Volume 55, Number 8, 2001 APPLIED SPECTROSCOPY 1025 0003-7028 / 01 / 5508-1025$2.00 / 0 q 2001 Society for Applied Spectroscopy Detection of Parasites in Cod Fillets by Using SIMCA Classication in Multispectral Images in the Visible and NIR Region JENS PETTER WOLD,* FRANK WESTAD, and KARSTEN HEIA MATFORSK Norwegian Food Research Institute, A Ê s, Norway (J.P.W., F.W.); and Norwegian Fisheries and Aquaculture Research Institute Ltd., Tromsø, Norway (K.H.) The presence of parasitic nematodes in llets of commercially im- portant sh species has been a serious quality problem for the sh- ing industry for several decades. Various approaches have been tried to develop an efcient method to detect the parasites, but so far the only reasonable solution is manual inspection and trimming of each sh llet on a candling table. In this study we have inves- tigated how multispectral imaging in combination with SIMCA classication can be used for automatic detection of parasites. The results indicate that the spectral characteristics of nematodes differ sufciently from those of sh esh to allow one to obtain fairly good classications. The method is able to detect parasites at depths down to about 6 mm into the sh muscle. The method shows promising results, but further studies are required to verify feasibility for the sh industry. Index Headings: Fish quality; Cod worms; Nematodes; Automatic detection; Multispectral imaging; Principal component analysis; PCA; SIMCA classication. INTRODUCTION The presence of parasitic nematodes (cod worms, seal worms, whale worms) in llets of various sh species has been a serious quality problem for the shing indus- try for several decades. The sh (e.g., cod, herring, coal- sh) serve as intermediate hosts for the parasites. In the sh, the worms can migrate from the intestines into the sh muscle, where they stay until the sh is eaten by a primary host (seal or whale). Human consumption of dead nematodes is harmless, so in countries where it is common to either boil, freeze, fry, or heavily salt the sh before consumption, it is not a public health problem. For the consumers, however, the presence of nematodes is unacceptable. To fulll market requirements and avoid complaints, the sh industry must be able to deliver par- asite-free products. Several approaches have been tried in the effort to develop an efcient method to detect the parasites, but so far, the only reasonable solution has been manual inspection and trimming of each llet on a can- dling table. 1 This process is very laborious and costly, and even with optimal conditions, not more than about 75% of the parasites can be expected to be found. 2 A technique for automatic detection of parasites in sh l- lets is therefore much needed. Several principles of detection have been tested [visi- ble light, IR light, uorescence, X-ray, ultrasound, com- puter tomography (CT) and magnetic resonance imag- ing], 3–5 but only CT and ultrasound seem to be able to detect deeply embedded parasites. CT is still too expen- Received 8 February 2001; accepted 24 April 2001. * Author to whom correspondence should be sent. sive for the industry. Ultrasound seems unpractical be- cause the method requires close physical contact between llet and transducers, and the method is very sensitive to air bubbles in/on the llets. Focus of the research has therefore been on optical methods. A problem with the use of trans-illumination by visible light is the very prominent light scattering in sh muscle, which makes it difcult to detect objects inside the llets. Visible light gives contrast between sh muscle and parasites, but by manual inspection, the worms cannot be detected deeper than about 6 mm. 6 Petursson 6 studied the optical prop- erties of sh muscle and reported that absorption spectra from parasites and white and dark sh muscle, as well as blood-stained muscle, showed differences most markedly in the 400–600 nm range. He also showed that scattering decreases with increasing wavelength. He concluded that the near-infrared (NIR) area from 800 to 1200 nm could give better results for deeply embedded parasites. In light of these ndings, it is reasonable to assume that detection of parasites can be based on spectral characteristics. Multispectral imaging has become a commonly used technique within elds spanning all the way from mi- croscopy and medical imaging to satellite remote sensing. It is a powerful basis for segmentation and classication, and it can be used to visualize the chemical composition of materials. 7 Applications have also been suggested for the agriculture and food industries. On-line detection of fecal contamination on poultry carcasses, 8 identication of food products such as maize, pea, soy, and wheat, 9 detection of defects on apples, 10 and mapping of lipid oxidation in chicken meat 11 are some reported applica- tions. Human beings are excellent at detecting parasites. With the combination of color and morphological features with a priori experience, it is rather easy to distinguish visible worms from the sh esh. A computer-based detection system using only morphological image features will probably have limited performance, because the parasites can appear in any shape and are often very similar to features in the sh llet. Spectral properties are indepen- dent of the parasite’s shape. The objective of the work presented in this paper was therefore to investigate whether parasites could be distinguished in cod llets purely on the basis of spectral characteristics. To do this, we collected multispectral images of parasite-infested cod llets in the visible and near-infrared. Modeling and clas- sication were performed by use of multivariate image analysis, including SIMCA classication (soft indepen- dent modeling of class analogies). The paper describes