So far, numerous studies have exhibited Silicon Valley and other thriving innovation ecosystems by distinguishing special characteristics in which their survival rely on sustaining activities that convert them to specific regions. These regions provide ready-made grounds for networking to be innovative. Meantime, it is struggling for innovations to be transformed into measurable economic results if players encounter a weak network of collaborative relationships in the ecosystem.

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.

The question of how agricultural research can best be used for developmental purposes is a topic of some debate in developmental circles. The idea that this is simply a question of better transfer of ideas from research to farmers has been largely discredited. Agricultural innovation is a process that takes a multitude of different forms, and, within this process, agricultural research and expertise are mobilised at different points in time for different purposes. This paper uses two key analytical principles in order to find how research is actually put into use.

Rural Advisory Services (RAS) are increasingly recognised as critical to agricultural and rural development. They provide rural communities with wide range of skills and knowledge and facilitate their interactions among the different actors to help them access support and services required for improving their livelihoods. Family Farmers are one of the important clients of RAS as they are the most predominant type of farmers worldwide.

There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.

African agriculture is currently at a crossroads, at which persistent food shortages are compounded by threats from climate change. But, as this book argues, Africa can feed itself in a generation and help contribute to global food security. To achieve this Africa has to define agriculture as a force in economic growth by: advancing scientific and technological research; investing in infrastructure; fostering higher technical training; and creating regional markets.

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 study examines the role of public–private partnerships in international agricultural research. It is intended to provide policymakers, researchers, and business decisionmakers with an understanding of how such partnerships operate, how they promote the exchange of knowledge and technology, and how they contribute to poverty reduction.

Presentation by Quintin Gray, Former Agriculture Counselor and U.S. Consulate in the United Arab Emirates,  at the Global Forum for innovations in agriculture (Abu Dhabi, 20-21 March 2017), an event to present solutions and inspire debate across all types of food production.

There is increasing evidence that public organizations dedicated exclusively to research and development (R&D) in agribusiness need systematic management tools to incorporate the uncertainties and complexities of technological and nontechnological factors of external environments in its long-term strategic plans. The major issues are: What will be the agribusiness science and technology (S&T) needs be in the future? How to prepare in order to meet these needs?