Evidence of vintage effects on grape wines using 1H NMR-based metabolomic study

Automatic Chemical Profiling of Wine by Proton Nuclear Magnetic Resonance Spectroscopy

We report the development of MagMet-W (magnetic resonance for metabolomics of wine), a software program that can automatically determine the chemical composition of wine via 1H nuclear magnetic resonance (NMR) spectroscopy. MagMet-W is an extension of MagMet developed for the automated metabolomic analysis of human serum by 1H NMR. We identified 70 compounds suitable for inclusion into MagMet-W. We then obtained 1D 1H NMR reference spectra of the pure compounds at 700 MHz and incorporated these spectra into the MagMet-W compound library. The processing of the wine NMR spectra and profiling of the 70 wine compounds were then optimized based on manual 1H NMR analysis. MagMet-W can automatically identify 70 wine compounds in most wine samples and can quantify them to 10-15% of the manually determined concentrations, and it can analyze multiple spectra simultaneously, at 10 min per spectrum. The MagMet-W Web server is available at https://www.magmet.ca.

Must protection, sulfites versus bioprotection: A metabolomic study

The reduction of chemical inputs in wine has become one of the main challenges of the wine industry. One of the alternatives to sulfites developed is bioprotection, which consists in using non-Saccharomyces strains to prevent microbial deviation. However, the impact of substituting sulfites by bioprotection on the final wine remains poorly studied. For the first time, we characterized this impact on Chardonnay wine through an integrative approach. Interestingly, physico-chemical analysis did not reveal any difference between both treatments regarding classical oenological parameters. Nevertheless, bioprotection did not seem to provide as much protection against oxidation as sulfites, as observed through phenolic compound analysis. At a deeper level, untargeted metabolomic analyses revealed substantial changes in wine composition according to must treatment. In particular, the specific footprint of each treatment revealed an impact on nitrogen-containing compounds. This observation could be related to modifications in S. cerevisiae metabolism, in particular amino acid biosynthesis and tryptophan metabolism pathways. Thus, the type of must treatment seemed to impact metabolic fluxes of yeast differently, leading to the production of different compounds. For example, we observed glutathione and melatonin, compounds with antioxidant properties, which were enhanced with sulfites, but not with bioprotection. However, despite substantial modifications in wines regarding their chemical composition, the change in must treatment did not seem to impact the sensory profile of wine. This integrative approach has provided relevant new insights on the impact of sulfite substitution by bioprotection on Chardonnay wines.

Emerging trends and applications of metabolomics in food science and nutrition

The study of all chemical processes involving metabolites is known as metabolomics. It has been developed into an essential tool in several disciplines, such as the study of plant physiology, drug development, human diseases, and nutrition. The field of food science, diagnostic biomarker research, etiological analysis in the field of medical therapy, and raw material quality, processing, and safety have all benefited from the use of metabolomics recently. Food metabolomics includes the use of metabolomics in food production, processing, and human diets. As a result of changing consumer habits and the rising of food industries all over the world, there is a remarkable increase in interest in food quality and safety. It requires the employment of various technologies for the food supply chain, processing of food, and even plant breeding. This can be achieved by understanding the metabolome of food, including its biochemistry and composition. Additionally, Food metabolomics can be used to determine the similarities and differences across crop kinds, as an indicator for tracking the process of ripening to increase crops' shelf life and attractiveness, and identifying metabolites linked to pathways responsible for postharvest disorders. Moreover, nutritional metabolomics is used to investigate the connection between diet and human health through detection of certain biomarkers. This review assessed and compiled literature on food metabolomics research with an emphasis on metabolite extraction, detection, and data processing as well as its applications to the study of food nutrition, food-based illness, and phytochemical analysis. Several studies have been published on the applications of metabolomics in food but further research concerning the use of standard reproducible procedures must be done. The results published showed promising uses in the food industry in many areas such as food production, processing, and human diets. Finally, metabolome-wide association studies (MWASs) could also be a useful predictor to detect the connection between certain diseases and low molecular weight biomarkers.

1H NMR-Based Metabolomics to Assess the Impact of Soil Type on the Chemical Composition of Nero d'Avola Red Wines

In this study, the soil effect on the micro-component composition of Nero d'Avola wines obtained from different locations was investigated through ¹H NMR-based metabolomics. Two different approaches were applied: the targeted (TA) and the non-targeted one (NTA). The former differentiated the wines by profiling (i.e., by identifying and quantifying) a number of different metabolites. The latter provided wine fingerprinting by processing the entire spectra with multivariate statistical analysis. NTA also allowed investigation of the hydrogen bond network inside wines via the analysis of ¹H NMR chemical shift dispersions. Results showed that the differences among wines were due not only to the concentrations of various analytes but also to the characteristics of the H-bond network where different solutes were involved. The H-bond network affects both gustatory and olfactory perceptions by modulating the way how solutes interact with the human sensorial receptors. Moreover, the aforementioned H-bond network is also related to the soil properties from which the grapes were taken. Therefore, the present study can be considered a good attempt to investigate terroir, i.e., the relationship between wine quality and soil characteristics.

Widely Targeted Metabolomics Was Used to Reveal the Differences between Non-Volatile Compounds in Different Wines and Their Associations with Sensory Properties

In this study, metabolites from six varieties of wines, including 'Haasan' (A1), 'Zuoshaner' (A2), 'Beibinghong' (A3), 'Shuanghong' (A4), 'Zijingganlu' (A5), and 'Cabernet Sauvignon' (A6), were identified and quantified using widely targeted metabolomics analysis techniques. Based on the test results, 1172 metabolites were detected and classified into 18 categories. These include 62 amino acids, 178 alkaloids, 189 flavonoids, 106 phenols, 148 terpenoids, etc. Comparing the differential metabolites between the comparison groups of each variety, differences between varieties based on P-values and VIP values were shown. Among these differential metabolites, Trimethoprim and Crotonoside were screened out as core differential metabolites. Multiple comparisons also screened the biomarkers for each species. We used widely targeted metabolomics to reveal the differences between non-volatile compounds in different wines and their associations with sensory properties. We also used the simultaneous weighted gene co-expression network analysis (WGCNA) to correlate metabolites with sensory traits, including color difference values and taste characteristics. Two of the six key modules were screened by WGCNA for relevance to sensory traits (brown module and turquoise module). This study provides a high-throughput method for linking compounds to various sensory characteristics of food, opening up new avenues for explaining differences in different varieties of wine.

Effects of Different Pesticides on the Brewing of Wine Investigated by GC-MS-Based Metabolomics

The application of pesticides is critical during the growth of high-quality grape for wine making. However, pesticide residues have significant influence on the wine flavor. In this study, gas chromatography-mass spectrometry (GC-MS) was performed and the obtained datasets were analyzed with multivariate statistical methods to investigate changes in flavor substances in wine during fermentation. The principal component analysis (PCA) score plot showed significant differences in the metabolites of wine treated with various pesticides. In trials using five pesticides (hexaconazole, difenoconazole, flutriafol, tebuconazole, and propiconazole), more than 86 metabolites were changed. Most of these metabolites were natural flavor compounds, like carbohydrates, amino acids, and short-chain fatty acids and their derivatives, which essentially define the appearance, aroma, flavor, and taste of the wine. Moreover, the five pesticides added to grape pulp exhibited different effects on the metabolic pathways, involving mainly alanine, aspartate and glutamate metabolism, butanoate metabolism, arginine, and proline metabolism. The results of this study will provide new insight into the potential impact of pesticide residues on the metabolites and sensory profile of wine during fermentation.

Research Progress in Imaging Technology for Assessing Quality in Wine Grapes and Seeds

The chemical composition of wine grapes changes qualitatively and quantitatively during the ripening process. In addition to the sugar content, which determines the alcohol content of the wine, it is necessary to consider the phenolic composition of the grape skins and seeds to obtain quality red wines. In this work, some imaging techniques have been used for the comprehensive characterisation of the chemical composition of red grapes (cv. Tempranillo and cv. Syrah) grown in a warm-climate region during two seasons. In addition, and for the first time, mathematical models trained with laboratory images have been extrapolated for using in field images, obtaining interesting results. Determination coefficients of 0.90 for sugars, 0.73 for total phenols, and 0.73 for individual anthocyanins in grape skins have been achieved with a portable hyperspectral camera between 400 and 1000 nm, and 0.83 for total and individual phenols in grape seeds with a desktop hyperspectral camera between 900 and 1700 nm.

1H-NMR Metabolomics as a Tool for Winemaking Monitoring

The chemical composition of wine is known to be influenced by multiple factors including some viticulture practices and winemaking processes. 1H-NMR metabolomics has been successfully applied to the study of wine authenticity. In the present study, 1H-NMR metabolomics in combination with multivariate analysis was applied to investigate the effects of grape maturity and enzyme and fining treatments on Cabernet Sauvignon wines. A total of forty wine metabolites were quantified. Three different stages of maturity were studied (under-maturity, maturity and over-maturity). Enzyme treatments were carried out using two pectolytic enzymes (E1 and E2). Finally, two proteinaceous fining treatments were compared (vegetable protein, fining F1; pea protein and PVPP, fining F2). The results show a clear difference between the three stages of maturity, with an impact on different classes of metabolites including amino acids, organic acids, sugars, phenolic compounds, alcohols and esters. A clear separation between enzymes E1 and E2 was observed. Both fining agents had a significant effect on metabolite concentrations. The results demonstrate that 1H-NMR metabolomics provides a fast and robust approach to study the effect of winemaking processes on wine metabolites. These results support the interest to pursue the development of 1H-NMR metabolomics to investigate the effects of winemaking on wine quality.

Workflow to Investigate Subtle Differences in Wine Volatile Metabolome Induced by Different Root Systems and Irrigation Regimes

To allow for a broad survey of subtle metabolic shifts in wine caused by rootstock and irrigation, an integrated metabolomics-based workflow followed by quantitation was developed. This workflow was particularly useful when applied to a poorly studied red grape variety cv. Chambourcin. Allowing volatile metabolites that otherwise may have been missed with a targeted analysis to be included, this approach allowed deeper modeling of treatment differences which then could be used to identify important compounds. Wines produced on a per vine basis, over two years, were analyzed using SPME-GC-MS/MS. From the 382 and 221 features that differed significantly among rootstocks in 2017 and 2018, respectively, we tentatively identified 94 compounds by library search and retention index, with 22 confirmed and quantified using authentic standards. Own-rooted Chambourcin differed from other root systems for multiple volatile compounds with fewer differences among grafted vines. For example, the average concentration of β-Damascenone present in own-rooted vines (9.49 µg/L) was significantly lower in other rootstocks (8.59 µg/L), whereas mean Linalool was significantly higher in 1103P rootstock compared to own-rooted. β-Damascenone was higher in regulated deficit irrigation (RDI) than other treatments. The approach outlined not only was shown to be useful for scientific investigation, but also in creating a protocol for analysis that would ensure differences of interest to the industry are not missed.

A Rapid and Accurate 1HNMR Method for the Identification and Quantification of Major Constituents in Qishen Yiqi Dripping Pills

BACKGROUND

Qishen Yiqi dripping pills (QSYQ), composed of four herbal medicines-Salvia miltiorrhiza, Astragalus membranaceus, Panax notoginseng, and Dalbergiaodorifera-are widely used to treat ischemic cerebrovascular and hemorrhagic cerebrovascular conditions.

OBJECTIVE

In this study, a rapid and accurate proton NMR (1HNMR) spectroscopy method was established to control the quality of QSYQ and ensure their clinical efficacy.

METHOD

Firstly, different types of metabolites were identified based on the proton signal peaks of chemical shifts, coupling constants, and related information provided through two-dimensional NMR spectroscopy. Secondly, a quantitative 1HNMR method was established for the simultaneous determination of major constituents in QSYQ samples. In addition, an HPLC method was performed to verify the results obtained by the quantitative proton NMR (qHNMR)  method.

RESULTS

In the present study, 26 metabolites were identified in the 1HNMR spectra of QSYQ. In addition, a rapid and accruate qHNMR method was established for the simultaneous determination of protocatechualdehyde, rosmarinic acid, danshensu, calycosin-7-O-β-D-glucoside, and ononin in ten batches of QSYQ samples for the first time. Moreover, the proposed qHNMR method and HPLC method were compared using Bland-Altman and plots Passing-Bablok regression, indicating no significant differences and a strong correlation between the two analytical methods.

CONCLUSIONS

This method is an important tool for the identification and quantification of major constituents in QSYQ.

HIGHLIGHTS

Compared with traditional HPLC, the established qHNMR method has the advantages of simple sample preparation, short analysis time, and non-destructive analysis.

Geographical origin authentication of southern Brazilian red wines by means of EEM-pH four-way data modelling coupled with one class classification approach

EEM data recorded at different pH values was exploited by MCR-ALS in order to determine qualitative information about Brazilian red wines. In addition, the geographical traceability of wines produced in the Serra Gaúcha (Rio Grande do Sul) was carried out by DD-SIMCA considering 53 samples from the target class and 20 from other producing regions. The fluorescence signal corresponds to 9 EEMs recorded at different pH (3-11), generating four-way data. By MCR-ALS decomposition, eight factors were retrieved and related to typical chemical compounds found in red wine. In addition, the EEM pH data was used to build a one-class classification model, considering that MCR scores and all samples of the target class were properly recognised as belonging to the target class, with maximal sensitivity equal to 1. Samples of the non-target class were also adequately rejected by the model, and the specificity was found to be 0.97.

Quality evaluation of Cabernet Sauvignon wines in different vintages by 1H nuclear magnetic resonance-based metabolomics

A proton nuclear magnetic resonance (NMR)-based metabolomic study was used to characterize 2009, 2010, 2011, and 2012 vintages of Cabernet Sauvignon wines from Ningxia, which were vinified using the same fermentation technique. The pattern recognition methods of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal PLS-DA (OPLS-DA) clearly distinguished between the different vintages of wine driven by the following metabolites: valine, 2,3-butanediol, ethyl acetate, proline, succinic acid, lactic acid, acetic acid, glycerol, gallic acid, and choline. The PLS-DA loading plots also differentiated among the metabolites of different vintages. In the 2009 vintage wines, we found the highest levels of gallic acid, valine, proline, and 2,3-butanediol. The 2011 vintage wines contained the highest levels of lactic acid, and the highest levels of ethyl acetate, succinic acid, glycerol, and choline were observed in the 2012 vintage wines. We selected eight metabolites from the 1H NMR spectra that were quantified according to their peak areas, and the concentrations were in agreement with the results of PLS-DA and OPLS-DA analyses.

Combination of two analytical techniques improves wine classification by Vineyard, Region, and vintage

Three important wine parameters: vineyard, region, and vintage year, were evaluated using fifteen Vitis vinifera L. 'Pinot noir' wines derived from the same scion clone (Pinot noir 667). These wines were produced from two vintage years (2015 and 2016) and eight different regions along the Pacific Coast of the United States. We successfully improved the classification of the selected Pinot noir wines by combining an untargeted 1D ¹H NMR analysis with a targeted peptide based differential sensing array. NMR spectroscopy was used to evaluate the chemical fingerprint of the wines, whereas the peptide-based sensing array is known to mimic the senses of taste, smell, and palate texture by characterizing the phenolic profile. Multivariate and univariate statistical analyses of the combined NMR and differential sensing array dataset classified the genetically identical Pinot noir wines on the basis of distinctive metabolic signatures associated with the region of growth, vineyard, and vintage year.

Metabolomic understanding of the difference between unpruning and pruning cultivation of tea (Camellia sinensis) plants

Tea (Camellia sinensis) leaf quality depends on several factors such as plucking seasons, cultivation practices, and climatic conditions, which affect the chemical compositions of tea leaves. Pruning has been practiced as one of the common cultivation managements in tea cultivation and is hypothesized to exhibit metabolic differences from unpruned tea plants. Although metabolomics studies provide immense information about production of distinct tea products, the metabolic physiology of the plants cultivated under unpruning conditions is poorly understood. Therefore, in the present study, we explored the metabolic characteristics of tea leaves obtained from unpruned tea plants collected at different plucking seasons in a single year and in a given plucking time in the three successive years, through ¹H NMR-based metabolomics approach. Seasonal variations in diverse tea leaf metabolites both in pruned and unpruned tea plants were observed along with marked metabolic differences in tea leaves collected from pruned and unpruned tea plants in a given plucking time. Particularly, in abnormal year of vintage with high rainfall in 2018, high synthesis of glucose followed by high accumulations of catechin, including its derivatives, in unpruned tea, demonstrated intense active photosynthesis compared to pruned tea plants, indicating different metabolic responses of pruned and unpruned tea plants to similar climatic conditions. The current study highlights the important role of tea cultivation practices in tea plants for better management of leaf quality and the strong metabolic dependence on climatic conditions in a given vintage.

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.

Wine and grape marc spirits metabolomics

INTRODUCTION

Mass spectrometry (MS)-based and nuclear magnetic resonance (NMR) spectroscopic analyses play a key role in the field of metabolomics due to their important advantages. The use of metabolomics in wine and grape marc spirits allows a more holistic perspective in monitoring and gaining information on the making processes and thus it can assist on the improvement of their quality.

OBJECTIVES

This review surveys the latest metabolomics approaches for wine and grape marc spirits with a focus on the description of MS-based and NMR spectroscopic analytical techniques.

METHODS

We reviewed the literature to identify metabolomic studies of wine and grape marc spirits that were published until the end of 2017, with the key term combinations of 'metabolomics', 'wine' and 'grape marc spirits'. Through the reference lists from these studies, additional articles were identified.

RESULTS

The results of this review showed that the application of different metabolomics approaches has significantly increased the knowledge of wine metabolome and grape marc spirits; however there is not yet a single analytical platform that can completely separate, detect and identify all metabolites in one analysis.

CONCLUSIONS

The authentication and quality control of wines and grape marc spirits has to be taken with caution, since the product's chemical composition could be affected by many factors. Despite intrinsic limitations, NMR spectroscopy and MS based strategies remain the key analytical methods in metabolomics studies. Authenticity, traceability and health issues related to their consumption are the major research initiatives in wine and grape marc spirits metabolomics analysis.

Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches

Chemical analysis of grape juice and wine has been performed for over 50 years in a targeted manner to determine a limited number of compounds using Gas Chromatography, Mass-Spectrometry (GC-MS) and High Pressure Liquid Chromatography (HPLC). Therefore, it only allowed the determination of metabolites that are present in high concentration, including major sugars, amino acids and some important carboxylic acids. Thus, the roles of many significant but less concentrated metabolites during wine making process are still not known. This is where metabolomics shows its enormous potential, mainly because of its capability in analyzing over 1000 metabolites in a single run due to the recent advancements of high resolution and sensitive analytical instruments. Metabolomics has predominantly been adopted by many wine scientists as a hypothesis-generating tool in an unbiased and non-targeted way to address various issues, including characterization of geographical origin (terroir) and wine yeast metabolic traits, determination of biomarkers for aroma compounds, and the monitoring of growth developments of grape vines and grapes. The aim of this review is to explore the published literature that made use of both targeted and untargeted metabolomics to study grapes and wines and also the fermentation process. In addition, insights are also provided into many other possible avenues where metabolomics shows tremendous potential as a question-driven approach in grape and wine research.

High-resolution mass spectrometry metabolomics of grape chemical markers to reveal use of not-allowed varieties in the production of Amarone and Recioto wines

INTRODUCTION

Grape varieties allowed to produce Amarone della Valpolicella and Recioto DOCG wines are strictly regulated by their disciplinary of production. These are Corvina Veronese and Corvinone grapes, to a lesser extent also Rondinella can be used. The use of other varieties, is not allowed.

OBJECTIVES

To identify chemical markers suitable to reveal addition of two not allowed grape varieties to the Corvina/Corvinone blend, such as Primitivo or Negro Amaro.

METHODS

The identification of the secondary metabolites of the four grape varieties was conducted by high-resolution mass spectrometry (HRMS) metabolomics. By using the signals of these metabolites the indexes able to identify the presence of Primitivo or Negro Amaro grapes in the Corvina/Corvinone 1:1 blend were calculated.

RESULTS

Indexes of laricitrin (Lr), delphinidin (Dp), and petunidin (Pt) signals were effective to identify the use of 10% Primitivo, while α-terpineol pentosyl-hexoside and linalool pentosyl-hexoside reveal the presence of Negro Amaro in the grape blend.

CONCLUSIONS

Varietal markers useful to detect the presence of Primitivo and Negro Amaro in the grape blend were identified by HRMS metabolomics, a method suitable to check the identity of grapes on arrival at the winery, as well as the fermenting musts. The effectiveness of the identified markers in the final wines have to be confirmed. Potentially, a similar approach can be used to reveal analogous frauds performed on other high-quality wines.

Wine evolution during bottle aging, studied by 1H NMR spectroscopy and multivariate statistical analysis

The study of wine evolution during bottle aging is an important aspect of wine quality. Ten different red wines (Vitis vinifera) from Piedmont region were analysed 3 months after bottling and after a further 48 month conservation in a climate controlled wine cellar kept at a constant/controlled temperature of 12 °C. Two white wines (Vitis vinifera) were included in this study for comparison purposes. White wines were analysed 3 months after bottling and after further 24 months of bottle aging in the same climate controlled wine cellar. Metabolite changes during this period were evaluated using ¹H NMR spectroscopy combined with statistical analysis. Metabolite variations due to wine aging were minimal compared to those that resulted from a different wine type and wine geographical origin. Therefore, it was necessary to remove this source of variability to discriminate between fresh and refined samples. The storage at low and controlled temperature for 2 or 4 years permitted a slow but progressive evolution of all wines under investigation. 1H NMR spectroscopy, implemented with statistical data analysis, allowed identifying and differentiating wine samples from the two aging stages. In most wines, a decrease in organic acids (lactic acid, succinic acid and tartaric acid) and an increase in esters (ethyl acetate and ethyl lactate) was observed. Catechin and epicatechin decreased during aging in all wines while gallic acid increased in almost all red wines.

Cool-Climate Red Wines-Chemical Composition and Comparison of Two Protocols for ¹H-NMR Analysis

This study investigates the metabolome of 26 experimental cool-climate wines made from 22 grape varieties using two different protocols for wine analysis by proton nuclear magnetic resonance (¹H-NMR) spectroscopy. The wine samples were analyzed as-is (wet) and as dried samples. The NMR datasets were preprocessed by alignment and mean centering. No normalization or scaling was performed. The “wet” method preserved the inherent properties of the samples and provided a fast and effective overview of the molecular composition of the wines. The “dried” method yielded a slightly better sensitivity towards a broader range of the compounds present in wines. A total of 27 metabolites including amino acids, organic acids, sugars, and alkaloids were identified in the ¹H-NMR spectra of the wine samples. Principal component analysis was performed on both NMR datasets evidencing well-defined molecular fingerprints for ‘Baco Noir’, ‘Bolero’, ‘Cabernet Cantor’, ‘Cabernet Cortis’, ‘Don Muscat’, ‘Eszter’, ‘Golubok’, ‘New York Muscat’, ‘Regent’, ‘Rondo’, ‘Triomphe d’Alsace’, ‘Précose Noir’, and ‘Vinoslivy’ wines. Amongst the identified metabolites, lactic acid, succinic acid, acetic acid, gallic acid, glycerol, and methanol were found to drive sample groupings. The ¹H-NMR data was compared to the absolute concentration values obtained from a reference Fourier transform infrared method, evidencing a high correlation.

NMR Spectroscopy Protocols for Food Metabolomics Applications

NMR spectroscopy has become an indispensable tool for the metabolic profiling of foods and food products. In the present protocol, we report an analytical approach based on liquid-state NMR for the determination of polar and nonpolar metabolites in some common liquid (wine, spirits, juice) and solid (cheese, coffee, honey) foods. Although the diversity of foods precludes the use of a single protocol, with small modifications, the proposed methodologies can be adapted to a broader range of foodstuffs.

Exploring the Effects of Geographical Origin on the Chemical Composition and Quality Grading of Vitis vinifera L. cv. Chardonnay Grapes

The relationship between berry chemical composition, region of origin and quality grade was investigated for Chardonnay grapes sourced from vineyards located in seven South Australian Geographical Indications (GI). Measurements of basic chemical parameters, amino acids, elements, and free and bound volatiles were conducted for grapes collected during 2015 and 2016. Multiple factor analysis (MFA) was used to determine the sets of data that best discriminated each GI and quality grade. Important components for the discrimination of grapes based on GI were 2-phenylethanol, benzyl alcohol and C₆ compounds, as well as Cu, Zn, and Mg, titratable acidity (TA), total soluble solids (TSS), and pH. Discriminant analysis (DA) based on MFA results correctly classified 100% of the samples into GI in 2015 and 2016. Classification according to grade was achieved based on the results for elements such as Cu, Na, Fe, volatiles including C₆ and aryl alcohols, hydrolytically-released volatiles such as (Z)-linalool oxide and vitispirane, pH, TSS, alanine and proline. Correct classification through DA according to grade was 100% for both vintages. Significant correlations were observed between climate, GI, grade, and berry composition. Climate influenced the synthesis of free and bound volatiles as well as amino acids, sugars, and acids, as a result of higher temperatures and precipitation.

Wine by-products: phenolic characterization and antioxidant activity evaluation of grapes and grape pomaces from six different French grape varieties

Grenache, Syrah, Carignan Noir, Mourvèdre, Counoise and Alicante Bouchet grape seeds and skins, harvested in 2009 and 2010 in the Rhône valley area of France, and their respective pomaces remaining after vinification, were analyzed for their phenolic composition and antioxidant activity. The polyphenol content was quantified by HPLC and the Folin-Ciocalteu assay. The antioxidant potential was measured with four different assays: ORAC, FRAP, ABTS and DPPH. Seeds contained higher amounts of total polyphenols, up to 44.5 mg of gallic acid equivalent [GAE]/g dry weight in Alicante pomace, than skin extracts. The maximum total phenolic in skins was 31.6 mg GAE/g dry weight detected in 2010 Alicante pomace. Seeds also had the highest antioxidant capacity. HPLC analysis revealed that, despite the vinification process, pomaces still contained an appreciable amount of proanthocyanidins as well as several anthocyanin glycosides. Alicante and Syrah proved to be the varieties of most interest in terms of their potential development for nutraceutical purposes.

Targeted and nontargeted wine analysis by (1)h NMR spectroscopy combined with multivariate statistical analysis. Differentiation of important parameters: grape variety, geographical origin, year of vintage

The authenticity, the grape variety, the geographical origin, and the year of vintage of wines produced in Germany were investigated by (1)H NMR spectroscopy in combination with several steps of multivariate data analysis including principal component analysis (PCA), linear discrimination analysis (LDA), and multivariate analysis of variance (MANOVA) together with cross-validation (CV) embedded in a Monte Carlo resampling approach (MC) and others. A total of about 600 wines were selected and carefully collected from five wine-growing areas in the southern and southwestern parts of Germany. Simultaneous saturation of the resonances of water and ethanol by application of a low-power eight-frequency band irradiation using shaped pulses allowed for high receiver gain settings and hence optimized signal-to-noise ratios. Correct prediction of classification of the grape varieties of Pinot noir, Lemberger, Pinot blanc/Pinot gris, Müller-Thurgau, Riesling, and Gewürztraminer of 95% in the wine panel was achieved. The classification of the vintage of all analyzed wines resulted in correct predictions of 97 and 96%, respectively, for vintage 2008 (n = 318) and 2009 (n = 265). The geographic origin of all wines from the largest German wine-producing regions, Rheinpfalz, Rheinhessen, Mosel, Baden, and Württemberg, could be predicted 89% correctly on average. Each NMR spectrum could be regarded as the individual "fingerprint" of a wine sample, which includes information about variety, origin, vintage, physiological state, technological treatment, and others.

Characterization of volatile components in makgeolli, a traditional Korean rice wine, with or without pasteurization, during storage

Changes in the volatile components of unpasteurized and pasteurized makgeolli during 30 days of storage were investigated by gas chromatography-mass spectrometry (GC-MS) and GC-olfactometry (GC-O). A total of 11 odor-active compounds such as 3-methyl-1-butanol (isoamyl alcohol), 2-methyl-1-butanol, 2,3-butanediol, butanoic acid, 3-methylbutanoic acid (isovaleric acid), 2-methylbutanoic acid, 3-(methylthio)-1-propanol (methionol), 2-phenylethanol, ethyl decanoate, ethyl dodecanoate, and ethyl tetradecanoate were determined in both the pasteurized and unpasteurized makgeolli during 30 days of storage. Although there were no significant differences in the concentrations of odor-active compounds at the initial storage time, most of odor-active compounds were more significantly increased in unpasteurized makgeolli compared to the pasteurized one during the storage period.

Untangling the chemistry of port wine aging with the use of GC-FID, multivariate statistics, and network reconstruction

Chromatography separates the different components of complex mixtures and generates a fingerprint representing the chemical composition of the sample. The resulting data structure depends on the characteristics of the detector used, univariate for devices such as a flame ionization detector (FID) or multivariate for mass spectroscopy (MS). This study addresses the potential use of a univariate signal for a nontargeted approach to (i) classify samples according to a given process or perturbation, (ii) evaluate the feasibility of developing a screening procedure to select candidates related to the process, and (iii) provide insight into the chemical mechanisms that are affected by the perturbation. To achieve this, it was necessary to use and develop methods for data preprocessing and visualization tools to assist an analytical chemist to view and interpret complex multidimensional data sets. Dichloromethane Port wine extracts were collected using GC-FID; the chromatograms were then aligned with correlation optimized warping (COW) and subsequently analyzed with multivariate statistics (MVA) by principal component analysis (PCA) and partial least-squares regression (PLS-R). Furthermore, wavelets were used for peak calling and alignment refinement, and the resulting matrix was used to perform kinetic network reconstruction via correlation networks and maximum spanning trees. Network-target correlation projections were used to screen for potential chromatographic regions/peaks related to aging mechanisms. Results from PLS between aligned chromatograms and target molecules showed high X to Y correlations of 0.91, 092, and 0.89 with 5-hydroxymethylfurfural (HMF) (Maillard), acetaldehyde (oxidation), and 4,5-dimethyl-(5H)-3-hydroxy-2-furanone, respectively. The context of the correlation (and therefore likely kinetic) relationships among compounds detected by GC-FID and the relationships between target compounds within different regions of the network can be clearly seen.

Identification of brain-targeted bioactive dietary quercetin-3-O-glucuronide as a novel intervention for Alzheimer's disease

Epidemiological and preclinical studies indicate that polyphenol intake from moderate consumption of red wines may lower the relative risk for developing Alzheimer's disease (AD) dementia. There is limited information regarding the specific biological activities and cellular and molecular mechanisms by which wine polyphenolic components might modulate AD. We assessed accumulations of polyphenols in the rat brain following oral dosage with a Cabernet Sauvignon red wine and tested brain-targeted polyphenols for potential beneficial AD disease-modifying activities. We identified accumulations of select polyphenolic metabolites in the brain. We demonstrated that, in comparison to vehicle-control treatment, one of the brain-targeted polyphenol metabolites, quercetin-3-O-glucuronide, significantly reduced the generation of β-amyloid (Aβ) peptides by primary neuron cultures generated from the Tg2576 AD mouse model. Another brain-targeted metabolite, malvidin-3-O-glucoside, had no detectable effect on Aβ generation. Moreover, in an in vitro analysis using the photo-induced cross-linking of unmodified proteins (PICUP) technique, we found that quercetin-3-O-glucuronide is also capable of interfering with the initial protein-protein interaction of Aβ(1-40) and Aβ(1-42) that is necessary for the formation of neurotoxic oligomeric Aβ species. Lastly, we found that quercetin-3-O-glucuronide treatment, compared to vehicle-control treatment, significantly improved AD-type deficits in hippocampal formation basal synaptic transmission and long-term potentiation, possibly through mechanisms involving the activation of the c-Jun N-terminal kinases and the mitogen-activated protein kinase signaling pathways. Brain-targeted quercetin-3-O-glucuronide may simultaneously modulate multiple independent AD disease-modifying mechanisms and, as such, may contribute to the benefits of dietary supplementation with red wines as an effective intervention for AD.

NMR spectroscopy and chemometrics as a tool for anti-TNFα activity screening in crude extracts of grapes and other berries

The identification of active ingredients in crude plant extracts offers great advantages. In this study, nuclear magnetic resonance and chemometrics were used for the screening of in vitro anti-TNFα activity in different berry types. Solid phase extraction was applied and the resulting water, methanol-water (1:1), and methanol fractions were tested for the activity. The methanol-water fraction contained most of the phenolics and showed significantly higher activity than the other two fractions. In the second phase of this study, grapes from 'Trincadeira', 'Touriga Nacional', and 'Aragonês', at four developmental stages were metabolically classified and tested for the TNFα inhibition. The initial stages of grape development, green and veraison, were found more active against TNFα production as compared to the later ripe and harvest stages. Among the cultivars, 'Touriga Nacional' was found to be the most potent inhibitor. Different multivariate data analyses algorithms based on projections to latent structures were applied to correlate the NMR and TNFα inhibition data. The variable importance in the projections plot showed that phenolics like quercetin, myricetin, (+)-catechin, (-)-epicatechin, caftarate, and coutarate, were positively correlated with high activity. This work demonstrates the great potential of NMR spectroscopy in combination with chemometrics for the screening of large set of crude extracts, to study the effects of different variables on the activity, and identifying active compounds in complex mixtures like plant extracts. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-012-0406-8) contains supplementary material, which is available to authorized users.

Metabolomics reveals simultaneous influences of plant defence system and fungal growth in Botrytis cinerea-infected Vitis vinifera cv. Chardonnay berries

Botrytis cinerea is a fungal plant pathogen of grape berries, leading to economic and quality losses in wine production. The global metabolite changes induced by B. cinerea infection in grape have not been established to date, even though B. cinerea infection is known to cause significant changes in chemicals or metabolites. In order to better understand metabolic mechanisms linked to the infection process and to identify the metabolites associated with B. cinerea infection, (1)H NMR spectroscopy was used in global metabolite profiling and multivariate statistical analysis of berries from healthy and botrytized bunches. Pattern recognition methods, such as principal component analysis, revealed clear metabolic discriminations between healthy and botrytized berries of botrytized bunches and healthy berries of healthy bunches. Significantly high levels of proline, glutamate, arginine, and alanine, which are accumulated upon plant stress, were found in healthy and botrytized berries of botrytized bunches. Moreover, largely degraded phenylpropanoids, flavonoid compounds, and sucrose together with markedly produced glycerol, gluconic acid, and succinate, all being directly associated with B. cinerea growth, were only found in botrytized berries of botrytized bunches. This study reports that B. cinerea infection causes significant metabolic changes in grape berry and highlights that both the metabolic perturbations associated with the plant defence system and those directly derived from fungal pathogen growth should be considered to better understand the interaction between metabolic variation and biotic pathogen stress in plants.

NMR-based metabolomics in wine science

As metabolomics is becoming an emerging field of 'omics' research, NMR serves as one of the major analytical approaches of the decade in metabolomic study, producing information-rich, highly reliable and reproducible data set in non-targeted or global and multivariate statistical analysis. Recently, NMR is successfully being used to characterize wine and find an association of wine metabolite with environmental and fermentative factors in vineyard and making wine. This review describes important analytical features and recent applications in/of NMR-based metabolomics in wine science.

Metabolite profiling of Angelica gigas from different geographical origins using 1H NMR and UPLC-MS analyses

Angelica gigas obtained from different geographical regions was characterized using (1)H nuclear magnetic resonance (NMR) spectroscopy and ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) followed by multivariate data analyses. Principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) score plots from (1)H NMR and UPLC-MS data sets showed a clear distinction among A. gigas from three different regions in Korea. The major metabolites that contributed to the discrimination factor were primary metabolites including acetate, choline, citrate, 1,3-dimethylurate, fumarate, glucose, histamine, lactose, malate, N-acetylglutamate, succinate, and valine and secondary metabolites including decursin, decursinol, nodakenin, marmesin, 7-hydroxy-6-(2R-hydroxy-3-methylbut-3-ethyl)coumarin in A. gigas roots. The results demonstrate that (1)H NMR and UPLC-MS-based metabolic profiling coupled with chemometric analysis can be used to discriminate the geographical origins of various herbal medicines and to identify primary and secondary metabolites responsible for discrimination.

Metabolic influence of Botrytis cinerea infection in champagne base wine

Botrytis cinerea infection of grape berries leads to changes in the chemical composition of grape and the corresponding wine and, thus, affects wine quality. The metabolic effect of Botrytis infection in Champagne base wine was investigated through a (1)H NMR-based metabolomic approach. Isoleucine, leucine, threonine, valine, arginine, proline, glutamine, γ-aminobutyric acid (GABA), succinate, malate, citrate, tartarate, fructose, glucose, oligosaccharides, amino acid derivatives, 2,3-butanediol, acetate, glycerol, tyrosine, 2-phenylethanol, trigonelline, and phenylpropanoids in a grape must and wine were identified by (1)H NMR spectroscopy and contributed to metabolic differentiations between healthy and botrytized wines by using multivariate statistical analysis such as principal component analysis (PCA). Lowered levels of glycerol, 2,3-butanediol, succinate, tyrosine, valine derivative, and phenylpropanoids but higher levels of oligosaccharides in the botrytized wines were main discriminant metabolites, demonstrating that Botrytis infection of grape caused the fermentative retardation during alcoholic fermentation because the main metabolites responsible for the differentiation are fermentative products. Moreover, higher levels of several oligosaccharides in the botrytized wines also indicated the less fermentative behavior of yeast in the botrytized wines. This study highlights a metabolomic approach for better understanding of the comprehensive metabolic influences of Botrytis infection of grape berries in Champagne wines.

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses

(1)H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of 'Riesling' and 'Mueller-Thurgau' white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. (1)H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. 'Riesling' wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for 'Mueller-Thurgau'. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine.