Use of an electronic tongue based on all-solid-state potentiometric sensors for the quantitation of alkaline ions

An array of eight nonspecific potentiometric sensors was used in combination with multivariate calibration for the simultaneous determination of NH 4+ , K + and Na + ions. The sensors were of the all-solid-state type and employed a PVC polymer membrane. Signals were processed by using a multilayer artificial neural network (ANN). The ANN configuration used was optimized by using 8 neurons in the input layer, 5 in the hidden layer and 3 in the output layer. Use of the Bayesian Regularization algorithm allowed a quick building of an accurate model, as confirmed by random multi-starting of network weights. The system was used to analyze synthetic and river water, waste water and fertilizer samples. Correct results were obtained for the three ions in synthetic and real water samples; in fertilizers, ammonium ion can be determined, while sodium and potassium show biased results. © 2005 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.