Multivariate Determination of Total Sugar Content and Ethanol in Bioethanol Production Using Carbon Electrodes Modified with MWCNT/MeOOH and Chemometric Data Treatment

This work reports the characterization and application of a voltammetric electronic tongue using an array of glassy carbon electrodes modified with multi‐walled carbon nanotubes containing metal (Pd, Au, Cu) and oxy‐hydroxide nanoparticles (MetalsOOH of Ni, Co) towards the determination of total sugar content in products related with sugarcane‐bioethanol production. The prediction model based on Artificial Neural Networks (ANN) has given satisfactory results for the carbohydrate sum and the obtained response had shown an adequate accuracy. Voltammetric data was first adapted for the computation using the Fast Fourier transform, and results from the electronic tongue approach were compared with use of different electrodes alone. Final performance was better using uniquely the Ni oxy‐hydroxide modified electrode, especially in the quantification of ethanol, a side‐effect of counter‐balancing its interference.     

A voltammetric electronic tongue made of modified epoxy-graphite electrodes for the qualitative analysis of wine

First results are presented of a new voltammetric electronic tongue which employs modified epoxy-graphite electrodes. This analytical tool has been applied to qualitative wine analysis, performing the classification of wine varieties, as well as recognition of the oxygenation effect. In the same way, studies related to the detection of some defects in wine production were also assessed, such as its vinegary taste in open-air contact or the use of excess sulphite preservative. The electronic tongue was formed by five voltammetric electrodes, four of them being bulk-modified with different substances: copper and platinum nanoparticles on one side, and polyaniline and polypyrrole powder on the other. The responses were preprocessed employing Principal Component Analysis (PCA) to visualize and identify distinct episodes. The resulting PCA scores were modelled with an artificial neural network that accomplishes final prediction with the qualitative classification of wines and/or detection of defects.     

Potentiometric Electronic Tongue for Taste Assessment of Ibuprofen Based Pharmaceuticals

The flavor aspect of pharmaceutical formulations is very important in terms of their acceptability for the patient. This work is aimed at using of a novel promising type of electronic tongue (ET), consisting of a potentiometric sensor array, for the discrimination and assessment the taste of commercial pharmaceuticals based on ibuprofen (Ibuflam 4 %). The sensor array was formed by six ion‐selective membranes (ISMs) based on both specific and non‐specific active components. Analysis of potentiometric signal outputs including statistical data processing utilizing the principal component analysis (PCA) method allowed evaluating the role of individual active components of the ISMs in the sense of taste control of the pharmaceutical preparation Ibuflam 4 % before and after flavoring. The sensing array can be used to identify differences in flavor within individual batches from the same producer, since ISMs provide a different response to all components present in the analyzed pharmaceutical. The ET contains ISMs which are able to recognize the bitter taste in the framework of the batches of ibuprofen based pharmaceuticals. To recognize bitter taste, it was essential to include ISMs, providing a response to a particular type of taste, namely, specific and non‐specific ISMs. The experimental findings show that taste‐sensing potentiometric sensor system can be a good alternative to the human panel and is able to detect the slight changes in taste.     

Zinc oxide nanotubes decorated with silver nanoparticles as an ultrasensitive substrate for surface-enhanced Raman scattering

We introduce a novel voltammetric method, so-called sinusoidal envelope voltammetry, for use in electronic tongues. Fourier transformation was used to transform the data of the signal from the time domain to the frequency domain. The four taste substances, acesulfame potassium, monosodium glutamate, potassium chloride and tartaric acid, are shown to exhibit abundant frequency characteristics in the power spectrum of a Fourier transformation. This indicates that the power spectrum from sinusoidal envelope voltammetry can be used as fingerprints of samples for classification. Principal component analysis along with discrimination index and multi-frequency large amplitude pulse voltammetry as a reference technique is used to evaluate the separation ability of sinusoidal envelope voltammetry. The score plots of the method for the four taste substances and for the five brands of Jiafan rice wine show better discrimination ability than multi-frequency large amplitude pulse voltammetry. Sinusoidal envelope voltammetry is considered to be a promising technique for use in voltammetric electronic tongues.

Voltammetric Electronic Tongue for the Qualitative Analysis of Beers

This paper deals with the application of a voltammetric electronic tongue (ET) towards beers classification. For this purpose, samples were analyzed using cyclic voltammetry without performing any sample pretreatment, albeit its dilution with distilled water. The voltammetric signals were first preprocessed employing Fast Fourier Transform (FFT). Then, using the obtained coefficients, responses were evaluated using three different clustering techniques: Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS‐DA) and Linear Discriminant Analysis (LDA). In this case, the ET has demonstrated a good capability to correctly discriminate and classify the different beer samples according to its type (Lager, Stout and IPA) and manufacture process (commercial and craft).     

State of the Art in the Field of Electronic and Bioelectronic Tongues – Towards the Analysis of Wines

This review compares various types of (bio)electronic tongues. The design and principles of potentiometric and voltammetric electronic tongues are discussed together with applications in food and environmental analysis. Different approaches towards bioelectronic tongue are presented. Several methods for evaluation and interpretation of the measured data are described. Finally, the potential of such devices for analysis of wine is discussed.     

Determination of indoor air quality of a phytosanitary plant

Effective fermentation monitoring is a growing need due to the rapid pace of change in the wine industry, which calls for fast methods providing real time information in order to assure the quality of the final product. The objective of this work is to investigate the potential of non-destructive techniques associated with chemometric data analysis, to monitor time-related changes that occur during red wine fermentation. Eight micro-fermentation trials conducted in the Valtellina region (Northern Italy) during the 2009 vintage, were monitored by a FT-NIR and a FT-IR spectrometer and by an electronic nose and tongue. The spectroscopic technique was used to investigate molecular changes, while electronic nose and electronic tongue evaluated the evolution of the aroma and taste profile during the must-wine fermentation. Must-wine samples were also analysed by traditional chemical methods in order to determine sugars (glucose and fructose) consumption and alcohol (ethanol and glycerol) production. Principal Component Analysis was applied to spectral, electronic nose and electronic tongue data, as an exploratory tool, to uncover molecular, aroma and taste modifications during the fermentation process. Furthermore, the chemical data and the PC1 scores from spectral, electronic nose and electronic tongue data were modelled as a function of time to identify critical points during fermentation. The results showed that NIR and MIR spectroscopies are useful to investigate molecular changes involved in wine fermentation while electronic nose and electronic tongue can be applied to detect the evolution of taste and aroma profile. Moreover, as demonstrated through the modeling of NIR, MIR, electronic nose and electronic tongue data, these non destructive methods are suitable for the monitoring of must-wine fermentation giving crucial information about the quality of the final product in agreement with chemical parameters. Although in this study the measurements were carried out in off-line mode, in future these non destructive techniques could be valid and simple tools, able to provide in-time information about the fermentation process and to assure the quality of wine.     

A Voltammetric Electronic Tongue for the Quantitative Analysis of Quality Parameters in Wastewater

The use of a voltammetric electronic tongue for the quantitative analysis of quality parameters in influent wastewater from a wastewater treatment plant (WWTP) that treats domestic and industrial wastewater is proposed. The electronic voltammetric tongue consists of a set of four noble electrodes (iridium, rhodium, platinum and gold) housed inside a stainless steel cylinder. These noble metals have high durability and are low maintenance‐demanding, as required for developing future automated equipment. A pulse voltammetry study was conducted in 35 wastewater samples to determine ammonia (NH₄⁺‐N), nitrates (NO₃⁻‐N), total phosphate (tot‐P), soluble chemical oxygen demand (CODs) and conductivity. These parameters were also determined in these samples by routine analytical methods in the WWTP laboratory. A partial least squares (PLS) analysis was run to obtain a model to predict each parameter. Twenty‐five samples were included in the calibration set and 10 in the validation set. Calibration and validation sets were selected randomly, except for the extreme values of each parameter, which were included in the calibration set. Variable selection was performed on the voltammetric data using Genetic Algorithms in the calibration data set for each parameter. The electronic tongue showed good predictive power to determine the concentrations of NH₄⁺‐N, NO₃⁻‐N and tot‐P and CODs.     

Analytical methods for the quantification of volatile aromatic compounds

The investigation of odorants is not an easy task, which needs to be undertaken in the context of fit-for-purpose quality systems. To date, great attention has been paid to determination of the volatile fractions of odorants, since they are responsible for the attributes of global flavor [i.e. a combination of olfactory (aroma) and gustatory (taste) sensations produced by chemicals]. This kind of determination can be carried out by analytical techniques [e.g., gas chromatography (GC) combined with mass spectrometry and/or olfactometric GC]. Methods complementary to GC analysis are available, allowing assessment of the olfactory impact by an electronic nose (e-nose) or a panel of selected individuals. Also, we consider some innovative analytical techniques to study the effects of odorants in food during consumption.     

Flow injection analysis applied to a voltammetric electronic tongue

A measurement system, based on flow injection analysis (FIA) technique applied to a voltammetric electronic tongue is described. A reference solution was thus continuously pumped through a cell with a voltammetric electronic tongue, and test samples were injected into the flow stream. Responses were obtained by measuring the resulting pulse height. The FIA technique offered several advantages, since relative measurements are performed, the system is less influenced by sensor baseline drift, calibration samples and/or washing solutions can be injected within a measurement series, and the system is well adapted for automatization. The system was used to analyze standard solutions of H₂O₂, KCl, CuNO₃, K₄[Fe(CN)₆], K₃[Fe(CN)₆] and NaCl, and results obtained were treated with multivariate data analysis. Principal component analysis performed showed that electrode drift could be considerably decreased, and the set-up was also used for classification of different apple juices.     

Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea

In an electronic tongue, preprocessing on raw data precedes pattern analysis and choice of the appropriate preprocessing technique is crucial for the performance of the pattern classifier. While attempting to classify different grades of black tea using a voltammetric electronic tongue, different preprocessing techniques have been explored and a comparison of their performances is presented in this paper. The preprocessing techniques are compared first by a quantitative measurement of separability followed by principle component analysis; and then two different supervised pattern recognition models based on neural networks are used to evaluate the performance of the preprocessing techniques.     

A Voltammetric Electronic Tongue Based on Commercial Screen‐printed Electrodes for the Analysis of Aminothiols by Differential Pulse Voltammetry

A voltammetric electronic tongue has been designed as a proof of concept for the analysis of aminothiols by differential pulse voltammetry and has been tested in ternary mixtures of cysteine (Cys), homocysteine (hCys) and glutathione (GSH). It consists of three screen‐printed electrodes of carbon, carbon nanofibers and gold cured at low temperature. A preliminary calibration study carried out separately for each aminothiol confirmed that, working at an optimal pH value of 7.4, every electrode produces differentiated responses for every analyte (cross‐response). As for the tongue, it was applied to calibration and validation mixtures of Cys, hCys and GSH and provided voltammograms that, baseline‐corrected, normalized and combined in different ways were submitted to partial least squares (PLS) calibration. The calibration models produced good predictions of the concentrations of all three analytes, which suggest that the proposed voltammetric tongue improves the performance of a previous design based on linear sweep voltammetric measurements under acidic conditions.     

Hybrid Electronic Tongue as a Tool for the Monitoring of Wine Fermentation and Storage Process

Hybrid electronic tongue based on potentiometric and voltammetric sensors was applied for the monitoring of wine production process. The sensor array formed by miniaturized ion‐selective electrodes and glassy carbon electrodes provided the analysis of the progress and correctness of wine fermentation and storage process, detection of the presence of disturbing factors and evaluation of the quality of final product. The efficiency of the proposed approach was compared with the monitoring of wine production carried out using standard reference methods. The results indicated that hybrid electronic tongue could be used as simple and reliable analytical tool dedicated to qualitative and quantitative assessment of wine production.     

Comparison of methods for the processing of voltammetric electronic tongues data

We are making a numerical comparison of various preprocessing strategies for dealing with data from voltammetric electronic tongues in order to reduce the high dimensionality of the response matrices. Different modelling tools are presented and briefly described. We then compare combinations of four preprocessing strategies (principal component analysis, fast Fourier transform, discrete wavelet transform, voltammogram-windowed slicing integral) with four modelling alternatives (principal component regression, partial least squares regression, multi-way partial least squares regression, artificial neural networks) by employing data from a voltammetric bioelectronic tongue, an array formed by enzyme-modified biosensors and applied to the discrimination and quantification of phenolic compounds.

Ammonium and Phosphate Quantification in Wastewater by Using a Voltammetric Electronic Tongue

Ammonia (NH₄? N) and orthophosphate (PO₄? P) quantification in wastewater treatment plants is important due to their implication in the eutrophication process. A voltammetric electronic tongue as a tool for the prediction of ammonia and orthophosphate concentrations from influent and effluent wastewater is proposed herein. An electrochemical study of the response of the ammonium and orthophosphate ions was performed in order to design a suitable waveform for each electrode. Partial Least Squares analysis was used to obtain a correlation between the data from the tongue and the concentrations of ammonia and orthophosphate measured in the laboratory showing good predictive power.     

Voltammetric Electronic Tongue Based on Carbon Paste Electrodes Modified with Biochar for Phenolic Compounds Stripping Detection

Biochar is a charcoal produced from the biomass pyrolysis process that presents a highly porous and functionalized surface. In the present work an array of carbon paste electrodes (CPE) made of different forms of carbon (graphite, carbon nanotubes and activated biochar) was evaluated in the development of an electronic tongue for discrimination and stripping voltammetric determination of catechol (CAT), 4‐ethylcatechol (4‐EC) and 4‐ethylguaiacol (4‐EG) phenolic compounds. Morphological characterization of carbon materials and electrodes surfaces was performed by scanning electron microscopy (SEM) and semi‐quantitative elemental composition by energy dispersive spectroscopy (EDS). Electrochemical Impedance Spectroscopy (EIS) measurements were used for electrochemical characterization of electrodes. Cyclic voltammetry measurements were performed for the phenolic compounds evaluated using different concentrations. Principal component analysis (PCA) was performed to evaluate the qualitative analysis. Quantitative data modeling was done using artificial neural networks (ANN). The proposed sensor array presented analytical potentiality allowing the distinction and determination of CAT, 4‐EC and 4‐EG by using chemometric processing. The method showed sensibility, reproducibility and a good linearity (R²>0.9940) for three compounds evaluated. Spontaneous preconcentration of three compounds was possible using all three sensors, which can allow the application of these as passive samplers for remote determinations of phenolic compounds in wine and food samples.     

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

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.     

Rapid honey characterization and botanical classification by an electronic tongue

In this paper a commercial electronic tongue (αAstree, Alpha M.O.S.) was applied for botanical classification and physicochemical characterization of honey samples. The electronic tongue was comprised of seven potentiometric sensors coupled with an Ag/AgCl reference electrode. Botanical classification was performed by PCA, CCA and ANN modeling on 12 samples of acacia, chestnut and honeydew honey. The physicochemical characterization of honey was obtained by ANN modeling and the parameters included were electrical conductivity, acidity, water content, invert sugar and total sugar. The initial reference values for the physicochemical parameters observed were determined by traditional methods. Botanical classification of honey samples obtained by ANN was 100% accurate while the highest correlation between observed and predicted values was obtained for electrical conductivity (0.999), followed by acidity (0.997), water content (0.994), invert sugar content (0.988) and total sugar content (0.979).All developed ANN models for rapid honey characterization and botanical classification performed excellently showing the potential of the electronic tongue as a tool in rapid honey analysis and characterization. The advantage of using such a technique is a simple sample preparation procedure, there are no chemicals involved and there are no additional costs except the initial measurements required for ANN model development.     

Electrochemical monitoring of citric acid production by Aspergillus niger

Hybrid electronic tongue was developed for the monitoring of citric acid production by Aspergillus niger. The system based on various potentiometric/voltammetric sensors and appropriate chemometric techniques provided correct qualitative and quantitative classification of the samples collected during standard Aspergillus niger culture and culture infected with yeast. The performance of the proposed approach was compared with the monitoring of the fermentation process carried out using classical methods. The results obtained proved, that the designed hybrid electronic tongue was able to evaluate the progress and correctness of the fermentation process.