This paper reports on the application of a potentiometric sensor array to the food analysis field, in order to distinguish simple tastes and to classify food samples. This array is formed by a set of non-specific all-solid-state potentiometric sensors and has been used in combination with principal component analysis (PCA) for the classification of food samples in batch and in flow injection mode. First attempt was to classify synthetic samples prepared with controlled variability. Once this ability is proven, satisfactory classification results are presented for commercial waters, orange-based drinks and tea samples. An interesting correlation is achieved between the natural juice content and its first calculated component, which allows for a very simple tool for screening purposes.