Electronic tongues (ETs) are multisensor systems based on the coupling of different sensors with high stability and cross-sensitivity towards different species, along with an appropriate chemometric tool that allow the classification of samples and/or the quantification of selected analytes. Despite the great advantages that the data processing stage may offer (e.g. allowing to offset matrix effects from the sample itself, or to resolve the presence of interferences, drifts or non-linearities obtained with the sensors), the stability of the sensors response together with its varied cross-sensitivity are of utmost importance. In this regard, despite the progress that has been made over the last years and the increasing number of publications dealing with ETs, researchers have focused mainly on the developed application itself or on the data treatment stage, but very few report on the choice of the sensors. In this direction, herein we explore on the development of a simple methodology that allows the a priori selection of the optimal sensor array to carry out a specific application. Concretely, the usage of principal component analysis (PCA) in combination with different clustering indices is proposed as a simple approach to simultaneously assess the cross-response and the reproducibility of the different sensors in a single step, what allows to define which sensors may constitute an ET array for a given qualitative or quantitative application. The above ideas have been applied to the study case of aromatic essential oils.
Keywords: Aromatic essential oils; Clustering indices; Electronic tongue; Partial least squares regression; Principal component analysis; Voltammetric sensors.
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