Carbamoylase-based impedimetric electronic tongue for rapid detection of paralytic shellfish toxins.

Phytotoxins produced by marine microalgae, such as paralytic shellfish toxins (PSTs), can accumulate in bivalve molluscs, representing a human health concern due to the life-threatening symptoms they cause. To avoid the commercialization of contaminated bivalves, monitoring programs were established in the EU. The purpose of this work is the implementation of a PST transforming enzyme-carbamoylase-in an impedimetric test for rapid simultaneous detection of several carbamate and N-sulfocarbamoyl PSTs. Carbamoylase hydrolyses carbamate and sulfocarbamoyl toxins, which may account for up to 90% of bivalve toxicity related to PSTs. Conformational changes of carbamoylase accompanying enzymatic reactions were probed by Fourier transform mid-infrared spectroscopy (FT-MIR) and electrochemical impedance spectroscopy (EIS). Furthermore, a combination of EIS with a metal electrode and a carbamoylase-based assay was employed to harness changes in the enzyme conformation and adsorption on the electrode surface during the enzymatic reaction as an analytical signal. After optimization of the working conditions, the developed impedimetric e-tongue could quantify N-sulfocarbamoyl toxins with a detection limit of 0.1 µM. The developed e-tongue allows the detection of these toxins at concentration levels observed in bivalves with PST toxicity close to the regulatory limit. The quantification of a sum of N-sulfocarbamoyl PSTs in naturally contaminated mussel extracts using the developed impedimetric e-tongue has been demonstrated.

Analysis of milk adulteration by means of a potentiometric electronic tongue.

The adulteration of milk presents significant challenges in the food industry, promoting the need for efficient detection methods. This study introduces a potentiometric electronic tongue for rapid and accurate milk adulteration detection. Utilizing polymeric membranes integrated with various additives, the electronic tongue distinguishes between different milk types and detects common adulterants. Experimental results demonstrate its effectiveness in discriminating raw, pasteurized, and medicated cow milk, as well as goat milk. Moreover, it successfully identifies adulterants like water and bovine milk in goat milk samples. Chemometric analyses, including Principal Component Analysis and Partial Least Squares regression, correlate sensor responses with traditional milk parameters such as fat, protein, and lactose content with up to a 0.97 R2 on the validation step. Strong correlations validate the electronic tongue's potential for rapid milk quality assessment. This innovative approach offers a cost-effective, reliable solution for detecting milk adulteration in contrast with current techniques that require numerous, time consuming experiments.

Effective strategy for distinguishing raw and vinegar Schisandrae Chinensis Fructus based on electronic eye and electronic tongue combined with chemometrics.

INTRODUCTION: Schisandrae Chinensis Fructus (SCF), a traditional Chinese medicine, has been used in treating virtual injury and strain since ancient times. The Chinese Pharmacopoeia reveals that SCF includes raw (RSCF) and vinegar-processed (VSCF) decoction pieces. OBJECTIVE: This study developed an effective method combining the electronic eye (e-eye), electronic tongue (e-tongue), and chemometrics to discriminate RSCF and VSCF from the perspective of chemical composition, color, and taste. MATERIAL AND METHODS: First, RSCF were collected and processed into VSCF, and their color parameters, e-tongue sensory properties, high-performance liquid chromatography (HPLC) and ultra-HPLC (UPLC) characteristic fingerprints, and nominal ingredients were determined. Multivariate statistical analyses, including principal component, linear discriminant, similarity, and partial least squares discriminant analyses, were conducted. RESULTS: HPLC and UPLC fingerprints were established, demonstrating a > 0.900 similarity. The content determination indicated increased schisantherin A, schisantherin B, and schisandrin A contents in VSCF. The e-eye data demonstrated a > 1.5 total color difference before and after processing ΔE*ab, indicating the significantly changed sample color and appearance before and after processing. The e-tongue technology was used to quantitatively characterize the taste of RSCF and VSCF. The t-test revealed significantly reduced sourness, aftertaste-bitter, and aftertaste-astringent values of SCF after vinegar processing. Principal component and partial least squares discriminant analyses indicated that e-eye and e-tongue realize the rapid RSCF and VSCF identification. CONCLUSION: The proposed comprehensive strategy of electronic eye and electronic tongue combined with chemometrics demonstrated satisfactory results with high efficiency, accuracy, and reliability. This can be developed into a novel and accurate method for discriminating RSCF and VSCF.

Development of a Bitterness Sensor Using Partially Dissociated Amine Compounds.

This study focused on developing an advanced bitterness sensor designed to minimize interference from common anions such as nitrate (NO3-) and iodide (I-) by incorporating partially dissociated amine compounds into the sensor membrane. The conventional bitter sensor (C00) uses fully dissociated quaternary ammonium salt tetradecyl ammonium bromide (TDAB), which typically exhibits high responses to these anions, leading to inaccurate bitterness assessments. To address this issue, we explored the use of three partially dissociated amines-oleylamine (OAm), dioctadecylamine (DODA), and tridodecylamine (TDA)-as lipids in the membrane components. We fabricated sensor membranes and tested their ion selectivity, interference resistance to anion, and sensitivity to iso-alpha acids (IAAs), representative bitter compounds in beer. The results showed that the membranes with partially dissociated amines significantly reduced anion interference. Notably, the sensitivity of the TDA membrane to IAAs was 80.4 mV/dec in concentration, exceeding the 68.5 mV/dec of the TDAB membrane. This enhanced sensitivity, coupled with reduced anion interference, reveals a novel property of partially dissociated lipids in taste sensors, distinguishing them from fully dissociated lipids. These findings pave the way for the development of sensors that can accurately assess a bitter taste and have potential applications in the food and beverage industry.

Taste Sensor Assessment of Bitterness in Medicines: Overview and Recent Topics.

In recent decades, taste sensors have been increasingly utilized to assess the taste of oral medicines, particularly focusing on bitterness, a major obstacle to patient acceptance and adherence. This objective and safe method holds promise for enhancing the development of patient-friendly medicines in pharmaceutical companies. This review article introduces its application in measuring the intensity of bitterness in medicine, confirming the achievement of taste masking, distinguishing taste differences between branded and generic medicines, and identifying substances to suppress bitterness in target medicines. Another application of the sensor is to predict a significant increase in bitterness when medicine is taken with certain foods/beverages or concomitant medication. Additionally, to verify the sensor's predictability, a significant correlation has been demonstrated between the output of a bitter-sensitive sensor designed for drug bitterness (BT0) and the bitterness responses of the human taste receptor hT2R14 from BitterDB (huji.ac.il). As a recent advancement, a novel taste sensor equipped with lipid/polymer membranes modified by 3-Br-2,6-dihydroxybenzoic acid (2,6-DHBA), based on the concept of allostery, is introduced. This sensor successfully predicts the bitterness of non-charged pharmaceuticals with xanthine skeletons, such as caffeine or related compounds. Finally, the future prospects of taste sensors are discussed.

Evaluation of a Voltametric E-Tongue Combined with Data Preprocessing for Fast and Effective Machine Learning-Based Classification of Tomato Purées by Cultivar.

The potential of a voltametric E-tongue coupled with a custom data pre-processing stage to improve the performance of machine learning techniques for rapid discrimination of tomato purées between cultivars of different economic value has been investigated. To this aim, a sensor array with screen-printed carbon electrodes modified with gold nanoparticles (GNP), copper nanoparticles (CNP) and bulk gold subsequently modified with poly(3,4-ethylenedioxythiophene) (PEDOT), was developed to acquire data to be transformed by a custom pre-processing pipeline and then processed by a set of commonly used classifiers. The GNP and CNP-modified electrodes, selected based on their sensitivity to soluble monosaccharides, demonstrated good ability in discriminating samples of different cultivars. Among the different data analysis methods tested, Linear Discriminant Analysis (LDA) proved to be particularly suitable, obtaining an average F1 score of 99.26%. The pre-processing stage was beneficial in reducing the number of input features, decreasing the computational cost, i.e., the number of computing operations to be performed, of the entire method and aiding future cost-efficient hardware implementation. These findings proved that coupling the multi-sensing platform featuring properly modified sensors with the custom pre-processing method developed and LDA provided an optimal tradeoff between analytical problem solving and reliable chemical information, as well as accuracy and computational complexity. These results can be preliminary to the design of hardware solutions that could be embedded into low-cost portable devices.

Integrating Computational and Experimental Methods to Identify Novel Sweet Peptides from Egg and Soy Proteins.

Sweetness in food delivers a delightful sensory experience, underscoring the crucial role of sweeteners in the food industry. However, the widespread use of sweeteners has sparked health concerns. This underscores the importance of developing and screening natural, health-conscious sweeteners. Our study represents a groundbreaking venture into the discovery of such sweeteners derived from egg and soy proteins. Employing virtual hydrolysis as a novel technique, our research entailed a comprehensive screening process that evaluated biological activity, solubility, and toxicity of the derived compounds. We harnessed cutting-edge machine learning methodologies, specifically the latest graph neural network models, for predicting the sweetness of molecules. Subsequent refinements were made through molecular docking screenings and molecular dynamics simulations. This meticulous research approach culminated in the identification of three promising sweet peptides: DCY(Asp-Cys-Tyr), GGR(Gly-Gly-Arg), and IGR(Ile-Gly-Arg). Their binding affinity with T1R2/T1R3 was lower than -15 kcal/mol. Using an electronic tongue, we verified the taste profiles of these peptides, with IGR emerging as the most favorable in terms of taste with a sweetness value of 19.29 and bitterness value of 1.71. This study not only reveals the potential of these natural peptides as healthier alternatives to traditional sweeteners in food applications but also demonstrates the successful synergy of computational predictions and experimental validations in the realm of flavor science.

Characterization of Flavor Profile of Sauced Pork from Different Regions of China Based on E-Nose, E-Tongue and Gas Chromatography-Ion Mobility Spectroscopy.

This study aimed to investigate the volatile flavor compounds and tastes of six kinds of sauced pork from the southwest and eastern coastal areas of China using gas chromatography-ion mobility spectroscopy (GC-IMS) combined with an electronic nose (E-nose) and electronic tongue (E-tongue). The results showed that the combined use of the E-nose and E-tongue could effectively identify different kinds of sauced pork. A total of 52 volatile flavor compounds were identified, with aldehydes being the main flavor compounds in sauced pork. The relative odor activity value (ROAV) showed that seven key volatile compounds, including 2-methylbutanal, 2-ethyl-3, 5-dimethylpyrazine, 3-octanone, ethyl 3-methylbutanoate, dimethyl disulfide, 2,3-butanedione, and heptane, contributed the most to the flavor of sauced pork (ROAV ≥1). Multivariate data analysis showed that 13 volatile compounds with the variable importance in projection (VIP) values > 1 could be used as flavor markers to distinguish six kinds of sauced pork. Pearson correlation analysis revealed a significant link between the E-nose sensor and alcohols, aldehydes, terpenes, esters, and hetero-cycle compounds. The results of the current study provide insights into the volatile flavor compounds and tastes of sauced pork. Additionally, intelligent sensory technologies can be a promising tool for discriminating different types of sauced pork.

Electronic eye and electronic tongue data fusion combined with a GETNet model for the traceability and detection of Astragalus.

BACKGROUND: Astragalus is a widely used traditional Chinese medicine material that is easily confused due to its quality, price and other factors derived from different origins. This article describes a novel method for the rapid tracing and detection of Astragalus via the joint application of an electronic tongue (ET) and an electronic eye (EE) combined with a lightweight convoluted neural network (CNN)-transformer model. First, ET and EE systems were employed to measure the taste fingerprints and appearance images, respectively, of different Astragalus samples. Three spectral transform methods - the Markov transition field, short-time Fourier transform and recurrence plot - were utilized to convert the ET signals into 2D spectrograms. Then, the obtained ET spectrograms were fused with the EE image to obtain multimodal information. A lightweight hybrid model, termed GETNet, was designed to achieve pattern recognition for the Astragalus fusion information. The proposed model employed an improved transformer module and an improved Ghost bottleneck as its backbone network, complementarily utilizing the benefits of CNN and transformer architectures for local and global feature representation. Furthermore, the Ghost bottleneck was further optimized using a channel attention technique, which boosted the model's feature extraction effectiveness. RESULTS: The experiments indicate that the proposed data fusion strategy based on ET and EE devices has better recognition accuracy than that attained with independent sensing devices. CONCLUSION: The proposed method achieved high precision (99.1%) and recall (99.1%) values, providing a novel approach for rapidly identifying the origin of Astragalus, and it holds great promise for applications involving other types of Chinese herbal medicines. © 2024 Society of Chemical Industry.

Peroxidase-Like FeCoZn Triple-Atom Catalyst-Based Electronic Tongue for Colorimetric Discrimination of Food Preservatives.

Recently, single-atom catalysts are attracting much attention in sensor field due to their remarkable peroxidase- or oxidase-like activities. Herein, peroxidase-like FeCoZn triple-atom catalyst supported on S- and N-doped carbon derived from ZIF-8 (FeCoZn-TAC/SNC) serves as a proof-of-concept nanozyme. In this paper, a dual-channel nanozyme-based colorimetric sensor array is presented for identifying seven preservatives in food. Further experiments reveal that the peroxidase-like activity of the FeCoZn TAzyme enables it to catalyze the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) and o-phenylenediamine (OPD) in the presence of H2 O2 , yielding the blue oxTMB and yellow oxOPD, respectively. However, food preservatives are adsorbed on the nanozyme surface through π-π stacking interaction and hydrogen bond, and the reduction in catalytic activity of FeCoZn TAzyme causes differential colorimetric signal variations, which provide unique "fingerprints" for each food preservative.

Comparison of taste characteristics between koji mold-ripened cheese and Camembert cheese using an electronic tongue system.

Koji mold, classified in the genus Aspergillus, is used to produce traditional Japanese fermented foods such as miso, soy sauce, and sake. In recent years, the application of koji mold to cheese ripening has attracted attention, and cheese surface-ripened with koji mold (koji cheese) has been studied. In this study, to evaluate the taste characteristics of koji cheese, an electronic tongue system was employed to measure the taste values of cheese samples ripened using 5 strains of koji mold in comparison with commercial Camembert cheese. All koji cheese samples exhibited lower sourness and greater bitterness, astringency, saltiness, and umami richness than the Camembert cheese samples. The intensity of each taste characteristic differed depending on the koji mold strain. These results indicate that koji cheese has a different taste value than conventional mold-ripened cheese. Furthermore, the results also indicate that various taste characteristics can be achieved by selecting different koji molds.

Research and development of taste sensors as a novel analytical tool.

Gustatory and olfactory receptors receive multiple chemical substances of different types simultaneously, but they can barely discriminate one chemical species from others. In this article, we describe a device used to measure taste, i.e., taste sensors. Toko and colleagues developed a taste sensor equipped with multiarray electrodes using a lipid/polymer membrane as the transducer in 1989. This sensor has a concept of global selectivity to decompose the characteristics of a chemical substance into taste qualities and to quantify them. The use of taste sensors has spread around the world. More than 600 examples of taste-sensing system have been used, while providing the first "taste scale" in the world. This article explains the principle of taste sensors and their application to foods and medicines, and also a novel type of taste sensor using allostery. Taste-sensor technology, the underlying principle of which is different from that of conventional analytical instruments, markedly affects many aspects including social economy as well as the food industry.

Juice Quality Evaluation with Multisensor Systems-A Review.

E-nose and e-tongue are advanced technologies that allow for the fast and precise analysis of smells and flavours using special sensors. Both technologies are widely used, especially in the food industry, where they are implemented, e.g., for identifying ingredients and product quality, detecting contamination, and assessing their stability and shelf life. Therefore, the aim of this article is to provide a comprehensive review of the application of e-nose and e-tongue in various industries, focusing in particular on the use of these technologies in the fruit and vegetable juice industry. For this purpose, an analysis of research carried out worldwide over the last five years, concerning the possibility of using the considered multisensory systems to test the quality and taste and aroma profiles of juices is included. In addition, the review contains a brief characterization of these innovative devices through information such as their origin, mode of operation, types, advantages and disadvantages, challenges and perspectives, as well as the possibility of their applications in other industries besides the juice industry.

New Electronic Tongue Sensor Array System for Accurate Liquor Beverage Classification.

The use of sensors in different applications to improve the monitoring of a process and its variables is required as it enables information to be obtained directly from the process by ensuring its quality. This is now possible because of the advances in the fabrication of sensors and the development of equipment with a high processing capability. These elements enable the development of portable smart systems that can be used directly in the monitoring of the process and the testing of variables, which, in some cases, must evaluated by laboratory tests to ensure high-accuracy measurement results. One of these processes is taste recognition and, in general, the classification of liquids, where electronic tongues have presented some advantages compared with traditional monitoring because of the time reduction for the analysis, the possibility of online monitoring, and the use of strategies of artificial intelligence for the analysis of the data. However, although some methods and strategies have been developed, it is necessary to continue in the development of strategies that enable the results in the analysis of the data from electrochemical sensors to be improved. In this way, this paper explores the application of an electronic tongue system in the classification of liquor beverages, which was directly applied to an alcoholic beverage found in specific regions of Colombia. The system considers the use of eight commercial sensors and a data acquisition system with a machine-learning-based methodology developed for this aim. Results show the advantages of the system and its accuracy in the analysis and classification of this kind of alcoholic beverage.

Nanotechnology and E-Sensing for Food Chain Quality and Safety.

Nowadays, it is well known that sensors have an enormous impact on our life, using streams of data to make life-changing decisions. Every single aspect of our day is monitored via thousands of sensors, and the benefits we can obtain are enormous. With the increasing demand for food quality, food safety has become one of the main focuses of our society. However, fresh foods are subject to spoilage due to the action of microorganisms, enzymes, and oxidation during storage. Nanotechnology can be applied in the food industry to support packaged products and extend their shelf life. Chemical composition and sensory attributes are quality markers which require innovative assessment methods, as existing ones are rather difficult to implement, labour-intensive, and expensive. E-sensing devices, such as vision systems, electronic noses, and electronic tongues, overcome many of these drawbacks. Nanotechnology holds great promise to provide benefits not just within food products but also around food products. In fact, nanotechnology introduces new chances for innovation in the food industry at immense speed. This review describes the food application fields of nanotechnologies; in particular, metal oxide sensors (MOS) will be presented.

A Bioinspired Artificial Gustatory Neuron for a Neuromorphic Based Electronic Tongue.

A novel biomimicked neuromorphic sensor for an energy efficient and highly scalable electronic tongue (E-tongue) is demonstrated with a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological gustatory neuron, the proposed E-tongue can simultaneously detect ion concentrations of chemicals on an extended gate and encode spike signals on the MOSFET, which acts as an input neuron in a spiking neural network (SNN). Such in-sensor neuromorphic functioning can reduce the energy and area consumption of the conventional E-tongue hardware. pH-sensitive and sodium-sensitive artificial gustatory neurons are implemented by using two different sensing materials: Al2O3 for pH sensing and sodium ionophore X for sodium ion sensing. In addition, a sensitivity control function inspired by the biological sensory neuron is demonstrated. After the unit device characterization of the artificial gustatory neuron, a fully hardware-based E-tongue that can classify two distinct liquids is demonstrated to show a practical application of the artificial gustatory neurons.

Review of Applications of Cyclodextrins as Taste-Masking Excipients for Pharmaceutical Purposes.

It is widely recognized that many active pharmaceutical ingredients (APIs) have a disagreeable taste that affects patient acceptability, particularly in children. Consequently, developing dosage forms with a masked taste has attracted a lot of interest. The application of cyclodextrins as pharmaceutical excipients is highly appreciated and well established, including their roles as drug delivery systems, solubilizers and absorption promoters, agents that improve drug stability, or even APIs. The first work describing the application of the taste-masking properties of CDs as pharmaceutical excipients was published in 2001. Since then, numerous studies have shown that these cyclic oligosaccharides can be effectively used for such purposes. Therefore, the aim of this review is to provide insight into studies in this area. To achieve this aim, a systematic evaluation was conducted, which resulted in the selection of 67 works representing both successful and unsuccessful works describing the application of CDs as taste-masking excipients. Particular attention has been given to the methods of evaluation of the taste-masking properties and the factors affecting the outcomes, such as the choice of the proper cyclodextrin or guest-host molar ratio. The conclusions of this review reveal that the application of CDs is not straightforward; nevertheless, this solution can be an effective, safe, and inexpensive method of taste masking for pharmaceutical purposes.

Bioactive Compounds, Antioxidant Activity and Sensory Properties of Northern Red Oak (Quercus rubra L., syn. Q. borealis F. Michx) Seeds Affected by Roasting Conditions.

The nutritional value and health-promoting properties cause the fruits (acorns) of Quercus spp. to have great potential for use in the food industry as functional ingredients and antioxidants source. The aim of this study was to examine the bioactive compound's composition, antioxidant potential, physicochemical properties and taste characteristics of northern red oak (Quercus rubra L.) seeds subjected to roasting at different temperatures and times. The results indicate that the roasting markedly affects the composition of bioactive components of acorns. In general, the use of roasting temperatures greater than 135 °C causes a decrease in the total phenolic compound content of Q. rubra seeds. Furthermore, along with an increase in temperature and thermal processing time, a remarkable increase in melanoidins, which are the final products of the Maillard reaction, was also observed in processed Q. rubra seeds. Both unroasted and roasted acorn seeds had high DPPH radical scavenging capacity, ferric reducing antioxidant power (FRAP) and ferrous ion chelating activity. Roasting at 135 °C caused negligible changes in total phenolics content and antioxidant activity of Q. rubra seeds. Almost all samples had lower antioxidant capacity along with an increase in the roasting temperatures. Additionally, thermal processing of acorn seeds contributes to the development of the brown color and the reduction of bitterness, and the creation of a more pleasant taste of the final products. Overall, the results of this study show that both unroasted and roasted Q. rubra seeds may be an interesting source of bioactive compounds with high antioxidant activity. Therefore, they can be used as a functional ingredient of beverages or food.

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.

The electronic tongue: an advanced taste-sensing multichannel sensory tool with global selectivity for application in the pharmaceutical and food industry.

Taste is a crucial organoleptic characteristic that determines whether a substance will be accepted for delivery through the mouth. However, the vast majority of medications have an unpleasant taste. Drugs with a bitter taste are often depicted using a variety of flavouring compounds to increase patient acceptance and compliance. Human panellists are the principal means of assessing the flavour of medication ingredients and formulations. Due to the toxicity of medications and subjectivity of taste panellists, as well as issues with hiring taste panellists and panel upkeep when working with unpleasant items, the use of sensory panellists in the industry is particularly challenging and troublesome. Furthermore, tests cannot be conducted on compounds that have not received FDA approval. As a result, the analytical taste-sensing multichannel sensory system known as the electronic tongue (also known as the artificial tongue or e-tongue) helps in reducing the number of samples that are ought to be assessed by trained sensory panels and also when the sample to be tasted is injurious or harmful for the concerned person. Therefore, e-tongue has advantages like lowering reliance on human panels. The working theory, the sensors used, and the pharmaceutical and food applications are covered, along with the major software used, difficulties, and future scope are also highlighted.