Seafood freshness: e-nose data for classification purposes

Abstract

The aim of this study was to develop an electronic nose system useful for the inspection of different seafood products and specifically designed to be applied as an auxiliary device for the management of seafood in the large-scale distribution chain. Since the freshness is a critical issue in determining the quality of fish it is of great importance to have a simple and rapid analytical method representing a useful tool for assessing the acceptability of the seafood products in the distribution centers or in the supermarkets. In this work a portable e-nose, composed by four selected metal oxide semiconductor sensors, a photoionization detector and two electrochemical cells, was applied to test three different seafood products - sole (Solea senegalensis) fillets, red mullet (Mullus barbatus) fillets and cuttlefish (Seppia officinalis) - during their shelf life from the day of arrival and packaging at the distribution center until beyond the expiration date. The K-means partitional clustering method was applied to group samples into three freshness classes, then confirmed by microbial analysis; two classification models based on k-nearest neighbors (K-NN) and partial least square-discriminant analysis were developed to classify the freshness of the seafood regardless the species and in particular, the KNN model provided 100% overall sensitivity, specificity and precision in prediction thus confirming the applicability of the system to inform retailers on product safety and quality.