Since its beginning in the early 70thies, the fast growing Atlantic salmon aquaculture industry in Norway has been and still is an object for research across numerous disciplines and research fields. This article presents an overview of the research studies applying Material Flow Analysis (MFA) based methods on Norwegian Aquaculture of Atlantic Salmon starting from 2004 until 2018. The studies were reviewed in relation to their applied method, involved institutions, flows, data acquisition, and suggestions for improvement. All of the reviewed studies applied different MFA methods suitable to the objective of each study, were done with involvement of multiple institutions and stakeholders, modeled credible data and provided specific suggestions for reducing the environmental impacts and optimizing nutrients utilization efficiency. The review concludes that MFA-based methods have the potential for having a functional role within the framework of the Norwegian Salmon Aquaculture industry's sustainable development. A key factor in fulfilling that potential would be diversifying the objectives of MFA research to be more inclusive of the three pillars of sustainability: environment, economy, and society.
The United Nations 2030 Agenda for Sustainable Development set the target of halving per capita global food waste and reducing food losses, including post-harvest losses. Food loss is a significant global challenge rising from the decrease in food quantities available for human consumption because of decisions and actions taken by food manufacturers and suppliers before it even reaches the retail market. Food loss within the Norwegian farmed salmon post-harvest processing system could be reduced by making change in the system’s behavior. This study, by following systems engineering principles, aimed to develop insight into the salmon post-harvest processing system’s behavioral dynamics causing current food loss and to consider conceptual keys to solutions. This study tied the food loss problem to systemic behavior of byproducts downgrading to non-food uses as the major cause. The decisions made on the materials flow are based on product design, quality control, and environmental solutions. Making a decision to conserve byproduct materials by prioritizing keeping them within the human food chain requires supportive data on their true potential as a food source. The system’s information pool that decision makers rely on can be fortified with the system’s engineering multidisciplinary outcomes that will enable the necessary paradigm shift to achieve the quested food loss reduction.
Purpose Practically all salmon fillets produced in Norway are trimmed clean of unwanted fat, bone remnants and other defects according to customer requirements. In today’s modern salmon-processing plants, the trimming operation is performed by a combination of automated trimming machines and manual post-trimming. Manual post-trimming is necessary due to the inability of current trimming machines to obtain satisfactory trimming. The purpose of this paper is to describe the work done so far toward a robotic post-trimming of salmon fillets. Design/methodology/approach A prototype concept system was developed to explore the possibility of robotic post-trimming. The concept is based on 3D machine vision, a high-speed robot manipulator and a flexible light-weight cutting knife. Findings The developed prototype demonstrated the feasibility of detecting a pre-defined object to be trimmed in 3D, and performing the specified trimming cut along a 3D cutting trajectory. Research limitations/implications The developed prototype system was built and integrated – focusing so far only on a single trimming operation: the tail cut. Originality/value The originality in the paper is the description of a prototype integrated system, focused on robotic post-trimming of salmon fillets. The value is in providing a starting point for further development toward a complete robotic post-trimming of salmon fillets.
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