Urea biosensors based on urease covalently immobilized on to ammonium and hydrogen ion-selective electrodes were included in arrays together with ammonium, potassium, sodium, hydrogen and generic response to alkaline sensors. Response models based on artificial neural network (ANN) and partial least squares (PLS1) were built, tested and compared for the simultaneous determination of urea, ammonium, potassium and sodium. The results show that it is possible to obtain good ANN and PLS calibration models for simultaneous determination of these four species, but with better prediction capability when the ANN are used. The developed bioelectronic tongue was applied to multidetermination in urine samples. The ANN model showed again better agreement with reference methods, allowing a simple direct determination of urea in the real samples without the necessity of eliminating the alkaline interferences, or compensating endogenous ammonium. © 2006 Elsevier B.V. All rights reserved.
|Journal||Biosensors and Bioelectronics|
|Publication status||Published - 15 Apr 2007|
- Artificial neural networks
- Biosensor array
- Electronic tongue
- Partial least squares