Rather than merely supporting R&D and strengthening innovation systems, the focus of innovation policy is currently shifting towards addressing societal challenges by transforming socio-economic systems. A particular trend within the emerging era of transformative innovation policy is the pursuit of challenge-based innovation missions, such as achieving a 50 % circular economy by 2030. By formulating clear and ambitious societal goals, policy makers are aiming to steer the directionality and adoption of innovation.
Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access.
Establishing food security remains a global challenge; it is thus a specific objective of the United Nations Sustainable Development Goals for 2030. Successfully delivering productive and sustainable agricultural systems worldwide will form the foundations for overcoming this challenge. Smart agriculture is often perceived as one key enabler when considering the twin objectives of eliminating world hunger and undernourishment. The practical realization, deployment, and adoption of smart agricultural systems remain distant due to a confluence of technological, social, and economic factors.
Agricultural communication to mitigate climate change enables information dissemination of both scientific knowledge (SCK) and indigenous knowledge (IDK) for practical farming. This research analyzed knowledge utilization and conducted community-based participatory communication to propose a practical agricultural communication framework for climate mitigation. Based on a qualitative method of data collection in Phichit province, the key findings showed that SCK and IDK can be mutually utilized to enhance the good relationship among the people and for the people with nature.
The poor performance of agriculture in sub-Saharan Africa is known to be largely due to the lack of effective and client- responsive agricultural research and development that could generate appropriate technologies and innovations to stimulate the agricultural development process. As a contribution to address this challenge, the Forum for Agricultural Research in Africa (FARA), with support from the United Kingdom’s Department for International Development (DFID), developed a project for Strengthening Capacity for Agricultural Research and Development in Africa (SCARDA).
This paper explores the application of the innovation systems framework to the design and construction of national agricultural innovation indicators. Optimally, these indicators could be used to gauge and benchmark national performance in developing more responsive, dynamic, and innovative agricultural sectors in developing countries.
Based on eleven case studies from Africa, Asia, and Latin America, this report describes farmer-led research findings and their dissemination, and analyzes available evidence on the impact of farmer-led approaches to agricultural research and development on rural livelihoods, local capacity to innovate and adapt, and influence on governmental institutions of agricultural research and development.
This guide is mainly for researchers already involved in natural resource management (NRM). It assumes some familiarity with the often complex and chaotic reality of NRM projects, and tries to provide a systematic treatment of all the issues that may need to be considered. While many issues are considered in the guide, only a subset of them have to be dealt with in any specific NRM project. This booklet will also be of interest to implementers of NRM projects, as many of the elements and strategies are common to research and implementation.
The Guidance Note on Operationalization provides a brief recap of the conceptual underpinnings and principles of the TAP Common Framework as well as a more detailed guide to operationalization of the proposed dual pathways approach. It offers also a strategy for monitoring and evaluation as well as a toolbox of select tools that may be useful at the different stages of the CD for AIS cycle.
The Conceptual Background provides an in-depth analysis of the conceptual underpinnings and principles of the TAP Common Framework. It is also available in French and Spanish.