The main goal of the study is to quantify the effects of a) change in nitrogen fertilization rate, b) adjustment of sowing date, c) implementation of new cultivars, and d) supplementary irrigation on maize cropping systems across six African countries including Ghana, Nigeria, Kenya, Malawi, Ethiopia and Burkina Faso. For this purpose, 30 years (1980-2010) of climate data are used as well as soil and management information obtained from global datasets at 0.5° x 0.5° spatial resolution.
The first section of this paper outlines the effect of gender norms on the productivity and incomes of women in the agricultural sectors of various African countries. The main challenges faced by women in value chains are outlined, including limited land rights, lower education levels and lower financial inclusion, as well as traditional division of labour in the household. These constraints are examined in turn, and their implications in terms of agricultural productivity and earnings are discussed.
In this paper, was used a case study approach to investigate the patterns of employment and income generation in cotton and rice value chains in Senegal and Benin. The purpose of the paper is to provide a comprehensive description of both value chains in both countries, emphasizing export potential and innovation entry points with the goal of assessing capacity to generate income, create jobs, and bring about food security.
This working paper provides the following text as a abstract:
This chapter aims to shed light on the broad debate surrounding when and why farmers adopt agricultural innovations, especially in the context of multi-stakeholder platforms (MSP) seeking to scale climate-smart agriculture (CSA) practices. No research has yet tested the hypothesis that farmer entrepreneurship—defined as the innovative use of agricultural resources to create opportunities for value creation—may facilitate the adoption of CSA practices. This study is intended to fill that information gap.
This chapter assesses the potential of farmer-to-farmer extension (F2FE) as a low-cost approach for promoting CSA. It is based on surveys of extension program managers and farmer-trainers in Cameroon, Kenya and Malawi who are involved in promoting a wide range of agricultural practices, including CSA. In the F2FE approach, extension programs provide education for farmer-trainers, who in turn educate other farmers, typically 17–37 per year. Extension program managers find this approach to be effective in boosting their ability to reach large numbers of farmers.
Here, it is described a new participatory protocol for assessing the climate-smartness of agricultural interventions in smallholder practices. This identifies farm-level indicators (and indices) for the food security and adaptation pillars of CSA. It also supports the participatory scoring of indicators, enabling baseline and future assessments of climate-smartness to be made. The protocol was tested among 72 farmers implementing a variety of CSA interventions in the climate-smart village of Lushoto, Tanzania.
In agricultural-dependent economies, extension programmes have been the main conduit for disseminating information on farm technologies, support rural adult learning and assist farmers in developing their farm technical and managerial skills. It is expected that extension programmes will help increase farm productivity, farm revenue, reduce poverty and minimize food insecurity.
Research-based evidence on the adoption of climate-smart agricultural practices is vital to their effective uptake, continued use and wider diffusion. In addition, an enabling policy environment at the national and regional levels is necessary for this evidence to be used effectively. This chapter analyzes a 4-year period of continuous policy engagement in East Africa in an attempt to understand the role of multi-stakeholder platforms (MSPs) in facilitating an enabling policy environment for climate change adaptation and mitigation.
Recent research has analyzed whether higher levels of farm production diversity contribute to improved diets in smallholder farm households. We add to this literature by using and comparing different indicators, thus helping to better understand some of the underlying linkages. The analysis builds on data from Indonesia, Kenya, and Uganda. On the consumption side, we used 7-day food recall data to calculate various dietary indicators, such as dietary diversity scores, consumed quantities of fruits and vegetables, calories and micronutrients, and measures of nutritional adequacy.