Alisa Rudnitskaya

Evaluation of Italian wine by the electronic tongue: recognition, quantitative analysis and correlation with human sensory perception

Abstract The electronic tongue based on a sensor array comprising 23 potentiometric cross-sensitive chemical sensors and pattern recognition and multivariate calibration data processing tools was applied to the analysis of Italian red wines. The measurements were made in 20 samples of Barbera d’Asti and in 36 samples of Gutturnio wine. The electronic tongue distinguished all wine samples of the same denomination and vintage, but from different vineyards. Simultaneously the following quantitative parameters of the wines were measured by the electronic tongue with precision within 12%: total and volatile acidity, pH, ethanol content, contents of tartaric acid, sulphur dioxide, total polyphenols, glycerol, etc. The electronic tongue is sensitive to multiple substances that determine taste and flavour of wine and, hence, the system was capable of predicting human sensory scores with average precision of 13% for Barbera d’Asti wines and 8% for Gutturnio wines.

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.

Electronic tongue: new analytical tool for liquid analysis on the basis of non-specific sensors and methods of pattern recognition

Abstract Development of promising sensor instrument — “electronic tongue” based on sensor arrays with data processing by pattern recognition methods have been described. The attention is paid to “electronic tongue” based on an array of original non-specific (non-selective) potentiometric chemical sensors with chalcogenide glass membranes. Principles of research, criteria for the development of non-selective sensing materials, pattern recognition methods have been described. Possible applications and some results of integral qualitative analysis of beverages and of quantitative analysis of complex liquids, containing heavy metals are reported. Discriminating power obtained and possibility of multicomponent analysis permit to consider “electronic tongue” as a perspective analytical concept.

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.

Instrumental measurement of beer taste attributes using an electronic tongue

The present study deals with the evaluation of the electronic tongue multisensor system as an analytical tool for the rapid assessment of taste and flavour of beer. Fifty samples of Belgian and Dutch beers of different types (lager beers, ales, wheat beers, etc.), which were characterized with respect to the sensory properties, were measured using the electronic tongue (ET) based on potentiometric chemical sensors developed in Laboratory of Chemical Sensors of St. Petersburg University. The analysis of the sensory data and the calculation of the compromise average scores was made using STATIS. The beer samples were discriminated using both sensory panel and ET data based on PCA, and both data sets were compared using Canonical Correlation Analysis. The ET data were related to the sensory beer attributes using Partial Least Square regression for each attribute separately. Validation was done based on a test set comprising one-third of all samples. The ET was capable of predicting with good precision 20 sensory attributes of beer including such as bitter, sweet, sour, fruity, caramel, artificial, burnt, intensity and body.

Application of electronic tongue for qualitative and quantitative analysis of complex liquid media

Abstract The present work is devoted to the assessment of analytical applications of a new instrument for multicomponent analysis in liquid media — “electronic tongue”, based on an array of originally designed non-specific solution chemical sensors and pattern recognition tools for processing of multidimensional output of this sensor array. The “electronic tongue” is supposed to be capable to produce integral qualitative imaging (artificial sensing) of complex liquids such as food stuffs and beverages, comparable to human taste panel sensing and enhancing its capabilities by durable and reproducible operation, analysis and tasting of toxic and potentially dangerous media, applicability to long-term routine industry analysis. The method is also successfully applicable to quantitative analysis of different objects such from biological liquids to natural waters. Promising experimental results of “electronic tongue” application in different beverages are reported.

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.

A comparison of five lipid extraction solvent systems for lipidomic studies of human LDL

Lipidome profile of fluids and tissues is a growing field as the role of lipids as signaling molecules is increasingly understood, relying on an effective and representative extraction of the lipids present. A number of solvent systems suitable for lipid extraction are commonly in use, though no comprehensive investigation of their effectiveness across multiple lipid classes has been carried out. To address this, human LDL from normolipidemic volunteers was used to evaluate five different solvent extraction protocols [Folch, Bligh and Dyer, acidified Bligh and Dyer, methanol (MeOH)-tert-butyl methyl ether (TBME), and hexane-isopropanol] and the extracted lipids were analyzed by LC-MS in a high-resolution instrument equipped with polarity switching. Overall, more than 350 different lipid species from 19 lipid subclasses were identified. Solvent composition had a small effect on the extraction of predominant lipid classes (triacylglycerides, cholesterol esters, and phosphatidylcholines). In contrast, extraction of less abundant lipids (phosphatidylinositols, lyso-lipids, ceramides, and cholesterol sulfates) was greatly influenced by the solvent system used. Overall, the Folch method was most effective for the extraction of a broad range of lipid classes in LDL, although the hexane-isopropanol method was best for apolar lipids and the MeOH-TBME method was suitable for lactosyl ceramides.