The creative process that leads to farmers’ innovations is rarely studied or described precisely in agricultural sciences. For academic scientists, obvious limitations of farmers’ experiments are e.g. precision, reliability, robustness, accuracy, validity or the correct analysis of cause and effect. Nevertheless, we propose that ‘farmers’ experiments’ underpin innovations that keep organic farming locally tuned for sustainability and adaptable to changing economic, social and ecological conditions.
This is the proceedings of the international conference ‘Innovations in Organic Food System for Sustainable Production and Enhanced Ecosystem Services’. The proceedings are a compilation of peer-reviewed articles based on presentations of 18 speakers invited conference speakers and published as a Special Issue of the scientific journal ‘Sustainable Agriculture Research’ by the Canadian Centre of Science and Education.
Farmers’ experiments can be defined as the autonomous activities of farmers to try or introduce something new at the farm, and include evaluation of success or failure with farmers’ own methods. Experiments enable farmers to adapt their farms to changing circumstances, build up local knowledge, and have resulted in countless agricultural innovations. Most research on the topic has been conducted in countries of the south.
Organic farming is recognized as one source for innovation helping agriculture to develop sustainably. However, the understanding of innovation in agriculture is characterized by technical optimism, relying mainly on new inputs and technologies originating from research. The paper uses the alternative framework of innovation systems describing innovation as the outcome of stakeholder interaction and examples from the SOLID (Sustainable Organic Low-Input Dairying) project to discuss the role of farmers, researchers and knowledge exchange for innovation.
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.
A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.
The study was designed to answer the following three key questions:
(1) What types of investment instruments have been tested to support innovation in agri-food systems in the Global South, and how can these be categorized into a working typology?
(2) What is the evidence on how well different instruments have supported SAI's multiple objectives (e.g. social equality and environmental) at scale and what contextual and design factors affect their success or failure in achieving these objectives (e.g. type of value chain, who participates)?