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.     

Use of the smart tongue to monitor mold growth and discriminate between four mold species grown in liquid media

A novel voltammetric electronic tongue, smart tongue, was employed to monitor the growth of mold and to differentiate between four types of mold grown in liquid medium. Principal component analysis (PCA) was used to extract the relevant information obtained by the smart tongue. Reference growth curves were based on measurements of dry weight and pH. The growth detected by the smart tongue was basically consistent with that observed by the measurement of dry weight and pH. The optimal combinations of electrodes and frequencies for monitoring growth were as follows: for Aspergillus, both the Pt and Au electrodes at 1 Hz, 10 Hz and 100 Hz; for Penicillium, the Pt and W electrodes at 100 Hz; for Mucor, the Pt, Pd and W electrodes at the three frequency segments; for Rhizopus, the Pd, Ti and Ag electrodes at the three frequency segments. The Ag electrode at 10 Hz or 100 Hz frequency could differentiate well between the four types of mold for culturing 6 h in the liquid media. Therefore, the smart tongue has a promising future as a modern rapid analytical technology for the real time detection of the growth of mold and for the classification model of mold.     

Use of copper and gold electrodes as sensitive elements for fabrication of an electronic tongue: Discrimination of wines and whiskies

A low-cost method is proposed to classify wine and whisky samples using a disposable voltammetric electronic tongue that was fabricated using gold and copper substrates and a pattern recognition technique (Principal Component Analysis). The proposed device was successfully used to discriminate between expensive and cheap whisky samples and to detect adulteration processes using only a copper electrode. For wines, the electronic tongue was composed of copper and gold working electrodes and was able to classify three different brands of wine and to make distinctions regarding the wine type, i.e., dry red, soft red, dry white and soft white brands.     

Determination of total polyphenol index in wines employing a voltammetric electronic tongue

This work reports the application of a voltammetric electronic tongue system (ET) made from an array of modified graphite-epoxy composites plus a gold microelectrode in the qualitative and quantitative analysis of polyphenols found in wine. Wine samples were analyzed using cyclic voltammetry without any sample pretreatment. The obtained responses were preprocessed employing discrete wavelet transform (DWT) in order to compress and extract significant features from the voltammetric signals, and the obtained approximation coefficients fed a multivariate calibration method (artificial neural network-ANN-or partial least squares-PLS-) which accomplished the quantification of total polyphenol content. External test subset samples results were compared with the ones obtained with the Folin–Ciocalteu (FC) method and UV absorbance polyphenol index (I₂₈₀) as reference values, with highly significant correlation coefficients of 0.979 and 0.963 in the range from 50 to 2400 mg L⁻¹ gallic acid equivalents, respectively. In a separate experiment, qualitative discrimination of different polyphenols found in wine was also assessed by principal component analysis (PCA).     

Visualized attribute analysis approach for characterization and quantification of rice taste flavor using electronic tongue

This paper deals with a novel visualized attributive analysis approach for characterization and quantification of rice taste flavor attributes (softness, stickiness, sweetness and aroma) employing a multifrequency large-amplitude pulse voltammetric electronic tongue. Data preprocessing methods including Principal Component Analysis (PCA) and Fast Fourier Transform (FFT) were provided. An attribute characterization graph was represented for visualization of the interactive response in which each attribute responded by specific electrodes and frequencies. The model was trained using signal data from electronic tongue and attribute scores from artificial evaluation. The correlation coefficients for all attributes were over 0.9, resulting in good predictive ability of attributive analysis model preprocessed by FFT. This approach extracted more effective information about linear relationship between electronic tongue and taste flavor attribute. Results indicated that this approach can accurately quantify taste flavor attributes, and can be an efficient tool for data processing in a voltammetric electronic tongue system.     

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.     

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.     

Electronic integrated multisensor tongue applied to grape juice and wine analysis

An integrated multisensor composed by six ISFET devices selective to common ions and heavy metals combined with a flow injection analysis (FIA) system has been applied as an electronic tongue to grape juice and wine sample analysis. The data obtained for several grape and wine variety samples analysis have been treated using multiparametric tools like principal component analysis (PCA) and soft independent modelling class analogy technique (SIMCA) for the patterning recognition and classification of samples and partial least squares (PLS) regression for quantification of several parameters of interest in wine production. The results obtained have demonstrated the potential of using those multisensors as electronic tongues not only for distinguishing the samples according to the grape variety and the vintage year but also for quantitative prediction of several sample parameters.     

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).     

Multivariate optimisation of electrochemically pre-treated electrodes used in a voltammetric electronic tongue

The use of experimental design as a tool to optimise electrochemically cleaned electrodes applied in a voltammetric electronic tongue is described. A simple and quick activation of electrode surfaces is essential for this type of device, especially for on-line applications in industrial processes. The electronic tongue consisted of four metal electrodes, e.g. Au, Ir, Pt, and Rh in a three-electrode configuration. Current was measured as a function of large potential pulses of decreasing amplitude applied to each electrode. Preliminary results showed that electrochemical cleaning activated the electrode surfaces to similar extent as polishing. Settings of potential and time for each electrode was determined with experimental design in a solution containing 1.0 mM K₄[Fe(CN)₆] in 0.1 M phosphate buffer (pH 6.8). Electrode surfaces were deactivated in-between measurements in a complex liquid, like tea. Optimal settings for potential and time in the electrochemical cleaning procedure at each electrode were chosen at recoveries of 100% (compared to polished electrodes). The recoveries were larger than 100% when too large potentials and times were applied. This could be explained by the fact that the electrode areas increased and therefore also the current responses. Principal component analysis (PCA) was used to investigate the stability of the electrode settings at 100% recoveries. No obvious trends of drift in the signals were found.     

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.     

Threshold detection of aromatic compounds in wine with an electronic nose and a human sensory panel

An electronic nose (e-nose) based on thin film semiconductor sensors has been developed in order to compare the performance in threshold detection and concentration quantification with a trained human sensory panel in order to demonstrate the use of an e-nose to assess the enologists in an early detection of some chemical compounds in order to prevent wine defects. The panel had 25 members and was trained to detect concentration thresholds of some compounds of interest present in wine. Typical red wine compounds such as whiskeylactone and white wine compounds such as 3-methyl butanol were measured at different concentrations starting from the detection threshold found in literature (in the nanograms to milligrams per liter range). Pattern recognition methods (principal component analysis (PCA) and neural networks) were used to process the data. The results showed that the performance of the e-nose for threshold detection was much better than the human panel. The compounds were detected by the e-nose at concentrations up to 10 times lower than the panel. Moreover the e-nose was able to identify correctly each concentration level therefore quantitative applications are devised for this system.     

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.     

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.     

Chemical sensors and their systems

The review presents a short record of the evolution of chemical sensors (ion selective electrodes) and multisensor systems of an electronic tongue type, based on the organization principles similar to those of biological sensors. The main types of chemical sensors and multisensor electronic tongue combinations elaborated today are considered along with sensitive materials used in them. Recent advances in chemical sensors, for example, lower detection limits and so-called true selectivity are scrutinized. Also, some widespread analytical applications of electron tongues, including those for the identification and classification of liquid media, for the quantification of various components in there, for the control of industrial processes, as well as the type and intensity evaluation of the taste of food and medications are discussed.     

Development of an electronic tongue based on a PEDOT-modified voltammetric sensor

Three different electrodes were tested for use as nonspecific amperometric sensors for blind analysis on real matrices, namely different fruit juices from different fruits or different brands. The first two electrodes were traditional Pt and Au electrodes, while the third one was modified with poly(3,4-ethylenedioxythiophene) conducting polymer. The sensors were tested separately, tested coupled to each other, and also tested together. The responses of the electrode system(s) were first screened via PCA and then their discriminant capabilities were quantified in terms of the sensitivities and specificities of their corresponding PLS-DA multivariate classification models. Particular attention was paid to analyzing the evolution of the response over subsequent potential sweeps. The modified electrode demonstrated the most discriminating ability, and it was the only system capable of satisfactorily performing the most complex task attempted during the analysis: discriminating between juices from the same fruit but from different brands. Moreover, the electrode "cleaning" procedure required between two subsequent potential sweeps was much simpler for the modified electrode than for the others. This electrode system was therefore shown to be a good candidate for use as an informative element in an electronic tongue applied to the analysis of other food matrices.     

Detection of antibiotic residues in bovine milk by a voltammetric electronic tongue system

A voltammetric electronic tongue (VE-tongue) was developed to detect antibiotic residues in bovine milk. Six antibiotics (Chloramphenicol, Erythromycin, Kanamycin sulfate, Neomycin sulfate, Streptomycin sulfate and Tetracycline HCl) spiked at four different concentration levels (0.5, 1, 1.5 and 2 maximum residue limits (MRLs)) were classified based on VE-tongue by two pattern recognition methods: principal component analysis (PCA) and discriminant function analysis (DFA). The VE-tongue was composed of five working electrodes (gold, silver, platinum, palladium, and titanium) positioned in a standard three-electrode configuration. The Multi-frequency large amplitude pulse voltammetry (MLAPV) which consisted of four segments (1 Hz, 10 Hz, 100 Hz and 1000 Hz) was applied as potential waveform. The six antibiotics at the MRLs could not be separated from bovine milk completely by PCA, but all the samples were demarcated clearly by DFA. Three regression models: Principal Component Regression Analysis (PCR), Partial Least Squares Regression (PLSR), and Least Squares-Support Vector Machines (LS-SVM) were used for concentrations of antibiotics prediction. All the regression models performed well, and PCR had the most stable results.     

Automatic sequential injection analysis electronic tongue with integrated reference electrode for the determination of ascorbic acid, uric acid and paracetamol

A new approach towards a voltammetric electronic tongue has been developed. Automation of the system was achieved by the use of a sequential injection analysis (SIA) system. Design and construction of a small detection device containing 3 working electrodes was carried out. Platinum, gold and epoxy-graphite discs were used for this purpose. An Ag/AgCl reference electrode was integrated into the measuring cell in order to minimise electrical noise. Three oxidisable compounds of clinical interest i.e., ascorbic acid, uric acid and paracetamol, could be quantified by the system. Employing the voltammograms as departure information, artificial neural networks (ANN) have been used as chemometric tool for the modelling of the system.     

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.