Detection of Parasites in Cod Fillets by Using SIMCA Classification in Multispectral Images in the Visible and NIR Region

Abstract

The presence of parasitic nematodes in fillets of commercially important fish species has been a serious quality problem for the fishing industry for several decades. Various approaches have been tried to develop an efficient method to detect the parasites, but so far the only reasonable solution is manual inspection and trimming of each fish fillet on a candling table. In this study we have investigated how multispectral imaging in combination with SIMCA classification can be used for automatic detection of parasites. The results indicate that the spectral characteristics of nematodes differ sufficiently from those of fish flesh to allow one to obtain fairly good classifications. The method is able to detect parasites at depths down to about 6 mm into the fish muscle. The method shows promising results, but further studies are required to verify feasibility for the fish industry.