Classification of red wines using suitable markers coupled with multivariate statistic analysis

Comparative study on the use of seasoned or unseasoned casks made of wood from different origins for the ageing of Sherry vinegar

BACKGROUND

In the present study, the ageing process of Sherry vinegar in used (seasoned) or new casks made of chestnut, American oak, Spanish oak or French oak wood has been investigated, considering that no research has investigated whether this seasoning has a definite influence on the final composition of the aged beverage. The polyphenolic and volatile contents of the aged vinegars were determined and their sensory properties were evaluated. Different statistical tools were applied to the data collected.

RESULTS

With respect to polyphenolic contents, ageing time was the most influential factor, followed by the seasoned-cask factor. The type of wood was only significant for gallic acid, p-hydroxybenzoic acid, methylfurfural, ethyl gallate, ferulic acid, coniferyl aldehyde and sinapaldehyde. Principal component analysis according to polyphenols did not allow the samples to be differentiated, whereas cluster analysis revealed a slight grouping trend according to ageing time and seasoning of the wood. In relation to volatile compounds, variance analysis revealed that, again, ageing time and cask-seasoning were the most significant factors, with the samples clustering according to these two parameters. Following the sensory study, a clear difference between seasoned and new cask vinegars could be established as a result of the high scores in olfactory quality obtained for those vinegars aged in new casks. This was probably because of an excess of the descriptor 'ethyl acetate' exhibited by seasoned-cask Sherry vinegars.

CONCLUSION

The previous seasoning of the casks together with the ageing time conditioned the composition of the vinegars aged in casks of different botanical origin, which translated into differences at a sensory level. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

UHPLC-QTOF-MS-based untargeted metabolomic authentication of Chinese red wines according to their grape varieties

Wine is a very popular alcoholic drink owing to its health benefits of antioxidant effects. However, profits-driven frauds of wine especially false declarations of variety frequently occurred in markets. In this work, an UHPLC-QTOF-MS-based untargeted metabolomics method was developed for metabolite profiling of 119 bottles of Chinese red wines from four varieties (Cabernet Sauvignon, Merlot, Cabernet Gernischt, and Pinot Noir). The metabolites of red wines from different varieties were assessed using orthogonal partial least-squares discriminant analysis (OPLS-DA) and analyzed using KEGG metabolic pathway analysis. Results showed that the differential compounds among different varieties of red wines are mainly flavonoids, phenols, indoles and amino acids. The KEGG metabolic pathway analysis showed that indoles metabolism and flavonoids metabolism are closely related to wine varieties. Based on the differential compounds, OPLS-DA models could identify external validation wine samples with a total correct rate of 90.9 % in positive ionization mode and 100 % in negative ionization mode. This study indicated that the developed untargeted metabolomics method based on UHPLC-QTOF-MS is a potential tool to identify the varieties of Chinese red wines.

The Effect of Hokkaido Red Wines on Vascular Outcomes in Healthy Adult Men: A Pilot Study

Moderate red wine intake has been associated with lower cardiovascular mortality, due in part to the intake of polyphenols and anthocyanins, whose content can vary from varietal and year of harvest. This study assessed the vascular effects in response to a single intake of 2015 and 2018 Zweigelt red wines from Hokkaido, Japan. Healthy men were randomly assigned to consume 240 mL each of a red wine, or a sparkling white grape juice as a control in a randomized three-arm cross-over design with a 7 day washout between arms. The augmentation index (AI; a measure of arterial stiffness) and AI at 75 beats/min (AI75), reactive hyperemia index, systolic and diastolic blood pressure (SBP and DBP, respectively), and platelet reactivity were assessed at baseline and two and four hours after each beverage intake. Changes from the baseline were analyzed using a linear mixed model. Significant treatment effects (p = 0.02) were observed, with AI 13% lower after the intake of the 2015 or 2018 vintages compared to the control. Intake of the 2018 vintage reduced SBP and DBP (-4.1 mmHg and -5.6 mmHg, respectively; p = 0.02) compared to the 2015 wine and the control drink. The amount of hydroxytyrosol in the 2018 wine was almost twice the amount as in the 2015 wine, which may help explain the variable blood pressure results. Future studies exploring the vascular effects of the same red wine from different vintage years and different phenolic profiles are warranted.

Evaluating the Chemical Hazards in Wine Production Associated with Climate Change

The climate warming trend challenges the chemical risk associated with wine production worldwide. The present study investigated the possible difference between chemical wine profile during the drought year 2012 compared to the post-drought year 2013. Toxic metals (Cd and Pb), microelements (Mn, Ni, Zn, Al, Ba, and Cu), macroelements (Na, Mg, K, Ca, and P), isotopic ratios (87Sr/86Sr and 206Pb/207Pb), stable isotopes (δ18O, δ13C, (D/H)I, and (D/H)II), and climatic data were analyzed. The multivariate technique, correlation analysis, factor analysis, partial least squares–discriminant analysis, and hierarchical cluster analysis were used for data interpretation. The maximum temperature had a maximum difference when comparing data year apart. Indeed, extreme droughts were noted in only the spring and early summer of 2012 and in 2013, which increased the mean value of ground frost days. The microelements, macroelements, and Pb presented extreme effects in 2012, emphasizing more variability in terms of the type of wine. Extremely high Cd values were found in the wine samples analyzed, at up to 10.1 µg/L. The relationship between precipitation and δ18O from wine was complex, indicating grape formation under the systematic influence of the current year precipitation, and differences between years were noted. δ13C had disentangled values, with no differentiation between years, and when coupled with the deuterium–hydrogen ratio, it could sustain the hypothesis of possible adulteration. In the current analysis, the 87Sr/86Sr showed higher values than in other Romanian studies. The temperature had a strong positive correlation with Pb, while the ground frost day frequency correlated with both Pb and Cd toxic elements in the wine. Other significant relationships were disclosed between the chemical properties of wine and climate data. The multivariate statistical analysis indicated that heat stress had significant importance in the chemical profile of the wine, and the ground frost exceeded the influence of water stress, especially in Transylvania.

Total Phenolic, Anthocyanins HPLC-DAD-MS Determination and Antioxidant Capacity in Black Grape Skins and Blackberries: A Comparative Study

Anthocyanins are flavonoids with an antioxidant effect. They are the pigments that give rich colours to berries, red onions, pomegranates, and grapes. In addition to acting as antioxidants and fighting free radicals, anthocyanins may offer anti-inflammatory, anti-viral, and anti-cancer benefits. Among various types of fruits, blackberries and grapes are distinguished by their rich content in polyphenols, including anthocyanins. The purpose of this study was the identification and quantification of the anthocyanins in black grape skins and blackberries, but also the determination of the total phenolic content and total antioxidant capacity. The grape skins and blackberry extracts were prepared by an ultrasound-assisted acidified ethanol and methanol extraction method, with the 80% methanol solution being the most effective. Alcoholic extracts of blackberries and grape skins were analysed by the HPLC-DAD-MS method. There were five glycosylated anthocyanin compounds in blackberries, eight glycosylated anthocyanins compounds, and seven fragments of anthocyanin derivatives in grape skins identified. It was concluded that the anthocyanin profile of blackberries and grapes revealed mainly anthocyanin monoglycosides and acetylglycosides. Cyanidin-3-glucoside was the main component (86.49%) in blackberries, while, in the grape skins, the main component was delphinidin-3-O-glucoside (about 40.64%). Principal component analysis (PCA) was carried out on the basis of the 13 identified compounds in order to separate the extracts and describe the anthocyanins characteristics of different groups, the findings being in agreement with the experimental results. Compared to methanol extracts, ethanol extracts showed higher antioxidant activity, being related to the total phenolic content for the blackberries. Overall, the obtained results indicated that the blackberries and grapes skins possessed a high antioxidant content, similar to other berries, highlighting their potential use as fresh functional foods or fruit-derived products.

From Soil to Grape and Wine: Geographical Variations in Elemental Profiles in Different Chinese Regions

Elemental profiles are frequently applied to identify the geographical origin and authenticity of food products, to guarantee quality. The concentrations of fifteen major, minor, and trace elements (Na, Mg, K, Ca, Al, Fe, Mn, Cu, Zn, Rb, Sr, Li, Cd, Cs, and Ba) were determined in soils, “Meili” grapes, and wines from six regions in China by inductively coupled plasma mass spectrometry (ICP-MS). The elemental concentrations in these samples, according to the geographical origins, were analyzed by one-way analysis of variance (ANOVA) with Duncan’s multiple comparisons. The bioconcentration factor (BCF) from soil to grape and the transfer factor (TF) from grape to wine were calculated. Mg, K, Ca, Cu, Zn, Rb, Sr, and Ba presented higher BCF values than the other seven elements. The TF values of six elements (Na, Mg, K, Zn, Li, and Cs) were found to be greater than one. Moreover, the correlation of element content between the pairs of soil–grape, grape–wine, and bioconcentration factor (BCF)–environmental factor were analyzed. Significant correspondences among soil, grape, and wine were observed for K and Li. Two elements (Sr and Li) showed significant correlations between BCF and environmental factor (relative humidity, temperature, and latitude). A linear discriminant analysis (LDA) with three variables (K, Sr, Li) revealed a high accuracy (>90%) to determine the geographical origin for different Chinese regions.

Recent advances in NMR-based metabolomics of alcoholic beverages

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NMR-based techniques can be used for establishing metabolic “fingerprint” .

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Biomarkers for discrimination of wine varietals were identified.

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COSY and DOSY techniques may aid in assigning phenolic compounds and disaccharides.

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NMR-based metabolomic studies of alcoholic beverages remain limited in Asia.

Alcoholic beverages have a complex chemistry that can be influenced by their alcoholic content, origin, fermentation process, additives, and contaminants. The complex composition of these beverages leave them susceptible to fraud, potentially compromising their authenticity, quality, and market value, thus increasing risks to consumers’ health. In recent years, intensive studies have been carried out on alcoholic beverages using different analytical techniques to evaluate the authenticity, variety, age, and fermentation processes that were used. Among these techniques, NMR-based metabolomics holds promise in profiling the chemistry of alcoholic beverages, especially in Asia where metabolomics studies on alcoholic beverages remain limited.

Selected Instrumental Techniques Applied in Food and Feed: Quality, Safety and Adulteration Analysis

This review presents an overall glance at selected instrumental analytical techniques and methods used in food analysis, focusing on their primary food science research applications. The methods described represent approaches that have already been developed or are currently being implemented in our laboratories. Some techniques are widespread and well known and hence we will focus only in very specific examples, whilst the relatively less common techniques applied in food science are covered in a wider fashion. We made a particular emphasis on the works published on this topic in the last five years. When appropriate, we referred the reader to specialized reports highlighting each technique's principle and focused on said technologies' applications in the food analysis field. Each example forwarded will consider the advantages and limitations of the application. Certain study cases will typify that several of the techniques mentioned are used simultaneously to resolve an issue, support novel data, or gather further information from the food sample.

NMR spectroscopy in wine authentication: An official control perspective

Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, ² H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, ¹ H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of ¹ H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.

NMR in the Service of Wine Differentiation

NMR is a swift and highly reproducible spectrometric technique that makes it possible to obtain spectra containing a lot of information about the sample analyzed. This approach helps major components be described in complex mixtures such as wine in just one analysis. Analysis of wine metabolites is very often used to understand the impact of geographical origin or variety on wine quality. NMR is often used for tracing the geographical origin of wine. Research on NMR metabolic effects of geographical origin is of great importance as the high added value of wines results from compliance with state legislation on the protected denomination of origin (PDO) and protected geographical indication (PGI) for the administration of the appellation of wines. A review of NMR with emphasis on SNIF-NMR in the analysis of wine authenticity is given. SNIF-NMR remains a method of choice for the detection of wine chaptalization as it is the only approach which provides position-specific information on the origin of sugar in wine. However, the sample preparation step, which lacks major improvements since its conception, is strenuous and expensive, and suffers from drawbacks in terms of low sample throughput. Mainstream 1D and 2D NMR experiments provide a fast and affordable way to authenticate wine based on the geographical origin, vintage, and variety discrimination, and include a simple and non-destructive sample preparation step. With this approach, spectral data processing often represents a crucial step of the analysis. With properly performed NMR experiments good to excellent differentiation of wines from different vintages, regions, and varieties was achieved recently.

Comprehensive Classification and Regression Modeling of Wine Samples Using 1H NMR Spectra

Recently, ¹H NMR (nuclear magnetic resonance) spectroscopy was presented as a viable option for the quality assurance of foods and beverages, such as wine products. Here, a complex chemometric analysis of red and white wine samples was carried out based on their ¹H NMR spectra. Extreme gradient boosting (XGBoost) machine learning algorithm was applied for the wine variety classification with an iterative double cross-validation loop, developed during the present work. In the case of red wines, Cabernet Franc, Merlot and Blue Frankish samples were successfully classified. Three very common white wine varieties were selected and classified: Chardonnay, Sauvignon Blanc and Riesling. The models were robust and were validated against overfitting with iterative randomization tests. Moreover, four novel partial least-squares (PLS) regression models were constructed to predict the major quantitative parameters of the wines: density, total alcohol, total sugar and total SO₂ concentrations. All the models performed successfully, with R² values above 0.80 in almost every case, providing additional information about the wine samples for the quality control of the products. ¹H NMR spectra combined with chemometric modeling can be a good and reliable candidate for the replacement of the time-consuming traditional standards, not just in wine analysis, but also in other aspects of food science.

Phenolic Compounds as Markers of Wine Quality and Authenticity

Targeted and untargeted determinations are being currently applied to different classes of natural phenolics to develop an integrated approach aimed at ensuring compliance to regulatory prescriptions related to specific quality parameters of wine production. The regulations are particularly severe for wine and include various aspects of the viticulture practices and winemaking techniques. Nevertheless, the use of phenolic profiles for quality control is still fragmented and incomplete, even if they are a promising tool for quality evaluation. Only a few methods have been already validated and widely applied, and an integrated approach is in fact still missing because of the complex dependence of the chemical profile of wine on many viticultural and enological factors, which have not been clarified yet. For example, there is a lack of studies about the phenolic composition in relation to the wine authenticity of white and especially rosé wines. This review is a bibliographic account on the approaches based on phenolic species that have been developed for the evaluation of wine quality and frauds, from the grape varieties (of V. vinifera and non vinifera), to the geographical origin, the vintage year, the winemaking process, and wine aging. Future perspectives on the role of phenolic compounds in different wine quality aspects, which should be still exploited, are also outlined.

Carbohydrate composition of red wines during early aging and incidence on spoilage by Brettanomyces bruxellensis

Wine is generally considered as hostile medium in which spoilage microbes have to manage with many abiotic factors among which low nutrient content. Wines elaborated in 8 wineries were sampled during the first summer of aging over two consecutive vintages, and analysed for carbohydrate composition. This revealed the systematic presence of many carbohydrates including those useful for the spoilage yeast Brettanomyces bruxellensis. However, during the first summer of aging, the changes in wine carbohydrate composition were low and it was difficult to assess how much carbohydrate composition contributed to wine spoilage by B. bruxellensis. Subsequent laboratory experiments in inoculated wines showed that the sugars preferentially consumed in wine by the spoilage yeast are d-glucose, d-fructose, and trehalose, whatever the yeast strain considered. The addition of these sugars to red wines accelerates the yeast growth and the volatile phenols formation. Although probably not the only promoting factor, the presence of high amounts of metabolisable sugars thus really increases the risk of "brett" spoilage.

Polyphenols: Natural Antioxidants to Be Used as a Quality Tool in Wine Authenticity

Polyphenols are a diverse group of compounds possessing various health-promoting properties that are of utmost importance for many wine sensory attributes. Apart from genetic and environmental parameters, the implementation of specific oenological practices as well as the subsequent storage conditions deeply affect the content and nature of the polyphenols present in wine. However, polyphenols are effectively employed in authenticity studies. Provision of authentic wines to the market has always been a prerequisite meaning that the declarations on the wine label should mirror the composition and provenance of this intriguing product. Nonetheless, multiple cases of intentional or unintentional wine mislabeling have been recorded alarming wine consumers who demand for strict controls safeguarding wine authenticity. The emergence of novel platforms employing instrumentation of exceptional selectivity and sensitivity along with the use of advanced chemometrics such as NMR (nuclear magnetic resonance)- and MS (mass spectrometry)-based metabolomics is considered as a powerful asset towards wine authentication.

13C NMR-Based Chemical Fingerprint for the Varietal and Geographical Discrimination of Wines

A fast, economic, and eco-friendly methodology for the wine variety and geographical origin differentiation using ¹³C nuclear magnetic resonance (NMR) data in combination with machine learning was developed. Wine samples of different grape varieties cultivated in different regions in Greece were subjected to ¹³C NMR analysis. The relative integrals of the ¹³C spectral window were processed and extracted to build a chemical fingerprint for the characterization of each specific wine variety, and then subjected to factor analysis, multivariate analysis of variance, and k-nearest neighbors analysis. The statistical analysis results showed that the ¹³C NMR fingerprint could be used as a rapid and accurate indicator of the wine variety differentiation. An almost perfect classification rate based on training (99.8%) and holdout methods (99.9%) was obtained. Results were further tested on the basis of Cronbach's alpha reliability analysis, where a very low random error (0.30) was estimated, indicating the accuracy and strength of the aforementioned methodology for the discrimination of the wine variety. The obtained data were grouped according to the geographical origin of wine samples and further subjected to principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The PLS-DA and variable importance in projection (VIP) allowed the determination of a chemical fingerprint characteristic of each geographical group. The statistical analysis revealed the possibility of acquiring useful information on wines, by simply processing the ¹³C NMR raw data, without the need to determine any specific metabolomic profile. In total, the obtained fingerprint can be used for the development of rapid quality-control methodologies concerning wine.

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.

Multivariate optimization of an analytical method for the analysis of Abruzzo white wines by ICP OES

An inductively coupled plasma-optical emission spectrometry (ICP OES) method was optimized and applied for determining the concentration of 14 elements (Ba, Ca, Co, Cu, Fe, K, Li, Mg, Mn, Na, Ni, Sr, V, and Zn) in three representative white wines of the Abruzzo region (Italy). In order to optimise an ICP OES method a three level factorial design for three variables was used. The intensity of the emission lines for analytes was simultaneously maximised by using Derringer's desirability function. Using this approach, the optimal experimental conditions for wine analysis of 0.48 L min-1, 1.8 mL min-1 and 0.5 L min-1 for the nebulizer gas flow rate, sample uptake rate and auxiliary gas flow rate respectively were achieved. A total of 46 white wine samples of the three varieties were analysed by using the optimised experimental conditions. Linear Discriminant Analysis (LDA) and Partial Least Squares Linear Discriminant Analysis (PLS LDA) allowed an acceptable classification of the three varietal samples.

Application of Spectroscopic UV-Vis and FT-IR Screening Techniques Coupled with Multivariate Statistical Analysis for Red Wine Authentication: Varietal and Vintage Year Discrimination

One of the most important issues in the wine sector and prevention of adulterations of wines are discrimination of grape varieties, geographical origin of wine, and year of vintage. In this experimental research study, UV-Vis and FT-IR spectroscopic screening analytical approaches together with chemometric pattern recognition techniques were applied and compared in addressing two wine authentication problems: discrimination of (i) varietal and (ii) year of vintage of red wines produced in the same oenological region. UV-Vis and FT-IR spectra of red wines were registered for all the samples and the principal features related to chemical composition of the samples were identified. Furthermore, for the discrimination and classification of red wines a multivariate data analysis was developed. Spectral UV-Vis and FT-IR data were reduced to a small number of principal components (PCs) using principal component analysis (PCA) and then partial least squares discriminant analysis (PLS-DA) and linear discriminant analysis (LDA) were performed in order to develop qualitative classification and regression models. The first three PCs used to build the models explained 89% of the total variance in the case of UV-Vis data and 98% of the total variance for FR-IR data. PLS-DA results show that acceptable linear regression fits were observed for the varietal classification of wines based on FT-IR data. According to the obtained LDA classification rates, it can be affirmed that UV-Vis spectroscopy works better than FT-IR spectroscopy for the discrimination of red wines according to the grape variety, while classification of wines according to year of vintage was better for the LDA based FT-IR data model. A clear discrimination of aged wines (over six years) was observed. The proposed methodologies can be used as accessible tools for the wine identity assurance without the need for costly and laborious chemical analysis, which makes them more accessible to many laboratories.

Characterization and classification of wines according to geographical origin, vintage and specific variety based on elemental content: a new chemometric approach

A highly informative chemometric approach using elemental data to distinguish and classify wine samples according to different criteria was successfully developed. The robust chemometric methods, such fuzzy principal component analysis (FPCA), FPCA combined with linear discriminant analysis (LDA), namely FPCA-LDA and mainly fuzzy divisive hierarchical associative-clustering (FDHAC), including also classical methods (HCA, PCA and PCA-LDA) were efficaciously applied for characterization and classification of white wines according to the geographical origin, vintage or specific variety. The correct rate of classification applying LDA was 100% in all cases, but more compact groups have been obtained for FPCA scores. A similar separation of samples resulted also when the FDHAC was employed. In addition, FDHAC offers an excellent possibility to associate each fuzzy partition of wine samples to a fuzzy set of specific characteristics, finding in this way very specific elemental contents and fuzzy markers according to the degrees of membership (DOMs).

1H NMR metabolomics applied to Bordeaux red wines

The q-NMR metabolomics has already demonstrated its potential for classifying wines of different geographical origins, grape varieties, or vintages. This study focuses on the characterisation of Bordeaux red wines, seeking to discriminate them from others produced in the major French wine regions. A sampling of 224 commercial French wines was analysed by ¹H NMR and forty compounds were quantified. Non-supervised and supervised statistical analyses revealed a singular imprint of Bordeaux wines in comparison with other French wines, with classification rates ranging from 71% to 100%. Within the Bordeaux vineyards, red wines from the different Bordeaux subdivisions were analysed from different vintages. Our results indicate that q-NMR metabolomics enables the differentiation of Médoc and Libournais vineyard highlighting the most discriminant constituents. In addition, the effects of wine evolution during bottle aging and vintage on Bordeaux red wines were pointed out and discussed.

Exploiting combined absorption and front face fluorescence spectroscopy to chase classification: A proof of concept in the case of Sardinian red wines

We present the analysis of optical spectroscopy fingerprints of three different varieties of Sardinian red wine, Carignano, Cannonau and Monica, belonging to Italian DOC (Controlled Origin Designation) red wines family. We selected 15 commercial wines (five for each variety), produced in the middle and south regions of Sardinia form monovarietal grapes. Despite different grapes, farming and tasting, all the samples share common absorption and fluorescence features. A two steps analysis is applied to achieve good classification of the wines. We recorded typical absorbance spectra with a large absorption below 300 nm and a visible absorption band at about 520 nm. Colour attributes according to chromaticity coordinates were evaluated by means of transmittance data and coupled to wine aging data to achieve classification. Despite similar values of lightness (L*), chroma (C*_ab), and hue angle (h°_ab) for the three varieties, good clustering was gathered for Carignano and Cannonau wines, whilst Monica variety has wide spread chromatic coordinates. UV excited fluorescence spectra display large and composite emission bands from the near UV down to the whole visible range. We performed multivariate analysis in the framework of the principal component analysis of fluorescence spectra coupled with absorption ones being able to achieve good clustering between the three varieties. One anomaly among Cannonau wines is discussed.

Polyphenol Fingerprinting Approaches in Wine Traceability and Authenticity: Assessment and Implications of Red Wines

Like any other food/feed matrix, regardless of the employed analytical method, wine requires authentication strategies; a suitable qualitative and quantitative analysis represents the fingerprint which defines its identity. Until recently, fingerprinting approaches using liquid chromatography applications have been regarded as an effective tool for the assessment of wines employing polyphenol profiles. These profiles are of considerable importance for grapes and wines as they influence greatly the color, sensory, and nutritional quality of the final product. The authenticity and typicity characters are fundamental characteristics, which may be evaluated by the use of polyphenol fingerprinting techniques. Under these conditions, the evolution of polyphenols during the red wine elaboration and maturation processes shows a high importance at the level of the obtained fingerprints. Moreover, the environment factors (vintage, the area of origin, and variety) and the technological conditions significantly influence wine authenticity through the use of polyphenol profiles. Taking into account the complexity of the matter at hand, this review outlines the latest trends in the polyphenol fingerprinting of red wines in association with the transformations that occur during winemaking and storage.

Potential use of surface-assisted LIBS for determination of strontium in wines

Laser-induced breakdown spectroscopy (LIBS) is a well-established technique for elemental analysis and has been widely used for qualitative and quantitative analysis of different solid samples. LIBS is also well-known for not requiring sample preparation, but the analysis of liquids is actually a great challenge. In the present work, a novel approach of elemental analysis of liquids with an organic matrix has been performed, to the best of our knowledge, making a liquid-to-solid matrix conversion by drying wine samples on aluminum and silicon wafers, which have demonstrated an increase in the analytical performance of LIBS. A red wine from Slovakia (not blended with any other variety or wine from other regions or adulterants) was prepared according to the procedure consisting of drying 2 ml of wine dropped on a solid wafer having a flat surface area of about 25  cm². Surface-assisted LIBS in combination with the conversion of liquid into solid avoids the difficulties and limitations of working with liquid samples by LIBS, improving the limit of detection (LOD), repeatability, and sensitivity. The quantification of strontium (Sr) has been realized by addition of the known concentration of SrCl₂·6H₂O in wine before the drying process. Sr is an important element among those usually used as markers for identification of the soils on which the vines grow. Two ionic (407.771 nm and 421.552 nm) and two neutral (460.733 nm and 481.188 nm) Sr lines were used to plot the calibration curves in order to study the LODs and the matrix effects for the analysis of Sr in the tested wines and for different wafer materials. This direct surface-assisted LIBS measuring method has been successfully applied for the determination of Sr in a red wine sample from Slovakia, and the obtained results with two kinds of substrates (Al and Si) were compared. Finally, a validation sample has been employed to test the accuracy of the established calibration curves.

Wine Traceability Using Chemical Analysis, Isotopic Parameters, and Sensory Profiles

NMR/IRMS techniques are now widely used to assess the geographical origin of wines. The sensory profile of a wine is also an interesting method of characterizing its origin. This study aimed at elaborating chemical, isotopic, and sensory parameters by means of statistical analysis. The data were determined in some Italian white wines—Verdicchio and Fiano—and red wines—Refosco dal Peduncolo Rosso and Nero d’Avola—produced from grapes grown in two different regions with different soil and climatic conditions during the years 2009–2010. The grapes were cultivated in Veneto (northwest Italy) and Marches (central Italy). The results show that the multivariate statistical analysis PCA (Principal Component Analysis) of all the data can be a useful tool to characterize the vintage and identify the origin of wines produced from different varieties. Moreover, it could discriminate wines of the same variety produced in regions with different soil and climatic conditions.

Antioxidant activity and phenolic profiles of the wild currant Ribes magellanicum from Chilean and Argentinean Patagonia

The Patagonian currant Ribes magellanicum is highly valued due to its pleasant flavor and sweet taste. The aim of this study was to characterize its constituents and to assess their antioxidant and cytoprotective properties. For the fruit phenolic‐enriched extract (PEE), total phenolics (TP), total flavonoids (TF), and antioxidant activity (DPPH, Ferric reducing antioxidant power (FRAP), and Trolox equivalent antioxidant activity (TEAC)) were determined. Argentinean samples presented better activity in the DPPH and FRAP assays. Best cytoprotection against oxidative stress induced by H₂O₂ in AGS cells was found in one Argentinean sample at 500 μg mL⁻¹ (65.7%). HPLC MS/MS analysis allowed the tentative identification of 59 constituents, including eight anthocyanins, 11 conjugates of caffeic‐, ferulic‐, and coumaric acid, and 38 flavonoids, most of them quercetin and kaempferol derivatives. Argentinean samples showed a more complex pattern of anthocyanins, hydroxycinnamic acids (HCA), and flavonoids. Cyanidin rhamnoside hexoside and cyanidin hexoside were the main anthocyanins, accounting for 35 and 55% for the Argentinean and 60 and 27% for the ripe Chilean fruits. HCA content was about three times higher in Argentinean samples. The phenolic profiles of Chilean and Argentinean Ribes magellanicum show remarkable differences in chemical composition with higher HCA and flavonoid content in Argentinean samples.