Final report of the Evidence-based Food System Design project (EFSD). This research project aimed at building a data-driven mapping of the Amsterdam Metropolitan Food System, as an evidence base for vision and scenario development, policymaking and other initiatives aimed at transitioning to a more sustainable regional food system.
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Banana is an important commercial fruit crop for smallholder farmers in Arba Minch, southern Ethiopia. However, its sector is experiencing many constraints and limited attention given to productivity and marketing. Therefore, this study was conducted to analyze the banana value chain in order to identify constraints on productivity and marketing, and possibilities of improvements towards a sustainable value chain in Arba Minch. Data were collected through a survey, key informants’ interviews, and focus group discussions. Different analytical and statistical tools were used for data analysis. Results describe actors, supporters, and influencers of the existing banana chain. The current banana chain has three different distribution channels in Arba Minch. The channel that connects with rural consumers has the highest value share for farmers while the channel that includes traveling traders has the lowest value share for farmers. The marketing cooperative channel has an intermediate value share for farmers in the chain. Poor agronomic practice, diseases, pests, and climate change were the major constraints for the banana yield while limited market information, lack of cold store and refrigerated trucks, poor post-harvest handling, lack of alternative markets, and weak capacity of cooperatives were the main constraints for banana marketing in Arba Minch. Economic, social and environmental indicators have a moderate sustainability performance within the Ethiopian context. The chain has an advantage in terms of profitability, employment, emission of air pollutants and constraints in terms of coordination, value share, profit margin, market diversity, product and market information, transportation, waste management, and safety and hygiene.
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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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