Building a predictive empirical model of salmon filet yield of individual whole fish based on characterisation of external anatomical physiology.

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Global fish populations are under increasing pressure as the human population grows, but a great deal of fish is wasted in processing owing to the natural variability in anatomical characteristics of individuals. We are investigating a novel technique, leveraging automated machine vision inspection methodology, to help fish processing facilities optimize the yield of high quality filets from raw fish based on the physiology of individuals. For decades, manufacturers around the world have benefited from automation and machine vision inspection tools to refine processes and optimize yield. These techniques and tools are not widely used in the food processing industry, but show a great deal of promise if they can be adapted for use on high-inherent-variability biological raw materials.