A new sensor technology, an electronic tongue based on voltammetry has been developed at Linköping University. Three different metallic working electrodes are used in combination with a set of voltage "pulses", a waveform, to separate different samples. In this paper, three different waveforms are investigated. This is done through a study with nine different teas. Multivariate data analysis ((MVDA), principal component analysis (PCA)) is used to evaluate the data (the recorded current responses). The waveforms are large amplitude pulse voltammetry (LAPV), small amplitude pulse voltammetry (SAPV), and staircase voltammetry. Each method discriminated between the tea samples to some extent, but differently from each other. Best discrimination is achieved when the combination LAPV and staircase are merged together. When SAPV is included in the combination a worse separation is observed. It is clearly the case that more waveforms do not automatically lead to more information. © 2001 Elsevier Science B.V.

An electronic tongue based on voltammetry and a multichannel lipid membrane taste sensor based on potentiometry are compared using two aqueous examples: detergents and teas. The electronic tongue consists of four electrodes of different metals, a reference electrode and a counter electrode. The measurement principle is based on pulse voltammetry in which current is measured during the change of the amplitude of the applied potential. The taste sensor is based on eight different lipid/polymer membranes. The voltage difference between the electrodes and an Ag/AgCl reference electrode is measured when the current is close to zero. The responses from the two sensors systems are treated separately with multivariate data analysis based on principal component analysis and then merged to examine if further information could be extracted. It is shown that although the two sensor systems are about equal in separation ability in the two cases, extra information can be gained by combination of the two sensor systems. © 2001 Elsevier Science B.V. All rights reserved.

A study that investigates if it is possible to discriminate between the different rinses in a household washing machine with a voltammetric electronic tongue is concluded. The voltammetric electronic tongue applies a potential pulse train over two electrodes and measures the produced current. Multivariate data analysis is used to treat the data. In this paper, a simplified electronic tongue, with only 5% of the original current responses, is used. The rinses from 20 machine wash runs with four different prerequisites are investigated. Principal component analysis (PCA) and Soft-independent modelling of class analogy (SIMCA) are used in order to classify the rinses. In PCA, only one of the rinses is classified erroneous, and in SIMCA none of the rinses are classified only to the wrong class, although 38% of the rinses are classitied to more than one class. (c) 2005 Elsevier B.V. All rights reserved.