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.
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.
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.
Social learning in multi-actor innovation networks is increasingly considered an important precondition for addressing sustainability in regional development contexts. Social learning is seen as a means for enabling stakeholders to take advantage of the diversity in perspectives, interests and values for generating more sustainable practices and policies. Although more and more research is done on the meaning and manifestations of social learning, particularly in the context of natural resource management, little is known about the social dynamics in the process of social learning.
This study examines the influence of an extra-curricular educational program on children's knowledge and cultural valuation of wild food plants, which are an important component of their diets. This program aims to reinforce children's traditional knowledge and values around biological resources in Wayanad, India's Western Ghats, encouraging tribal and non-tribal children to learn from each other and from their own communities. Results show that the educational program has enhanced children's ability to identify selected wild food plants.
This methodological guide was initially developed and used in Latin America and the Caribbean-LAC (Honduras, Nicaragua, Colombia, Peru, Venezuela, Dominican Republic), and was later improved during adaptation and use in eastern African (Uganda, Tanzania, Kenya, Ethiopia) through a South-South exchange of expertise and experiences. The aim of the methodological guide is to constitute an initial step in the empowerment of local communities to develop a local soil quality monitoring and decision-making system for better management of soil resources.
In this chapter the authors compute measures of total factor productivity (TFP) growth for developing countries and then contrast TFP growth with technological capital indexes. In developing these indexes, the authors incorporate schooling capital to yield two new indexes: Invention-Innovation Capital and Technology Mastery. They find that TFP performance is strongly related to technological capital and that technological capital is required for TFP and cost reduction growth.
The increasing complexity of technology development and adoption is rapidly changing the effectiveness of scientific and technological policies. Complex technologies are developed and disseminated by networks of agents. The impact of these networks depends on the assets they command, their learning routines, the socio-economic environment in which they operate and their history.
Innovation systems can be defined in a variety of ways: they can be national, regional, sectoral, or technological. They all involve the creation, diffusion, and use of knowledge. Systems consist of components, relationships among these, and their characteristics or attributes. The focus of this paper is on the analytical and methodological issues arising from various system concepts. There are three issues that stand out as problematic. First, what is the appropriate level of analysis for the purpose at hand?