Analysis of the influence of the type of closure in the organoleptic characteristics of a red wine by using an electronic panel

Electronic Noses: From Gas-Sensitive Components and Practical Applications to Data Processing

Artificial olfaction, also known as an electronic nose, is a gas identification device that replicates the human olfactory organ. This system integrates sensor arrays to detect gases, data acquisition for signal processing, and data analysis for precise identification, enabling it to assess gases both qualitatively and quantitatively in complex settings. This article provides a brief overview of the research progress in electronic nose technology, which is divided into three main elements, focusing on gas-sensitive materials, electronic nose applications, and data analysis methods. Furthermore, the review explores both traditional MOS materials and the newer porous materials like MOFs for gas sensors, summarizing the applications of electronic noses across diverse fields including disease diagnosis, environmental monitoring, food safety, and agricultural production. Additionally, it covers electronic nose pattern recognition and signal drift suppression algorithms. Ultimately, the summary identifies challenges faced by current systems and offers innovative solutions for future advancements. Overall, this endeavor forges a solid foundation and establishes a conceptual framework for ongoing research in the field.

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.

Effect of Different Packaging Strategies on the Secondary Shelf Life of Young and Structured Red Wine

When bottled wine is opened, a completely different scenario occurs that can accelerate the oxidation of the product. This is called the secondary shelf life (SSL), which is generally shorter and less predictable than the primary shelf life (PSL). In this context, the research aim was to evaluate the changes that occur in two types of red wine during two tests to evaluate the secondary shelf life as a function of the packaging systems. The variation of Total SO₂ and Free SO₂ and the other chemical parameters (polyphenols, anthocyanins, proanthocyanidins, color, and volatile acidity) were used to assess the oxidation rate of the packaging samples after opening during the SSL. In both tests and for the two types of stored red wine, the polymeric cap showed the best results. The other types of closure (screw cap, natural cork, crow cap, and Tetra Brik) showed a negative trend and a reduced SSL for both red wines. Finally, the sensory results confirmed that with the polymeric cap, the SSL increases considerably compared to other capping systems. These results may be due to the technical characteristics of polymeric materials, which tend to vary slightly in shape after repeated usage.

Application progress of intelligent flavor sensing system in the production process of fermented foods based on the flavor properties

Fermented foods are sensitive to the production conditions because of microbial and enzymatic activities, which requires intelligent flavor sensing system (IFSS) to monitor and optimize the production process based on the flavor properties. As the simulation system of human olfaction and gustation, IFSS has been widely used in the field of food with the characteristics of nondestructive, pollution-free, and real-time detection. This paper reviews the application of IFSS in the control of fermentation, ripening, and shelf life, and the potential in the identification of quality differences and flavor-producing microbes in fermented foods. The survey found that electronic nose (tongue) is suitable to monitor fermentation process and identify food authenticity in real time based on the changes of flavor profile. Gas chromatography-ion mobility spectrometry and nuclear magnetic resonance technology can be used to analyze the flavor metabolism of fermented foods at various production stages and explore the correlation between flavor substances and microorganisms.

The Past and the Future of Langmuir and Langmuir-Blodgett Films

The Langmuir-Blodgett (LB) technique, through which monolayers are transferred from the air/water interface onto a solid substrate, was the first method to allow for the controlled assembly of organic molecules. With its almost 100 year history, it has been the inspiration for most methods to functionalize surfaces and produce nanocoatings, in addition to serving to explore concepts in molecular electronics and nanoarchitectonics. This paper provides an overview of the history of Langmuir monolayers and LB films, including the potential use in devices and a discussion on why LB films are seldom considered for practical applications today. Emphasis is then given to two areas where these films offer unique opportunities, namely, in mimicking cell membrane models and exploiting nanoarchitectonics concepts to produce sensors, investigate molecular recognitions, and assemble molecular machines. The most promising topics for the short- and long-term prospects of the LB technique are also highlighted.

Toward the Development of Combined Artificial Sensing Systems for Food Quality Evaluation: A Review on the Application of Data Fusion of Electronic Noses, Electronic Tongues and Electronic Eyes

Devices known as electronic noses (ENs), electronic tongues (ETs), and electronic eyes (EEs) have been developed in recent years in the in situ study of real matrices with little or no manipulation of the sample at all. The final goal could be the evaluation of overall quality parameters such as sensory features, indicated by the "smell", "taste", and "color" of the sample under investigation or in the quantitative detection of analytes. The output of these sensing systems can be analyzed using multivariate data analysis strategies to relate specific patterns in the signals with the required information. In addition, using suitable data-fusion techniques, the combination of data collected from ETs, ENs, and EEs can provide more accurate information about the sample than any of the individual sensing devices. This review's purpose is to collect recent advances in the development of combined ET, EN, and EE systems for assessing food quality, paying particular attention to the different data-fusion strategies applied.

Application of untargeted volatile profiling and data driven approaches in wine flavoromics research

Traditional flavor chemistry research usually makes use of targeted approaches by focusing on the detection and quantification of key flavor active metabolites that are present in food and beverages. In the last decade, flavoromics has emerged as an alternative to targeted methods where non-targeted and data driven approaches have been used to determine as many metabolites as possible with the aim to establish relationships among the chemical composition of foods and their sensory properties. Flavoromics has been successfully applied in wine research to gain more insights into the impact of a wide range of flavor active metabolites on wine quality. In this review, we aim to provide an overview of the applications of flavoromics approaches in wine research based on existing literature mainly by focusing on untargeted volatile profiling of wines and how this can be used as a powerful tool to generate novel insights. We highlight the fact that untargeted volatile profiling used in flavoromics approaches ultimately can assist the wine industry to produce different wine styles and to market existing wines appropriately based on consumer preference. In addition to summarizing the main steps involved in untargeted volatile profiling, we also provide an outlook about future perspectives and challenges of wine flavoromics research.

Assessment of Smoke Contamination in Grapevine Berries and Taint in Wines Due to Bushfires Using a Low-Cost E-Nose and an Artificial Intelligence Approach

Bushfires are increasing in number and intensity due to climate change. A newly developed low-cost electronic nose (e-nose) was tested on wines made from grapevines exposed to smoke in field trials. E-nose readings were obtained from wines from five experimental treatments: (i) low-density smoke exposure (LS), (ii) high-density smoke exposure (HS), (iii) high-density smoke exposure with in-canopy misting (HSM), and two controls: (iv) control (C; no smoke treatment) and (v) control with in-canopy misting (CM; no smoke treatment). These e-nose readings were used as inputs for machine learning algorithms to obtain a classification model, with treatments as targets and seven neurons, with 97% accuracy in the classification of 300 samples into treatments as targets (Model 1). Models 2 to 4 used 10 neurons, with 20 glycoconjugates and 10 volatile phenols as targets, measured: in berries one hour after smoke (Model 2; R = 0.98; R² = 0.95; b = 0.97); in berries at harvest (Model 3; R = 0.99; R² = 0.97; b = 0.96); in wines (Model 4; R = 0.99; R² = 0.98; b = 0.98). Model 5 was based on the intensity of 12 wine descriptors determined via a consumer sensory test (Model 5; R = 0.98; R² = 0.96; b = 0.97). These models could be used by winemakers to assess near real-time smoke contamination levels and to implement amelioration strategies to minimize smoke taint in wines following bushfires.

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.

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

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

Nutritional constituents, phytochemical profiles, in vitro antioxidant and antimicrobial properties, and gas chromatography-mass spectrometry analysis of various solvent extracts from grape seeds (Vitis vinifera L.)

The present study revealed that the nutritive value of grape seeds (Vitis vinifera L.) was 383.55±0.13 Kcal/100 g, with magnesium as the most abundant mineral element (70.44±0.88 mg/L). The maximum phenolic (392.58±1.70mg of GAE/g), flavonoid (256.16±1.60 mg of QE/g), and tannin (30.95±0.17mg of CE/g) contents were also found in the ethanol, dichloromethane, and hexane extracts, respectively. The major phytochemical compounds in the ethyl acetate extract were identified via gas chromatography-mass spectrometry (GC-MS) analysis. The ethanol extract has the highest antioxidant activity (IC50=140±1.20 μg/mL for DPPH, 145.28±0.45mg α-tocopherol/g for total antioxidant capacity, and EC50=80±1.41 μg/mL for ferric-reducing power assays). For β-carotene test, the highest antioxidant activity was obtained in the hexane extract. A satisfactory antimicrobial activity was found against a panel of microorganisms with the ethyl acetate extract as the best antimicrobial agent. Additionally, it was found that the bactericidal concentration required for the grape seed extract to kill Listeria monocytogenes should be less than 12.50 mg/mL (minimum inhibitory concentration=4).

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.

Electronic Noses and Tongues in Wine Industry

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

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

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

A Novel Method for the Discrimination of Semen Arecae and Its Processed Products by Using Computer Vision, Electronic Nose, and Electronic Tongue

Areca nut, commonly known locally as Semen Arecae (SA) in China, has been used as an important Chinese herbal medicine for thousands of years. The raw SA (RAW) is commonly processed by stir-baking to yellow (SBY), stir-baking to dark brown (SBD), and stir-baking to carbon dark (SBC) for different clinical uses. In our present investigation, intelligent sensory technologies consisting of computer vision (CV), electronic nose (E-nose), and electronic tongue (E-tongue) were employed in order to develop a novel and accurate method for discrimination of SA and its processed products. Firstly, the color parameters and electronic sensory responses of E-nose and E-tongue of the samples were determined, respectively. Then, indicative components including 5-hydroxymethyl furfural (5-HMF) and arecoline (ARE) were determined by HPLC. Finally, principal component analysis (PCA) and discriminant factor analysis (DFA) were performed. The results demonstrated that these three instruments can effectively discriminate SA and its processed products. 5-HMF and ARE can reflect the stir-baking degree of SA. Interestingly, the two components showed close correlations to the color parameters and sensory responses of E-nose and E-tongue. In conclusion, this novel method based on CV, E-nose, and E-tongue can be successfully used to discriminate SA and its processed products.

Data fusion methodologies for food and beverage authentication and quality assessment - a review

The ever increasing interest of consumers for safety, authenticity and quality of food commodities has driven the attention towards the analytical techniques used for analyzing these commodities. In recent years, rapid and reliable sensor, spectroscopic and chromatographic techniques have emerged that, together with multivariate and multiway chemometrics, have improved the whole control process by reducing the time of analysis and providing more informative results. In this progression of more and better information, the combination (fusion) of outputs of different instrumental techniques has emerged as a means for increasing the reliability of classification or prediction of foodstuff specifications as compared to using a single analytical technique. Although promising results have been obtained in food and beverage authentication and quality assessment, the combination of data from several techniques is not straightforward and represents an important challenge for chemometricians. This review provides a general overview of data fusion strategies that have been used in the field of food and beverage authentication and quality assessment.

Evaluation of oxygen exposure levels and polyphenolic content of red wines using an electronic panel formed by an electronic nose and an electronic tongue

An electronic panel formed by an electronic nose and an electronic tongue has been used to analyse red wines showing high and low phenolic contents, obtained by flash release and traditional soaking, respectively, and processed with or without micro-oxygenation. Four oxygen transfer rate conditions (0.8, 1.9, 8.0, and 11.9 μl oxygen/bottle/day) were ensured by using synthetic closures with controlled oxygen permeability and storage under controlled atmosphere. Twenty-five chemical parameters associated with the polyphenolic composition, the colour indices and the levels of oxygen were measured in triplicate and correlated with the signals registered (seven replicas) by means of the electronic nose and the electronic tongue using partial least squares regression analysis. The electronic nose and the electronic tongue showed particularly good correlations with those parameters associated with the oxygen levels and, in particular, with the influence of the porosity of the closure to oxygen exposure. In turn, the electronic tongue was particularly sensitive to redox species including oxygen and phenolic compounds. It has been demonstrated that a combined system formed from the electronic nose and the electronic tongue provides information about the chemical composition of both the gas and the liquid phase of red wines. This complementary information improves the capacity to predict values of oxygen-related parameters, phenolic content and colour parameters.