The private sector’s presence in agricultural advisory services worldwide has been on the increase for over three decades. This trend has also been observed in the Mantaro Valley (Peru), in a context of dairy family farming. The objective of the communication is to analyse the modalities of advisory services privatization and assess the consequences of this privatization for the farmers and their livestock systems. Data were collected through input suppliers, different types of advisers and producers interviews.
The focus of this paper is on how the institutional arrangements within the on-farm sector of the New Zealand dairy industry influence industry participants and encourage them to be innovative, in the context of industry productivity goals. The authors will present and discuss an approach to policy systems analysis that facilitates shared understanding between system participants and enables strategies for change to be identified.
This article applies a historical analysis of the progressive development and complexity of Malawi’s diary innovation system through phased emphasis on technological, organizational and institutional development to illustrate the centrality of smallholder dairy farmers in the innovation system. A social network analysis is applied to assess the influence of smallholder farmers on other actors. The existence and growth of the diary innovation system in Malawi is founded on the resilience of smallholder dairy farmers to produce milk.
As the name suggests, the original aim of the Rural Knowledge Network (RKN) was to make more information available specifically about markets, to smallholder farmers. The core idea was to provide information to farmers and traders about current market prices in different markets around the country. This was done by building a network of entrepreneurs who regularly collected the price information and sent it to a central collecting Internet platform facility.
In the 90’s first steps were taken in Cuba to strengthen family farming. A participatory seeds breeding, multiplication and diffusion project started, a challenge to Cuban scientists, not used to involve farmers in the decision making process and recognizing them as equal partners. This project further evolved to become the Local Agricultural Innovation Programme, Spanish acronym PIAL (Programa de Innovación Agropecuaria Local).
In this paper the authors provide climate smart agriculture (CSA) planners and implementers at all levels with a generic framework for evaluating and prioritising potential interventions. This entails an iterative process of mapping out recommendation domains, assessing adoption potential and estimating impacts. Through examples, related to livestock production in sub-Saharan Africa, they demonstrate each of the steps and how they are interlinked. The framework is applicable in many different forms, scales and settings.
The project “Strengthening Community Resilience to Change: Combining Local Innovative Capacity with Scientific Research” (CLIC–SR), supported by the Rockefeller Foundation, was completed on 31 August 2016. During the four years since 2012, the Prolinnova Country Platforms in Ethiopia, Kenya, Tanzania and Uganda made large strides in:
The CLIC–SR project started on 1 September 2012, ended on 31 August 2016, and was implemented in four countries: Ethiopia, Kenya, Tanzania and Uganda. This report covers the work done in the final project period: January–August 2016. The report adds a chapter that reviews the achievements of the project over the full project cycle. The report from an independent external evaluation was a major source of information for this final chapter.
Technological innovations have driven economic development and improvement in living conditions throughout history. However, the majority of smallholder farmers in sub‐Saharan Africa have seldom adopted or used science‐based technological innovations. Consequently, several scholars have been persistently questioning the effectiveness of intervention models in smallholder agriculture.
The capacity of existing monitoring and decision making tools in generating evidence about the performance of R4D with multi-stakeholder processes, such as innovation platforms (IPs), public private partnerships (PPP), participatory value chain management (PVCM) is very limited. Results of these tools are either contextual and qualitative such as case studies that can not be used by other R4D interventions or quantitative i.e. impact assessments that do not inform what works in R4D.