Red Wine Samples Research Articles

Smartphone-based dual-mode aptasensor with bifunctional metal-organic frameworks as signal probes for ochratoxin A detection

Ochratoxin A (OTA) poses significant risks to human health, being potentially nephrotoxic, carcinogenic, genotoxic, and immuno-toxic. In this work, we developed a dual-mode aptasensor for OTA analysis, integrating colorimetric, electrochemical, and smartphone-based detection. The bifunctional Fe-MIL-88 metal-organic framework, acting as both a nanozyme capable of catalyzing the 3,3′,5,5′-tetramethylbenzidine substrate and an electrochemical signal amplifier, enabled OTA quantification through current response or changes in color and absorbance intensity. Besides, the spatial confinement effect enhances the local concentration of Fe-MIL-88 signal probes through rolling circle amplification reaction, thereby contributing to a substantial enhancement in sensitivity. The proposed technique is simple, disposable, highly sensitive and selective, enabling OTA detection in the range of 1 fg/mL to 250 ng/mL, with a limit of detection of 0.22 fg/mL (3σ rule). Furthermore, we successfully detected OTA in corn, wheat, and red wine samples, with results good concordance with those obtained using commercial enzyme-linked immunoassay kits.

A novel dialdehyde cellulose-based colorimetric and turn-on fluorescent probe for H2S detection and its application in red wine

Hydrogen sulfide (H2S) is considered one of the most important gaseous transmitters in the metabolic system, and the abnormal concentration of H2S is associated with a variety of diseases. Up to now, it is still a challenge to develop a portable assay for H2S even though the research about the detection of H2S is booming. Herein, a novel bifunctional dialdehyde-cellulose fluorescent probe DAC-DPD was prepared with high selectivity and sensitivity to H2S with colorimetric and fluorescent “turn-on” characteristics, and the limit of detection (LOD) of DAC-DPD for H2S was 0.831 μM. The sensing mechanism of DAC-DPD's to H2S was a Michael addition reaction confirmed by HRMS, 1H NMR and density-functional theory (DFT) calculations. DAC-DPD can be used to detect H2S in red wine samples. In Addition, the prepared DAC-DPD embedded fluorescent membrane can be used as a reliable sensing platform for rapid detection of H2S. It provided a convenient and rapid detection material, simplifying the detection process of H2S, which is of great significance for the development of cellulose-based fluorescent smart material.

A 1,3,4-thiadiazole based turn-on probe with large Stoke’s shift and ESIPT effect for fluorescent detection of H2S and its applications

Based on a useful 1,3,4-thiadiazole scaffold in our lab, a turn-on fluorescent probe for sensing H2S in environment, biological imaging and food analysis was rationally designed and synthesized. In this probe, 1,3,4-thiadiazole unit was used as fluorophore with ESIPT effect and 2,4-dinitrophenyl moiety was used as recognition fragment and fluorescent bursting agent to inhibt ESIPT. Thus, a PET process was formed and an “off–on” procedure arose after added target analyte. These brought the probe could specifically detect H2S without being interfered by other biological thiols. It showed high sensitivity (LOD=60.8 nM), large Stoke’s shift (133 nm) and had a stable performance over pH range of 6.0–9.0 in H2S monitoring system. More importantly, probe could be used for detection of H2S in real water, three beer samples and red wine sample. Furthermore, probe was successfully utilized for visualizing H2S in HeLa cells and applied for real-time monitoring of H2S during food spoilage by “naked eye” and smartphone colorimetric analysis.

A ‘‘Turn-on’’ Al(III)-Mediated Fluorescent Micro-Probe for Quercetin Sensing

Quercetin (Qr) is a common flavonoid widely found in plants with promising pharmacological activities. It is thus worthwhile to design a convenient method for its detection. In this work, a specific Al3+-regulated poly(cyclotriphosphazene-co-curcumin) (PC-Al) micro-probe was designed for real-time detection of Qr, therein significant “turn-on” fluorescence was observed after addition of Qr to PC-Al. Under optimal conditions, the probe has a detection limit of 23.2 nM for Qr sensing with good linearity in the range of 0–5 × 10−5 M. Moreover, real-time applications of the PC-Al probe in red wine, orange juice, and honey samples were validated. Furthermore, assisted by a consumer smartphone sensing platform, the sensor shows an excellent linear response between the red/blue ratio (R/B) of the two color channels in the picture and the concentration of Qr in the range of 1–120 μM, achieving quantitative detection of Qr. The introduction of smartphone system to realize convenient detection of Qr demonstrates good application prospects of this Al3+-mediated fluorescence probe.

Multidimensional fluorescence spectroscopy of wine using synchronous excitation/emission matrices and time-resolved fluorescence interferometric detection

Wines are complex mixtures of chemical compounds with broad and overlapping absorption and emission spectral features in the UV and visible spectral regions, making them challenging to study with conventional optical spectroscopic techniques. Multidimensional fluorescence spectroscopies correlate fluorescence spectra with other degrees of freedom, and have proven useful for studying complex molecular systems, offering a pathway for the analysis of wines utilising their inherent fluorescence. Here we employ steady-state excitation-emission matrix (EEM) and time-resolved fluorescence spectral measurements to investigate representative commercial white and red wine samples and a fluorescent ‘model’ wine base. Combining these multidimensional measurement methods provides information on the emission characteristics of the components that wines contain. This investigation illustrates the potential for multidimensional fluorescence techniques as diagnostic tools for the wine industry.

Revealing the key antioxidant compounds and potential action mechanisms of Chinese Cabernet Sauvignon red wines by integrating UHPLC-QTOF-MS-based untargeted metabolomics, network pharmacology and molecular docking approaches

In recent years, red wine drinking has become more popular in China owing to its antioxidant effects. However, the key antioxidant compounds and their action mechanisms of Chinese red wines are still unclear. Herein, the antioxidant activities and chemical compositions of 45 Chinese Cabernet Sauvignon red wine samples were determined using chemical antioxidant assays and an UHPLC-QTOF-MS-based untargeted metabolomics method. The key antioxidant compounds in red wines and potential action mechanisms were revealed by integrating network pharmacology and molecular docking approaches. Results showed that there are 8 key antioxidant compounds in the red wine samples. These compounds are involved in several metabolic pathways in the body, particularly PI3K/AKT. What's more, they bind to the core antioxidant targets through hydrogen bonding and hydrophobic interaction. Among them, myricetin, laricitrin, 2,3,8-tri-O-methylellagic acid and AKT1 have the highest binding energies. This study could provide the theoretical basis for further investigation of physiological activities and functions of Chinese red wines.

Use of Non-Destructive Ultrasonic Techniques as Characterization Tools for Different Varieties of Wine.

In this work, we have verified how non-destructive ultrasonic evaluation allows for acoustically characterizing different varieties of wine. For this, a 3.5 MHz transducer has been used by means of an immersion technique in pulse-echo mode. The tests were performed at various temperatures in the range 14-18 °C. The evaluation has been carried out studying, on the one hand, conventional analysis parameters (velocity and attenuation) and, on the other, less conventional parameters (frequency components). The experimental study comprised two stages. In the first, the feasibility of the study was checked by inspecting twelve samples belonging to six varieties of red and white wine. The results showed clearly higher ultrasonic propagation velocity values in the red wine samples. In the second, nine samples of different monovarietal wine varieties (Grenache, Tempranillo and Cabernet Sauvignon) were analyzed. The results show how ultrasonic velocity makes it possible to unequivocally classify the grape variety used in winemaking with the Cabernet Sauvignon variety having the highest values and the Grenache the lowest. In addition, the wines of the Tempranillo variety are those that present higher values of the attenuation coefficient, and those from the Grenache variety transmit higher frequency waves.

Determination of the total phenolic content in Hardaliye by amperometric laccase-based biosensor and comparison of the LC-MS/MS

In this study, a laccase-based amperometric biosensor was fabricated for the quantitative analysis of total phenolic content in Hardaliye. The biosensor was constructed using a carbon paste electrode with simple modifications. The laccase obtained from Trametes versicolor was immobilized into a carbon paste electrode modified with a gelatin matrix. The immobilization parameters for biosensor fabrication, as well as its working conditions were optimized with gallic acid as the phenolic standard. Additionally, molecular docking simulation was used to examine the interaction between Trametes versicolor laccase and gallic acid. The biosensor's analytical parameters were determined under optimal conditions including linearity, repeatability, stability and selectivity. The linear range of gallic acid was calculated as 0.5–100 μM, with the detection limit of 0.1323 ± 0.1 μM. With good selectivity and stability, the biosensor successfully determined the total phenolic contents in Hardaliye, and red-wine samples. Comparison studies showed that the biosensor results agreed with those obtained from the Liquid Chromatography-Tandem Mass Spectrometry method. This work indicates that the proposed biosensor is a promising analytic tool for total phenolic analyses of beverages.

Hypersensitive quantification of major astringency markers in food and wine by substoichiometric quenching of silicon-rhodamine conjugates

Tannins are chemically diverse polyphenols in plant-derived products that not only show diverse biological activities but also play a crucial role in determining the sensory attributes of food and beverages. Therefore, their accurate and cost-effective quantification is essential.Here, we identified a novel fluorescence quenching mechanism of different synthetic rhodamine fluorophores, with a high selectivity towards tannic acid (TA) and catechin-3-gallate (C3G) compared to a structurally diverse panel of tannins and polyphenols. Specific chemical conjugates of silicon-rhodamine with alkyl linkers attached to bulky apolar moieties had a limit of detection near 500 pM and a linear range spanning 5–100 nM for TA. We validated the assay on 18 distinct red wine samples, which showed high linearity (R2 = 0.92) with methylcellulose precipitation with no interference from anthocyanins. In conclusion, a novel assay was developed and validated that allows the sensitive and selective quantification of major astringency markers abundant in food and beverages.

Chemical vapor deposition-grown single-layer graphene-supported nanostructured Co3O4 composite as binder-free electrode for asymmetric supercapacitor and electrochemical detection of caffeic acid

In this study, we developed a monolayer graphene/nanostructured cobalt oxide (MLG/Co3O4) composite for asymmetric supercapacitor and electrochemical sensor applications. The MLG was grown by chemical vapor deposition process and the Co3O4 nanostructures were electrodeposited on the MLG surface. Scanning electron microscopy proved that there were flower-like nanostructured Co3O4 densely electrodeposited on the MLG surface. At a current density of 3 mA cm−2, the MLG/Co3O4 composite produced an areal capacitance of 3.73 F cm−2. After 10,000 cycles, the composite electrode still had 93.6 % of its initial capacitance at 5 mA cm−2. The asymmetric system displayed an areal capacitance of 929 mF cm−2 at 4 mA cm−2 with good cycle stability. The asymmetric electrode produced a specific energy of 51 μWh cm−2 and a specific power of 11.1 mW cm−2. Cyclic voltammetric measurements demonstrated that the composite showed redox peaks at 0.48 eV and 0.09 eV toward the determination of CA. With a sensitivity of 0.13 µA/µM/cm2 and a limit of detection of 0.009 µM, the composite showed CA concentrations, ranging from 0.5 to 480 M. The composite displayed excellent selectivity and the current produced for the interfering compounds was exceedingly low. Using the composite electrode, the spiked CA in red wine and green tea samples recovered remarkably effectively.

Simultaneous determination of six catechins and caffeine in tea and wine using salting-out assisted liquid-liquid extraction and high-performance liquid chromatography with ultraviolet detection.

Catechins, renowned for their antioxidant properties and health benefits, are commonly present in beverages, particularly tea and wine. An efficient and cost-effective salting-out assisted liquid-liquid extraction (SALLE) method has been developed and validated for the simultaneous determination of six catechins and caffeine in tea and wine samples using high-performance liquid chromatography-ultraviolet (HPLC-UV). This method demonstrates outstanding performance: linearity (1-120µg/mL, r2>0.999), accuracy (96.5%-103.4% recovery), and precision (≤14.7% relative standard deviation), meeting validation requirements set by the US Food and Drug Administration. The reduced sample size (0.1g) minimizes matrix interferences and costs without compromising sensitivity. All analytes were detected in Camellia sinensis teas, with green tea displaying the highest total catechin content (47.5-100.1mg/mL), followed by white and black teas. Analysis of wine samples reveals the presence of catechin in all red and white wines, and epigallocatechin gallate in all red wine samples, highlighting the impact of winemaking processes on catechin content. The SALLE-HPLC-UV approach represents a green alternative by eliminating organic waste, surpassing conventional dilution methods in specificity and sensitivity for catechin determination. AGREEprep assessment emphasizes the strengths of the SALLE procedure, including material reusability, throughput efficiency, minimal sample requirements, low energy consumption, and the absence of organic waste generation.

RED WINE QUALITY PREDICTION USING MACHINE LEARNING

Wine quality assessment is a critical task in the beverage industry, as it directly impacts consumer satisfaction and market competitiveness. Among various types of wine, red wine stands out for its complexity in flavor, aroma, and texture, making its quality prediction a challenging yet crucial endeavor. This project aims to develop a machine learning model for predicting the quality of red wine based on its physicochemical properties. The dataset utilized for this project consists of various attributes such as acidity, pH, alcohol content, and volatile acidity, among others, collected from red wine samples. These attributes serve as input features for the machine learning model, while the quality of wine, typically rated on a scale, serves as the target variable. The proposed approach involves several stages: data preprocessing, feature selection, model selection, and evaluation. During data preprocessing, techniques like normalization and handling missing values are employed to ensure data quality. Feature selection techniques such as correlation analysis and feature importance are utilized to identify the most relevant attributes for predicting wine quality. Several machine learning algorithms, including but not limited to, linear regression, decision trees, random forests, and support vector machines, are trained and evaluated to determine the most suitable model for the task. Performance metrics such as mean squared error, accuracy, and F1 score are utilized to assess the model's predictive capability. Key Words: Wine quality, market, aroma, texture, physicochemical, alcohol, acidity.

Red Wine Quality Prediction using Machine Learning

The objective of this study aimed to create a model to forecast the quality of red wine by examining its physicochemical attributes. Various factors affect the precision of quality prediction in red wine analysis. This paper presents a computational intelligence approach employing machine learning methods. Specifically, the Random Forest Classifier, Naive Bayes Algorithm, and Support Vector Machine were applied. Using these machine learning techniques and the provided information, it becomes possible to predict the quality of a given red wine sample.

A novel headspace solid-phase microextraction arrow method employing comprehensive two-dimensional gas chromatography–mass spectrometry combined with chemometric tools for the investigation of wine aging

BackgroundOmics is used as an analytical tool to investigate wine authenticity issues. Aging authentication ensures that the wine has undergone the necessary maturation and developed its desired organoleptic characteristics. Considering that aged wines constitute valuable commodities, the development of advanced omics techniques that guarantee aging authenticity and prevent fraud is essential. ResultsΑ solid phase microextraction Arrow method combined with comprehensive two-dimensional gas chromatography-mass spectrometry was developed to identify volatiles in red wines and investigate how aging affects their volatile fingerprint. The method was optimized by examining the critical parameters that affect the solid phase microextraction Arrow extraction (stirring rate, extraction time) process. Under optimized conditions, extraction took place within 45 min under stirring at 1000 rpm. In all, 24 monovarietal red wine samples belonging to the Xinomavro variety from Naoussa (Imathia regional unit of Macedonia, Greece) produced during four different vintage years (1998, 2005, 2008 and 2015) were analyzed. Overall, 237 volatile compounds were tentatively identified and were treated with chemometric tools. Four major groups, one for each vintage year were revealed using the Hierarchical Clustering Analysis. The first two Principal Components of Principal Component Analysis explained 86.1% of the total variance, showing appropriate grouping of the wine samples produced in the same crop year. A two-way orthogonal partial least square – discriminant analysis model was developed and successfully classified all the samples to the proper class according to the vintage age, establishing 17 volatile markers as the most important features responsible for the classification, with an explained total variance of 88.5%. The developed prediction model was validated and the analyzed samples were classified with 100% accuracy according to the vintage age, based on their volatile fingerprint. SignificanceThe developed methodology in combination with chemometric techniques allows to trace back and confirm the vintage year, and is proposed as a novel authenticity tool which opens completely new and hitherto unexplored possibilities for wine authenticity testing and confirmation.

A microfluidic sensor for continuously measuring membrane potential changes in interactions between taste substances and lipid polymer membranes

To evaluate the taste changes experienced by humans over time, we developed a microfluidic sensor for continuously measuring membrane potential changes in interactions between taste substances and lipid polymer membranes. The performance of the proposed sensing device was evaluated by determining the dependence on concentration using tannic acid (astringency substance) solutions and measuring the selectivity using other taste quality samples. Furthermore, to demonstrate the practicality of the sensor, we measured three samples of red wine. The fabricated microfluidic sensor could measure changes in membrane potential over time and was shown to have high selectivity comparable to that of the commercialized sensor. In addition, measurements were performed on a real sample of red wine, and the membrane potential response over time was measured for several different wines. Thus, it was shown that a new sensor could be realized for objectively quantifying changes in taste perceived by humans over time.

From vineyard to table: Uncovering wine quality for sales management through machine learning

The literature currently offers limited guidance for retailers on how to use analytics to decipher the relationship between product attributes and quality ratings. Addressing this gap, our study introduces an advanced ensemble learning approach to develop a nuanced framework for assessing product quality. We validated the effectiveness of our framework with a dataset comprising 1,599 red wine samples from Portugal’s Minho region. Our findings show that this model surpasses previous ones in accurately predicting product quality, presenting retailers with a sophisticated tool to transform product data into actionable insights for sales management. Furthermore, our approach yields significant benefits for researchers by identifying latent attributes in extensive data collections, which can inform a deeper understanding of consumer preferences and guide the strategic planning of marketing promotions.

A ferrocene-based probe for colourimetric/electrochemical detection of bisulfite ions and its practical application

A simple ferrocene-based organic probe (AK5) is described for selective and sensitive colourimetric/electrochemical detection of HSO3- ions in a 95 % aqueous solution. Upon adding HSO3− ions, the colour of the solution changes from brown to colourless instantaneously. The plausible mechanism of detection of HSO3− ions by AK5 was illustrated by 1H NMR, 13C NMR, HR-MS and DFT/TD-DFT analysis, which revealed nucleophilic addition of HSO3− ion to olefinic C-atom. The limits of detection (LOD) are determined to be 5.58 and 0.12 µM in colourimetric and electrochemical methods, respectively. The probe is successfully applied to estimate the levels of HSO3− ions in natural water and red wine samples.

Nitrogen- and Sulfur-Codoped Strong Green Fluorescent Carbon Dots for the Highly Specific Quantification of Quercetin in Food Samples.

Carbon dots (CDs) doped with heteroatoms have garnered significant interest due to their chemically modifiable luminescence properties. Herein, nitrogen- and sulfur-codoped carbon dots (NS-CDs) were successfully prepared using p-phenylenediamine and thioacetamide via a facile process. The as-developed NS-CDs had high photostability against photobleaching, good water dispersibility, and excitation-independent spectral emission properties due to the abundant amino and sulfur functional groups on their surface. The wine-red-colored NS-CDs exhibited strong green emission with a large Stokes shift of up to 125 nm upon the excitation wavelength of 375 nm, with a high quantum yield (QY) of 28%. The novel NS-CDs revealed excellent sensitivity for quercetin (QT) detection via the fluorescence quenching effect, with a low detection limit of 17.3 nM within the linear range of 0-29.7 μM. The fluorescence was quenched only when QT was brought near the NS-CDs. This QT-induced quenching occurred through the strong inner filter effect (IFE) and the complex bound state formed between the ground-state QT and excited-state NS-CDs. The quenching-based detection strategies also demonstrated good specificity for QT over various interferents (phenols, biomolecules, amino acids, metal ions, and flavonoids). Moreover, this approach could be effectively applied to the quantitative detection of QT (with good sensing recovery) in real food samples such as red wine and onion samples. The present work, consequently, suggests that NS-CDs may open the door to the sensitive and specific detection of QT in food samples in a cost-effective and straightforward manner.

Synergistic enhancement of potassium permanganate-induced chemiluminescence by nitrogen and silver carbon dots and formaldehyde for selective detection of tannin

In this study, nitrogen and silver doped carbon dots (NAg-CDs) were synthesized via a simple and environmentally friendly hydrothermal one-pot method and were utilized in combination with formaldehyde to enhance potassium permanganate-induced chemiluminescence (CL). Remarkably, a chemiluminescent enhancement of approximately 448-fold was observed in the NAg-CDs-KMnO4-HCHO system than in the KMnO4-HCHO system. The enhanced CL intensity of the NAg-CDs-KMnO4-HCHO system can be significantly quenched by tannin. On this basis, we developed a simple, rapid, sensitive, and selective flow injection CL method for the detection of tannin, featuring a linear range of 0.4–10.0 μM and a detection limit of 43.0 nM. Furthermore, we effectively applied this method to the detection of tannin in red wine and tea samples, and the standard recoveries were 98.6 %104.9 %.

Nonchromatographic analysis of polyphenols in red wine samples: Evaluation of front-face fluorescence spectroscopy and third-order multivariate calibration to quantify catechin and epicatechin

In this work, an analytical approach based on third-order multivariate calibration and front-face fluorescence spectroscopy to determine the levels of (+)-catechin and (-)-epicatechin in wine samples was evaluated. An extra reaction mode (pH gradient) was incorporated into excitation-emission fluorescence second-order data, leading to higher predictivity and selectivity for catechin detection. Application of a Multivariate curve resolution-alternating least squares (MCR-ALS) algorithm resolved the systems, even in the presence of uncalibrated interferences, and yielded suitable figures of merit. Through the method, the level of (+)-catechin was directly determined, and the concentration of (-)-epicatechin was determined by the difference in total catechins (Epi + Cat) between synthetic samples. Finally, the levels of catechin were satisfactorily determined in real wine samples at mg L-1 levels with minimal sample treatment and in accordance with a reference method based on chromatographic separation.