Monitoring the aging of beers using a bioelectronic tongue

Endogenous storage proteins influence Rice flavor: Insights from protein-flavor correlations and predictive modeling

This study investigated the correlation between endogenous storage proteins and aromatic compounds in rice, and their collective influence on rice eating quality. Six rice samples, varying in four endogenous storage proteins through gene editing genetically modified, were analyzed for their sensory characteristics and volatile compounds utilizing GC-E-nose, GC-MS, GC-MS-O, texture analyzer, and sensory evaluation. The results indicated that a total of 55 flavor compounds were identified, with 2-acetyl-1-pyrroline identified as the key aroma compound, positively correlated with prolamin content, while negatively correlated with glutelin and albumin. The concentrations of glutelin and prolamin significantly influence the odor, taste, and texture of rice. Additionally, six prediction models were evaluated, with the optimal Support Vector Regression (SVR) model selected for predicting rice flavor profiles based on protein content. This study provides a foundation for understanding key factors in rice aroma and texture, offering valuable guidance for gene-editing strategies aimed at enhancing rice flavor.

Electronic panel for sensory assessment of food: A review on technologies integration and their benefits

Sensory assessment of food has been the measure for the acceptance or rejection of it in the market. However, the methods employed require human panels which are expensive. They have also been associated with various psychological and physiological biases being reported. In such cases, the novel E-panel technology including e-eye, e-nose, and e-tongue could be used and has proved to be applicable in various analyses such as fruit ripening stages and maturity tracing, identification and classification of volatile compounds, identification of specific taste, adulteration monitoring, pathogen detection, discrimination of geographical region, and cultivar region. E-nose, e-tongue, and e-eye work like the human olfactory system, human gustometry system, and performs computer vision or colorimetric analysis. Therefore, the e-panel technology could be explored for various food and food products to analyze their quality from the view of safety and consumer acceptance. Moreover, the qualities and demerits of E-panel over traditional sensory methods are weighed to understand their full potential. The current review exhibits the critical analysis of E-panel technology concerning the traditional sensory methods and individual e-nose, e-tongue along with the challenges associated with and future recommendations.

Electrochemical biosensors for dopamine

Dopamine (DA), a key catecholamine, plays a pivotal role in the regulation of human cognition and emotions. It has profound effects on the hormonal, memory, and cardiovascular systems. Anomalies like Alzheimer's, Parkinson's, schizophrenia, and senile dementia are linked to abnormal DA levels. Consequently, the precise determination of DA levels in biological systems is critical for the accurate diagnosis and treatment of these disorders. Among all analytical techniques, electrochemical studies provide the most selective and highly sensitive methods for detecting DA in biological samples. Ascorbic acid and uric acid are two examples of small biomolecules that can obstruct the detection of DA in biological fluids. To address this issue, numerous attempts have been made to modify bare electrodes to separate the signals of these substances and enhance the electrocatalytic activity towards DA. Various surface modifiers, including coatings, conducting polymers, ionic liquids, nanomaterials, and inorganic complexes, have been employed in the modification process. Despite the reported success in DA detection using electrochemical sensors, many of these approaches are deemed too complex and costly for real-world applications. Therefore, this review aims to provide an overview of DA electrochemical biosensors that are practical for real-world applications.

Charge Transfer Mechanism in Guanine-Based Self-Assembled Monolayers on a Gold Surface

In this work, we have theoretically determined the one-electron oxidation potentials and charge transfer mechanisms in complex systems based on a self-assembled monolayer of guanine molecules adsorbed on a gold surface through different organic linkers. Classical molecular dynamics simulations were carried out to sample the conformational space of both the neutral and the cationic species. Thus, the redox potentials were determined for the ensembles of geometries through multiscale quantum-mechanics/molecular-mechanics/continuum solvation model calculations in the framework of the Marcus theory and in combination with an additive scheme previously developed. In this context, conformational sampling, description of the environment, and effects caused by the linker have been considered. Applying this methodology, we unravel the phenomena of electric current transport by evaluating the different stages in which charge transfer could occur. The results revealed how the positive charge migrates from the organic layer to the gold surface. Specifically, the transport mechanism seems to take place mainly along a single ligand and driven with the help of the electrostatic interactions of the surrounding molecules. Aside, several self-assembled monolayers with different linkers have been analyzed to understand how the nature of that moiety can tune the redox properties and the efficiency of the transport. We have found that the conjugation between the guanine and the linker, at the same time conjugated to the gold surface, gives rise to a more efficient transport. In conclusion, the established computational protocol sheds light on the mechanism behind charge transport in electrochemical DNA-based biosensor nanodevices.

Flow-Through Amperometric Biosensor System Based on Functionalized Aryl Derivative of Phenothiazine and PAMAM-Calix-Dendrimers for the Determination of Uric Acid

A flow-through biosensor system for the determination of uric acid was developed on the platform of flow-through electrochemical cell manufactured by 3D printing from poly(lactic acid) and equipped with a modified screen-printed graphite electrode (SPE). Uricase was immobilized to the inner surface of a replaceable reactor chamber. Its working volume was reduced to 10 μL against a previously reported similar cell. SPE was modified independently of the enzyme reactor with carbon black, pillar[5]arene, poly(amidoamine) dendrimers based on the p-tert-butylthiacalix[4]arene (PAMAM-calix-dendrimers) platform and electropolymerized 3,7-bis(4-aminophenylamino) phenothiazin-5-ium chloride. Introduction of the PAMAM-calix-dendrimers into the electrode coating led to a fivefold increase in the redox currents of the electroactive polymer. It was found that higher generations of the PAMAM-calix-dendrimers led to a greater increase in the currents measured. Coatings consisted of products of the electropolymerization of the phenothiazine with implemented pillar[5]arene and PAMAM-calix-dendrimers showing high efficiency in the electrochemical reduction of hydrogen peroxide that was formed in the enzymatic oxidation of uric acid. The presence of PAMAM-calix-dendrimer G2 in the coating increased the redox signal related to the uric acid assay by more than 1.5 times. The biosensor system was successfully applied for the enzymatic determination of uric acid in chronoamperometric mode. The following optimal parameters for the chronoamperometric determination of uric acid in flow-through conditions were established: pH 8.0, flow rate 0.2 mL·min-1, 5 U of uricase per reactor. Under these conditions, the biosensor system made it possible to determine from 10 nM to 20 μM of uric acid with the limit of detection (LOD) of 4 nM. Glucose (up to 1 mM), dopamine (up to 0.5 mM), and ascorbic acid (up to 50 μM) did not affect the signal of the biosensor toward uric acid. The biosensor was tested on spiked artificial urine samples, and showed 101% recovery for tenfold diluted samples. The ease of assembly of the flow cell and the low cost of the replacement parts make for a promising future application of the biosensor system in routine clinical analyses.

An Efficient Multilayer Approach to Model DNA-Based Nanobiosensors

In this work, we present a full computational protocol to successfully obtain the one-electron reduction potential of nanobiosensors based on a self-assembled monolayer of DNA nucleobases linked to a gold substrate. The model is able to account for conformational sampling and environmental effects at a quantum mechanical (QM) level efficiently, by combining molecular mechanics (MM) molecular dynamics and multilayer QM/MM/continuum calculations within the framework of Marcus theory. The theoretical model shows that a guanine-based biosensor is more prone to be oxidized than the isolated nucleobase in water due to the electrostatic interactions between the assembled guanine molecules. In addition, the redox properties of the biosensor can be tuned by modifying the nature of the linker that anchor the nucleobases to the metal support.

Physicochemical, Electronic Nose and Tongue, Sensory Evaluation Determination Combined with Chemometrics to Characterize Ficus hirta Vahl. (Moraceae) Beer

Ficus hirta Vahl. (FHV) is widely consumed because of its functional and aromatic compounds. The incorporation of adjuncts contributes to the functional and flavor properties of beers. This study aims to enrich FHV extractions to develop beers with satisfactory physicochemical, antioxidant, and sensory characteristics. As a result, beers with 0.1 g/mL (P1) and 0.067 g/mL (P3) FHV extraction showed the highest values of physicochemical properties including °Brix, antioxidant activity, foam, lightness, and color intensity. Electronic nose and tongue results show that the aroma of P1 and taste of P3 were quite different from those of other FHV beers, resulting in substantially high consumer preference. The liking drivers of FHV beers were color appearance, hop and malty odor, sweet and malty flavor, thickness, and carbonation mouthfeel. However, the astringency flavor attribute was the disliking factor for beers. The results of this study may provide some references and guidelines for the development of Ficus hirta Vahl. functional beer to control the physicochemical, antioxidative, and sensory properties of the beer.

Recent Advances in Electrochemical Biosensors: Applications, Challenges, and Future Scope

The electrochemical biosensors are a class of biosensors which convert biological information such as analyte concentration that is a biological recognition element (biochemical receptor) into current or voltage. Electrochemical biosensors depict propitious diagnostic technology which can detect biomarkers in body fluids such as sweat, blood, feces, or urine. Combinations of suitable immobilization techniques with effective transducers give rise to an efficient biosensor. They have been employed in the food industry, medical sciences, defense, studying plant biology, etc. While sensing complex structures and entities, a large data is obtained, and it becomes difficult to manually interpret all the data. Machine learning helps in interpreting large sensing data. In the case of biosensors, the presence of impurity affects the performance of the sensor and machine learning helps in removing signals obtained from the contaminants to obtain a high sensitivity. In this review, we discuss different types of biosensors along with their applications and the benefits of machine learning. This is followed by a discussion on the challenges, missing gaps in the knowledge, and solutions in the field of electrochemical biosensors. This review aims to serve as a valuable resource for scientists and engineers entering the interdisciplinary field of electrochemical biosensors. Furthermore, this review provides insight into the type of electrochemical biosensors, their applications, the importance of machine learning (ML) in biosensing, and challenges and future outlook.

Electrochemical Sensors Coupled with Multivariate Statistical Analysis as Screening Tools for Wine Authentication Issues: A Review

Consumers are increasingly interested in the characteristics of the products they consume, including aroma, taste, and appearance, and hence, scientific research was conducted in order to develop electronic senses devices that mimic the human senses. Thanks to the utilization of electroanalytical techniques that used various sensors modified with different electroactive materials coupled with pattern recognition methods, artificial senses such as electronic tongues (ETs) are widely applied in food analysis for quality and authenticity approaches. This paper summarizes the applications of electrochemical sensors (voltammetric, amperometric, and potentiometric) coupled with unsupervised and supervised pattern recognition methods (principal components analysis (PCA), linear discriminant analysis (LDA), partial least square (PLS) regression, artificial neural network (ANN)) for wine authenticity assessments including the discrimination of varietal and geographical origins, monitoring the ageing processes, vintage year discrimination, and detection of frauds and adulterations. Different wine electrochemical authentication methodologies covering the electrochemical techniques, electrodes types, functionalization sensitive materials and multivariate statistical analysis are emphasized and the main advantages and disadvantages of using the proposed methodologies for real applications were concluded.

Voltammetric Electronic Tongues in Food Analysis

A critical revision is made on recent applications of voltammetric electronic tongues in the field of food analysis. Relevant works are discussed dealing with the discrimination of food samples of different type, origin, age and quality and with the prediction of the concentration of key substances and significant indexes related to food quality.

Influence of gamma irradiation on linear and nonlinear optical properties of nanocrystalline manganese(III) chloride tetraphenylporphine thin films

90 nm thickness of MnTPPCl thin films were deposited by thermal evaporation technique on glass and quartz substrates under vacuum. The examined thin films were irradiated by ⁶⁰Co γ-rays with 150 kGy. XRD and FTIR techniques are used to comprehend the structure of MnTPPCl thin films. The results confirmed that the structure of pristine thin films is nanocrystallites dispersed in the amorphous matrix and the irradiated films have an amorphous structure. Refractive index, oscillator's parameters (dispersion energy, E_d, oscillator energy, E_o), the absorption coefficient, optical energy gap, and Urbach energy were estimated before and after exposure to γ-irradiation by using spectrophotometric measurements. All mentioned parameters were influenced by the γ-irradiation process. The type of electronic transition was classified as a direct allowed transition. The gamma irradiation process was caused an increase in the fundamental band gap energy from 2.48 to 2.52 eV (blue shift) which is good for solar cells window. Third-order nonlinear optical susceptibility χ⁽³⁾ and the nonlinear refractive index n₂ of MnTPPCl thin films were studied before and after γ-irradiation. An increase in χ⁽³⁾ and n₂ with γ-irradiation is observed, so it is recommended to be used as optical switching applications.

Optimization of rendering process of poultry by-products with batch cooker model monitored by electronic nose

The best available controlled technology for transforming the disposal of animal by-products and mortalities is rendering. Two aspects of rendering process are mentioned in this research; product quality and emissions. A model of batch cooker with temperature, pressure and agitator speed controllers was designed and developed in order to optimize the process and to investigate the effect of changes in rendering conditions on quality of poultry by-product meal and also on pollutant emissions. An electronic nose system was designed and built based on metal oxide semiconductor sensors to monitor the gases emitted from batch cooker model. Also, GC-MS was used to identify the emitted components. In order to optimize the rendering process, response surface methodology was performed on temperature, cooking time and agitator speed variables. Results showed that the temperature of 140 °C (internal pressure equivalent to about 3.2 bar), the cooking time of 45 min and the agitator speed of 20 rpm optimized the process of batch cooking to maximize the percentage of protein and minimize the percentage of fat, moisture content, energy consumption and emission of pollutants. By GC-MS analysis, about 100 compounds include hydrocarbons, volatile fatty acids, sulfur-containing compounds, alcohols, ketones, aldehydes, and furans were observed in the emission of a batch cooker model. The major groups were organic acids and amides. Principle component analysis showed the most suitable sensors for detecting unpleasant odors from rendering plants.

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.

Electronic Tongue-A Tool for All Tastes?

Electronic tongue systems are traditionally used to analyse: food products, water samples and taste masking technologies for pharmaceuticals. In principle, their applications are almost limitless, as they are able to almost completely reduce the impact of interferents and can be applied to distinguish samples of extreme complexity as for example broths from different stages of fermentation. Nevertheless, their applications outside the three principal sample types are, in comparison, rather scarce. In this review, we would like to take a closer look on what are real capabilities of electronic tongue systems, what can be achieved using mixed sensor arrays and by introduction of biosensors or molecularly imprinted polymers in the matrix. We will discuss future directions both in the sense of applications as well as system development in the ever-growing trend of low cost analysis.

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.

Array of biosensors for discrimination of grapes according to grape variety, vintage and ripeness

A bioelectronic tongue based on nanostructured biosensors specific for the simultaneous detection of sugars and phenols has been developed. The array combined oxidases and dehydrogenases immobilized on a lipidic layer prepared using the Langmuir-Blodgett technique where Glucose oxidase, d-Fructose dehydrogenase, Tyrosinase or Laccase were imbibed. A phthalocyanine was co-immobilized in the sensing layer and used as electron mediator. The array thus formed has been used to analyze grapes and provides global information about the samples while providing specific information about their phenolic and their sugar content. Using Principal Component Analysis (PCA) the array of voltammetric biosensors has been successfully used to discriminate musts prepared from different varieties of grapes (Tempranillo, Garnacha, Cabernet-Sauvignon, Prieto Picudo and Mencía). Differences could be also detected between grapes of the same variety and cultivar harvested in two successive vintages (2012 and 2013). Moreover, the ripening of grapes could be monitored from veraison to maturity due to the changes in their phenolic and sugar content. Using Partial Least Squares (PLS-1) analysis, excellent correlations have been found between the responses provided by the array of biosensors and classical parameters directly related to phenols (total polyphenol index, TPI) and sugar concentration (degree Brix) measured by chemical methods with correlation coefficients close to 1 and errors close to 0. It is also worthy to notice the good correlations found with parameters associated with the pH and acidity that can be explained by taking into account the influence of the pH in the oxidation potentials of the phenols and in the enzymatic activity. This bioelectronic tongue can assess simultaneously the sugar and the phenolic content of grapes and could be used to monitor the maturity of the fruit and could be adapted easily to field analysis.

Biosensors and their applications - A review

The various types of biosensors such as enzyme-based, tissue-based, immunosensors, DNA biosensors, thermal and piezoelectric biosensors have been deliberated here to highlight their indispensable applications in multitudinous fields. Some of the popular fields implementing the use of biosensors are food industry to keep a check on its quality and safety, to help distinguish between the natural and artificial; in the fermentation industry and in the saccharification process to detect precise glucose concentrations; in metabolic engineering to enable in vivo monitoring of cellular metabolism. Biosensors and their role in medical science including early stage detection of human interleukin-10 causing heart diseases, rapid detection of human papilloma virus, etc. are important aspects. Fluorescent biosensors play a vital role in drug discovery and in cancer. Biosensor applications are prevalent in the plant biology sector to find out the missing links required in metabolic processes. Other applications are involved in defence, clinical sector, and for marine applications.

Integrated, paper-based potentiometric electronic tongue for the analysis of beer and wine

The following manuscript details the stages of construction of a novel paper-based electronic tongue with an integrated Ag/AgCl reference, which can operate using a minimal amount of sample (40 μL). First, we optimized the fabrication procedure of silver electrodes, testing a set of different methodologies (electroless plating, use of silver nanoparticles and commercial silver paints). Later a novel, integrated electronic tongue system was assembled with the use of readily available materials such as paper, wax, lamination sheets, bleach etc. New system was thoroughly characterized and the ion-selective potentiometric sensors presented performance close to theoretical. An electronic tongue, composed of electrodes sensitive to sodium, calcium, ammonia and a cross-sensitive, anion-selective electrode was used to analyze 34 beer samples (12 types, 19 brands). This system was able to discriminate beers from different brands, and types, indicate presence of stabilizers and antioxidants, dyes or even unmalted cereals and carbohydrates added to the fermentation wort. Samples could be classified by type of fermentation (low, high) and system was able to predict pH and in part also alcohol content of tested beers. In the next step sample volume was minimalized by the use of paper sample pads and measurement in flow conditions. In order to test the impact of this advancement a four electrode system, with cross-sensitive (anion-selective, cation-selective, Ca(2+)/Mg(2+), K(+)/Na(+)) electrodes was applied for the analysis of 11 types of wine (4 types of grapes, red/white, 3 countries). Proposed matrix was able to group wines produced from different varieties of grapes (Chardonnay, Americanas, Malbec, Merlot) using only 40 μL of sample. Apart from that, storage stability studies were performed using a multimeter, therefore showing that not only fabrication but also detection can be accomplished by means of off-the-shelf components. This manuscript not only describes new paper-based, potentiometric sensors but also according to our knowledge is the first description of an electrochemical paper-based electronic tongue with integrated reference.

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.

New trends in beer flavour compound analysis

As the beer market is steadily expanding, it is important for the brewing industry to offer consumers a product with the best organoleptic characteristics, flavour being one of the key characteristics of beer. New trends in instrumental methods of beer flavour analysis are described. In addition to successfully applied methods in beer analysis such as chromatography, spectroscopy, nuclear magnetic resonance, mass spectrometry or electronic nose and tongue techniques, among others, sample extraction and preparation such as derivatization or microextraction methods are also reviewed.

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.

Bioelectronic tongue based on lipidic nanostructured layers containing phenol oxidases and lutetium bisphthalocyanine for the analysis of grapes

In this work, a multisensor system formed by nanostructured voltammetric biosensors based on phenol oxidases (tyrosinase and laccase) has been developed. The enzymes have been incorporated into a biomimetic environment provided by a Langmuir-Blodgett (LB) film of arachidic acid (AA). Lutetium bisphthalocyanine (LuPc2) has also been introduced in the films to act as electron mediator. The incorporation of the enzymes to the floating layers to form Tyr/AA/LuPc2 and Lac/AA/LuPc2 films has been confirmed by the expansion in the surface pressure isotherms and by the AFM images. The voltammetric response towards six phenolic compounds demonstrates the enhanced performance of the biosensors that resulted from a preserved activity of the tyrosinase and laccase combined with the electron transfer activity of LuPc2. Biosensors show improved detection limits in the range of 10(-7)-10(-8) mol L(-1). An array formed by three sensors AA/LuPc2, Tyr/AA/LuPc2 and Lac/AA/LuPc2 has been employed to discriminate phenolic antioxidants of interest in the food industry. The Principal Component Analysis scores plot has demonstrated that the multisensor system is able to discriminate phenols according to the number of phenolic groups attached to the structure. The system has also been able to discriminate grapes of different varieties according to their phenolic content. This good performance is due to the combination of four factors: the high functionality of the enzyme obtained using a biomimetic immobilization, the signal enhancement caused by the LuPc2 mediator, the improvement in the selectivity induced by the enzymes and the complementary activity of the enzymatic sensors demonstrated in the loading plots.