This article analyses spatial innovation dispersion and also level of innovation development across the crop sector. For this, five crude indicators viz. Mechanisation indicator, Vulnerability indicator, Concentration indicator, Stability indicator and Adoption indicator were constructed which determined the direction of innovation. Agricultural Innovation System encompasses both the facets of technology development and technology dissemination. However, much concentration and efforts were exerted on innovation and technology development part while the other part i.e.
Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.
Controlled Environment Agriculture (CEA) is the production of plants, fish, insects, or animals inside structures such as greenhouses, vertical farms, and growth chambers, in which environmental parameters such as humidity, light, temperature and CO2 can be controlled to create optimal growing conditions.
The Chinese Government has initiated a series of agricultural reforms since the 1970s to encourage agents to provide more services to farmers. In 2006, a new round of agricultural reforms was extended nationwide; however, the effectiveness of these reforms has not been examined. Based on a comparison of survey data sets before and after the reforms, we found that overall they significantly increased the time agents spend on agricultural extension services, although their effectiveness differs among three major components of the reforms.
In this book, the authors assessed the role of biotechnology innovation for sustainable development in emerging and developing economies. This book compiles studies that each illustrate the potential, demonstrated value and challenges of biotechnology applications for sustainable agricultural innovation and/or industrial development in a national, regional and international context.
Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance.
This paper examines the role of postsecondary agricultural education and training (AET) in sub-Saharan Africa in the context of the region’s agricultural innovation systems. Specifically, the paper looks at how AET in sub-Saharan Africa can contribute to agricultural development by strengthening innovative capacity, or the ability of individuals and organisations to introduce new products and processes that are socially or economically relevant, particularly with respect to smallholder farmers who represent the largest group of agricultural producers in the region.
The Commission on Sustainable Agriculture Intensification (CoSAI) and the Foreign, Commonwealth and Development Office (FCDO) jointly commissioned a gap study to determine how far away innovation investment is from helping agri-food systems achieve zero hunger goals and the Paris Agreement while reducing impacts on water resources in the Global South. The results show that the world can come much closer with some well-placed investments.
Considering the new opportunities that ICT innovations bring to improve performance of financial and extension services, this study looks at the potential contribution of financial and extension services to the Sustainable Development Goals (SDGs). The approach used extends the standard Data Envelopment Analysis (DEA) model to include longer-term management goals and find a solution that balances the efficient use of innovation investments and the achievement of policy goals, making this approach well suited for the analysis of the SDGs.