Le projet CALAO – Capitalisation d’expériences d’acteurs pour le développement de techniques agroécologiques résilientes en Afrique de l’Ouest – a été mis en œuvre au cours de l’année 2017 dans le cadre du Projet d’appui à la sécurité alimentaire en Afrique de l’Ouest (PASANAO), financé par l’AFD et dont la maîtrise d’ouvrage est assurée par la CEDEAO.
Este informe presenta la evaluación de los resultados del Proyecto de Fortalecimiento de los Mercados, Diversificación de los Ingresos y Mejoramiento de las Condiciones de Vida en la Sierra Sur (PDSS) en el Perú llevada a cabo por la Oficina de Evaluación Independiente (IOE) del FIDA en 2017. El PDSS fue implementado en el periodo 2005-2011. Antes de la fecha de cierre del proyecto, se decidió financiar un préstamo suplementario en el ámbito de la sierra sur peruana (2010-2015).
The objectives of this study twofold (i) First to assess farmer's perceptions of IT and secondly (ii) to determine the major factors influencing farmer's adoption decisions. This study offers for policy makers important considerations that could stimulate and sustain adoption of these IT in Tunisian arid agricultural areas. The present study is based on the hypothesis that the farm adoption decision of farmers has no relationship with the type of technology
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 document has as objectives characterizing the promising technological innovations developed for rice, soybean, small ruminant and poultry sectors.
The current study sought to analyse the livelihood impact of innovation platforms on small holders in the study areas based on the previous studies that identified successful Innovation Platforms in Eastern and Western Kenya. The study concentrated on four successful innovation platforms that were identified in a previous study In that study, fifteen innovation platforms were ranked based on a given criterion out of which the four innovation platforms were purposively chosen.
This document ains to update the inventory of existing functional promising agricultural innovations in Nigeria. The salient results from this study are as follows: 116 technologies were identified nationally during the review period (2006-2014). The strongest or most frequent triggers of innovation include yield improvement, resistance to pests and diseases, wide ecological adaptation, high quality cassava flour, HQCF, shorter time to maturity, drought resistance, seed or grain colour, malting quality and grain weight or size.
The overall objective of this research was to undertake a rapid milk value chain analysis toward identifying innovation opportunitiesto boost the milk production in Rwanda. The identified opportunities include boosting milk production through improved cattle breeds and animal nutrition, introduction of small and medium scale processors, development of business hub models around MCCs, consumer sensitization and school programs to boost milk demand
The present study was commissioned to carry out an update of the “Integrated Agricultural Research for Development (IAR4D)” with a view to evaluating the quantitative and qualitative impact of the several outcomes on stakeholders in the The sub-Saharan Africa Challenge Program (SSA CP). The present study is also to validate the hypotheses that the IAR4D (i) works (ii) delivers more benefits than the conventional R&D method and (iii) can be scaled out and up beyond the current area of operation.
The study was conducted in Kirinyaga County on rice and bananas and in Kisumu County on rice. Was used qualitative and quantitative methods and interviewed 247 farmers comprising 182 rice and 60 banana farmers respectively. Ten key informant interviews were conducted in Ahero and nine in Mwea Rice Schemes and the surrounding areas. One focus group discussion was held with Mwea Jua Kali/Valley bottom farmers. The data were analysed using descriptive statistics, frequency analysis and cross tabulations.