Wine science in the metabolomics era

A digital image smartphone-based approach to Slovak Tokaj wine authentication chemometric assisted

The authentication of Slovak wines in comparison to other similar wines from various geographical regions, namely Hungary, France, Austria, and Ukraine, was conducted using the OC-PLS, DD-SIMCA, and PLS-DM models, all of them operating in rigorous way. The study involved 63 samples, of which 41 originated from Slovakia, covering diverse wine types such as varietal wines, cuvée selections (different "putňový"), and essence. To capture digital images under controlled conditions, a custom-made cardboard box with white inner surfaces was devised and equipped with a smartphone. During the training phase, sensitivities of 96%, 100%, and 96% were attained for OC-PLS, DD-SIMCA, and PLS-DM, respectively. In the subsequent stages of validation and testing for DD-SIMCA and PLS-DM, the proposed methods displayed optimal efficiency, achieving both sensitivity and specificity rates of 100%. However, such results were not achieved in the case of OC-PLS, which exhibited efficiency levels of 90% in validation and 80% in testing.

Aroma determination in alcoholic beverages: Green MS-based sample preparation approaches

Aroma determination in alcoholic beverages has become a hot research topic due to the ongoing effort to obtain quality products, especially in a globalized market. Consumer satisfaction is mainly achieved by balancing several aroma compounds, which are mixtures of numerous volatile molecules enclosed in challenging matrices. Thus, sample preparation strategies for quality control and product development are required. They involve several steps including copious amounts of hazardous solvents or time-consuming procedures. This is bucking the trend of the ever-increasing pressure to reduce the environmental impact of analytical chemistry processes. Hence, the evolution of sample preparation procedures has directed towards miniaturized techniques to decrease or avoid the use of hazardous solvents and integrating sampling, extraction, and enrichment of the targeted analytes in fewer steps. Mass spectrometry coupled to gas or liquid chromatography is particularly well suited to address the complexity of these matrices. This review surveys advancements of green miniaturized techniques coupled to mass spectrometry applied on all categories of odor-active molecules in the most consumed alcoholic beverages: beer, wine, and spirits. The targeted literature consider progresses over the past 20 years.

Metabolomics analysis based on UHPLC-QqQ-MS/MS to discriminate grapes and wines from different geographical origins and climatological characteristics

With the proliferation of the consumer's awareness of wine provenance, wines with unique origin characteristics are increasingly in demand. This study aimed to investigate the influence of geographical origins and climatological characteristics on grapes and wines. A total of 94 anthocyanins and 78 non-anthocyanin phenolic compounds in grapes and wines from five Chinese viticultural vineyards (CJ, WH, QTX, WW, and XY) were identified by UHPLC-QqQ-MS/MS. Chemometric methods PCA and OPLS-DA were established to select candidate differential metabolites, including flavonols, stilbenes, hydroxycinnamic acids, peonidin derivatives, and malvidin derivatives. CCA showed that malvidin-3-O-glucoside had a positive correlation with mean temperature, and quercetin-3-O-glucoside had a negative correlation with precipitation. In addition, enrichment analysis elucidated that the metabolic diversity in different origins mainly occurred in flavonoid biosynthesis. This study would provide some new insights to understand the effect of geographical origins and climatological characteristics on phenolic compounds in grapes and wines.

Untargeted Metabolomics Analysis Based on LC-QTOF-MS to Investigate the Phenolic Composition of Red and White Wines Elaborated from Sonicated Grapes

Ultrasounds are considered an emerging technology in the wine industry. Concretely, in 2019, the International Organization of Vine and Wine (OIV) officially approved their use for the treatment of crushed grapes to increase the level of phenolic compound extraction. The main objective of this study was to validate an untargeted metabolomics approach as an analytical tool for identifying novel markers associated with sonication. To do so, the influence of a sonication treatment on the metabolic profile was studied in four typically commercial varietal wines, i.e., two red wines from 'Syrah' and 'Cabernet Sauvignon' grapes and two white wines from 'Macabeo' and 'Airén' grapes. A robust classification and prediction model was created employing supervised techniques such as partial least-squares discriminant analysis (PLS-DA). The findings indicated that the grapes subjected to high-power ultrasound conditions experienced cell wall disruption due to the cavitation phenomenon, resulting in significant changes in various phenolic compounds (including hydroxycinnamic acids and flavonoids) present in these wines compared to wines from non-sonicated grapes. Additionally, new metabolites were tentatively identified through untargeted metabolomics techniques. This study represents the successful application of the untargeted metabolomics approach employing a UHPLC-QTOF system to discern how grape sonication affects bioactive secondary metabolites in wines.

Targeted 1-H-NMR wine analyses revealed specific metabolomic signatures of yeast populations belonging to the Saccharomyces genus

This study aimed to explore the non-volatile metabolomic variability of a large panel of strains (44) belonging to the Saccharomyces cerevisiae and Saccharomyces uvarum species in the context of the wine alcoholic fermentation. For the S. cerevisiae strains flor, fruit and wine strains isolated from different anthropic niches were compared. This phenotypic survey was achieved with a special focus on acidity management by using natural grape juices showing opposite level of acidity. A 1H NMR based metabolomics approach was developed for quantifying fifteen wine metabolites that showed important quantitative variability within the strains. Thanks to the robustness of the assay and the low amount of sample required, this tool is relevant for the analysis of the metabolomic profile of numerous wines. The S. cerevisiae and S. uvarum species displayed significant differences for malic, succinic, and pyruvic acids, as well as for glycerol and 2,3-butanediol production. As expected, S. uvarum showed weaker fermentation fitness but interesting acidifying properties. The three groups of S. cerevisiae strains showed different metabolic profiles mostly related to their production and consumption of organic acids. More specifically, flor yeast consumed more malic acid and produced more acetic acid than the other S. cerevisiae strains which was never reported before. These features might be linked to the ability of flor yeasts to shift their metabolism during wine oxidation.

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

BACKGROUND

Omics 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.

RESULTS

Α 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.

SIGNIFICANCE

The 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.

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.

Development of a Fully Automated Method HS-SPME-GC-MS/MS for the Determination of Odor-Active Carbonyls in Wines: a "Green" Approach to Improve Robustness and Productivity in the Oenological Analytical Chemistry

The aim of this study was the optimization and validation of a green, robust, and comprehensive method for the determination of volatile carbonyl compounds (VCCs) in wines that could be added as a new quality control tool for the evaluation of a complete fermentation, correct winemaking style, and proper bottling and storage. A HS-SPME-GC-MS/MS method was optimized and automated using the autosampler to improve overall performance. A solvent-less technique and a strong minimization of all volumes were implemented to comply with the green analytical chemistry principles. There were as many as 44 VCC (mainly linear aldehydes, Strecker aldehydes, unsaturated aldehydes, ketones, and many other) analytes under investigation. All compounds showed a good linearity, and the LOQs were abundantly under the relevant perception thresholds. Intraday, 5-day interday repeatability, and recovery performances in a spiked real sample were evaluated showing satisfactory results. The method was applied to determine the evolution of VCCs in white and red wines after accelerated aging for 5 weeks at 50 °C. Furans and linear and Strecker aldehydes were the compounds that showed the most important variation; many VCCs increased in both classes of samples, whereas some showed different behaviors between white and red cultivars. The obtained results are in strong accordance with the latest models on carbonyl evolution related to wine aging.

A volatilomics analytical protocol employing solid phase microextraction coupled to GC × GC-MS analysis and combined with multivariate chemometrics for the detection of pomegranate juice adulteration

In this work, a solid-phase microextraction (SPME) method combined with two-dimensional gas chromatography coupled to mass spectrometry (GC × GC-MS) was optimized and used to assess the authenticity of pomegranate juice to prevent fraudulent practices. A divinylbenzene/carboxen/polydimethylsiloxane (DVB/CAR/PDMS) fiber was used for the extraction of the volatiles. The critical parameters that affect the extraction process, such as the sample volume, and the extraction time were studied. The optimized protocol involved the addition of 15 mL of juice in 50 mL vial and saturation with 30% w/v NaCl.The extraction was carried out within 45 min under 1000 rpm stirring and was applied in the analysis of real juice samples to assess authenticity and detect low levels of pomegranate juice adulteration with grape and apple juice down to 1%. Commercially available pomegranate juice samples were acquired (n1 = 6) and adulterated with 1% of apple juice (n2 = 6), 1% of grape juice (n3 = 6), and a mixture of 1% apple juice and 1% grape juice (n4 = 6). Authentic pomegranate juice samples and adulterated mixtures were analyzed by SPME-GC × GC-MS. The analysis resulted in the identification of 123 volatile compounds that were further processed with chemometric tools. Principal component analysis (PCA) was employed to visualize the clustering of the samples, and a two-way orthogonal partial least squares discriminant analysis (O2PLS-DA) chemometric model was developed and successfully classified the samples to authentic pomegranate juice or adulterated with an explained total variance of 87.4%. The O2PLS-DA prediction model revealed characteristic volatile markers that could be used to detect pomegranate juice fraud.

Influence of Different Types, Utilization Times, and Volumes of Aging Barrels on the Metabolite Profile of Red Wine Revealed by 1H-NMR Metabolomics Approach

It is well recognized that the aging process is a critical step in winemaking because it induces substantial chemical changes linked to the organoleptic properties and stability of the finished wines. Therefore, this study aimed to investigate the influence of different types, utilization times, and volumes of aging barrels on the metabolite profile of red wines, produced from Thai-grown Shiraz grapes, using a non-targeted proton nuclear magnetic resonance (1H-NMR) metabolomics approach. As a result, 37 non-volatile polar metabolites including alcohols, amino acids, organic acids, carbohydrates and low-molecular-weight phenolics were identified. Chemometric analysis allowed the discrimination of wine metabolite profiles associated with different types of aging containers (oak barrels vs. stainless-steel tanks), as well as the utilization times (2, 6 and >10 years old) and volumes (225, 500 and 2000 L) of the wooden barrels employed. Significant variations in the concentration of formate, fumarate, pyruvate, succinate, citrate, gallate, acetate, tyrosine, phenylalanine, histidine, γ-aminobutyrate, methionine and choline were statistically suggested as indicators accountable for the discrimination of samples aged under different conditions. These feature biomarkers could be applied to manipulate the use of aging containers to achieve the desired wine maturation profiles.

Development of a portable optical device with a multi-channel spectrometer sensor for quantification of glycerol in wine: a maker approach for on-site analysis

In this work we present a novel and environmentally friendly approach for quantifying glycerol in wine samples using a portable optical device based on the maker concept and do-it-yourself (DIY) principles. This method offers significant advantages, including cost-effectiveness, reduced sample and reagent consumption, and the potential for integrating IoT (Internet of Things) technology. The chemical strategy involves the oxidation of glycerol using periodate, followed by the formation of the 3,5-diacetyl-1,4-dihydrolutidine (DDL) compound through a reaction with acetylacetone. The utilization of a cost-effective AS7341 color sensor as a detector enables accurate and sensitive detection of glycerol levels in wine samples. The optimized procedure demonstrates adequate analytical performance for glycerol determination in wine samples, encompassing a wide linear range (0.5 mg L-1 to 40.0 mg L-1), high correlation coefficient (r = 0.998), and low limits of detection (0.050 mg L-1). The method exhibits excellent precision, with the coefficient of variation estimated to be 0.1% for 10 independent measurements of a 20 mg L-1 solution. These features render it suitable not only for routine glycerol analysis in the wine industry, but also for addressing challenges related to wine adulteration and counterfeiting.

Untargeted Metabolomics Approach Using UHPLC-HRMS to Unravel the Impact of Fermentation on Color and Phenolic Composition of Rosé Wines

Color is a major quality trait of rosé wines due to their packaging in clear glass bottles. This color is due to the presence of phenolic pigments extracted from grapes to wines and products of reactions taking place during the wine-making process. This study focuses on changes occurring during the alcoholic fermentation of Syrah, Grenache and Cinsault musts, which were conducted at laboratory (250 mL) and pilot (100 L) scales. The color and phenolic composition of the musts and wines were analyzed using UV-visible spectrophotometry, and metabolomics fingerprints were acquired by ultra-high performance liquid chromatography-high-resolution mass spectrometry. Untargeted metabolomics data highlighted markers of fermentation stage (must or wine) and markers related to the grape variety (e.g., anthocyanins in Syrah, hydroxycinnamates and tryptophan derivatives in Grenache, norisoprenoids released during fermentation in Cinsault). Cinsault wines contained higher molecular weight compounds possibly resulting from the oxidation of phenolics, which may contribute to their high absorbance values.

Comprehensive elucidation of the terroir of Korean kimchi through the study of recipes, metabolites, microbiota, and sensory characteristics

The aim of this study was to investigate the differences in characteristics of the fermented food kimchi based on the regions where it is produced. A total of 108 kimchi samples were collected from five different provinces in Korea to analyze the recipes, metabolites, microbes, and sensory characteristics. Overall, 18 ingredients (including salted anchovy and seaweed), 7 quality indicators (such as salinity and moisture content), 14 genera of microorganisms (mainly Tetragenococcus and Weissella belonging to LAB), and 38 metabolites contributed to the characteristics of kimchi by region. Kimchi from the southern and northern regions showed distinct metabolite profile (collected 108 kimchi) and flavor profile differences (kimchi manufactured using the standard regional recipes). This is the first study to investigate the terroir effect of kimchi by identifying differences in ingredients, metabolites, microbes, and sensory characteristics based on the region of production, and the correlations between these factors.

Authentication of Polish Red Wines Produced from Zweigelt and Rondo Grape Varieties Based on Volatile Compounds Analysis in Combination with Machine Learning Algorithms: Hotrienol as a Marker of the Zweigelt Variety

The aim of this study was to determine volatile compounds in red wines of Zweigelt and Rondo varieties using HS-SPME/GC-MS and to find a marker and/or a classification model for the assessment of varietal authenticity. The wines were produced by using five commercial yeast strains and two types of malolactic fermentation. Sixty-seven volatile compounds were tentatively identified in the test wines; they represented several classes: 9 acids, 24 alcohols, 2 aldehydes, 19 esters, 2 furan compounds, 2 ketones, 1 sulfur compound and 8 terpenes. 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) was found to be a variety marker for Zweigelt wines, since it was detected in all the Zweigelt wines, but was not present in the Rondo wines at all. The relative concentrations of volatiles were used as an input data set, divided into two subsets (training and testing), to the support vector machine (SVM) and k-nearest neighbor (kNN) algorithms. Both machine learning methods yielded models with the highest possible classification accuracy (100%) when the relative concentrations of all the test compounds or alcohols alone were used as input data. An evaluation of the importance value of subsets consisting of six volatile compounds with the highest potential to distinguish between the Zweigelt and Rondo varieties revealed that SVM and kNN yielded the best classification models (F-score of 1, accuracy of 100%) when 3-ethyl-4-methylpentan-1-ol or 3,7-dimethyl-1,5,7-octatrien-3-ol (hotrienol) or subsets containing one or both of them were used. Moreover, the best SVM model (F-score of 1) was built with a subset containing 2-phenylethyl acetate and 3-(methylsulfanyl)propan-1-ol.

Derivatization Strategies in Flavor Analysis: An Overview over the Wine and Beer Scenario

Wine and beer are the most appreciated and consumed beverages in the world. This success is mainly due to their characteristic taste, smell, and aroma, which can delight consumer’s palates. These olfactory characteristics are produced from specific classes of volatile compounds called “volatile odor-active compounds” linked to different factors such as age and production. Given the vast market of drinking beverages, the characterization of these odor compounds is increasingly important. However, the chemical complexity of these beverages has led the scientific community to develop several analytical techniques for extracting and quantifying these molecules. Even though the recent “green-oriented” trend is directed towards direct preparation-free procedures, for some class of analytes a conventional step like derivatization is unavoidable. This review is a snapshot of the most used derivatization strategies developed in the last 15 years for VOAs’ determination in wine and beer, the most consumed fermented beverages worldwide and among the most complex ones. A comprehensive overview is provided for every method, whereas pros and cons are critically analyzed and discussed. Emphasis was given to miniaturized methods which are more consistent with the principles of “green analytical chemistry”.

Profiling of polar ionogenic metabolites in Polish wines by capillary electrophoresis-mass spectrometry

The composition of wine is determined by a complex interaction between environmental factors, genetic factors (i.e., grape varieties), and winemaking practices (including technology and storage). Metabolomics using NMR spectroscopy, GC-MS, and/or LC-MS has shown to be a useful approach for assessing the origin, authenticity, and quality of various wines. Nonetheless, the use of additional analytical techniques with complementary separation mechanisms may aid in the deeper understanding of wine's metabolic processes. In this study, we demonstrate that CE-MS is a very suitable approach for the efficient profiling of polar ionogenic metabolites in wines. Without using any sample preparation or derivatization, wine was analyzed using a 10-min CE-MS workflow with interday RSD values for 31 polar and charged metabolites below 3.8% and 23% for migration times and peak areas, respectively. The utility of this workflow for the global profiling of polar ionogenic metabolites in wine was evaluated by analyzing different cool-climate Polish wine samples.

Effects of Water Stress, Defoliation and Crop Thinning on Vitis vinifera L. cv. Solaris Must and Wine Part II: 1H NMR Metabolomics

Proton nuclear magnetic resonance (1H NMR) metabolomics was employed to investigate the impact of water deficit, defoliation, and crop thinning on the chemical composition of must and wines from the cool-climate white grape variety Solaris. The obtained results show that viticultural practices (defoliation and crop thinning) affected the amino acid and sugar content of Solaris must and thereby the quality of the final wine—mainly in terms of compounds normally related to fruity aroma (i.e., isopentanol), non-sugar sweetness (i.e., proline and glycerol), and alcohol content. The content of tyrosol, a natural phenolic antioxidant with a high bioavailability, was increased in the final wine by a combination of defoliation and crop thinning. The results of the metabolomics analysis performed on the must and wine samples from the water stress experiment showed that short-term water deficit significantly affected the concentration of several flavor-related compounds, including glutamate, butyrate and propanol, of the organic acids lactate and fumarate, and of the phenolic compounds caffeic acid and p-coumaric acid. ANOVA simultaneous component analysis showed that the effect of water deficit accounted for 11% (p < 0.001) and 8% (p < 0.001) of the variability in the metabolite concentrations in must and wines, respectively, while viticultural practices accounted for 38% (p < 0.001) and 30% (p < 0.001) of the metabolite variability in must and wines, respectively.

1H NMR and UPLC-HRMS-based metabolomic approach for evaluation of the grape maturity and maceration time of Touriga Nacional wines and their correlation with the chemical stability

Touriga Nacional is a well-adapted Portuguese grape variety in São Francisco River Valley (northeastern Brazil). Nevertheless, it has only been indicated to short-term consumption because of the lack of chemical stability, which is attributed to low grape acidity and incomplete phenolic maturity. Therefore, we used Ultra-Performance Liquid Chromatography coupled High-resolution Mass Spectrometry, Nuclear Magnetic Resonance and chemometrics (PCA and PLS-DA) to evaluate the grape maturity and maceration time on chemical composition of wines from two harvest seasons. Moreover, we investigated how these experimental factors could affect their chemical stability. Grapes maturity showed to be the main effect. Overall, phenolic acids and short-chain organic acids were found to be at higher levels in wines produced with unripe grapes from February and shorter maceration time (p < 0.05). Proanthocyanidins and other flavonoids were increased in wines macerated for longer time using overripe grapes harvested in July. Furthermore, stable wines were made from overripe grapes, which contained more galacturonic acid.

Chemometric and sensometric techniques in enological data analysis

Enological evaluations capture the chemical and sensory space of wine using different techniques; many sensory methods as well as a variety of analytical chemistry techniques contribute to the amount of information generated. Data fusion, especially integrating data sets, is important when working with complex systems. The success reported when trying to integrate different modalities is generally low and has been attributed to the lack of statistically considerate strategies focusing on the data handling process. Multiple stages of data handling must be carefully considered when dealing with multi-modal data. In this review, the different stages in the data analysis process were examined. The study revealed misconceptions surrounding the process and elucidated rules for purpose-driven approaches by examining the complexities of each stage and the impact the decisions made at each stage have on the resulting models. The two major modeling approaches are either supervised (discrimination, classification, prediction) or unsupervised (exploration). Supervised approaches were emphatic on the pre-processing steps and prioritized increasing performance. Unsupervised approaches were mostly used for preliminary steps. The review found aspects often neglected when it came to the data collection and capturing which in the end contributed to the low success in combining sensory and chemistry data.

Untargeted metabolomic analysis of Chinese red wines for geographical origin traceability by UPLC-QTOF-MS coupled with chemometrics

Identifying geographical origins of red wines made in specific regions is of significance since the false claim of geographical origins has been frequently exposed in China's wine industry. In this work, an untargeted metabolomic approach based on UPLC-QTOF-MS was established to discriminate geographical origins of Chinese red wines. The principal component analysis (PCA) showed significant differences between wine samples from three famous geographical origins in China. The metabolites contributing to the differentiation were screened by orthogonal partial least squares-discriminant analysis (OPLS-DA) with pairwise modeling. 40 and 46 differential metabolites in positive and negative ionization modes were putatively identified as chemical markers. Furthermore, heatmap visualization and OPLS-DA models were constructed based on these identified markers and external verification wine samples from different regions were successfully discriminated, with recognition rate up to 96.7%. This study indicated that UPLC-QTOF-MS-based untargeted metabolomics has great potential for the geographical origin traceability of Chinese red wines.

Use of Multivariate Statistics in the Processing of Data on Wine Volatile Compounds Obtained by HS-SPME-GC-MS

This review takes a snapshot of the main multivariate statistical techniques and methods used to process data on the concentrations of wine volatile molecules extracted by means of solid phase micro-extraction and analyzed using GC-MS. Hypothesis test, exploratory analysis, regression models, and unsupervised and supervised pattern recognition methods are illustrated and discussed. Several applications in the wine volatolomic sector are described to highlight different interactions among the various matrix components and volatiles. In addition, the use of Artificial Intelligence-based methods is discussed as an innovative class of methods for validating wine varietal authenticity and geographical traceability.

Characterization of Cabernet Sauvignon Wines by Untargeted HS-SPME GC-QTOF-MS

Untargeted metabolomics approaches are emerging as powerful tools for the quality evaluation and authenticity of food and beverages and have been applied to wine science. However, most fail to report the method validation, quality assurance and/or quality control applied, as well as the assessment through the metabolomics-methodology pipeline. Knowledge of Mexican viticulture, enology and wine science remains scarce, thus untargeted metabolomics approaches arise as a suitable tool. The aim of this study is to validate an untargeted HS-SPME-GC-qTOF/MS method, with attention to data processing to characterize Cabernet Sauvignon wines from two vineyards and two vintages. Validation parameters for targeted methods are applied in conjunction with the development of a recursive analysis of data. The combination of some parameters for targeted studies (repeatability and reproducibility < 20% RSD; linearity > 0.99; retention-time reproducibility < 0.5% RSD; match-identification factor < 2.0% RSD) with recursive analysis of data (101 entities detected) warrants that both chromatographic and spectrometry-processing data were under control and provided high-quality results, which in turn differentiate wine samples according to site and vintage. It also shows potential biomarkers that can be identified. This is a step forward in the pursuit of Mexican wine characterization that could be used as an authentication tool.

Non-volatile molecular composition and discrimination of single grape white of chardonnay, riesling, sauvignon blanc and silvaner using untargeted GC-MS analysis

This study developed and applied a GC-MS method aiming at molecular fingerprinting of 120 commercial single grape white wines (Chardonnay, Riesling, Sauvignon Blanc and Silvaner) for possible authentication according to grape variety. The method allowed detection of 372 peaks and tentative identification of 146 metabolites including alcohols, organic acids, esters, amino acids and sugars. The grape variety effect explained 8.3% of the total metabolite variation. Univariate tests showed two-thirds of the metabolites being different between grape varieties. Partial least squares-discriminant analysis based classification models were developed for each grape variety and a panel of classifiers (42 metabolites) was established. All the classification models for grape variety showed a high certainty (>91%) for an independent test set. Riesling contained the highest relative concentrations of sugars and organic acids, while concentrations of hydroxytyrosol and gallic acid, common antioxidants in wine, decreased in the order of Chardonnay > Riesling > Sauvignon Blanc > Silvaner.

Simultaneous Monitoring of the Evolution of Chemical Parameters in the Fermentation Process of Pineapple Fruit Wine Using the Liquid Probe for Near-Infrared Coupled with Chemometrics

This study used Fourier transform-near-infrared (FT-NIR) spectroscopy equipped with the liquid probe in combination with an efficient wavelength selection method named searching combination moving window partial least squares (SCMWPLS) for the determination of ethanol, total soluble solids, total acidity, and total volatile acid contents in pineapple fruit wine fermentation using Saccharomyces cerevisiae var. burgundy. Two fermentation batches were produced, and the NIR spectral data of the calibration samples in the wavenumber range of 11,536–3952 cm⁻¹ were obtained over ten days of the fermentation period. SCMWPLS coupled with second derivatives searched and optimized spectral intervals containing useful information for building calibration models of four parameters. All models were validated by test samples obtained from an independent fermentation batch. The SCMWPLS models showed better predictions (the lowest value of prediction error and the highest value of residual predictive deviation) with acceptable statistical results (under confidence limits) among the results achieved by using the whole region. The results of this study demonstrated that FT-NIR spectroscopy using a liquid probe coupled with SCMWPLS could select the optimized wavelength regions while reducing spectral points and increasing accuracy for simultaneously monitoring the evolution of four chemical parameters in pineapple fruit wine fermentation.

A Validated Ultrasound-Assisted Extraction Coupled with SPE-HPLC-DAD for the Determination of Flavonoids in By-Products of Plant Origin: An Application Study for the Valorization of the Walnut Septum Membrane

Walnut byproducts have been shown to exert functional properties, but the literature on their bioactive content is still scarce. Among walnut byproducts, walnut septum is a dry ligneous diaphragm tissue that divides the two halves of the kernel, exhibiting nutritional and medicinal properties. These functional properties are owing to its flavonoid content, and in order to explore the flavonoid fraction, an ultrasound-assisted (UAE) protocol was combined with solid phase extraction (SPE) and coupled to high-performance liquid chromatography with diode array detection (HPLC-DAD) for the determination of flavonoids in Greek walnut septa membranes belonging to Chandler, Vina, and Franquette varieties. The proposed UAE-SPE-HPLC-DAD method was validated and the relative standard deviations (RSD%) of the within-day and between-day assays were lower than 6.2 and 8.5, respectively, showing good precision, and high accuracy ranging from 90.8 (apigenin) to 97.5% (catechin) for within-day assay, and from 88.5 (myricetin) to 96.2% (catechin) for between-day assay. Overall, seven flavonoids were determined (catechin, rutin, myricetin, luteolin, quercetin, apigenin, and kaempferol) suggesting that the walnut septum is a rich source of bioactive constituents. The quantification results were further processed using ANOVA analysis to examine if there are statistically significant differences between the concentration of each flavonoid and the variety of the walnut septum.

Production of Functional Buttermilk and Soymilk Using Pediococcus acidilactici BD16 (alaD+)

Functional foods or drinks prepared using lactic acid bacteria (LAB) have recently gained considerable attention because they can offer additional nutritional and health benefits. The present study aimed to develop functional drinks by the fermentation of buttermilk and soymilk preparations using the Pediococcus acidilactici BD16 (alaD⁺) strain expressing the L-alanine dehydrogenase enzyme. LAB fermentation was carried out for 24 h and its impact on the physicochemical and quality attributes of the fermented drinks was evaluated. Levels of total antioxidants, phenolics, flavonoids, and especially L-alanine enhanced significantly after LAB fermentation. Further, GC-MS-based metabolomic fingerprinting was performed to identify the presence of bioactive metabolites such as 1,2-benzenedicarboxylic acid, 1-dodecene, 2-aminononadecane, 3-octadecene, 4-octen-3-one, acetic acid, azanonane, benzaldehyde, benzoic acid, chloroacetic acid, colchicine, heptadecanenitrile, hexadecanal, quercetin, and triacontane, which could be accountable for the improvement of organoleptic attributes and health benefits of the drinks. Meanwhile, the levels of certain undesirable metabolites such as 1-pentadecene, 2-bromopropionic acid, 8-heptadecene, formic acid, and propionic acid, which impart bitterness, rancidity, and unpleasant odor to the fermented drinks, were reduced considerably after LAB fermentation. This study is probably the first of its kind that highlights the application of P. acidilactici BD16 (alaD⁺) as a starter culture candidate for the production of functional buttermilk and soymilk.

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.

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.

Development of a Wine Metabolomics Approach for the Authenticity Assessment of Selected Greek Red Wines

Wine metabolomics constitutes a powerful discipline towards wine authenticity assessment through the simultaneous exploration of multiple classes of compounds in the wine matrix. Over the last decades, wines from autochthonous Greek grape varieties have become increasingly popular among wine connoisseurs, attracting great interest for their authentication and chemical characterization. In this work, 46 red wine samples from Agiorgitiko and Xinomavro grape varieties were collected from wineries in two important winemaking regions of Greece during two consecutive vintages and analyzed using ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QToF-MS). A targeted metabolomics methodology was developed, including the determination and quantification of 28 phenolic compounds from different classes (hydroxycinnamic acids, hydroxybenzoic acids, stilbenes and flavonoids). Moreover, 86 compounds were detected and tentatively identified via a robust suspect screening workflow using an in-house database of 420 wine related compounds. Supervised chemometric techniques were employed to build an accurate and robust model to discriminate between two varieties.

Qualitative Factor-Based Comparison of NMR, Targeted and Untargeted GC-MS and LC-MS on the Metabolomic Profiles of Rioja and Priorat Red Wines

Wine origin and ageing are two factors related to wine quality which in turn is associated to wine metabolome. Currently, new metabolomic techniques and proper statistics procedures allow accurate profiling of wine metabolome. Thus, the main goal was to evaluate different metabolomic methodologies on their ability to provide patterns on the wine metabolome based on selected factors, such as ageing of barrel-aged wine (factor time), prior usage of the barrels (factor barrel-type), and differences between wine ageing in barrels or glass bottles (factor bottled-wine). In the current study, we implement NMR, targeted and untargeted GC-MS and LC-MS metabolomic analytical techniques so as to gain insights into the volatile and nonvolatile wine metabolome composition of red wines from two cellars located in the only two Spanish Qualified Appellations of Origin; DOQ Priorat and DOCa Rioja regions. Overall, 95 differentially significant metabolites were identified facilitating the evaluation of the analytical methodologies performance and finding common trends of those metabolites depending on the considered factor. The results did not favor NMR as an effective technique on the current dataset whereas suggested LC-MS as an adequate technique for revealing differences based on the factor time, targeted GC-MS on the factor barrel-type, and untargeted GC-MS on the factor bottled-wine. Thus, a combination of different metabolomic techniques is necessary for a complete overview of the metabolome changes. These results ease the selection of the correct methodology depending on the specific factor investigated.

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.

HPLC-MS/MS-based targeted metabolomic method for profiling of malvidin derivatives in dry red wines

Anthocyanin derivatives are critical components that impart color to aging red wine. In this study, we developed a targeted metabolomic method for the simultaneously profiling of the primary thirty-seven malvidin-derived anthocyanin derivatives in red wine, including various pyranoanthocyanins and flavanols-related condensation products. First, high-performance liquid chromatography (HPLC) tandem ion trap and triple-quadrupole (QqQ) mass spectrometry were used to construct the mass spectral and chromatographic database of the anthocyanin derivatives that were formed in a model wine solution. Next, the targeted profiling analysis of these compounds was achieved on a QqQ mass spectrometer in the multiple reaction monitoring mode (MRM). The method displayed excellent linearity (R² 0.9391-0.9998), sensitivity (0.221-0.604 μg/L of limit of detection (LOD) and 0.274-1.157 μg/L of limit of quantification (LOQ) equivalent to malvidin-3-O-glucoside (Mv-glc)), and repeatability (less than 10% and 15% for intra-day and inter-day relative standard deviation (RSD) respectively). Partial least squares discriminant analysis (PLS-DA) based on this method showed great discrimination over different vintage wines, thereby promising to be an effective tool in wine anthocyanin and aging related study.

Classification of Red Wines Produced from Zweigelt and Rondo Grape Varieties Based on the Analysis of Phenolic Compounds by UPLC-PDA-MS/MS

The authentication of grape variety from which wine is produced is necessary for protecting a consumer from adulteration and false labelling. The aim of this study was to analyze phenolic compounds in red monovarietal wines produced from Zweigelt (Vitis vinifera) and Rondo (non-Vitis vinifera) varieties while using the UPLC-PDA-MS/MS method and to assess whether these wines can be classified according to grape variety that is based on chemometric analysis. Fifty-five phenolic compounds belonging to five classes—anthocyanins, flavonols, flavan-3-ols, phenolic acids, and stilbenes—were identified and quantified in Zweigelt and Rondo wines. The wines of the Zweigelt variety were characterized by lower concentrations of phenolic compounds than those of the Rondo variety. Furthermore, wines of the Zweigelt variety contained the highest concentrations of flavan-3-ols, and wines of the Rondo variety—the highest concentrations of anthocyanins. Hierarchical cluster analysis (HCA) revealed that Zweigelt wines and Rondo wines formed two separate groups. The Rondo group was divided into two subgroups, differing in type of malolactic fermentation (spontaneous or induced). Phenolic compounds analysis by means of UPLC-PDA-MS/MS combined with HCA is a useful tool for the classification of red wines that were produced from Zweigelt and Rondo grape varieties, regardless of yeast strain and type of malolactic fermentation.

Chemical typicality of South American red wines classified according to their volatile and phenolic compounds using multivariate analysis

In this study, 83 wines representating four commercial categories: "Argentinean Malbec", "Brazilian Merlot", "Uruguayan Tannat" and "Chilean Carménère" were analyzed according to their phenolic and volatile compounds. The objective was to identify the chemical compounds that would typify each category. From approximately about 600 peaks obtained by chromatographic techniques, 169 were identified and 53 of them were selected for multivariate statistical analysis. Chilean Carménère was the best discriminated group by the methods applied in our study, followed by Argentinean Malbec. Brazilian Merlot mixed mainly with some Carménère, whileTannat mixed with all wines categories, especially Malbec. In general, Chilean Carménère wines can be characterized by a bluish color, higher amounts of sulphur dioxide, higher content of octanoic acid, isobutanol, ethyl isoamyl succinate and catechin and a smaller amount of quercetin. These data can contribute for further process of authenticity or typification of South American red wines.

Different forms of nitrogen application affect metabolite patterns in grapevine leaves and the sensory of wine

The quality of grapevine berries, must and wine is influenced by environmental and viticultural inputs and their complex interactions. Aroma and flavour are decisive for quality and are mainly determined by primary and secondary metabolites. In particular, phenolic compounds contribute to berry and wine quality. The influence of various nitrogen forms on i) the composition of phenolic compounds in leaves and wine and; ii) the resulting wine quality were studied in a vineyard system. Must and wine quality was evaluated by chemical analysis and sensory testing. Metabolomic profiling was also performed. Aroma and sensory profile were significantly changed by the application of nitrogen in contrast to no nitrogen fertilisation. The levels of 33 metabolites in leaves and 55 metabolites in wine were significantly changed altered by fertilisation with the various nitrogen forms. In leaves, more metabolites were increased by the use of calcium nitrate or ammonium but were decreased by the use of urea. In terms of wine, the used nitrogen forms decreased more metabolites compared with no fertilisation.

Comprehensive study of sulfamethoxazole effects in marine mussels: Bioconcentration, enzymatic activities and metabolomics

Antibiotics accumulation in aquatic organisms may be of great concern from an ecological point of view but also from a human perspective, especially when they are accumulated in edible animals like marine mussels. In this work, mussels (Mytilus galloprovincialis) were exposed to sulfamethoxazole antibiotic (SMX) at 10 µg/L during 96 h, followed by 24 h of depuration. The experiment was carried out at summer and winter conditions. SMX showed a bioconcentration factor in mussel of 1.5 L/kg (dry weight) and 69% of the compound was eliminated from the organism in 24 h. The metabolomics approach revealed alterations in amino acids levels (aspartate, phenylalanine, valine and tryptophan) pinpointing disturbances in osmotic regulation and energy metabolism. Besides, the levels of some nucleotides (guanosine and inosine) and a carboxylic acid were also affected. However, SMX exposed mussels did not show any significant alteration in the enzymatic activities related to the xenobiotic metabolism and oxidative stress. Moreover, some of the changes observed in mussel's metabolites suggested alterations in mussel's organoleptic characteristics that can affect its quality as seafood commodity. Overall, our results showed that SMX exposure to marine mussels may have ecological implications by provoking sub-lethal effects to exposed organisms. Nevertheless, no risk for consumers derived from mussel ingestion is expected due to the low bioconcentration capacity of SMX and fast depuration in this seafood type.

Metabolomics-Based Approach for the Discrimination of Potato Varieties ( Solanum tuberosum) using UPLC-IMS-QToF

One hundred eighty-two authentic potato samples ( Solanum tuberosum) of known variety were collected from various German regions in 2016 and 2017. Samples were extracted with a liquid-liquid-extraction protocol that included isopropanol, methanol, and water in order to focus on lipophilic metabolites. The analysis of nonpolar extracts was performed using an UPLC-IMS-QToF-MS system; data sets obtained were evaluated via multivariate data analysis. A selection of 14 key metabolites with a significant difference in their abundance profiles was identified. This set of markers contained four hydroxylated glucocerebrosides, two phosphoinositols, one phosphocholine, and seven acylated sterol glucosides based on stigmasterol and β-sitosterol, which primarily enable the varietal discrimination. Fragments and neutral losses commonly appearing within one class or subclass of lipids were summarized within a new database that included ion mobility data. The performance of the approach was verified with twenty-nine commercial potato samples.

A Triple Quadrupole and a Hybrid Quadrupole Orbitrap Mass Spectrometer in Comparison for Polyphenol Quantitation

Liquid chromatography coupled to low-resolution mass spectrometry (LRMS) has historically been a popular approach for compound quantitation. Recently, high-resolution mass spectrometry (HRMS) technical developments led to the introduction of new approaches for quantitative analysis. Whereas the performances of HRMS have been largely assessed for qualitative purposes, there are still questions about its suitability for quantitative analysis. Several papers on LRMS and HRMS comparison have been published; however, none of them was applied to polyphenol quantitation. In this work, a comparison between HRMS, operated in data-dependent acquisition mode, and LRMS, operated in selected-reaction-monitoring mode, was performed for polyphenol quantitation in wine. The two techniques were evaluated in terms of sensitivity, linearity range, matrix effect, and precision, showing the better performances of HRMS. The suitability of HRMS for quantitation purposes as well as qualitative screening makes HRMS the new technique of choice for both targeted and untargeted analysis.