An electronic tongue (ET) employing the transient response of an array of non-specific-response potentiometric sensors was developed for a quantitative application. A sequential injection analysis (SIA) system was used in order to automate its training and operation. This procedure takes profit of the dynamic nature of the sensor's response, which can be of high information content, improving the discrimination ability between primary and interfering ions. This work presents the extraction of significant information contained in the pulse sample transient response of a sensor array formed by eight sensors. The tool employed was the fast Fourier transform (FFT) analysis, from which three coefficients per sensor were fed into an artificial neural network (ANN) model. The studied case was the multidetermination of quaternary mixtures of Ca 2+ , Mg 2+ , Na + and K + in water samples, showing improved resolution when compared to classical ET approaches. © 2007 Elsevier B.V. All rights reserved.
- Artificial neural network
- Electronic tongue
- Fourier transform
- Potentiometric sensor array
- Sequential injection analysis