NMR metabolite fingerprinting in grape derived products: An overview

The Metabolic and Antioxidant Activity Profiles of Aged Greek Grape Marc Spirits

In the last decade, "expressions" of grape marc spirits aged in wooden barrels of characteristic amber color and complex sensory attributes have been introduced. Yet studies on constituents migrating from the barrel to the beverage are scarce, and their metabolic profile remains unexplored. Furthermore, the literature on the assessment of their antioxidant activity is limited. NMR metabolomics and spectrophotometry have been implemented in 38 samples to elucidate the impact of the aging procedure on the metabolites' composition and establish whether these beverages exhibit antioxidant activity. Provenance was related to fusel alcohols, esters, acetaldehyde, methanol, saccharides, and 2-phenylethanol, while ethyl acetate and ethyl lactate contributed to discriminating samples of the same winery. Identified metabolites such as vanillin, syringaldehyde, and sinapaldehyde were related to the aging procedure. The maturation in the barrel was also associated with an increase in xylose, glucose, fructose, and arabinose. The antioxidant potential of the aged Greek grape marc spirits resulting from their maturation in oak barrels was highlighted. The metabolic profiling and antioxidant potential of aged Greek grape marc spirits were assessed for the first time. Finally, the enrichment of the aromatic region was noted with the presence of metabolites with a furanic and phenolic ring derived, respectively, from the polysaccharides' degradation or the thermal decomposition of lignin.

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.

Blockchain-Based Wine Supply Chain for the Industry Advancement

The wine sector is one of the most ‘amazing’ and significant agri-food sectors worldwide since ancient times, considering revenue or employment as well as health aspects. This article aims to describe the impact of the implementation of blockchain technology (BCT) in the wine supply chain. After the literature review, the study is based on Agent Based Models (ABMs) and carried out by the GAMA program. Then, the model and simulation of BCT wine supply chain is designed. Finally, the paper compares traditional and BCT-based supply chains, and the advantages of the last one are evident. Blockchain is a useful tool to ensure a traceability system and to protect the production from any type of fraud and contamination.

Liquid chromatographic methods coupled to chemometrics: a short review to present the key workflow for the investigation of wine phenolic composition as it is affected by environmental factors

The guarantee of wine authenticity arises great concern because of its nutritional and economic importance. Phenolic fingerprints have been used as a source of chemical information for various authentication issues, including botanical and geographical origin, as well as vintage age. The local environment affects wine production and especially its phenolic metabolites. Integrated analytical methodologies combined with chemometrics can be applied in wine fingerprinting studies for the determination and establishment of phenolic markers that contain comprehensive and standardized information about the wine profile and how it can be affected by various environmental factors. This review summarizes all the recent trends in the generation of chemometric models that have been developed for treating chromatographic data and have been used for the investigation of critical wine authenticity issues, revealing phenolic markers responsible for the botanical, geographical, and vintage age classification of wines. Overall, the current review suggests that chromatographic methodologies are promising and powerful techniques that can be used for the accurate determination of phenolic compounds in difficult matrices like wine, highlighting the advantages of the applications of supervised chemometric tools over unsupervised for the construction of prediction models that have been successfully used for the classification based on their territorial and botanical origin.

Nontargeted 1 H NMR fingerprinting and multivariate statistical analysis for traceability of Greek PDO Vostizza currants

In this study, non-targeted ¹ H NMR fingerprinting was used in combination with multivariate statistical analyses for the classification of Greek currants based on their geographical origins (Aeghion, Nemea, Kalamata, Zante, and Amaliada). As classification techniques, Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) were carried out. To elucidate different components according to PDO (Protected Designation of Origin), products from Aeghion (Vostizza) were statistically compared with each one of the four other regions. PLS-DA plots ensure that currants from Kalamata, Nemea, Zante, and Amaliada are well classified with respect to the PDO currants, according to differences observed in metabolites. Results suggest that composition differences in carbohydrates, amino, and organic acids of currants are sufficient to discriminate them in correlation to their geographical origin. In conclusion, currants metabolites which mostly contribute to classification performance of such discriminant analysis model present a suitable alternative technique for currants traceability. The study results contribute information to the currants' metabolite fingerprinting by NMR spectroscopy and their geographical origin. PRACTICAL APPLICATION: This study presents an analytical approach for a high nutritional value Greek PDO product, Vostizza currant. A further research and implementation of this method in food industry, can be the key to food fraud incidents. Thus, application of this work opens up posibilities to "farm to table" mission.

On the Identification and Quantification of Ergothioneine and Lovastatin in Various Mushroom Species: Assets and Challenges of Different Analytical Approaches

In recent years, mushrooms have drawn the attention of agro-industries and food-industries as they were considered to be valuable natural sources of health promoting compounds such as β-glucans, ergothioneine, and lovastatin. The detection and quantification of such compounds by implementing reliable analytical approaches is of the utmost importance in order to adjust mushrooms’ cultivation conditions and maximize the production in different species. Toward this direction, the current study focuses on the comparison of ultraviolet–visible (UV–Vis) spectrometry and liquid chromatography–mass spectrometry (LC–MS) methods (a) by evaluating the content of ergothioneine and lovastatin in mushrooms and (b) by highlighting any possible substrate-based interferences that hinder the accurate determination of these two compounds in order to propose the technique-of-choice for a standardized bioactive compounds monitoring. For this purpose, mushrooms produced by three species (i.e., Agaricus bisporus, Pleurotus ostreatus, and P. citrinopileatus) on various cultivation substrates, namely wheat straw (WS), winery (grape marc (GM)), and olive oil (OL) by-products, were examined. Among the two applied techniques, the developed and validated LC–MS methods, exhibiting relatively short analysis time and higher resolution, emerge as the methods-of-choice for detecting ergothioneine and lovastatin in mushrooms. On the contrary, UV–Vis methods were hindered due to co-absorbance of different constituents, resulting in invalid results. Among the studied mushrooms, P. citrinopileatus contained the highest amount of ergothioneine (822.1 ± 20.6 mg kg⁻¹ dry sample), whereas A. bisporus contained the highest amounts of lovastatin (1.39 ± 0.014 mg kg⁻¹ dry sample). Regarding the effect of different cultivation substrates, mushrooms produced on OL and WS contained the highest amount of ergothioneine, while mushrooms deriving from GM-based substrates contained the highest amount of lovastatin.

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.

Impact of grapevine red blotch disease on primary and secondary metabolites in 'Cabernet Sauvignon' grape tissues

The grapevine red blotch disease (GRBD) was first noticed in 2008, impacting grape ripening. In general, GRBD reduces grape and wine quality resulting in significant economic losses. The purpose of the present study was to evaluate the effect of GRBD on agronomical parameters of 'Cabernet Sauvignon' vines at harvest. Using a metabolomics approach, the influence on primary and secondary metabolite profiling in skin + pulp/flesh and seeds were also determined. GRBD influenced °Brix and berry weight, as well as primary and secondary metabolites in both tissues. 1D ¹H NMR was effective in quantifying the main primary and secondary metabolites affected by GRBD. RP-HPLC was similarly able to quantify the main phenolics affected. Multivariate analysis showed the influence of the virus on grape metabolites using both tools in two berry tissues. The effectiveness of both tools to describe sample variability was compared and the most affected metabolites in each tissue could be identified.

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

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

Trunk Girdling Increased Stomatal Conductance in Cabernet Sauvignon Grapevines, Reduced Glutamine, and Increased Malvidin-3-Glucoside and Quercetin-3-Glucoside Concentrations in Skins and Pulp at Harvest

Girdling is a traditional horticultural practice applied at fruit set or other phenological stages, and is used mostly as a vine management. In grapevines, it is used primarily for table grapes to improve berry weight, sugar content, color, and to promote early harvest. The objective of this study was to evaluate the effect of trunk girdling applied at veraison, in 'Cabernet Sauvignon' wine grapes (Vitis vinifera L.), on agronomical and physiological parameters during vine development from the onset of ripening (veraison) to harvest, and additionally to quantify the effect of girdling on primary and secondary metabolism. Girdling was applied 146 days after pruning (dap) at veraison, when berry sampling for metabolomics and agronomical evaluations commenced, with a further three sampling dates until harvest, at 156 dap (30% maturation, 10 days after girdling-dag), 181 dap (70% maturation, 35 dag), and 223 dap (commercial harvest, 77 dag). Skin/pulp and seed tissues were extracted separately and metabolomics was performed using one-dimensional proton nuclear magnetic resonance (1D 1H NMR) spectroscopy and high performance liquid chromatography (HPLC-DAD). At harvest, girdling significantly increased stomatal conductance (gs) in vines, decreased glutamine concentrations, and increased anthocyanin and flavonol concentrations in the skin/pulp tissues of grape berries. Berry weight was reduced by 27% from 181 dap to harvest, and was significantly higher in grapes from girdled vines at 181 dap. Sugars, organic acids, and other amino acids in skin/pulp or seeds were not significantly different, possibly due to extra-fascicular phloem vessels transporting metabolites from leaves to the roots. Using a metabolomics approach, differences between skin/pulp and seeds tissues were meaningful, and a greater number of secondary metabolites in skin/pulp was affected by girdling than in seeds. Girdling is a simple technique that could easily be applied commercially on vine management to improve berry color and other phenolics in 'Cabernet Sauvignon' grapes.

Analysis of metabolites in chardonnay dry white wine with various inactive yeasts by 1H NMR spectroscopy combined with pattern recognition analysis

The study aimed to investigate the effect of five inactive yeasts on the metabolites of Chardonnay dry white wines vinified in 2016 in Shacheng Manor Wine Co. Ltd., Hebei province, China. In this research, proton nuclear magnetic resonance (NMR) spectroscopy coupled multivariate analysis (¹H NMR-PCA/PLS-DA) were applied to identify and discriminate the different wine products. The results of principle component analysis (PCA) showed that there was significant difference between the metabolites of sample wines with different inactive yeasts, among them, the content of polyols, organic acids, amino acids and choline was notably influenced. The results of partial least squares discrimination analysis (PLS-DA) confirmed that the metabolites contributed to the discrimination of the wines were 2,3-butanediol, ethyl acetate, malic acid, valine, succinic acid, lactic acid, tartaric acid, glycerol, gallic acid, choline, proline, and alanine.

Identification of metabolites in coriander seeds (Coriandrum Sativum L.) aided by ultrahigh resolution total correlation NMR spectroscopy

NMR is a fast method for obtaining a holistic snapshot of the metabolome and also offers quantitative information without separating the compounds present in a complex mixture. Identification of the metabolites present in a plant extract sample is a crucial step for all plant metabolomics studies. In the present work, we used various two dimensional (2D) NMR methods such as J-resolved NMR, total correlation spectroscopy (TOCSY), and heteronuclear single quantum coherence sensitivity enhanced NMR spectroscopy for the identification of 36 common metabolites present in Coriandrum sativum L. seed extract. The identified metabolites belong to the following classes: organic acids, amino acids, and carbohydrates. ¹ H NMR spectra of such complex mixtures in general display tremendous signal overlap due to the presence of a large number of metabolites with closely resonating multiplet signals. This signal overlapping leads to ambiguity in an assignment, and hence, identification of metabolites becomes tedious or impossible in many cases. Therefore, the utility of pure-shift proton spectrum along the indirect (F₁ ) dimension of the F₁ -PSYCHE-TOCSY spectrum is demonstrated for overcoming ambiguity in assignment of metabolites in crowded spectral regions from Coriandrum sativum L. seed extract sample. Because pure-shift NMR methods yield ultrahigh resolution spectrum (i.e., a singlet peak per chemical site) along one or more dimensions, such spectra provide better identification of metabolites compared with regular 2D TOCSY where signal overlap and peak distortions lead to ambiguity in the assignment. Nine metabolites were unambiguously assigned by pure-shift F₁ -PSYCHE-TOCSY spectrum, which was unresolved in regular TOCSY spectrum.

From Academia to Reality Check: A Theoretical Framework on the Use of Chemometric in Food Sciences

There is no doubt that the current knowledge in chemistry, biochemistry, biology, and mathematics have led to advances in our understanding about food and food systems. However, the so-called reductionist approach has dominated food research, hindering new developments and innovation in the field. In the last three decades, food science has moved into the digital and technological era, inducing several challenges resulting from the use of modern instrumental techniques, computing and algorithms incorporated to the exploration, mining, and description of data derived from this complexity. In this environment, food scientists need to be mindful of the issues (advantages and disadvantages) involved in the routine applications of chemometrics. The objective of this opinion paper is to give an overview of the key issues associated with the implementation of chemometrics in food research and development. Please note that specifics about the different methodologies and techniques are beyond the scope of this review.

Data fusion approaches in spectroscopic characterization and classification of PDO wine vinegars

Spain is one of the major producers of high-quality wine vinegars having three protected designations of origin (a.k.a. PDOs): "Vinagre de Jerez", "Vinagre de Condado de Huelva" and "Vinagre de Montilla-Moriles". Their high prices due to their high quality and their high production costs explain the need for developing an adequate quality control technique and the interest in extensive characterization in order to capture the identity of each denomination. In this framework, methodologies based on non-targeted techniques, such as spectroscopies, are becoming popular in food authentication. Thus, for improving vinegar quality assessment, fusion of data blocks obtained from the same samples but different analytical techniques could be a good strategy, since the quantity and quality of sample knowledge could be enhanced providing new insights into the differentiation of vinegars. Therefore, the aim of this manuscript is the development of a multi-platform methodology and a model able to classify the Spanish wine vinegar PDOs. Sixty-five PDO wine vinegars were analyzed by four spectroscopic techniques: Fourier-transform mid-infrared spectroscopy (MIR), near infrared spectroscopy (NIR), multidimensional fluorescence spectroscopy (EEM) and proton nuclear magnetic resonance (¹H-NMR). Two different data fusion strategies were evaluated: Mid-level data fusion with different preprocessing, and Common Component and Specific Weights analysis multiblock method. Exploratory and classification analysis on the data from individual techniques were also performed and compared with data fusion models. The data fusion models improved the classification, providing a more efficient differentiation, than the models based on single methods, and supporting the approach to combine these methods to achieve synergies for an optimized PDO differentiation.

Nuclear Magnetic Resonance (NMR) Spectroscopy in Food Science: A Comprehensive Review

Nuclear magnetic resonance (NMR) spectroscopy is a robust method, which can rapidly analyze mixtures at the molecular level without requiring separation and/or purification steps, making it ideal for applications in food science. Despite its increasing popularity among food scientists, NMR is still an underutilized methodology in this area, mainly due to its high cost, relatively low sensitivity, and the lack of NMR expertise by many food scientists. The aim of this review is to help bridge the knowledge gap that may exist when attempting to apply NMR methodologies to the field of food science. We begin by covering the basic principles required to apply NMR to the study of foods and nutrients. A description of the discipline of chemometrics is provided, as the combination of NMR with multivariate statistical analysis is a powerful approach for addressing modern challenges in food science. Furthermore, a comprehensive overview of recent and key applications in the areas of compositional analysis, food authentication, quality control, and human nutrition is provided. In addition to standard NMR techniques, more sophisticated NMR applications are also presented, although limitations, gaps, and potentials are discussed. We hope this review will help scientists gain some of the knowledge required to apply the powerful methodology of NMR to the rich and diverse field of food science.

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.

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.

Analysis of Metabolites in Cabernet Sauvignon and Shiraz Dry Red Wines from Shanxi by 1H NMR Spectroscopy Combined with Pattern Recognition Analysis

Metabolomics technology based on proton nuclear magnetic resonance (1H NMR) spectroscopy combined with pattern recognition analysis was used to characterize the Cabernet Sauvignon and Shiraz dry red wines vinified in the Linfen of Shanxi Province, China, in 2016. The results showed that there was a very significant difference between the metabolites of Cabernet Sauvignon and Shiraz dry red wines from the area of Linfen. Compared with Shiraz dry red wines, Cabernet Sauvignon dry red wines contained higher levels of proline, valine, tartaric acid, citric acid, malic acid, gallic acid, β-glucose and ethyl acetate, whereas 2,3-butanediol, lactic acid, choline, glycerol, α-D-glucuronic acid, succinic acid and alanine were present in lower levels. Application of NMR spectroscopy combined with pattern recognition analysis showed the discriminative power between wine varietals from the same production area. The loading plot from partial least squares discriminant analysis (PLs-DA) indicated that the key biomarkers for this differentiation were proline, tartaric acid, glycerol, lactic acid, choline, succinic acid and gallic acid, which was consistent with the result of quantitative analysis.

Handling Complexity in Animal and Plant Science Research-From Single to Functional Traits: Are We There Yet?

The current knowledge of the main factors governing livestock, crop and plant quality as well as yield in different species is incomplete. For example, this can be evidenced by the persistence of benchmark crop varieties for many decades in spite of the gains achieved over the same period. In recent years, it has been demonstrated that molecular breeding based on DNA markers has led to advances in breeding (animal and crops). However, these advances are not in the way that it was anticipated initially by the researcher in the field. According to several scientists, one of the main reasons for this was related to the evidence that complex target traits such as grain yield, composition or nutritional quality depend on multiple factors in addition to genetics. Therefore, some questions need to be asked: are the current approaches in molecular genetics the most appropriate to deal with complex traits such as yield or quality? Are the current tools for phenotyping complex traits enough to differentiate among genotypes? Do we need to change the way that data is collected and analysed?

Herbal distillates: A new era of grape marc distillates with enriched antioxidant profile

Grape marc distillates are traditional alcoholic beverages, produced mostly in the Mediterranean countries. The present study proposes the enrichment of a Greek traditional grape marc distillate (tsikoudia) with selected herbs to enhance its natural antioxidants and functional properties. Total phenolic content, the antiradical and antioxidant activities, as well as the phenolic and sugar profiles using NMR and FT-IR spectroscopy were evaluated. The enrichment of distillates with Syzygium aromaticum L., Jasminum officinale L. and Eucalyptus globulus Labill. exhibited the highest total phenolic content as well as the highest antioxidant and antiradical activities, whereas the lowest values were observed with Hippophae rhamnoides L. and Lycium Barbarum Mill. The implementation of NMR and FT-IR spectroscopies attested to the presence of phenolic compounds and of specific carbohydrates in herbal distillates, postulating their migration from selected herbal species to tsikoudia and probably contributing to their organoleptic characteristics. The target of this approach leads to new added-value distillates with enhanced characteristics.

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.

Differential phenolic production in leaves of Vitis vinifera cv. Alvarinho affected with esca disease

Esca is a destructive disease of complex etiology affecting grapevines worldwide. A major constraint to the study and control of esca is that the disease is not diagnosed until external leaf and/or fruit symptoms are visible; however external symptoms usually appear several years after infection onset. We studied the phenolic content of V. vinifera cv. Alvarinho leaves using high performance liquid chromatography-diode array detection-mass spectrometry (HPLC-DAD-MS)/LC-MS. Leaves from affected cordons with and without visible symptoms (diseased and apparently healthy leaves, respectively) and leaves from asymptomatic cordons (healthy leaves) were analyzed. Application of principal components analysis (PCA) to HPLC data showed a clear separation between diseased, apparently healthy, and healthy leaves, with the apparently healthy leaves clustered in a medial position. Several compounds were highly correlated with diseased leaves indicating a differential phenolic production due to esca disease in V. vinifera cv. Alvarinho leaves. Total phenolic production was shown to significantly increase in diseased leaves, compared to healthy leaves, with apparently healthy leaves containing a medial amount. Trans-caffeoyltartaric acid, trans-coumaroyl-tartaric acid, quercetin-3-O-glucoside, quercetin-3-O-galactoside, kaempferol-3-glucoside and myricetin were identified among the compounds associated with disease and their content shown to change similarly to total phenolic production. This study shows that it is possible to discriminate between diseased, healthy and apparently healthy leaves by applying PCA to HPLC data.

Addressing Facts and Gaps in the Phenolics Chemistry of Winery By-Products

Grape and wine phenolics display a noticeable structural diversity, encompassing distinct compounds ranging from simple molecules to oligomers, as well as polymers usually designated as tannins. Since these compounds contribute critically to the organoleptic properties of wines, their analysis and quantification are of primordial importance for winery industry operators. Besides, the occurrence of these compounds has been also extensively described in winery residues, which have been pointed as a valuable source of bioactive phytochemicals presenting potential for the development of new added value products that could fit the current market demands. Therefore, the cumulative knowledge generated during the last decades has allowed the identification of the most promising compounds displaying interesting biological functions, as well as the chemical features responsible for the observed bioactivities. In this regard, the present review explores the scope of the existing knowledge, concerning the compounds found in these winery by-products, as well as the chemical features presumably responsible for the biological functions already identified. Moreover, the present work will hopefully pave the way for further actions to develop new powerful applications to these materials, thus, contributing to more sustainable valorization procedures and the development of newly obtained compounds with enhanced biological properties.

Ethanol determination in frozen fruit pulps: an application of quantitative nuclear magnetic resonance

This study reports the chemical composition of five types of industrial frozen fruit pulps (acerola, cashew, grape, passion fruit and pineapple fruit pulps) and compares them with homemade pulps at two different stages of ripening. The fruit pulps were characterized by analyzing their metabolic profiles and determining their ethanol content using quantitative Nuclear Magnetic Resonance (qNMR). In addition, principal component analysis (PCA) was applied to extract more information from the NMR data. We detected ethanol in all industrial and homemade pulps; and acetic acid in cashew, grape and passion fruit industrial and homemade pulps. The ethanol content in some industrial pulps is above the level recommended by regulatory agencies and is near the levels of some post-ripened homemade pulps. This study demonstrates that qNMR can be used to rapidly detect ethanol content in frozen fruit pulps and food derivatives. Copyright © 2015 John Wiley & Sons, Ltd.