Advanced Taste Sensors Based on Artificial Lipids with Global Selectivity to Basic Taste Qualities and High Correlation to Sensory Scores

Effective R&D and strict quality control of a broad range of foods, beverages, and pharmaceutical products require objective taste evaluation. Advanced taste sensors using artificial-lipid membranes have been developed based on concepts of global selectivity and high correlation with human sensory score. These sensors respond similarly to similar basic tastes, which they quantify with high correlations to sensory score. Using these unique properties, these sensors can quantify the basic tastes of saltiness, sourness, bitterness, umami, astringency and richness without multivariate analysis or artificial neural networks. This review describes all aspects of these taste sensors based on artificial lipid, ranging from the response principle and optimal design methods to applications in the food, beverage, and pharmaceutical markets

Development and Evaluation of a Miniaturized Taste Sensor Chip

A miniaturized taste sensor chip was designed for use in a portable-type taste sensing system. The fabricated sensor chip (40 mm × 26 mm × 2.2 mm) has multiple taste-sensing sites consisting of a poly(hydroxyethyl methacrylate) hydrogel with KCl as the electrolyte layer for stability of the membrane potential and artificial lipid membranes as the taste sensing elements. The sensor responses to the standard taste substances showed high accuracy and good reproducibility, which is comparable with the performance of the sensor probe of the commercialized taste sensing system. Thus, the fabricated taste sensor chip could be used as a key element for the realization of a portable-type taste sensing system

Independent comparison study of six different electronic tongues applied for pharmaceutical analysis

Electronic tongue technology based on arrays of cross-sensitive chemical sensors and chemometric data processing has attracted a lot of researchers' attention through the last years. Several so far reported applications dealing with pharmaceutical related tasks employed different e-tongue systems to address different objectives. In this situation, it is hard to judge on the benefits and drawbacks of particular e-tongue implementations for R&D in pharmaceutics. The objective of this study was to compare the performance of six different e-tongues applied to the same set of pharmaceutical samples. For this purpose, two commercially available systems (from Insent and AlphaMOS) and four laboratory prototype systems (two potentiometric systems from Warsaw operating in flow and static modes, one potentiometric system from St. Petersburg, one voltammetric system from Barcelona) were employed. The sample set addressed in the study comprised nine different formulations based on caffeine citrate, lactose monohydrate, maltodextrine, saccharin sodium and citric acid in various combinations. To provide for the fair and unbiased comparison, samples were evaluated under blind conditions and data processing from all the systems was performed in a uniform way. Different mathematical methods were applied to judge on similarity of the e-tongues response from the samples. These were principal component analysis (PCA), RV' matrix correlation coefficients and Tuckeŕs congruency coefficients

Taste profile characterization of white ginseng by electronic tongue analysis

We conducted taste profile analysis of white ginseng (Panax ginseng) using a taste-sensing system. Taste such as sourness, bitterness, astringent, aftertaste, umami, richness, and saltiness of the four subfractions (n-hexane fr. = Pg1; EtOAc fr. = Pg2; CHCl3 fr. = Pg3; n-BuOH fr. = Pg4) from white ginseng was checked using an electronic tongue. The bitterness and aftertaste-B of Pg3 were perceived as significantly higher than those of the other subfractions. The sourness of Pg2 had the highest rating compared to that of the other subfractions. The umami of Pg4 was higher than that of the other subfractions, but bitterness was lowest. As a result, the Pg3 subfraction of the white ginseng ch oroform fraction showed the largest variation in taste. Medium pressure liquid chromatography of the white ginseng chloroform fraction led to the isolation of two phytosterols, which were identified as β-sitosterol and daucosterol by spectral analysis. Additional study of these compounds on taste should be conducted.Key words: Electronic tongue, Panax ginseng, phytosterol, taste, white ginseng

Characterization of Whole Grain Pasta: Integrating Physical, Chemical, Molecular, and Instrumental Sensory Approaches

The consumption of whole-grain foodincluding pastahas been increasing steadily. In the case of whole-grain pasta, given the many different producers, it seems important to have some objective parameters to define its overall quality. In this study, commercial whole-grain pasta samples representative of the Italian market have been characterized from both molecular and electronic-senses (electronic nose and electronic tongue) standpoint in order to provide a survey of the properties of different commercial samples. Only 1 pasta product showed very low levels of heat damage markers (furosine and pyrraline), suggesting that this sample underwent to low temperature dry treatment. In all samples, the furosine content was directly correlated to protein structural indices, since protein structure compactness increased with increasing levels of heat damage markers. Electronic senses were able to discriminate among pasta samples according to the intensity of heat treatment during the drying step. Pasta sample with low furosine content was discriminated by umami taste and by sensors responding to aliphatic and inorganic compounds. Data obtained with this multidisciplinary approach are meant to provide hints for identifying useful indices for pasta quality. Practical ApplicationAs observed for semolina pasta, objective parameters based on heat-damage were best suited to define the overall quality of wholegrain pasta, almost independently of compositional differences among commercial samples. Drying treatments of different intensity also had an impact on instrumental sensory traits that may provide a reliable alternative to analytical determination of chemical markers of heat damage in all cases where there is a need for avoiding time-consuming procedures

Sugars' quantifications using a potentiometric electronic tongue with cross-selective sensors: Influence of an ionic background

Glucose, fructose and sucrose are sugars with known physiological e ects, and their consumption has impact on the human health, also having an important e ect on food sensory attributes. The analytical methods routinely used for identification and quantification of sugars in foods, like liquid chromatography and visible spectrophotometry have several disadvantages, like longer analysis times, high consumption of chemicals and the need for pretreatments of samples. To overcome these drawbacks, in this work, a potentiometric electronic tongue built with two identical multi-sensor systems of 20 cross-selectivity polymeric sensors, coupled with multivariate calibration with feature selection (a simulated annealing algorithm) was applied to quantify glucose, fructose and sucrose, and the total content of sugars as well. Standard solutions of ternary mixtures of the three sugars were used for multivariate calibration purposes, according to an orthogonal experimental design (multilevel fractional factorial design) with or without ionic background (KCl solution). The quantitative models’ predictive performance was evaluated by cross-validation with K-folds (internal validation) using selected data for training (selected with the K-means algorithm) and by external validation using test data. Overall, satisfactory predictive quantifications were achieved for all sugars and total sugar content based on subsets comprising 16 or 17 sensors. The test data allowed us to compare models’ predictions values and the respective sugar experimental values, showing slopes varying between 0.95 and 1.03, intercept values statistically equal to zero (p-value 0.05) and determination coe cients equal to or greater than 0.986. No significant di erences were found between the predictive performances for the quantification of sugars using synthetic solutions with or without KCl (1 mol L1), although the adjustment of the ionic background allowed a better homogenization of the solution’s matrix and probably contributed to an enhanced confidence in the analytical work across all of the calibration working range.This research work was funded by strategic project CIMO–PEst-OE/AGR/UI0690/2014 and Associate Laboratory LSRE-LCM–UID/EQU/50020/2019, financially supported by the FEDER—Fundo Europeu de Desenvolvimento Regional through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI); and by national funds through FCT—Fundação para a Ciência e a Tecnologia, Portugalinfo:eu-repo/semantics/publishedVersio

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

Olive oil quality grading is traditionally assessed by human sensory evaluation of positive and negative attributes (olfactory, gustatory, and final olfactorygustatory sensations). However, it is not guaranteed that trained panelist can correctly classify monovarietal extra-virgin olive oils according to olive cultivar. In this work, the potential application of human (sensory panelists) and artificial (electronic tongue) sensory evaluation of olive oils was studied aiming to discriminate eight single-cultivar extra-virgin olive oils. Linear discriminant, partial least square discriminant, and sparse partial least square discriminant analyses were evaluated. The best predictive classification was obtained using linear discriminant analysis with simulated annealing selection algorithm. A low-level data fusion approach (18 electronic tongue signals and nine sensory attributes) enabled 100 % leave-one-out cross-validation correct classification, improving the discrimination capability of the individual use of sensor profiles or sensory attributes (70 and 57 % leave-one-out correct classifications, respectively). So, human sensory evaluation and electronic tongue analysis may be used as complementary tools allowing successful monovarietal olive oil discrimination.This work was co-financed by FCT/MEC and FEDER under Program PT2020 (Project UID/EQU/50020/2013); by Fundacao para a Ciencia e Tecnologia under the strategic funding of UID/BIO/04469/2013 unit; and by Project POCTEP through Project RED/AGROTEC-Experimentation network and transfer for development of agricultural and agro industrial sectors between Spain and Portugal

Discrimination of sweet cherry cultivars based on electronic tongue potentiometric fingerprints

Sweet cherry is highly appreciated by its characteristic flavor, which conditions the consumer’s preference. In this study, four sweet cherry cultivars (Durona, Lapins, Summit, and Van cultivars) were characterized according to biometric (fruit and stone weights, length, maximum and minimum diameters, pulp/stone mass ratio), physicochemical (CIELAB color, penetration force, titratable acidity, and total soluble solids), and potentiometric profiles (recorded by a lab-made electronic tongue with lipid polymeric membranes). Biometric and physicochemical data were significantly cultivar-dependent (p-value < 0.0001, one-way ANOVA). Summit cherries had higher masses and dimensions. Lapins cherries had the highest penetration force values having, together with Summit cherries, the highest CIELAB values. Van cherries showed the highest total soluble solids contents. No significant differences were found for fruits’ acidity (similar titratable acidities). The possibility of discriminating cherry cultivars was also evaluated using a linear discriminant analysis/simulated-annealing algorithm. A discriminant model was established based on nine non-redundant biometric-physicochemical parameters (using a low-level data fusion), with low sensitivity (75 ± 15% for the repeated K-fold cross-validation). On the contrary, a discriminant model, based on the potentiometric fingerprints of 11 selected sensors, allowed a better discrimination, with sensitivities of 88 ± 7% for the repeated K-fold cross-validation procedure. Thus, the electronic tongue could be used as a practical tool to discriminate cherry cultivars and, if applied by fruit traders, may reduce the risk of mislabeling, increasing the consumers’ confidence when purchasing this high-value product.The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support by national funds FCT/MCTES to CIMO (UIDB/00690/2020) and to CEB (UIDB/04469/2020) units, as well as BioTecNorte operation (NORTE-01-0145-FEDER-000004), funded by the European Regional Development Fund under the scope of Norte2020—Programa Operacional Regional do Norte. Nuno Rodrigues also thanks the national funding by FCT–Foundation for Science and Technology, P.I., through the Institutional scientific employment program contract.info:eu-repo/semantics/publishedVersio

Evaluation of extra-virgin olive oils shelf life using an electronic tongue-chemometric approach

Physicochemical quality parameters, olfactory and gustatoryretronasal positive sensations of extra-virgin olive oils vary during storage leading to a decrease in the overall quality. Olive oil quality decline may prevent the compliance of olive oil quality with labeling and significantly reduce shelf life, resulting in important economic losses and negatively condition the consumer confidence. The feasibility of applying an electronic tongue to assess olive oils usual commercial light storage conditions and storage time was evaluated and compared with the discrimination potential of physicochemical or positive olfactory/gustatory sensorial parameters. Linear discriminant models, based on subsets of 58 electronic tongue sensor signals, selected by the meta-heuristic simulated annealing variable selection algorithm, allowed the correct classification of olive oils according to the light exposition conditions and/or storage time (sensitivities and specificities for leave-one-out cross-validation: 8296 %). The predictive performance of the E-tongue approach was further evaluated using an external independent dataset selected using the KennardStone algorithm and, in general, better classification rates (sensitivities and specificities for external dataset: 67100 %) were obtained compared to those achieved using physicochemical or sensorial data. So, the work carried out is a proof-of-principle that the proposed electrochemical device could be a practical and versatile tool for, in a single and fast electrochemical assay, successfully discriminate olive oils with different storage times and/or exposed to different light conditions.The authors acknowledge the financial support from the strategic funding of UID/BIO/04469/2013 unit, from Project POCI-01-0145-FEDER-006984—Associate Laboratory LSRELCM funded by FEDER funds through COMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI)—and by national funds through FCT—Fundação para a Ciência e a Tecnologia and under the strategic funding of UID/BIO/04469/2013 unit. Nuno Rodrigues thanks FCT, POPH-QREN and FSE for the Ph.D. Grant (SFRH/BD/104038/2014).info:eu-repo/semantics/publishedVersio