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 issue of regional differences in development has moved to the center of the development debate in Sri Lanka, partly after the release of regional poverty data. For the past many years, there have been significant and increasing differences between the Western province and the rest of the country in terms of per capita income levels, growth rates of per capita income, poverty rates, and the structure of provincial economies. The structure of the report is as follows: chapter two looks at the poverty/growth/agriculture nexus in the poorest regions of Sri Lanka.
This review's objectives were to examine the structure and performance of the agricultural research and extension systems (public and private) at the central and provincial levels, identify successes as well as constraints to improving the system s effectiveness for fostering innovation, and propose options for further policy and institutional development, drawing on lessons from international experience. The review focused principally on nonplantation crops, although its main recommendations apply across the agricultural sector.
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.
The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.
A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.
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.