The objective of this study was to generate groups of agri-food producers with high affinity in relation to their sustainable waste management practices. The aim of conforming these groups is the development of synergies, knowledge management, and policy- and decision-making by diverse stakeholders. A survey was conducted among the most experienced farmers in the region of Nuevo Urecho, Michoacán, Mexico, and a total of eight variables relating to sustainable waste management practices, agricultural food loss, and the waste generated at each stage of the production process were examined. The retrieved data were treated using the maximum inverse correspondence algorithm and the Galois Lattice was applied to generate clusters of highly affine producers. The results indicate 163 possible elements that generate the power set, and 31 maximum inverse correspondences were obtained. At this point, it is possible to determine the maximum number of relationships, called affinities. In general, all 15 considered farmers shared the measure of revaluation of food waste and 90% of the farmers shared affinity in measures related to ecological care and the proper management of waste. A practical implication of this study is the conformation of highly affine clusters for both policy and strategic decision-making.
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The growing appetite of cities is one of the greatest future challenges. There is no set menu for meeting this appetite, but a trend is observed in which city authorities focus on region-based food provision. Regionalism is motivated by the importance of increased self-reliance. Besides, regional food systems, are associated with more sustainable production and reduced carbon footprints, the reconnection of consumers with production, and the increased uptake of whole foods in urban diets. However, the question remains to what extend region based food systems may become self-reliant? How may they contribute to improved sustainability and healthy lifestyles? With the Dutch city of Almere as a case in point this paper provides a food flow data-based analysis of the opportunities and limitations of regional based food system approaches. The paper sets off with defining the concepts of sustainable self-reliance and regionalism. Next, it describes the methodology of measuring and mapping the actual food flows. We combined secondary, publicly available, with primary quantitative and qualitative datasets, involving regional businesses, urban policymakers, and residents. Our study uncovers the coinciding disconnect and interconnectedness of local, regional and global food systems. The regional scale offers opportunities for tackling many food related challenges, however, sustainable urban food security demands connections beyond the regional sphere and beyond the food domain. To assess the effects of the policy options available at the local and regional level, a solid evidence base is essential. This paper advances the development of evidence-based methodologies to monitor and inform food system policies.
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BackgroundScientific software incorporates models that capture fundamental domain knowledge. This software is becoming increasingly more relevant as an instrument for food research. However, scientific software is currently hardly shared among and (re-)used by stakeholders in the food domain, which hampers effective dissemination of knowledge, i.e. knowledge transfer.Scope and approachThis paper reviews selected approaches, best practices, hurdles and limitations regarding knowledge transfer via software and the mathematical models embedded in it to provide points of reference for the food community.Key findings and conclusionsThe paper focusses on three aspects. Firstly, the publication of digital objects on the web, which offers valorisation software as a scientific asset. Secondly, building transferrable software as way to share knowledge through collaboration with experts and stakeholders. Thirdly, developing food engineers' modelling skills through the use of food models and software in education and training.
