The changes in skin and fillet color of anesthetized and exhausted Atlantic salmon were determined immediately after killing, during rigor mortis, and after ice storage for 7 d. Skin color (CIE L*, a*, b*, and related values) was determined by a Minolta Chroma Meter. Roche SalmoFan Lineal and Roche Color Card values were determined by a computer vision method and a sensory panel. Before color assessment, the stress levels of the 2 fish groups were characterized in terms of white muscle parameters (pH, rigor mortis, and core temperature). The results showed that perimortem handling stress initially significantly affected several color parameters of skin and fillets. Significant transient fillet color changes also occurred in the prerigor phase and during the development of rigor mortis. Our results suggested that fillet color was affected by postmortem glycolysis (pH drop, particularly in anesthetized fillets), then by onset and development of rigor mortis. The color change patterns during storage were different for the 2 groups of fish. The computer vision method was considered suitable for automated (online) quality control and grading of salmonid fillets according to color.

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The present study describes the possibilities for using computer vision-based methods for the detection and monitoring of transient 2D and 3D changes in the geometry of a given product. The rigor contractions of unstressed and stressed fillets of Atlantic salmon (Salmo salar) and Atlantic cod (Gadus morhua) were used as a model system. Gradual changes in fillet shape and size (area, length, width, and roundness) were recorded for 7 and 3 d, respectively. Also, changes in fillet area and height (cross-section profiles) were tracked using a laser beam and a 3D digital camera. Another goal was to compare rigor developments of the 2 species of farmed fish, and whether perimortem stress affected the appearance of the fillets. Some significant changes in fillet size and shape were found (length, width, area, roundness, height) between unstressed and stressed fish during the course of rigor mortis as well as after ice storage (postrigor). However, the observed irreversible stress-related changes were small and would hardly mean anything for postrigor fish processors or consumers. The cod were less stressed (as defined by muscle biochemistry) than the salmon after the 2 species had been subjected to similar stress bouts. Consequently, the difference between the rigor courses of unstressed and stressed fish was more extreme in the case of salmon. However, the maximal whole fish rigor strength was judged to be about the same for both species. Moreover, the reductions in fillet area and length, as well as the increases in width, were basically of similar magnitude for both species. In fact, the increases in fillet roundness and cross-section height were larger for the cod. We conclude that the computer vision method can be used effectively for automated monitoring of changes in 2D and 3D shape and size of fish fillets during rigor mortis and ice storage. In addition, it can be used for grading of fillets according to uniformity in size and shape, as well as measurement of fillet yield measured in thickness. The methods are accurate, rapid, nondestructive, and contact-free and can therefore be regarded as suitable for industrial purposes.