Despite its vast agriculture potential, Africa is increasingly dependent on food imports from the rest of the world to satisfy its consumption needs. Food output has not kept pace with population growth, and more than 80 percent of production gains since 1980 have come from the expansion of cropped areas rather than from greater productivity of areas already cultivated. This paper looks at the current requirements for seed trade in Africa, the obstacles, status of ongoing plans for regional harmonization, challenges of harmonization, and opportunities for near-term improvement.
This editorial paper brings together different streams of research providing novel perspectives on co-design and co-innovation in agriculture, including methods, tools and organizations.
The concept of open innovation is currently one of the key issues regarding the innovative development of micro, small, and medium enterprises (SMEs). It has been the subject of research both in the theoretical and empirical context. At present, there is no unambiguous definition conceptualizing the conceptual scope of open innovation (OI). However, enterprises do not always decide by themselves to be open to the environment.
Despite typically beingregarded as ‘low-tech,’ the Food Manufacturing and Technology Sectoris increasingly turning to open innovation practices involving collaboration with universities in order to innovate. Given the broad range of activities undertaken by this sector and thefact that it utilises analytical, synthetic, and symbolic knowledge for innovation, it makes an interesting case study on the factors that influence the formation of University-Industry links.
This free Massive Open Online Course (MOOC) on Open Data Management in Agriculture and Nutrition was first created in 2016. The course was delivered 5 times between November 2017 and November 2018, reaching over 5000 people globally, before being made available for unrestricted use
For an intelligent agricultural robot to reliably operate on a large-scale farm, it is crucial to accurately estimate its pose. In large outdoor environments, 3D LiDAR is a preferred sensor. Urban and agricultural scenarios are characteristically different, where the latter contains many poorly defined objects such as grass and trees with leaves that will generate noisy sensor signals. While state-of-the-art methods of state estimation using LiDAR, such as LiDAR odometry and mapping (LOAM), work well in urban scenarios, they will fail in the agricultural domain.
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.
To keep yield advances, farmers in Mato Grosso (MT) have been adopting several technological innovations. Therefore, agricultural production systems in MT have become complex and dynamic since farmers have to consider the increase of decision variables when planning and implementing their farming practices. These variables are widely spread across many distinct topics, bringing them together and summarizing information from diverse fields of research has become a difficult task in farmers’ decision-making process.
The present study was designed with the following objectives: i) to evaluate selected stress-tolerant maize hybrids developed by CIMMYT in eastern Africa under farmers’ conditions; ii) to identify farmers’ selection criteria in evaluating and selecting maize hybrids; iii) to let farmers evaluate the varieties and score them for the identified criteria and overall.
The aim of the study was to provide the examples of eco-innovations in agriculture relating to the concept of sustainable development and the indication of their conditions. Quantitative and qualitative methods were applied to the research, namely: descriptive statistical and economic analysis of the Polish Farm Accountancy Data Network (FADN) data and Statistics Poland data, as well as case studies of organic food producers, covering the years 2005–2019.