A novel method for classification of wine based on organic acids

Abstract

Bio-electronic tongue was linked to artificial intelligence processing unit and used for classification of wines based on carboxylic acids levels, which were indirectly related to malolactic fermentation. The system employed amperometric biosensors with lactate oxidase, sarcosine oxidase, and fumarase/sarcosine oxidase in the three sensing channels. The results were processed using two statistical methods - principal component analysis (PCA) and self-organized maps (SOM) in order to classify 31 wine samples from the South Moravia region in the Czech Republic. Reference assays were carried out using the capillary electrophoresis (CE). The PCA patterns for both CE and biosensor data provided good correspondence in the clusters of samples. The SOM treatment provided a better resolution of the generated patterns of samples compared to PCA, the SOM derived clusters corresponded with the PCA classification only partially. The biosensor/SOM combination offers a novel procedure of wine classification.