The book documents a diversity of approaches for and results from the development of innovation processes (endorsing the definition proposed by FARA) through a review of twelve agricultural platforms in sub-Saharan Africa. These cases are far from exhaustive but nevertheless bring up a wealth of experiences. The authors do not pretend to present a model or template for the perfect innovation platform. To the contrary – they do not believe this is possible.
This research explores the role of innovation platforms and how they relate to IAR4D and the innovation system perspective, with treatment both at the theoretical and case study level (Africa). The chapters of the book take up several sticky issues and engage with them critically: policy pathways, gender equity and inclusion, and knowledge and information sharing. The introductory chapter provides context on food crops, food security and the importance of women in production, processing and trade.
This note is part of the Global Good Practices Initiative, which aims to provide information about extension approaches and methods in easy-to-understand formats. It focuses on Innovation Platforms, examining in particular two case studies: the Ghana Oil Palm platform and the Research Into Use (RIU) programme in Tanzania.
In this book, West African research associates from the CoS-SIS programme describe how they initiated innovation platforms and facilitated the different steps in a CIG cycle. The stories show that the facilitation of innovation platforms is not easy: it requires specific skills and a lot of time, and is very much determined by the context. But they also illustrate that there are creative ways of dealing with the challenges and unpredictable situations that facilitators face.
In-depth analysis of the role and capacity development needs of farmers organization in innovation processes, using the evidence from a number of case studies from contemporary SSA agriculture. Experiences indicate that Farmers’organizations (FOs) can play an important role in sharing knowledge-for-innovation by initiating multi-actor platforms for interactive learning and by implementing joint activity programmes (including use of the media) with extension services on a cost-sharing basis.
The European Innovation Partnership for agricultural productivity and sustainability (EIP-AGRI), which can be perceived as a platform based on interaction among farmers, researchers, and advisors/extensionists, represents a useful tool for a better understanding of applied innovation processes.
Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected.
This article starts by describing the evolution of innovation in agricultural research and cooperation for development, including an historical overview of agricultural research for development from green revolution to the re-discover of traditional knowledge. Then the authors analyze participation in innovation processes and make a comparison of innovation systems and platforms targeting the agri-food sector in developing countries. A particular focus is reserved to the European regional networks and to the experience of the USAID Middle East Water and Livelihoods Initiative.
This report presents the main results of the EU-funded IN-SIGHT project ‘Strengthening Innovation Processes for Growth and Development’. The authors sketched out a conceptual framework and knowledge base for a more effective European policy on innovation in agriculture and rural areas. Both conceptual framework and knowledge base are consistent with the new European agenda for agricultural and rural policy and sensitive to the diversity of the European agricultural and rural systems.
Crop surface models (CSMs) representing plant height above ground level are a useful tool for monitoring in-field crop growth variability and enabling precision agriculture applications. A semiautomated system for generating CSMs was implemented. It combines an Android application running on a set of smart cameras for image acquisition and transmission and a set of Python scripts automating the structure-from-motion (SfM) software package Agisoft Photoscan and ArcGIS. Only ground-control-point (GCP) marking was performed manually.