Yuri Vlasov

Tasting of beverages using an electronic tongue

An electronic tongue based on the sensor array of non-specific solution sensors together with pattern recognition tools has been applied to qualitative analysis of different beverages. It has been found that it is capable both to discriminate reliably between various sorts of the same type of beverages (tea, coffee, beer, soft drinks, juice, etc.) and to monitor the process of aging of juice. Correlations have been found between integral parameters produced by electronic tongue and quality of juice. Some conceptions and backgrounds used for electronic tongue development have been put forward and discussed.

Electronic nose and electronic tongue integration for improved classification of clinical and food samples

Abstract A combined approach based on a multisensor system, to get chemical information from liquid samples through the analysis of the solution and its head space is illustrated and commented. Sensors operating in liquid (electronic tongue) and in the head space (electronic nose) are based on the same sensitive materials: the metalloporphyrins. This gives the opportunity of a certain uniformity of interaction putting in evidence the differences between the solution and its related volatile part. The combined system has been tested in two different experiments in the fields of clinical and food analysis, respectively. Results have shown a net increase of information when the combined systems are used. The sensor fusion procedure has been optimised in order to achieve the best results.

Multicomponent analysis on polluted waters by means of an electronic tongue

In this paper the simultaneous measurements of the concentrations of a number of chemical species in solutions performed by a sensor array of ion sensitive electrodes are presented and discussed. By analogy with the well known electronic nose this sensor array operating in solutions, will be here called electronic tongue. In order to extract optimized information from the electronic tongue output data, many different techniques have been applied; they were based on chemometrics, non-linear least squares and neural networks. The best results have been achieved by the introduction of modular models which make use, at the same time, of both qualitative and quantitative information.

All-solid-state electronic tongue and its application for beverage analysis

Disposable all-solid-state planar-type potentiometric electronic tongue has been developed with the carbon paste electrode array screen-printed on a polymeric substrate. Highly cross-sensitive solvent polymeric membranes based on different matrices [e.g. poly(vinyl chloride) (PVC), aromatic polyurethane, and polypyrrole (Ppy)] and doped with common electroactive components for potentiometric measurements (e.g. various plasticizers, and cation- and anion-selective ionophores) were deposited on the screen-printed carbon paste electrodes (SCPEs). It was observed that an incorporation of 10 wt.% of Prussian Blue (PB; Fe4(III)[Fe(II)(CN)6]3) into a commercially available carbon paste and electrochemical preanodization of SCPEs in KCl solution at 1.6 V provide the all-solid-state planar-type electrodes with significantly improved potentiometric stability. The proposed fabrication method gives possibility for simple and reproducible mass-production of low-cost disposable electronic tongue microsystems. The practical utility of all-solid-state disposable electronic tongue chips has been demonstrated with a flow injection cell for the analysis of potable waters, soft drinks, and beers. It is shown that the potentiometric measurements with the SCPE-based all-solid-state chips and the combined use of chemometric methods (e.g. principal components analysis, partial least regression (PLS), and principal component regression (PCR)) for the analysis of obtained data sets successfully discriminate various types of samples according to their tastes.

Cross-sensitivity evaluation of chemical sensors for electronic tongue: determination of heavy metal ions

The development of the promising new field of sensor applications, multisensor arrays for liquid analysis based on the principles of the electronic tongue, implies some new demands on sensor material research and development. Stable and reproducible sensors with partial specificity and considerable cross-sensitivities to different components in solutions are of primary interest. Solid-state potentiometric sensors, both crystalline and vitreous, are likely to be the most promising ones for multisensor devices designed for long-term analytical application in natural and artificial complex media. The present paper deals with development of a method of evaluation of integral heavy metal cation sensitivity of solid-state sensors with special consideration of cross-sensitivity features. The method involves a comparative study of different sensor materials in individual component solutions, using several criteria based on integral response parameters. The procedure scheme can be applied to evaluate cross-sensitivity of any kind of potentiometric sensors for liquid media.

Multicomponent analysis of Korean green tea by means of disposable all-solid-state potentiometric electronic tongue microsystem

Abstract All-solid-state ‘electronic tongue’ microsystem comprised of polymeric sensors of different types such as highly cross-sensitive sensors based both on PVC and aromatic polyurethane (ArPU) matrices doped with various membrane active components, electrochemically deposited conductive films of polypyrrole (PPy) and polyaniline (PAn) and potentiometric glucose biosensors has been developed and applied for the analysis of beverages: natural coffee, black tea and different sorts of green teas. The system can discriminate different kinds of teas (black and green) and natural coffees. Components that are responsible for giving unique taste such as caffeine, catechines, sugar, amino acid l -arginine have been determined for green tea samples with unknown manufacturer specifications.

Application of a combined artificial olfaction and taste system to the quantification of relevant compounds in red wine

Abstract The combined application of an electronic nose and an electronic tongue to a number of samples of red wine having the same denomination, produced in the same year but from different vineyards, is illustrated and discussed. Artificial sense data have been compared with the analytical chemistry analysis performed with ordinary methods. The data reveal, first of all, a net distinction between electronic nose and electronic tongue, confirming the hypotheses that both the systems offer independent information on the samples. A certain correlation with some of the analytical indicators has also been found and a neural network regression model has been assessed for the qualitative determination of some of them.

Enzyme semiconductor sensor based on butyrylcholinesterase

Abstract An enzyme field-effect transistor with a gelatin membrane containing butyrylcholinesterase (BCE) is investigated. The membrane formation procedure and experimental conditions are optimized. The sensor exhibits sensitivity to butyrylcholine in the range 10−4−10−2 mol/l with a response time 2 min. The influence of reversible and irreversible inhibitors on the sensor characteristics is studied.

Multicomponent analysis of heavy metal cations and inorganic anions in liquids by a non-selective chalcogenide glass sensor array

Abstract A first step towards a multisensor system, based on ion-selective electrodes, for the analysis of complex solutions is presented. An array formed by chalcogenide glass electrodes has been utilized for the quantitative analysis of solutions containing seven ionic species (heavy metal cations and inorganic anions). An important step in working with a sensor array is the data analysis strategy. The array data have been processed by multiple linear regression, partial least squares and artificial neural network. By using neural networks the best performances were obtained. It is worth noting that zince and sulphate have been measured although no specific sensors for these ions were present in the array.

Chemical sensor array for multicomponent analysis of biological liquids

Abstract The development of new methods of on-line monitoring of biological liquids such as human blood, blood plasma or dialysis solutions for artificial kidney is still an urgent task. Ion-selective chemical sensors (ISEs) are convenient instruments for this purpose and are widely used in commercial blood analysers. However, they have significant drawbacks. The promising way to overcome them is the use of array of sensors with cross-sensitivity together with pattern recognition methods. The present work has been concerned with the development of a multisensor system for simultaneous determination of Ca 2+ , Mg 2+ , Na + , HCO − 3 , Cl − , H + and HPO 2− 4 ions in solution modelling human blood plasma. The sensor array included 30 sensors based on non-specific original PVC materials, both cation- and anion-sensitive. Sensing materials for the array were chosen on the basis of cross-sensitivity estimation results with the help of the method that we suggested earlier. Back-propagation artificial neural network was utilised for data processing. It was demonstrated that the sensor array approach allows to measure the content of all these species with an average precision of about 1–4% depending on the component in typical ranges for biological liquids, including Mg 2+ , HCO − 3 and H 2 PO − 4 determination and pH measurement without an oxide glass pH-electrode.