Sweetener Recognition and Taste Prediction of Coke Drinks by Electronic Tongue

Natural and artificial sweetener monitoring methods are getting more important, since soft drinks with low energy play a considerable role in the market. Our objective is to describe the relevant sensory attributes and to determine the applicability of the electronic tongue to discriminate the coke drink samples with different sweeteners. Furthermore, the aim is to find a relationship between the taste attributes and measurement results received by the electronic tongue. An Alpha astree electronic tongue and a trained sensory panel are used to evaluate coke samples. Panelists found significant differences between the samples in 13 cases from the 18 sensory attributes defined previously by the consensus group. The samples are definitely distinguished by the electronic tongue. The main difference is found according to the sweetener content of the samples. The electronic tongue is able to distinguish samples containing different kinds of artificial and natural sweeteners, as well. The electronic tongue is able to predict, by the partial least squares regression method, the taste attributes of the coke drinks determined by the sensory panel with close correlation and low prediction error.