Sensory evaluation and electronic tongue analysis for sweetener recognition in coke drinks

Abstract

Consumption of beverages with low energy has an increasing role. Furthermore hydrolyzed starch products such as inverted syrup show a wide application in the beverage industry. Therefore the importance of methods which can monitor the usage of natural and artificial sweeteners is increasing. The task was 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 was to find relationship between the taste attributes and measurement results provided by electronic tongue. An Alpha Astree Electronic Tongue and a trained sensory panel were used to evaluate the coke samples. Panelists found significant differences between the samples in 15 cases from the 18 sensory attributes defined previously by the consensus group. Coke drinks containing different kind of sweeteners can be characterized according to these sensory attributes. The samples were definitely distinguished by the electronic tongue. The main difference was found between the samples made with natural and artificial sweeteners. However electronic tongue was able to distinguish samples containing different kind of artificial and different kind of natural sweeteners, as well. Taste attributes of coke drinks determined by sensory panel were predicted by partial least squares regression method based on the results of electronic tongue with close correlation and low prediction error.