Application of a portable electronic nose device to discriminate and identify cheeses with known percentages of cow's and goat's milk

Abstract

A portable electronic nose comprising an array of 6 metal oxide semiconductor sensors was developed and used, jointly with pattern recognition methods, to discriminate and identify several cheeses made from goat's, cow's milk and their mixtures. Principal Component Analysis (PCA) was used to visualize the different categories of aroma profiles and Multivariate Analysis of Variance (MANOVA) was performed to test the significance of the differences between cheeses groups. Database was then elaborated using supervised classifiers such as Discriminant Factor Analysis (DFA) with leave one out approach. The results indicate that the portable electronic nose device can clearly and rapidly distinguish between cow's milk cheese, goat's milk cheese and cheeses containing variable amounts of cow's and goat's milk. So, this system can be used in order to avoid fraud and to fulfill customer expectations.