Towards reliable estimation of an “electronic tongue” predictive ability from PLS regression models in wine analysis

High-performance bioelectronic tongue for the simultaneous analysis of phenols, sugars and organic acids in wines

BACKGROUND

Electronic tongues have been widely used to analyze wines. However, owing to the complexity of the matrix, the problem is not completely solved and further improvements are required.

RESULTS

A high-performance potentiometric bioelectronic tongue (bio-ET) specifically devoted to the assessment of wine components is presented. The novelty of this system is due to two innovative approaches. First, the improved performance is obtained through the use of potentiometric biosensors based on carboxylated polyvinyl chloride (PVC) membranes, where enzymes (glucose oxidase, tyrosinase, laccase, and lyase) specific to compounds of interest are linked covalently. Second, the performance is further enhanced by introducing electron mediators (gold nanoparticles or copper phthalocyanine) into the PVC membrane to facilitate the electron transfer process. Individual sensors exposed to target analytes (glucose, catechol, cysteine, or tartaric acid) show a linear behavior, with limits of detection in the region of 10-4  mol L-1 for all the compounds analyzed, with excellent reproducibility (coefficient of variation lower than 3%). Sensors combined to form a bio-ET show excellent capabilities. Principal component (PC) analysis can discriminate monovarietal white wines (PC1 77%; PC2 15%) and red wines (PC1 63%; PC2 30%). Using partial least squares, the bio-ET can provide information about chemical parameters, including glucose, total polyphenols, total anthocyanins, free and total sulfur dioxide, total acidity, and pH with R2 between 0.91 and 0.98 in calibration and between 0.89 and 0.98 in validation.

CONCLUSIONS

This advanced instrument is able to assess the levels of seven parameters in a single measurement, providing an advantageous method to the wine industry. © 2023 Society of Chemical Industry.

Near infrared spectroscopic variable selection by a novel swarm intelligence algorithm for rapid quantification of high order edible blend oil

The quantification of single oil in high order edible blend oil is a challenging task. In this research, a novel swarm intelligence algorithm, discretized whale optimization algorithm (WOA), was first developed for reducing irrelevant variables and improving prediction accuracy of hexanary edible blend oil samples. The WOA is inspired by hunting strategy of humpback whales, which mainly includes three behaviors, i.e., encircling prey, bubble-net attacking and searching for prey. In discretized WOA, positions of whales were updated and then discretized by arctangent function. The whale population performance, iteration number and whale number of WOA were investigated. To validate the performance of selected variables, partial least squares (PLS) was used to build model and predict single oil contents in hexanary blend oil. Results show that WOA-PLS can provide the best prediction accuracy compared with full-spectrum PLS, continuous wavelet transform-PLS (CWT-PLS), uninformative variable elimination-PLS (UVE-PLS), Monte Carlo uninformative variable elimination-PLS (MCUVE-PLS) and randomization test-PLS (RT-PLS). Furthermore, CWT-WOA-PLS can further produce better results with fewer variables compared with WOA-PLS.

Recent Applications of Potentiometric Electronic Tongue and Electronic Nose in Sensory Evaluation

Electronic tongue (e-tongue) and electronic nose (e-nose) have been widely used to determine food products' taste, aroma, and flavor profiles. Several researchers and industries have recently attempted to find relationships between these e-senses and human sensory panels to ultimately replace sensory panels or use them as a viable alternative to timeconsuming and expensive traditional sensory evaluation (e.g., consumer acceptance testing or descriptive sensory analysis). This study investigated the recent applications of e-tongue and e-nose in the food and beverages sectors and their relationships with human sensory panels, including a trained sensory panel and naïve consumers. According to several studies, the e-tongue, e-nose, or a combination of e-tongue and e-nose can be an effective and powerful tool for rapid assessment of sensory profiles and quality detection with significant correlations with human sensory data. These instruments are also often reported to be more sensitive to detect subtle changes/differences that the human panel cannot detect. Future trends and projections of the e-tongue and e-nose with limitations are also discussed.

Screening of Yeast in Various Vineyard Soil and Study on Its Flavor Compounds from Brewing Grape Wine

In order to screen out Saccharomyces cerevisiae suitable for table grape fermentation, and compare it with commercial Saccharomyces cerevisiae in terms of fermentation performance and aroma producing substances, differences of fermentation flavor caused by different strains were discussed. In this experiment, yeast was isolated and purified from vineyard soil, 26s rDNA identification and fermentation substrate tolerance analysis were carried out, and the causes of flavor differences of wine were analyzed from three aspects: GC-MS, PCA and sensory evaluation. The results showed that strain S1 had the highest floral aroma fraction, corresponding to its high production of ethyl octanoate and other substances, and it had the characteristics of high sugar tolerance. The fruit sensory score of S3 wine was the highest among the six wines. Through exploration and analysis, it was found that compared with commercial Saccharomyces cerevisiae, the screened strains had more advantages in fermenting table grapes. The flavor of each wine was directly related to the growth characteristics and tolerance of its strains.

Sensory Profile, Shelf Life, and Dynamics of Bioactive Compounds during Cold Storage of 17 Edible Flowers

In this study, 17 edible flowers (Allium ursinum L., Borago officinalis L., Calendula officinalis L., Centaurea cyanus L., Cichorium intybus L., Dianthus carthusianorum L., Lavandula angustifolia Mill., Leucanthemum vulgare (Vaill.) Lam., Paeonia officinalis L., Primula veris L., Robinia pseudoacacia L., Rosa canina L., Rosa pendulina L., Salvia pratensis L., Sambucus nigra L., Taraxacum officinale Weber, and Tropaeolum majus L.) were investigated to assess their sensory profile at harvest and their shelf life and bioactive compounds dynamics during cold storage. The emerging market of edible flowers lacks this information; thus, the characteristics and requirements of different flower species were provided. In detail, a quantitative descriptive analysis was performed by trained panelists at flower harvest, evaluating 10 sensory descriptors (intensity of sweet, sour, bitter, salt, smell, specific flower aroma, and herbaceous aroma; spiciness, chewiness, and astringency). Flower visual quality, biologically active compounds content (total polyphenols and anthocyanins), and antioxidant activity (FRAP, DPPH, and ABTS assays) were evaluated both at harvest and during storage at 4 °C for 14 days to assess their shelf life. Generally, species had a wide range of peculiar sensory and phytochemical characteristics at harvest, as well as shelf life and bioactive compounds dynamics during postharvest. A strong aroma was indicated for A. ursinum, D. carthusianorum, L. angustifolia, and L. vulgare, while B. officinalis and C. officinalis had very low values for all aroma and taste descriptors, resulting in poor sensory profiles. At harvest, P. officinalis, R. canina, and R. pendulina exhibited the highest values of polyphenols (884–1271 mg of gallic acid equivalents per 100 g) and antioxidant activity (204–274 mmol Fe2+/kg for FRAP, 132–232 and 43–58 µmol of Trolox equivalent per g for DPPH and ABTS). The species with the longest shelf life in terms of acceptable visual quality was R. pendulina (14 days), followed by R. canina (10 days). All the other species lasted seven days, except for C. intybus and T. officinale that did not reach day 3. During cold storage, the content of bioactive compounds differed, as total phenolics followed a different trend according to the species and anthocyanins remained almost unaltered for 14 days. Considering antioxidant activity, ABTS values were the least variable, varying in only four species (A. ursinum, D. carthusianorum, L. angustifolia, and P. officinalis), while both DPPH and FRAP values varied in eight species. Taken together, the knowledge of sensory profiles, phytochemical characteristics and shelf life can provide information to select suitable species for the emerging edible flower market.

Taste Masking Study Based on an Electronic Tongue: the Formulation Design of 3D Printed Levetiracetam Instant-Dissolving Tablets

Purpose

Proper taste-masking formulation design is a critical issue for instant-dissolving tablets (IDTs). The purpose of this study is to use the electronic tongue to design the additives of the 3D printed IDTs to improve palatability.

Methods

A binder jet 3D printer was used to prepare IDTs of levetiracetam. A texture analyzer and dissolution apparatus were used to predict the oral dispersion time and in vitro drug release of IDTs, respectively. The palatability of different formulations was investigated using the ASTREE electronic tongue in combination with the design of experiment and a model for masking bitter taste. Human gustatory sensation tests were conducted to further evaluate the credibility of the results.

Results

The 3D printed tablets exhibited rapid dispersion (<30 s) and drug release (2.5 min > 90%). The electronic tongue had an excellent ability of taste discrimination, and levetiracetam had a good linear sensing performance based on a partial least square regression analysis. The principal component analysis was used to analyze the signal intensities of different formulations and showed that 2% sucralose and 0.5% spearmint flavoring masked the bitterness well and resembled the taste of corresponding placebo. The results of human gustatory sensation test were consistent with the trend of the electronic tongue evaluation.

Conclusions

Owing to its objectivity and reproducibility, this technique is suitable for the design and evaluation of palatability in 3D printed IDT development.

Challenges in using electronic tongue to study rasa of plants: I. Finding the right tool for the right job

There is growing interest in understanding how ayurveda, the indigenous medical system of India, uses plants for therapeutic purpose. The aim of this two parts article is to explore how the analytical technique of Electronic tongue (E-tongue) can be used for studying rasa, one of the major ayurvedic parameter in the study of medicinal and nutritional plants. Although E-tongue is widely used in pharmaceutical, food and beverage industries for objective evaluation of taste, its use in plants from an ayurvedic perspective is novel. This first of the two parts article introduces the technique of E-tongue, positioning it in context for the following part. The latter discusses crucial control experiments required prior using E-tongue for studies on medicinal plants from an ayurvedic standpoint.

Analysis of Phenolic Content in Grape Seeds and Skins by Means of a Bio-Electronic Tongue

A bio-electronic tongue has been developed to evaluate the phenolic content of grape residues (seeds and skins) in a fast and easy way with industrial use in mind. A voltammetric electronic tongue has been designed based on carbon resin electrodes modified with tyrosinase combined with electron mediators. The presence of the phenoloxydase promotes the selectivity and specificity towards phenols. The results of multivariate analysis allowed discriminating seeds and skins according to their polyphenolic content. Partial least squares (PLS) has been used to establish regression models with parameters related to phenolic content measured by spectroscopic methods i.e., total poliphenol content (TPC) and Folin–Ciocalteu (FC) indexes. It has been shown that electronic tongue can be successfully used to predict parameters of interest with high correlation coefficients (higher than 0.99 in both calibration and prediction) and low residual errors. These values can even be improved using genetic algorithms for multivalent analysis. In this way, a fast and simple tool is available for the evaluation of these values. This advantage may be due to the fact that the electrochemical signals are directly related to the phenolic content.

Analytical Figures of Merit for Multisensor Arrays

Multisensor arrays employing various sensing principles are a rapidly developing field of research as they allow simple and inexpensive quantification of various parameters in complex samples. Quantitative analysis with such systems is based on multivariate regression techniques, and deriving of traditional analytical figures of merit (e.g., sensitivity, selectivity, limit of detection, and limit of quantitation) for such systems is not obvious and straightforward. Nevertheless, it is absolutely needed for further development of the multisensor research field and for introducing these instruments into the general context of analytical chemistry. Here, we report on the protocol for calculation of sensitivity, selectivity, and detection limits for multisensor arrays. The results are provided and discussed in detail for several real-world data sets.

Organoleptic Analysis of Drinking Water Using an Electronic Tongue Based on Electrochemical Microsensors

The standards that establish water’s quality criteria for human consumption include organoleptic analysis. These analyses are performed by taste panels that are not available to all water supply companies with the required frequency. In this work, we propose the use of an electronic tongue to perform organoleptic tests in drinking water. The aim is to automate the whole process of these tests, making them more economical, simple, and accessible. The system is composed by an array of electrochemical microsensors and chemometric tools for multivariable processing to extract the useful chemical information. The array of sensors is composed of six Ion-Sensitive Field Effect Transistors (ISFET)-based sensors, one conductivity sensor, one redox potential sensor, and two amperometric electrodes, one gold microelectrode for chlorine detection, and one nanocomposite planar electrode for sensing electrochemical oxygen demand. A previous study addressed to classify water samples according to taste/smell descriptors (sweet, acidic, salty, bitter, medicinal, chlorinous, mouldy, and earthy) was performed. A second study comparing the results of two organoleptic tests (hedonic evaluation and ranking test) with the electronic tongue, using Partial Least Squares regression, was conducted. The results show that the proposed electronic tongue is capable of analyzing water samples according to their organoleptic characteristics, which can be used as an alternative method to the taste panel.

Analysis of musts and wines by means of a bio-electronic tongue based on tyrosinase and glucose oxidase using polypyrrole/gold nanoparticles as the electron mediator

A bioelectronic tongue (bioET) based on combinations of enzymes (tyrosinase and glucose oxidase) and polypyrrole (Ppy) or polypyrrole/AuNP (Ppy/AuNP) composites was build up and applied to the analysis and discrimination of musts and wines. Voltammetric responses of the array of sensors demonstrated the effectiveness of polymers as electron mediators and the existence of favorable synergistic effects between Ppy and the AuNPs. Using Principal Component Analysis and Parallel Factor Analysis it was possible to discriminate musts according to the °Brix and TPI (Total Polyphenol Index), and wines according to the alcoholic degree and TPI. Partial Least Squares provided good correlations between the bioET output and traditional chemical parameters. Moreover, Support Vector Machines permitted to predict the TPI and the alcoholic degree of wines, from data provided by the bioET in the corresponding grapes. This result opens the possibility to predict wine characteristics from the beginning of the vinification process.

Discrimination of Milks with a Multisensor System Based on Layer-by-Layer Films

A nanostructured electrochemical bi-sensor system for the analysis of milks has been developed using the layer-by-layer technique. The non-enzymatic sensor [CHI+IL/CuPcS]₂, is a layered material containing a negative film of the anionic sulfonated copper phthalocyanine (CuPcS) acting as electrocatalytic material, and a cationic layer containing a mixture of an ionic liquid (IL) (1-butyl-3-methylimidazolium tetrafluoroborate) that enhances the conductivity, and chitosan (CHI), that facilitates the enzyme immobilization. The biosensor ([CHI+IL/CuPcS]₂-GAO) results from the immobilization of galactose oxidase on the top of the LbL layers. FTIR, UV⁻vis, and AFM have confirmed the proposed structure and cyclic voltammetry has demonstrated the amplification caused by the combination of materials in the film. Sensors have been combined to form an electronic tongue for milk analysis. Principal component analysis has revealed the ability of the sensor system to discriminate between milk samples with different lactose content. Using a PLS-1 calibration models, correlations have been found between the voltammetric signals and chemical parameters measured by classical methods. PLS-1 models provide excellent correlations with lactose content. Additional information about other components, such as fats, proteins, and acidity, can also be obtained. The method developed is simple, and the short response time permits its use in assaying milk samples online.

Solid-Contact Potentiometric Sensors and Multisensors Based on Polyaniline and Thiacalixarene Receptors for the Analysis of Some Beverages and Alcoholic Drinks

Electronic tongue is a sensor array that aims to discriminate and analyze complex media like food and beverages on the base of chemometrics approaches for data mining and pattern recognition. In this review, the concept of electronic tongue comprising of solid-contact potentiometric sensors with polyaniline and thacalix[4]arene derivatives is described. The electrochemical reactions of polyaniline as a background of solid-contact sensors and the characteristics of thiacalixarenes and pillararenes as neutral ionophores are briefly considered. The electronic tongue systems described were successfully applied for assessment of fruit juices, green tea, beer, and alcoholic drinks They were classified in accordance with the origination, brands and styles. Variation of the sensor response resulted from the reactions between Fe(III) ions added and sample components, i.e., antioxidants and complexing agents. The use of principal component analysis and discriminant analysis is shown for multisensor signal treatment and visualization. The discrimination conditions can be optimized by variation of the ionophores, Fe(III) concentration, and sample dilution. The results obtained were compared with other electronic tongue systems reported for the same subjects.

Monitoring the Phenolic Ripening of Red Grapes Using a Multisensor System Based on Metal-Oxide Nanoparticles

The maturity of grapes is usually monitored by means of the sugar concentration. However, the assessment of other parameters such as the phenolic content is also important because the phenolic maturity has an important impact on the organoleptic characteristics of wines. In this work, voltammetric sensors able to detect phenols in red grapes have been developed. They are based on metal oxide nanoparticles (CeO2, NiO, and TiO2,) whose excellent electrocatalytic properties toward phenols allows obtaining sensors with detection limits in the range of 10-8 M and coefficients of variation lower than 7%. An electronic tongue constructed using a combination of the nanoparticle-based sensors is capable to monitor the phenolic maturity of red grapes from véraison to maturity. Principal Component Analysis (PCA) can be successfully used to discriminate samples according to the ripeness. Regression models performed using Partial Least Squares (PLS-1) have established good correlations between voltammetric data obtained with the electrochemical sensors and the Total Polyphenolic Index, the Brix degree and the Total Acidity, with correlation coefficients close to 1 and low number of latent variables. An advantage of this system is that the electronic tongue can be used for the simultaneous assessment of these three parameters which are the main factors used to monitor the maturity of grapes. Thus the electronic tongue based on metal oxide nanoparticles can be a valuable tool to monitor ripeness. These results demonstrate the exciting possible applications of metal oxide nanoparticles in the field of electronic tongues.

A different approach for the analysis of grapes: Using the skin as sensing element

In this work, an alternative method to monitor the phenolic maturity of grapes was developed. In this approach, the skins of grapes were used to cover the surface of carbon paste electrodes and the voltammetric signals obtained with the skin-modified sensors were used to obtain information about the phenolic content of the skins. These sensors could easily detect differences in the phenolic composition of different Spanish varieties of grapes (Mencía, Prieto Picudo and Juan García). Moreover, sensors were able to monitor changes in the phenolic content throughout the ripening process from véraison until harvest. Using PLS-1 (Partial Least Squares), correlations were established between the voltammetric signals registered with the skin-modified sensors and the phenolic content measured by classical methods (Glories or Total Polyphenol Index). PLS-1 models provided additional information about Brix degree, density or sugar content, which usually used to establish the harvesting date. The quality of the correlations was influenced by the maturation process and the structural and mechanical skin properties. Thus the skin sensors fabricated with Juan García and Prieto Picudo grapes (that showed faster polyphenolic maturation and a higher amount of extractable polyphenols than Mencía), showed good correlations and therefore could be used to monitor the ripening.

Reference samples guide variable selection for correlation of wine sensory and volatile profiling data

The relationship between wine flavour and wine volatile composition is well recognised, however with thousands of compounds in wine the exact nature of individual contributions may be hard to determine due to synergistic and masking effects. Untargeted chemical analyses coupled with descriptive sensory and partial least squares regression modelling can help unravel interactions to identify groups of compounds that contribute to sensory properties. Variable selection is often applied prior to modelling to eliminate irrelevant variables. In this study, sensory references used to train the sensory panel were chemically analysed and employed to reduce the number of variables used to construct the models. This novel variable selection approach was compared against the inclusion of all variables and the most commonly applied variable selection method - analysis of variance. Models constructed from variables present in sensory references performed similarly to other models and identified interesting groups of compounds to investigate further.

Multisensor systems based on phthalocyanines for monitoring the quality of grapes

Arrays of phthalocyanine-based sensors with complementary activity have been used to develop voltammetric electronic tongues. Such systems have demonstrated to be useful in enology for the evaluation of quality of wines in different production stages, from grapes to bottles. In this paper, the state of the art of multisensor systems based on phthalocyanines dedicated to the analysis of musts (juices obtained from crushed grapes) is described. Such multisensor systems cover different types of sensors from simple Carbon Paste Electrodes, to sophiticated nanostructured sensors, including Langmuir–Blodgett or Layer by Layer thin films and biomimetic biosensors where phthalocyanines play a crucial role as electron mediator between enzymes and electrodes. In all cases, multisensor systems based on phthalocyanines have been able to discriminate musts prepared from different varieties of grapes. The performance of these systems can be improved by combining non-specific sensors with biosensors containing enzymes selective to phenols. In this case, excellent relationships have been found between the responses provided by the array and the content in phenols and acids provided by traditional chemical analysis.

Electronic Noses and Tongues in Wine Industry

The quality of wines is usually evaluated by a sensory panel formed of trained experts or traditional chemical analysis. Over the last few decades, electronic noses (e-noses) and electronic tongues have been developed to determine the quality of foods and beverages. They consist of arrays of sensors with cross-sensitivity, combined with pattern recognition software, which provide a fingerprint of the samples that can be used to discriminate or classify the samples. This holistic approach is inspired by the method used in mammals to recognize food through their senses. They have been widely applied to the analysis of wines, including quality control, aging control, or the detection of fraudulence, among others. In this paper, the current status of research and development in the field of e-noses and tongues applied to the analysis of wines is reviewed. Their potential applications in the wine industry are described. The review ends with a final comment about expected future developments.

Discrimination of Apple Liqueurs (Nalewka) Using a Voltammetric Electronic Tongue, UV-Vis and Raman Spectroscopy

The capability of a phthalocyanine-based voltammetric electronic tongue to analyze strong alcoholic beverages has been evaluated and compared with the performance of spectroscopic techniques coupled to chemometrics. Nalewka Polish liqueurs prepared from five apple varieties have been used as a model of strong liqueurs. Principal Component Analysis has demonstrated that the best discrimination between liqueurs prepared from different apple varieties is achieved using the e-tongue and UV-Vis spectroscopy. Raman spectra coupled to chemometrics have not been efficient in discriminating liqueurs. The calculated Euclidean distances and the k-Nearest Neighbors algorithm (kNN) confirmed these results. The main advantage of the e-tongue is that, using PLS-1, good correlations have been found simultaneously with the phenolic content measured by the Folin-Ciocalteu method (R² of 0.97 in calibration and R² of 0.93 in validation) and also with the density, a marker of the alcoholic content method (R² of 0.93 in calibration and R² of 0.88 in validation). UV-Vis coupled with chemometrics has shown good correlations only with the phenolic content (R² of 0.99 in calibration and R² of 0.99 in validation) but correlations with the alcoholic content were low. Raman coupled with chemometrics has shown good correlations only with density (R² of 0.96 in calibration and R² of 0.85 in validation). In summary, from the three holistic methods evaluated to analyze strong alcoholic liqueurs, the voltammetric electronic tongue using phthalocyanines as sensing elements is superior to Raman or UV-Vis techniques because it shows an excellent discrimination capability and remarkable correlations with both antioxidant capacity and alcoholic content-the most important parameters to be measured in this type of liqueurs.

Bioelectronic tongues: New trends and applications in water and food analysis

Over the last years, there has been an increasing demand for fast, highly sensitive and selective methods of analysis to meet new challenges in environmental monitoring, food safety and public health. In response to this demand, biosensors have arisen as a promising tool, which offers accurate chemical data in a timely and cost-effective manner. However, the difficulty to obtain sensors with appropriate selectivity and sensitivity for a given analyte, and to solve analytical problems which do not require the quantification of a certain analyte, but an overall effect on a biological system (e.g. toxicity, quality indices, provenance, freshness, etc.), led to the concept of electronic tongues as a new strategy to tackle these problems. In this direction, to improve the performance of electronic tongues, and thus to spawn new application fields, biosensors have recently been incorporated to electronic tongue arrays, leading to what is known as bioelectronic tongues. Bioelectronic tongues provide superior performance by combining the capabilities of electronic tongues to derive meaning from complex or imprecise data, and the high selectivity and specificity of biosensors. The result is postulated as a tool that exploits chemometrics to solve biosensors' interference problems, and biosensors to solve electronic tongues' selectivity problems. The review presented herein aims to illustrate the capabilities of bioelectronic tongues as analytical tools, especially suited for screening analysis, with particular emphasis in water analysis and the characterization of food and beverages. After briefly reviewing the key concepts related to the design and principles of electronic tongues, we provide an overview of significant contributions to the field of bioelectronic tongues and their future perspectives.

An Electrochemical Quartz Crystal Microbalance Multisensor System Based on Phthalocyanine Nanostructured Films: Discrimination of Musts

An array of electrochemical quartz crystal electrodes (EQCM) modified with nanostructured films based on phthalocyanines was developed and used to discriminate musts prepared from different varieties of grapes. Nanostructured films of iron, nickel and copper phthalocyanines were deposited on Pt/quartz crystals through the Layer by Layer technique by alternating layers of the corresponding phthalocyanine and poly-allylamine hydrochloride. Simultaneous electrochemical and mass measurements were used to study the mass changes accompanying the oxidation of electroactive species present in must samples obtained from six Spanish varieties of grapes (Juan García, Prieto Picudo, Mencía Regadío, Cabernet Sauvignon, Garnacha and Tempranillo). The mass and voltammetric outputs were processed using three-way models. Parallel Factor Analysis (PARAFAC) was successfully used to discriminate the must samples according to their variety. Multi-way partial least squares (N-PLS) evidenced the correlations existing between the voltammetric data and the polyphenolic content measured by chemical methods. Similarly, N-PLS showed a correlation between mass outputs and parameters related to the sugar content. These results demonstrated that electronic tongues based on arrays of EQCM sensors can offer advantages over arrays of mass or voltammetric sensors used separately.

Characterization of Chinese rice wine taste attributes using liquid chromatographic analysis, sensory evaluation, and an electronic tongue

To evaluate the taste characteristics of Chinese rice wine, wine samples sourced from different vintage years were analyzed using liquid chromatographic analysis, sensory evaluation, and an electronic tongue. Six organic acids and seventeen amino acids were measured using high performance liquid chromatography (HPLC). Five monosaccharides were measured using anion-exchange chromatography. The global taste attributes were analyzed using an electronic tongue (E-tongue). The correlations between the 28 taste-active compounds and the sensory attributes, and the correlations between the E-tongue response and the sensory attributes were established via partial least square discriminant analysis (PLSDA). E-tongue response data combined with linear discriminant analysis (LDA) were used to discriminate the Chinese rice wine samples sourced from different vintage years. Sensory evaluation indicated significant differences in the Chinese rice wine samples sourced from 2003, 2005, 2008, and 2010 vintage years in the sensory attributes of harmony and mellow. The PLSDA model for the taste-active compounds and the sensory attributes showed that proline, fucose, arabinose, lactic acid, glutamic acid, arginine, isoleucine, valine, threonine, and lysine had an influence on the taste characteristic of Chinese rice wine. The Chinese rice wine samples were all correctly classified using the E-tongue and LDA. The electronic tongue was an effective tool for rapid discrimination of Chinese rice wine.

Sweetener blend optimization by using mixture design methodology and the electronic tongue

Utilizing more than one sweetener has been shown to be an effective way to substitute sucrose in food products. The objective of this study was to apply the augmented simplex-centroid mixture design for the optimization of acceptable sweetener blends using coconut sugar, agave, and stevia. Sweetener blends were evaluated in aqueous solutions and gluten-free granola bars by a trained panel and consumers (n = 60). Significant differences were found between sweetener mixtures in solutions by both panelists and consumers (P < 0.05). Taste profiles for the sweetener solutions were also generated using the electronic tongue. Most consumer and trained intensity ratings were highly correlated (R(2) ≥ 0.79) with the electronic tongue taste profile analysis. Granola bars were also found to be significantly different (P < 0.05), with consumers preferring coconut sugar mixtures. Using contour plots and desirability function analysis, an optimal sweetener combination was found for a granola bar formulation of 89.9% coconut sugar, 6.1% agave, and 4% stevia. These results indicate that a mixture design can be a reliable way to develop new sweetener blends for product development.

Development of a sweetness sensor for aspartame, a positively charged high-potency sweetener

Taste evaluation technology has been developed by several methods, such as sensory tests, electronic tongues and a taste sensor based on lipid/polymer membranes. In particular, the taste sensor can individually quantify five basic tastes without multivariate analysis. However, it has proven difficult to develop a sweetness sensor, because sweeteners are classified into three types according to the electric charges in an aqueous solution; that is, no charge, negative charge and positive charge. Using membrane potential measurements, the taste-sensing system needs three types of sensor membrane for each electric charge type of sweetener. Since the commercially available sweetness sensor was only intended for uncharged sweeteners, a sweetness sensor for positively charged high-potency sweeteners such as aspartame was developed in this study. Using a lipid and plasticizers, we fabricated various lipid/polymer membranes for the sweetness sensor to identify the suitable components of the sensor membranes. As a result, one of the developed sensors showed responses of more than 20 mV to 10 mM aspartame and less than 5 mV to any other taste. The responses of the sensor depended on the concentration of aspartame. These results suggested that the developed sweetness sensor had high sensitivity to and high selectivity for aspartame.

Mimicking Daphnia magna bioassay performance by an electronic tongue for urban water quality control

Toxicity is one of the key parameters of water quality in environmental monitoring. However, being evaluated as a response of living beings (as their mobility, fertility, death rate, etc.) to water quality, toxicity can only be assessed with the help of these living beings. This imposes certain restrictions on toxicity bioassay as an analytical method: biotest organisms must be properly bred, fed and kept under strictly regulated conditions and duration of tests can be quite long (up to several days), thus making the whole procedure the prerogative of the limited number of highly specialized laboratories. This report describes an original application of potentiometric multisensor system (electronic tongue) when the set of electrochemical sensors was calibrated against Daphnia magna death rate in order to perform toxicity assessment of urban waters without immediate involvement of living creatures. PRM (partial robust M) and PLS (projections on latent structures) regression models based on the data from this multisensor system allowed for prediction of toxicity of unknown water samples in terms of biotests but in the fast and simple instrumental way. Typical errors of water toxicity predictions were below 20% in terms of Daphnia death rate which can be considered as a good result taking into account the complexity of the task.

Food analysis using artificial senses

Nowadays, consumers are paying great attention to the characteristics of food such as smell, taste, and appearance. This motivates scientists to imitate human senses using devices known as electronic senses. These include electronic noses, electronic tongues, and computer vision. Thanks to the utilization of various sensors and methods of signal analysis, artificial senses are widely applied in food analysis for process monitoring and determining the quality and authenticity of foods. This paper summarizes achievements in the field of artificial senses. It includes a brief history of these systems, descriptions of most commonly used sensors (conductometric, potentiometric, amperometic/voltammetric, impedimetric, colorimetric, piezoelectric), data analysis methods (for example, artificial neural network (ANN), principal component analysis (PCA), model CIE L*a*b*), and application of artificial senses to food analysis, in particular quality control, authenticity and falsification assessment, and monitoring of production processes.

Quality and availability of organic foods by Slovak consumers

The increasing consumer demand for organic products caused that the organic food market has expanded in all continents of the world. Organic foods represent a specific segment of the food market. Currently land area farmed organically in Slovakia represents 9% of the total agricultural land. In this work we identified organic foods purchase by Slovak consumers, the availability, reasons of purchase and quality assortment of organic foods at the Slovak market. Questionnaire survey involved 271 respondents. The Hierarchical multiple factor analysis was used for the segregation and classification of consumers into representative groups. The group of respondents was based on algorithms divided into three groups. In the first group of respondents, prevalent are responses that assortment is not sufficient and no answer, in the second group think that organic food assortment is not sufficient, and in the third group of respondents also dominates opinion that is not sufficient. At the question of organic food quality in all three groups is prevalent opinion that it is rather high, in the first group nearly the third of respondents considered the quality of organic foods as rather low, in the second group of respondents is rate: „rather low“ response and „rather high“ almost equal. In the third group of respondents strongly dominated response that the quality of organic food is rather high. Regarding the availability of organic products at the Slovak market, 16% of respondents considered it to be sufficient, 54% of consumers considered assortment as not enough available for all. We also analyzed the reasons of buying organic food. 42% of respondents reported that the main reason for buying organic food is a concern for the environment and landscape, 33% of respondents state it is a pleasure and the opportunity to try something unusual, 11% reported confidence in the quality of organic food and 7% their health care. Environmental education in the family since childhood and the opinions of friends significantly influence consumers when buying food and organic food. We assume that, organic food will be processed minimally in the future. Consumer demand for organic food we recommend to increase by increased support of the direct sales, informing about quality of organic foods and their beneficial effects on the human body at basic and secondary schools, organizing of excursions to organic farms and processing companies.

On-line monitoring of food fermentation processes using electronic noses and electronic tongues: a review

Fermentation processes are often sensitive to even slight changes of conditions that may result in unacceptable end-product quality. Thus, close follow-up of this type of processes is critical for detecting unfavorable deviations as early as possible in order to save downtime, materials and resources. Nevertheless the use of traditional analytical techniques is often hindered by the need for expensive instrumentation and experienced operators and complex sample preparation. In this sense, one of the most promising ways of developing rapid and relatively inexpensive methods for quality control in fermentation processes is the use of chemical multisensor systems. In this work we present an overview of the most important contributions dealing with the monitoring of fermentation processes using electronic noses and electronic tongues. After a brief description of the fundamentals of both types of devices, the different approaches are critically commented, their strengths and weaknesses being highlighted. Finally, future trends in this field are also mentioned in the last section of the article.

Rapid field identification of subjects involved in firearm-related crimes based on electroanalysis coupled with advanced chemometric data treatment

We demonstrate a novel system for the detection and discrimination of varying levels of exposure to gunshot residue from subjects in various control scenarios. Our aim is to address the key challenge of minimizing the false positive identification of individuals suspected of discharging a firearm. The chemometric treatment of voltammetric data from different controls using Canonical Variate Analysis (CVA) provides several distinct clusters for each scenario examined. Multiple samples were taken from subjects in controlled tests such as secondary contact with gunshot residue (GSR), loading a firearm, and postdischarge of a firearm. These controls were examined at both bare carbon and gold-modified screen-printed electrodes using different sampling methods: the 'swipe' method with integrated sampling and electroanalysis and a more traditional acid-assisted q-tip swabbing method. The electroanalytical fingerprint of each sample was examined using square-wave voltammetry; the resulting data were preprocessed with Fast Fourier Transform (FFT), followed by CVA treatment. High levels of discrimination were thus achieved in each case over 3 classes of samples (reflecting different levels of involvement), achieving maximum accuracy, sensitivity, and specificity values of 100% employing the leave-one-out validation method. Further validation with the 'jack-knife' technique was performed, and the resulting values were in good agreement with the former method. Additionally, samples from subjects in daily contact with relevant metallic constituents were analyzed to assess possible false positives. This system may serve as a potential method for a portable, field-deployable system aimed at rapidly identifying a subject who has loaded or discharged a firearm to verify involvement in a crime, hence providing law enforcement personnel with an invaluable forensic tool in the field.

Chemical composition and sensory profile of pomelo (Citrus grandis (L.) Osbeck) juice

Two cultivars (Citrus grandis (L.) Osbeck PO 51 and PO 52) of Malaysian pomelo juices were studied by examining their physicochemical properties (i.e. pH, °Brix and titratable acidity), volatile and non-volatile components (sugars and organic acids). Using solvent extraction and headspace solid-phase microextraction, 49 and 65 volatile compounds were identified by gas chromatography-mass spectrometer/flame ionisation detector, respectively. Compared to pink pomelo juice (cultivar PO 52), white pomelo juice (cultivar PO 51) contained lower amount of total volatiles but higher terpenoids. Descriptive sensory evaluation indicated that white pomelo juice was milder in taste especially acidity. Furthermore, principal component analysis and partial least square regression revealed a strong correlation in pomelo juices between their chemical components and some flavour attributes (i.e. acidic, fresh, peely and sweet). Hence, this research enabled a deeper insight into the flavour of this unique citrus fruit.

BioElectronic Tongue for the quantification of total polyphenol content in wine

This work reports the application of a BioElectronic Tongue (BioET) in the estimation of polyphenol content in wine. The approach used an array of enzyme biosensors capable of giving a wide and complete response of the analyzed species, plus a chemometric processing tool able to interpret the chemical signals and extract meaningful data from the complex readings. In our case, the proposed BioET was formed by an array of four voltammetric enzymatic biosensors based on epoxy-graphite composites, one blank electrode and the other three bulk-modified with tyrosinase and laccase on one side, and copper nanoparticles on the other; these modifiers were used in order to incorporate differentiated or catalytic response to different polyphenols present in wine and aimed to the determination of its total polyphenol content value. The obtained voltammetric responses were pre-processed employing the Fast Fourier Transform (FFT); this was used to compress the relevant information whereas the obtained coefficients fed an Artificial Neural Network (ANN) model that accomplished the quantification of total polyphenol content. For comparison purposes, obtained polyphenol content was compared against the one assessed by two different reference methods: Folin-Ciocalteu and UV polyphenol index (I(280)); good prediction ability was attained with correlation coefficients higher than 0.949 when comparing against reference methods. Qualitative discrimination of individual polyphenols found in wine was also assessed by means of Principal Component Analysis which allowed the discrimination of the individual polyphenols under study.