Use Of Electronic Tongue Research Articles

A fused convolutional transformer for voltammetric electronic tongue analysis tasks

Electronic tongue and artificial intelligence have been evaluated as new rapid analysis technologies in complex solution research. The use of nanomaterials to modify the screen-printed carbon electrode (SPCE) increased the specific surface area and electrocatalytic active sites of the electrode. The voltammetric electronic tongue utilizes multiple cross sensitive sensors to describe the overall characteristics of complex samples, and the complementary information between sensors provides rich and comprehensive descriptions for analyzing various components. The use of electronic tongue for rapid analysis of water quality has gradually become a trend, but the overlapping phenomenon of peaks formed by the similar redox potential of each component in water and the interference of the substrate makes it difficult to obtain effective information of each component in water quality. Here, we propose a Fused Convolutional Transformer model (FCvT) that removes the limitation of overlapping peaks by fusing local features and global complementary features to quantify components in complex solutions. The performance of FCvT was evaluated by testing synthetic water samples consisting of four standardized substance solutions and compared with partial least squares (PLS), support vector regression (SVR), artificial neural networks (ANN), and convolutional neural networks (CNN). The results show that the FCvT obtains the lowest mean absolute percentage error in the set of independent tests.The average quantization error of FCvT is reduced by 34.4 % relative to other methods.

(General Student Poster Award Winner, 1st Place) Accelerated Estimation of Chemical and Sensory Liquid Attributes Using an AI-Assisted Electrochemical Electronic Tongue

Electronic tongues based on arrays of potentiometric sensors bears promises for enabling portable and fast analysis of complex liquids by leveraging low-selectivity and high-sensitivity of the inherent sensing materials. Thus, they have been studied and developed to target multiple applications, including analysis of chemical compositions or for untargeted quality control in the food industry. A key element to enable practical use of electronic tongues, however, has often been the analysis and interpretation of their combinatorial response due to the cross-sensitivity of the employed sensors. Indeed, disentangling the effect of multiple liquid constituents on the potentiometric response is the main associated challenge. The present contribution aims at studying the feasibility and accuracy of employing this class of sensors to both the quantification of multiple analytes in water as well as prediction of sensory attributes in coffee samples. A proof-of-concept system comprises an integrated array of miniaturized polymeric sensors and an electronic board records 15 differential voltages, produced by the interaction with both ionic and organic constituents of liquids, and can transmit them via Bluetooth to an external device. An automated pipeline performs pre-processing, hand-crafted feature extraction and training of machine learning models that can be then deployed on the cloud or edge device (e.g., smartphone). The same array can be then reconfigured to address a new specific task by leveraging new potentiometric data collection and applying the automated data analysis. In particular, the device presented herein employed 16 polymeric sensors that were electrodeposited on conventional electroless nickel immersion gold (ENIG) electrodes. The conductive polymers (PEDOT, PPy, PANI and PAPBA) were synthesized by chronoamperometry or cyclic voltammetry and enriched with doping agents for enhanced sensitivity. Differential voltages between these polymeric sensors were measured during the transition of the sensor array from a reference solution to a test solution, thereby obviating the need for a conventional reference electrode. Indeed, the use of low-selective sensors for potentiometric measurements does not require integration of reference electrodes, which are known to be unpractical for remote sensing applications. The analysis of the potentiometric response revealed deviations from linear sensitivities, showing non-Nernstian voltage trends when varying concentration of target analytes. Training data were obtained by alternatively immersing the sensor array in reference (120 s) and test (60 s) solutions continuously using an automated test rig. In addition to the conventional approach of measuring the equilibrium potential after a certain settling time, the complete evolution of the potentiometric signal in time could provide richer information that could be useful for building calibration models. Hence, hand-crafted features were extracted from time series recorded during sensor training in order to reduce the dimension of data and describe the complete voltage perturbation of the sensor during transition between reference and test solution. If exposed to enough “known liquid examples”, the sensor array can learn patterns to perform accelerated qualitative and quantitative analysis. The device has demonstrated enhanced discrimination of various mixtures and was proved able to predict beverage sensory properties after intensive training with samples with known sensory attributes. Firstly, the sensitivity to multiple ionic species was estimated in model mixtures obtained following an Orthogonal Experimental Design (OED) for a set of four metal ions, including Al3+, Cu2+, Na+ and Fe3+, and another set comprising Ca2+, Mg2+ and Na+. The former experiment demonstrated that non-linear regression models, such as a Random Forest of Extra Trees, can cope with non-linearity of the sensor response and yielded better performances than widely used multivariate regression model i.e., Multiple Linear Regression (MLR). The mean relative quantification error varied between 1% for Fe3+ and 44% for Na+ in the concentration range 1-10 mg/L. The second mixture set was used instead to unveil the cross-sensitive response of the sensor array, build a quantification model to predict major cations in mineral water and proving the importance of feature selection for data-driven sensors. Overall, the sensor showed comparable accuracy to ICP-MS (MRE 12-24%) but with a drastic reduction of cost and processing time. Finally, the same sensor array configuration was also used to test 12 coffee samples, which were also evaluated by a sensory panel through 5 taste attributes. Regression models were built to map instrument response to sensory data and Extra-Tree algorithm yielded the highest performances with a MRE varying from 8% to 21% depending on coffee sample and validation scheme. Thus, it was demonstrated that data-driven sensor arrays could be also valuable alternative tools for accelerated evaluation of beverage sensory characteristics and support food innovation processes. Figure 1

Electronic Tongue for Direct Assessment of SARS-CoV-2-Free and Infected Human Saliva-A Feasibility Study.

An electronic tongue is a powerful analytical instrument based on an array of non-selective chemical sensors with a partial specificity for data gathering and advanced pattern recognition methods for data analysis. Connecting electronic tongues with electrochemical techniques for data collection has led to various applications, mostly within sensing for food quality and environmental monitoring, but also in biomedical research for the analyses of different bioanalytes in human physiological fluids. In this paper, an electronic tongue consisting of six electrodes (viz., gold, platinum, palladium, titanium, iridium, and glassy carbon) was designed and tested in authentic (undiluted, unpretreated) human saliva samples from eight volunteers, collected before and during the COVID-19 pandemic. Investigations of 11 samples using differential pulse voltammetry and a principal component analysis allowed us to distinguish between SARS-CoV-2-free and infected authentic human saliva. This work, as a proof-of-principle demonstration, provides a new perspective for the use of electronic tongues in the field of enzyme-free electrochemical biosensing, highlighting their potential for future applications in non-invasive biomedical analyses.

No ambiguity: Chemosensory-based ayurvedic classification of medicinal plants can be fingerprinted using E-tongue coupled with multivariate statistical analysis.

Background: Ayurveda, the indigenous medical system of India, has chemosensory property (rasa) as one of its major pharmacological metric. Medicinal plants have been classified in Ayurveda under six rasas/tastes-sweet, sour, saline, pungent, bitter and astringent. This study has explored for the first time, the use of Electronic tongue for studies of rasa-based classification of medicinal plants. Methods: Seventy-eight medicinal plants, belonging to five taste categories (sweet, sour, pungent, bitter, astringent) were studied along with the reference taste standards (citric acid, hydrochloric acid, caffeine, quinine, L-alanine, glycine, β-glucose, sucrose, D-galactose, cellobiose, arabinose, maltose, mannose, lactose, xylose). The studies were carried out with the potentiometry-based Electronic tongue and the data was analysed using Principle Component Analysis, Discriminant Function Analysis, Taste Discrimination Analysis and Soft Independent Modeling of Class Analogy. Results: Chemosensory similarities were observed between taste standards and the plant samples-citric acid with sour group plants, sweet category plants with sucrose, glycine, β-glucose and D-galactose. The multivariate analyses could discriminate the sweet and sour, sweet and bitter, sweet and pungent, sour and pungent plant groups. Chemosensory category of plant (classified as unknown) could also be identified. Conclusion: This preliminary study has indicated the possibility of fingerprinting the chemosensory-based ayurvedic classification of medicinal plants using E-tongue coupled with multivariate statistical analysis.

The use of electronic tongue (e-tongue) as a simple and rapid method for honey authentication

A simple and rapid test for honey authentication is required particularly for the food industry to assure the quality of honey. The conventional methods for honey authentication are costly, requires a long waiting time to obtain results, requires highly skilled personnel, and is difficult in terms of sample preparation. The electronic tongue can be utilized as an alternative technique for honey authentication. The electronic tongue frameworks are depended on an array of sensors with low selectivity while being sensitive to several components in the measured sample. The signals gathered by the sensors are processed through pattern recognition tools to produce prediction models that permit the grouping of the samples and the measurement of a portion of their physicochemical properties. Papers that were published from 2015 to 2020 from several databases such as Google Scholar, ScienceDirect, and Pubmed were collected to obtain abstracts and original articles related to the authentication of honey-based on sugar content as well as geographical and botanical origin. This review highlighted the electronic tongue as a simple and rapid test for honey authentication, several original papers also compare the validity of electronic tongue with the high-performance liquid chromatography methods as the gold standard.

Electrospun nanofibers versus drop casting films for designing an electronic tongue: comparison of performance for monitoring geosmin and 2‐methylisoborneol in water samples

Geosmin (GSM) and 2‐Methylisoborneol (MIB) are substances commonly found in river water and arise due to eutrophication process. Such contaminants affect the organoleptic properties of water, hampering its consumption, and use in beverage industries. As the human perception threshold for these compounds is low, the devices aimed at their detection must be sensitive enough to detect concentrations as low as a few nanogram per liter in order to guarantee the water quality parameters. Due to the experimental simplicity, fast analysis, portability, and capability for on‐site analysis, the use of electronic tongues and electronic noses employing hybrid and composite materials are potential for GSM and MIB determination. In this work, two distinct electronic tongues were applied in the electrical determination of GSM and MIB in pure and river water. The difference between them consisted in the type of polymer processing used in the fabrication of sensing units. The thin films deposited onto gold IDEs were based on polyamide 6, polypirrole, and polyaniline, but fabricated by drop‐casting and electrospinning. The differences in the electronic tongue performances were correlated to the distinct morphologies of the sensitive layers. Both devices were able to discriminate pure water from solutions tainted with GSM and MIB in concentration as low as 25 ng L−1, with high data correlation and a good reproducibility.

Evaluating the potential use of electronic tongue in early identification and diagnosis of bacterial infections.

BackgroundElectronic tongue (ET) is a simple device that may have some applications in the medical field as an alternative tool to traditional diagnostic methods. The aim of this study is to evaluate the potential use and accuracy of ET in the diagnosis of certain bacterial infections.MethodsAn alpha-Astree ET was used for the detection of known bacterial strains Staphylococcus aureus (ATCC 25923), Escherichia coli (ATCC 25922), and Pseudomonas aeruginosa (ATCC 27853) which were tested at three-time intervals; 15, 18, and 24 hrs (hr). This was used to build a qualitative and quantitative mathematical model to detect the presence of bacteria at the earliest possible time. When the model is robust, new unknown samples were tested after 15 hrs of bacterial growth. Samples were identified using multivariate data analysis techniques.ResultsPrincipal Component Analysis (PCA) scores showed that ET can distinguish between the three bacteria at different times 15, 18, and 24 hrs using different sensors. In the PCA scores plots, the discrimination index was 83% at 15 hrs, 88% at 18 hrs, and 96% at 24 hrs, the variances explained by the two principal components were 84%, 99%, and 97% at 15, 18, and 24 hrs, respectively. Fifteen hours was the earliest time at which the bacteria could be detected. Then six samples of E.coli (as unknown samples) were tested after 15 hrs of inoculation, the two discrimination function explained about 100% of the variance (ie, 79.7+22.3%) and all unknown samples were identified as E.coli.ConclusionET could differentiate between types of bacteria in addition to identifying unknown bacterial cultures (E. coli) at times shorter than that required in the current culture-based methods (24–48 hrs), this could be of a great value in early diagnosis of life-threatening infections.

Potential use of electronic tongue coupled with chemometrics analysis for early detection of the spoilage of Zygosaccharomyces rouxii in apple juice

Apple juice spoilage by Zygosaccharomyces rouxii could scarcely be identified at early stage. It is crucial to recognize the spoilage at early stage to prevent waste of products. In present study, electronic tongue was applied to detect the spoilage of Z. rouxii in apple juice, using taste evaluation by panelists as reference. Combined with linear discriminant analysis, identification of the contaminated juice was fulfilled after 12 h, equivalent to yeast population of less than 2.0 lg colony forming units/mL. At the level, panelists were not capable of discerning the spoilage. Sensors HA, ZZ, BB and BA were relatively more sensitive to the changes in overall taste of apple juice. Moreover, cell number of Z. rouxii could be properly quantified by partial least squares regression models with high determination coefficient of 0.98–0.99. Electronic tongue appears to be a powerful approach to realize early detection of contamination of Z. rouxii.

Honey Evaluation Using Electronic Tongues: An Overview

Honey-rich composition in biologically active compounds makes honey a food products highly appreciated due to the nutritional and healthy properties. Food-manufacturing is very prone to different types of adulterations and fraudulent labelling making it urgent to establish accurate, fast and cost-effective analytical techniques for honey assessment. In addition to the classical techniques (e.g., physicochemical analysis, microscopy, chromatography, immunoassay, DNA metabarcoding, spectroscopy), electrochemical based-sensor devices have arisen as reliable and green techniques for food analysis including honey evaluation, allowing in-situ and on-line assessment, being a user-friendly procedure not requiring high technical expertise. In this work, the use of electronic tongues, also known as taste sensor devices, for honey authenticity and assessment is reviewed. Also, the versatility of electronic tongues to qualitative (e.g., botanical and/or geographical origin assessment as well as detection of adulteration) and quantitative (e.g., assessment of adulterants levels, determination of flavonoids levels or antibiotics and insecticides residues, flavonoids) honey analysis is shown. The review is mainly focused on the research outputs reported during the last decade aiming to demonstrate the potentialities of potentiometric and voltammetric multi-sensor devices, pointing out their main advantages and present and future challenges for becoming a practical quality analytical tool at industrial and commercial levels.

Estudos de palatabilidade de medicamentos: análise sensorial e aceitabilidade de formulações pediátricas

Introduction: Children often reject non-palatable medications. Pediatric formulations contain sweeteners and flavorings to mask the unpleasant taste and avoid problems in administration and adherence. Taste assessment is an essential part of the development of oral liquid medicines. Objective: This paper aims to contextualize assessment and influence of palatability on the acceptance of pediatric medicines. Method: Narrative review of the literature through the electronic databases PubMed and Google Scholar. Articles related to the development of formulations, use of electronic tongue, and abstracts without access to the complete work were not considered. Results: Flavor is considered one of the main determinants for medications’ adhesion in pediatrics. Access to palatable and safe pediatric formulations can have a substantial effect on infant morbidity. Adults and children appreciate flavors in different ways, so sensory testing with children is the most reliable method regarding formulations for this population. Studies of sensory perception and acceptance of medications already used by children may be ethically feasible, given the concerns about research with children. Conclusions: Sensory analyzes should be carried out whenever there is a new formulation to be introduced on the market, addressed to different age brackets and cultural contexts, in order to assess the product’s acceptability

Monitoring olive oils quality and oxidative resistance during storage using an electronic tongue

Monitoring olive oils oxidative stability and quality parameters (free acidity, peroxide values, K232 and K270 extinction coefficients) is needed to guarantee that, during storage, their levels remain within the legal thresholds enabling their commercialization as high-value extra-virgin olive oils. Physicochemical levels are assessed using time-consuming routine analytical reference techniques. In this work, the feasibility of a novel approach that merges an electronic tongue and chemometric tools, for monitoring extra-virgin olive oils’ quality along one year of storage at dark or exposed to light is discussed. The results confirmed that physicochemical parameters varied with the storage lighting conditions and more significantly with time. Also, multiple linear regression models, using sub-sets of 22–28 sensors selected with a meta-heuristic simulated annealing algorithm, allow evaluating the storage time-evolution of olive oils’ peroxide values, extinction coefficients and oxidative stabilities with satisfactory accuracy (R2 ≥ 0.98 and ≥ 0.96, for leave-one-out and repeated K-fold cross-validation procedures, respectively). The capability of monitoring, in a single electrochemical assay, legal required quality parameters of olive oils, decreases considerable the analysis time and cost, allowing checking the compliance of extra-virgin olive oil quality with labeling. So, the use of electronic tongues for extra-virgin olive oil shelf-life assessment could be envisaged.

ELABORACIÓN Y OPTIMIZACIÓN DE UNA RED DE SENSORES ELECTROQUÍMICOS PARA UNA LENGUA ELECTRÓNICA ORIENTADA AL ANÁLISIS DE LECHE

En la actualidad, el uso de lenguas electrónicas ha cobrado importancia en la industria de alimentos, debido al crecimiento de la tecnología y su aprovechamiento en este sector. En el presente trabajo se muestra la elaboración y optimización de una red de sensores a base de polipirrol, el cual fue dopado con diferentes especies químicas para la modificación de una red de sensores de carbono como primera etapa de una lengua electrónica para el análisis de leche. Se analizó la estabilidad y variabilidad en la respuesta presentada por cada sensor mediante la aplicación de una técnica electroquímica conocida como voltametría cíclica, que se aplicó a través de dichos sensores a las muestras analizadas. Para el estudio de los datos se empleó un método estadístico de reconocimiento de patrones conocido como análisis de componentes principales (PCA) y para la optimización de los sensores modificados se usó el análisis de superficie de respuestas. Los resultados obtenidos demuestran que debido a la optimización de los sensores se generó una respuesta estable y con menor ruido en las señales respecto a los mismos sensores sin modificar. Se demostró la capacidad de esta red para responder diferente ante muestras de leche de diversa naturaleza.

Characterization of conventional, biodynamic, and organic purple grape juices by chemical markers, antioxidant capacity, and instrumental taste profile.

The objectives of this study were to characterize organic, biodynamic, and conventional purple grape juices (n = 31) produced in Europe based on instrumental taste profile, antioxidant activity, and some chemical markers and to propose a multivariate statistical model to analyze their quality and try to classify the samples from the 3 different crop systems. Results were subjected to ANOVA, correlation, and regression analysis, principal component analysis (PCA), hierarchical cluster analysis (HCA), soft independent modeling of class analogy (SIMCA), and partial least-squares discriminant analysis (PLSDA). No statistical significant differences (P > 0.05) were observed among juices from the 3 crop systems. Using PCA and HCA, no clear separation among crop systems was observed, corroborating the ANOVA data. However, PCA showed that the producing region highly affects the chemical composition, electronic tongue parameters, and bioactivity of grape juices. In this sense, when organic and biodynamic were grouped as "nonconventional" juices, SIMCA model was able to discriminate 12 out of 13 organic/biodynamic juices and 17 out of 18 conventional juices, presenting an efficiency of 93.5%, while 11 out of 13 non-conventional and 100% conventional grape juices were correctly classified using PLSDA. The use of electronic tongue and the determination of antioxidant properties and major phenolic compounds have shown to be a quick and accurate analytical approach to assess the quality of grape juices.

Comparison of a trained sensory panel and an electronic tongue in the assessment of bitter dairy protein hydrolysates

The bitter taste elicited by dairy protein hydrolysates (DPH) is a well known issue for their acceptability by consumers and therefore incorporation into foods. The traditional method of assessment of taste in foods is by sensory analysis but this can be problematic due to the overall unpleasantness of the samples. Thus, there is a growing interest into the use of electronic tongues (e-tongues) as an alternative method to quantify the bitterness in such samples. In the present study the response of the e-tongue to the standard bitter agent caffeine and a range of both casein and whey based hydrolysates was compared to that of a trained sensory panel.Partial least square regression (PLS) was employed to compare the response of the e-tongue and the sensory panel. There was strong correlation shown between the two methods in the analysis of caffeine (R2 of 0.98) and DPH samples with R2 values ranging from 0.94 to 0.99. This study exhibits potential for the e-tongue to be used in bitterness screening in DPHs to reduce the reliance on expensive and time consuming sensory panels.

Physical–chemical and sensory properties of pulsed electric field and high hydrostatic pressure treated citrus juices

Abstract The consumers have increasing desire towards fresh, long shelf-life and healthy products by consisting favourable sensory properties. As an ambivalent fact appears that the product should meet all these requirements and should be consumable long time. All these demands lead to the importance of the minimal processing methods. The properties of widely common citrus juices (100% orange, – grapefruit, – and tangerine juice) were analyzed by measuring the possible changes in the physical–chemical parameters (pH, Brix°, electric conductivity, colour) respectively the aroma and acid content. The applied technology was pulsed electric field (in furthers: PEF) treatment with the parameters of 28 kV/cm with 50 pulses; respectively high hydrostatic pressure (HHP) technology with the parameter of 600 MPa pressure for 10 min treatment time. The sensory properties of the juices were analyzed with electronic-nose and -tongue to measure the possible changes of the treated juices compared to the untreated (control) samples with the help of these electronic tools, which can serve as a potential detection system for the differentiation of the treatments mentioned above. Industrial relevance Fruit juices are preserved mainly by heat treatment which can change many prosperous flavour- , acid and sensory properties. The present work shows in case of citrus juices the application of pulsed electric field treatment and high hydrostatic pressure techniques as non-thermal preservation possibilities and the use of electronic tongue and – nose as a new method for sensory testing.

Potentiometric electronic tongue to resolve mixtures of sulfide and perchlorate anions.

This work describes the use of an array of potentiometric sensors and an artificial neural network response model to determine perchlorate and sulfide ions in polluted waters, by what is known as an electronic tongue. Sensors used have been all-solid-state PVC membrane selective electrodes, where their ionophores were different metal-phtalocyanine complexes with specific and anion generic responses. The study case illustrates the potential use of electronic tongues in the quantification of mixtures when interfering effects need to be counterbalanced: relative errors in determination of individual ions can be decreased typically from 25% to less than 5%, if compared to the use of a single proposed ion-selective electrode.

Nutrient Solution Monitoring in Greenhouse Cultivation Employing a Potentiometric Electronic Tongue

This work investigates the use of electronic tongues for monitoring nutrient solution compositions in closed soilless systems. This is a horticultural technique in which the nutrient solution is continuously recirculated and an automatic recomposition system maintains the concentration of the different ions in the optimum range for the plants. Electronic tongues used in this study comprised an array of potentiometric sensors and complex data processing by artificial neural networks. A first experiment was able to carry out the simultaneous inline monitoring of ammonium, potassium, sodium, chloride, and nitrate ions during the winter. In the second and third applications, done during summer, some changes were introduced in the sensor array to improve its response toward chloride ions and to incorporate phosphate in the model. This electronic tongue was validated with real greenhouse samples and was also able to detect the variations in the ion concentrations caused by an incorrect configuration of the recomposition system.

Remote environmental monitoring employing a potentiometric electronic tongue

This work investigates the use of electronic tongues for environmental monitoring. Electronic tongues were based on arrays of potentiometric sensors plus a complex data processing by artificial neural networks and data transmission by radiofrequency. A first application, intended for a system simulating real conditions in surface water, performed a simultaneous monitoring of ammonium, potassium, sodium, chloride, and nitrate ions. The proposed system allowed us to assess the effect of natural biodegradation stages for these species. A second application was used to monitor concentrations of ammonium, potassium, and sodium in the ‘Ignacio Ramírez’ dam (Mexico). The electronic tongue used here allowed us to determine the content of the three cations in real water samples, although a high matrix effect was encountered for sodium determination. The implemented radio transmission worked robustly during all the experiments, thus demonstrating the viability of the proposed systems for automated remote applications.