ICT-driven digital tools to support smallholder farmers are arguably inevitable for agricultural development, and they are gradually evolving with promising outlook. Yet, the development and delivery of these tools to target users are often fraught with non-trivial, and sometimes unanticipated, contextual realities that can make or mar their adoption and sustainability. This article unfolds the experiential learnings from a digital innovation project focusing on surveillance and control of a major banana disease in East Africa which is being piloted in Rwanda.
The building of sustainable innovation capabilities in Africa requires an innovation system capable of producing, disseminating and using new knowledge. This paper assesses the process of constructing the National Innovation System (NIS) in Rwanda. It is posited that consensus on and acceptance of the concept of NIS among stakeholders is crucial in the early process of constructing an efficient and dynamic innovation system. Primary empirical data are presented for the case of Rwanda and analyzed in a regional context.
This paper calls for a better integration of place-based, evidence-based and inclusive dimensions in the implementation of the Science, Technology and Innovation (STI) plans and industrial policies in sub-Saharan Africa. To this end, the analysis contrasts with and takes inspiration from the recent and ongoing international experiences in the elaboration of Innovation Strategies for Smart Specialisation (S3).
Technology and innovation are important in addressing complex problems in the agricultural sector in many developing communities. However, ways and mechanisms to integrate them in the agricultural sector are still a challenge due to the lack of clear pathways and trajectories. Value chains are seen as a strong policy instrument to increase profitability in the agricultural sector; there is also debate around whether value chains can be a potential option to organize technology and innovation trajectories in agriculture.
A central concern about achieving global food security is reconfiguring agri-food systems towards sustainability. However, historically-informed trajectories of agri-food system development remain resistant to a change in direction. Through a systematic literature review, the authors identify three research domains exploring this phenomenon and six explanations of resistance: embedded nature of technologies, misaligned institutional settings, individual attitudes, political economy factors, infrastructural rigidities, research and innovation priorities.
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.
Innovation rests not only on discovery but also on cooperation and interactive learning. In agriculture, forestry and related sectors, multi-actor partnerships for ‘co-innovation’ occur in many forms, from international projects to informal ‘actor configurations’. Common attributes are that they include actors with ‘complementary forms of knowledge’ who collaborate in an innovation process, engage with a ‘larger periphery’ of stakeholders in the Agricultural Knowledge and Innovation System (AKIS) and are shaped by institutions.
The merger of Dow and DuPont, the acquisition of Syngenta by Chem- China, and the acquisition of Monsanto by Bayer have recently reshaped the global seed and biotech industry and caused concern about growing mar- ket concentration. This review documents market concentration in seed and agricultural biotech markets and discusses its causes and impacts. The avail- able evidence suggests that concentration in seed markets varies strongly by crop and by country, while markets for biotech traits are considerably more concentrated.
For millennia, humans have modified plant genes in order to develop crops best suited for food, fiber, feed, and energy production. Conventional plant breeding remains inherently random and slow, constrained by the availability of desirable traits in closely related plant species. In contrast, agricultural biotechnology employs the modern tools of genetic engineering to reduce uncertainty and breeding time and to transfer traits from more distantly related plants.
Global adoption of transgenic crops reached 67.7 million hectares in 2003 from 2.8 million in 1996. Delivery has occurred almost entirely through the private sector and adoption has been rapid in areas where the crops addressed serious production constraints and where farmers had access to the new technologies. Three countries (USA, Argentina and Canada), three crops (soybean, cotton and maize) and two traits (insect resistance and herbicide tolerance) account for the vast majority of global transgenic area.