targeted three countries – Ethiopia, Madagascar and Tanzania. This project aims to Contributing to higher productivity and incomes, it fully conformed to the strategy of the EU-IFAD agriculture research for development programme (AR4D).
This report brings the information about the capacity needs analysis carried out by CRP in five countries. Capacity development is a core enabling factor in the delivery of the 5 Livestock CRP flagships. One of the strategic capacity development actions for the Livestock CRP is to design evidence based capacity development interventions based on capacity needs analysis.
This paper assesses the role of economic, social, political and organizational processes on technology adoption in smallholder livestock production systems based on innovation systems perspective. Functions of the innovation systems framework was used to assess the missing links in the dairy sector value chains
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.