Tongues, electronic

Some further examples of sample classification from electronic tongues containing ICP-modified electrodes as at least one of the elements constituting the sensor array are reported in Table 2.4. 

Finally, ICP-modified electrodes have also been proposed for the quantitative determination of some analytes by exploiting a multi-linear regression approach (see Chap. 1). By considering the entire voltammetric path registered in the sample it was possible to quantify meaningful parameters for quality control in the food industry, such as total polyphenol content [134, 139]. 

Data analysis of l voltammetric ET j Hi B X, signals Data processing, calculation of RMSE, selectivitv. specificity. F  

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MULTISENSOR SYSTEMS ELECTRONIC TONGUE BASED ON LOW-SELECTIVE SENSORS AND MULTIWAY METHODS OF RECEIVED DATA TREATMENT... 

The electronic nose and electronic tongue can be considered as a specific branch of the development of artificial intelligence and application of the electronic brain. 

Definition the electronic tongue is an analytical instrarment including an array of low-selective chemical sensors and appropriate pattern recognition tool, capable to recognize quantitative and qualitative compositions of simple and complex solutions . 

The paper describes the different chemical sensors and mathematical methods applied and presents the review of electronic tongue application for quantitative analysis (heavy metals and other impurities in river water, uranium in former mines, metal impurities in exhaust gases, ets) and for classification and taste determination of some beverages (coffee, bear, juice, wines), vegetable oil, milk, etc. [1]. 

Vlasov Y., Legin A., Rudnitskaya A. Electronic tongues and their analytical application. 

Chitosan-clay bio-nanocomposites are very stable materials without significant desorption of the biopolymer when they are treated with aqueous salt solutions for long periods of time. In this way, they act as active phases of electrochemical sensors for detection of ions (Figure 1.8). The particular nanostructuration of the biopolymer in the interlayer region drives the selective uptake of monovalent versus polyvalent anions, which has been applied in electrode arrays of electronic tongues [132]. 

Figure 11. Flow through chip which provides the basis for the Electronic Tongue biosensor (www.cm.utexas.edu/mcdevitt/tastechip.htm, March 22, 2004).

A. Legin, A. Rudnitskaya, and Y. Vlasov, Electronic tongues sensors, systems, applications. Sensors Update 10,143-188 (2002). 

The electronic nose and electronic tongue will be described as systems able to give olfactory and chemical images, respectively, in a variety of applications fields, including medicine, environment, food and agriculture. 

The term artificial tongue is used in two main branches of science. The first one concerns the neurophysiological studies aimed at developing perceptual supplementation devices, with biomedical engineering applications to human disabilities. The second utilization of the term artificial tongue concerns, instead, the laboratory analytical instruments used in combination with chemometric techniques to obtain complex information (often sensory-like, but not only) on samples. As for this latter meaning, also the synonymous electronic tongue is frequently used, particularly for electroanalytical devices. 

In order to better describe the utilization purposes, some authors proposed a distinction between electronic tongues and taste sensors the former term should have a wider meaning, embracing all the possible applications, while the latter should exclusively refer to sensory-like evaluations. 

FIGURE 2.3 Trend of electronic tongue original research papers over the period 1996-2009. Data obtained from a literature search using SciFinder Scholar. 

FIGURE 2.S Differentiation of beverages of very different nature by means of an electronic tongue based on potentiometric sensor arrays (reproduced from Vlasov et al., 2000, with permission). 

Several analytical devices have found application as test sensors or, more generally, as electronic tongues for characterizing foods or food ingredients, being able to provide information related to the human sensorial perception or to other important features. There are some examples of electronic tongues based on optical techniques as well as on mass measurements, but the analytical methods that have been most widely exploited in this field are, without any doubt, the electrochemical ones, as shown in Fig. 2.6. 

Within the electroanalytical sector, potentiometry and voltammetry are the principal methods applied in electronic tongue studies, followed by impedance spectroscopy. 

Voltammetry is the second most utilized technique for electronic tongue devices (see Fig. 2.6). It is a d)mamic electroanalytical method, that is, a current flow passes through the measurement cell (z 0). Voltammetry consists of the measurement of current at a controlled potential constant or, more frequently, varying. In the classic three-electrode cell configuration, the current flows between two electrodes, called working and counter (or auxiliary) respectively, while the potential is controlled between the working and a third electrode, the reference (Kissinger and Heineman, 1996). 

In chronoamperometry, which is employed in a few electronic tongue systems (Cortina et al., 2008 Han et al., 2004), the potential is kept constant, while the current variations, resulting from faradic processes occurring at the electrode, are monitored as a function of time. 

On the other hand, pattern recognition tools are widely employed for processing data in the field of electronic tongues and, more generally, of artificial senses. Nowadays, a large number of chemometric techniques, which are schematized in Fig. 2.7, are available, giving the... 

Nevertheless, in most of the electronic tongue applications found in the literature, classification techniques like linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) have been used in place of more appropriate class-modeling methods. Moreover, in the few cases in which a class-modeling technique such as soft independent modeling of class analogy (SIMCA) is applied, attention is frequently focused only on its classification performance (e.g., correct classification rate). Use of such a restricted focus considerably underutilizes the significant characteristics of the class-modeling approach. 

Artificial neural networks (ANNs) have been widely applied in the electronic tongue literature both for classification and multivariate regression problems almost one-third of the papers on electronic tongues examined for this review show ANN applications (see Fig. 2.10). 

Multilayer feed-forward neural networks (MLF) represent the type of ANNs most widely applied to electronic tongue data. Their scheme is shown in Fig. 2.17. 

Nevertheless, in many electronic tongue studies, such constraints are ignored and ANNs are used as the default choice. This choice is also made in cases with very poor data sets and without performing a proper validation. This may be due to the fact that the related computational software is easily available and that many people have a propensity to follow the predominant trends and to use the most potent instruments available, without critical considerations. Furthermore, perhaps, there is a fashionable association of ideas coimecting the concepts of artificial tongue and artificial intelligence. 

Unfortunately, electronic tongue variables are very often considerably intercorrelated in voltammetric profiles, for instance, currents evaluated at two consecutive potential values frequently carry almost the same information, so that their correlation coefficient is nearly 1. In such cases, standard OLS is absolutely not recommendable. Furthermore, the number of objects required for OLS regression must be at least equal to the number of predictors plus 1, and it is difficult to satisfy such a condition in many practical cases. 

Wine is the food which has been most extensively analyzed by means of electronic tongues. T)/pical qualitative studies concern the characterization of wine on fhe basis of vinfage and vineyard. 

Buratti et al. (2004) employed an electronic tongue based on ampero-metric detection in a flow injection system (FIA), coupled with an electronic nose, to discriminate wines from vineyard Barbera produced in four Ifalian oenological regions with different denominations Oltrepo Pavese, Piemonte, Asti, and Alba. The chemometric techniques applied were PCA for dafa exploration, and LDA and CART (classification and regression frees) for classification. 

Gutes and coworkers presented an automated electronic tongue based on sequential injection analysis (SIA) and linear sweep voltammetry, for the simultaneous determination of glucose and ascorbic acid, by means of ANN regression. The models were evaluated with an external test set (Gutes et al., 2006). 

Olsson et al. (2006) studied the performances of a mechanically selfpolishing electronic tongue based on pulsed voltammetry, for tea analysis. From the PCA scores (see Fig. 2.24), a drift in the measurements is clearly evident. An appropriate row pretreatment of the signals might reduce this effect without loss of useful information. 

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