PCA Scores showed (Fig. SI 1) that three valinomycin based membranes are not sufficient to cluster the samples into 7 groups. Analysis showed that at least two different sensor types are needed to obtain proper clustering of the samples. Interestingly presence of valinomycin based sensors was not a requisite, and similar results of PCA analysis were obtained for arrays (NH4 + ; K + Val) and (An, Cat, NH4 + , K + DB) (Fig. ). To predict the concentration potassium in real samples different models were tested, including Partial Least Squares (PLS), Multivariate Linear Regression (MLR), Multivarite Polynomial Regression (MLP), Principal Component Regression (PCR) and an ensemble Random Forest algorithm (RF). To compare all the methods in equal manner 25 % of the dataset was randomly chosen as the test set and the rest of the data was used to train the models. The same 4 random splits were used to test all the models and all the proposed compositions of the sensor arrays.