The generation of innovations has traditionally been attributed to research organizations and the farmer’s own potential for the development of innovative solutions has largely been neglected. In this chapter, we explore the innovativeness of farmers in Upper East Ghana. To this end, we employ farmer innovation contests for the identification of local innovations. Awards such as motorcycles function as an incentive for farmers to share innovations and develop new practices.
This chapter examines empirical results of evaluation reports from the AfrED database in order to unpack the relationship between the demand for evaluations and the capacities needed to meet that demand. The analysis further explores ways in which current M&E training and education provision can be enhanced to respond to capacity development needs. In achieving its objectives, the chapter also draws evidence from a secondary analysis of the results of a survey of evaluation practitioners’ perceptions of ECD challenges in the sector.
In this chapter, it is applied the CGPE model to analyzing the performance of policy processes with respect to the production of efficient policy choices. Within the CGPE approach participation of stakeholder organizations is modeled in two ways. First, as classical lobbying influence and second as informational influence within a model of political belief formation.
This chapter proposes a network-based framework to analyze and evaluate participatory and evidence-based policy processes. Four network based performance indicators are derived by incorporating a network model of political belief formation into a political bargaining model of the Baron–Grossmann–Helpman type. The application of our approach to the CAADP reform in Malawi delivers the following results: (i) beyond incentive problems, i.e.
Farmers in the Lake Victoria crescent zone have over the years struggled with pests and diseases in a country full of fake agricultural inputs, access to markets, post-harvest losses, declining soil fertility and the changes of weather. The production for most farmers is rain fed and is greatly affected by climatic changes. The Mukono Wakiso innovation platform (IP) was formed to help farmers find solutions to these issues.
This chapter documents the learning process within the framework of innovation of soil fertility management practices that emerged from the implementation of Participatory Extension Approach (PEA) as part of service delivery reorientation within the Limpopo Department of Agriculture in South Africa.The chapter gives a narrative description of what transpired during the interaction between researchers, extension officers and farmers, the processes involved, the lessons and the conclusion.
Research, extension, and advisory services are some of the most knowledge-intensive elements of agricultural innovation systems. They are also among the heaviest users of information communication technologies (ICTs). This module introduces ICT developments in the wider innovation and knowledge systems as well as explores drivers of ICT use in research and extension
The central question in increasing productivity and generating incomes in African agriculture is how to move from technology generation to innovations that respond to constraints of agricultural production along the value chains. This question was considered in the context of subsistence agriculture, smallholder production systems, inefficient marketing and investments by the private sector, a preponderance of public interventions, and inadequate policies.
Brazilian agriculture is facing another expansion cycle to the Cerrado region, more specific in the Northeast. The first agriculture expansion cycle to the Midwest was in seventies encouraged and developed by Brazilian Government with farmers from southern and southeast Brazil, which were traditional small farmers with some experience, low budget and a remarkable determination. All of these efforts after 20 years resulted in an outstanding development of a part of the country with economy based on agribusiness (soybean, corn, cotton, livestock, poultry, swine, etc.).