1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas

(1)H HR-MAS NMR Spectroscopy and the Metabolite Determination of Typical Foods in Mediterranean Diet

NMR spectroscopy has become an experimental technique widely used in food science. The experimental procedures that allow precise and quantitative analysis on different foods are relatively simple. For a better sensitivity and resolution, NMR spectroscopy is usually applied to liquid sample by means of extraction procedures that can be addressed to the observation of particular compounds. For the study of semisolid systems such as intact tissues, High-Resolution Magic Angle Spinning (HR-MAS) has received great attention within the biomedical area and beyond. Metabolic profiling and metabolism changes can be investigated both in animal organs and in foods. In this work we present a proton HR-MAS NMR study on the typical vegetable foods of Mediterranean diet such as the Protected Geographical Indication (PGI) cherry tomato of Pachino, the PGI Interdonato lemon of Messina, several Protected Designation of Origin (PDO) extra virgin olive oils from Sicily, and the Traditional Italian Food Product (PAT) red garlic of Nubia. We were able to identify and quantify the main metabolites within the studied systems that can be used for their characterization and authentication.

Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography

Numerous factors such as geographical origin, cultivar, climate, cultural practices, and manufacturing processes influence the chemical compositions of tea, in the same way as growing conditions and grape variety affect wine quality. However, the relationships between these factors and tea chemical compositions are not well understood. In this study, a new approach for non-targeted or global analysis, i.e., metabolomics, which is highly reproducible and statistically effective in analysing a diverse range of compounds, was used to better understand the metabolome of Camellia sinensis and determine the influence of environmental factors, including geography, climate, and cultural practices, on tea-making. We found a strong correlation between environmental factors and the metabolome of green, white, and oolong teas from China, Japan, and South Korea. In particular, multivariate statistical analysis revealed strong inter-country and inter-city relationships in the levels of theanine and catechin derivatives found in green and white teas. This information might be useful for assessing tea quality or producing distinct tea products across different locations, and highlights simultaneous identification of diverse tea metabolites through an NMR-based metabolomics approach.

Isoflavones profiling of soybean [Glycine max (L.) Merrill] germplasms and their correlations with metabolic pathways

The isoflavone diversity (44 varieties) of the soybean, Glycine max (L.) Merrill, from China, Japan, and Korea was examined by high-performance liquid chromatography. The profiles of 12 isoflavones identified from the grains were subjected to data-mining processes, including partial least-squares discriminant analysis (PLS-DA), Pearson's correlation analysis, and hierarchical clustering analysis (HCA). Although PLS-DA did not reveal significant differences among extracts of soybean from 3 countries, the results clearly show that the variation between varieties was low. The CS02554 variety was separate from the others in the first 2 principal components of PLS-DA. HCA of these phytochemicals resulted in clusters derived from closely related biochemical pathways. Daidzin, genistin, and glycitin contents were significantly correlated with their respective malonyl glycoside contents. Daidzein content correlated positively with genistein content (r=0.8189, P<0.0001). The CS02554 variety appears to be a good candidate for future breeding programs, as it contains high levels of isoflavone compounds. These results demonstrate the use of metabolite profiling combined with chemometrics as a tool for assessing the quality of food and identifying metabolic links in biological systems.

How subtle is the "terroir" effect? Chemistry-related signatures of two "climats de Bourgogne"

The chemical composition of grape berries is influenced by various environmental conditions often considered to be representative of a “terroir”. If grapes from a given terroir are assumed to reflect this origin in their chemical compositions, the corresponding wine should also reflect it. The aim of this work was therefore to reveal the “terroir” expression within the chemodiversity of grapes and related wines, using ultrahigh-resolution mass spectrometry. Grapes and corresponding wines, from two distinct – though very proximate – terroirs of Burgundy were analyzed over three vintages (2010, 2011 and 2012). Ultrahigh-resolution mass spectrometry and ultra-high performance liquid chromatography were used as untargeted and targeted approaches to discriminate complex chemical fingerprints for vintages, classes (wines, skins or musts), and terroirs. Statistical analyses revealed that even if vintages have the most significant impact on fingerprints, the most significant terroir differences are seen in the grapes of a given vintage.

Viticultural practice and winemaking effects on metabolic profile of Negroamaro

Metabolic profiles of 32 Negroamaro red wines were analysed using (1)H NMR spectroscopy and multivariate statistical analyses (Principal Component Analysis, PCA, and Orthogonal Partial Least Square Discriminant Analysis, OPLS-DA). Among winemaking technologies three were compared: ultrasounds (U; 12 samples), cryomaceration using dry ice (C; 12 samples) and traditional (T; 8 samples). Moreover, each vinification technology was used for grapes grown by two different soil management practices, soil tillage (ST; 16 samples) and cover crop (CC; 16 samples), and by two different training systems, monolateral (M; 16 samples) and bilateral Guyot (B; 16 samples). All statistical models applied on NMR data revealed a good separation between ST (soil tillage) and CC (cover crop), showing a higher influence of the soil management practices compared to the winemaking technologies (ultrasound, cryomaceration and traditional). The differentiation among samples, due to soil management practices, was mainly caused by metabolites such as glycerol, 2,3-butanediol, malic acid, α/β-glucose and phenolic compounds, such as tyrosine and caffeic acid.

Sparse partial-least-squares discriminant analysis for different geographical origins of Salvia miltiorrhiza by (1) H-NMR-based metabolomics

INTRODUCTION

(1) H nuclear magnetic resonance (NMR) spectroscopy has clear advantages in respect of detecting various primary and secondary metabolites in plants simultaneously, non-targeted and non-destructively.

OBJECTIVE

To establish a method for detecting both primary and secondary metabolites in Salvia miltiorrhiza and screening potential geographical biomarkers effectively.

METHODS

Primary and secondary metabolites of S. militiorrhiza were detected and identified by (1) H-NMR fingerprint. Sparse partial-least-squares discriminant analysis (sPLS-DA) was undertaken for classification and variable selection in a one-step procedure and the classification error rates were implemented to estimate the cluster validation of sPLS-DA. Potential candidate metabolites by characterised different geographical origins of S. miltiorrhiza were identified according to the sparse loading vectors. The levels of these metabolites were quantified and evaluated by Kruskal-Wallis tests and also showed significant difference.

RESULTS

Twenty-six primary and secondary metabolites were identified in samples from different regions. The results suggest that malonate and succinate can be possibly recognised as the key markers for discriminating the geographical origin of S. miltiorrhiza based on the regulation and influence on the root respiratory rates of plants.

CONCLUSION

(1) H-NMR metabolic profiling combination with PLS-DA provided a very efficient and visualised representation of similarities and dissimilarities between S. miltiorrhiza samples.

NMR study of histidine metabolism during alcoholic and malolactic fermentations of wine and their influence on histamine production

The metabolic pathways of amino acids play a crucial role in the organoleptic and hygienic quality in wines. In particular, histidine is one of the most studied amino acids of wines due to histamine toxicity in humans, a biogenic amine derived from histidine by enzymatic decarboxylation. The development of new tools to increase knowledge on metabolism that produces histamine in wine is critical. This study investigated by using nuclear magnetic resonance (NMR) spectroscopy the transformation of histidine into histaminol and histamine during alcoholic and malolactic fermentations. The transformations of histidine into histaminol during alcoholic fermentation and into histamine during malolactic fermentation were observed. This paper highlights the importance of selecting lactic acid bacteria for malolactic fermentation to avoid the production of biogenic amines such as histamine.

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.

Metabolic profiling of Chinese tobacco leaf of different geographical origins by GC-MS

Tobacco leaf obtained from different geographical areas in China was profiled using gas chromatography-mass spectrometry (GC-MS) coupled with multivariate data analyses. Hierarchical cluster analysis (HCA) and principal component analysis (PCA) showed that the tobacco metabolome was clearly dependent on geographical origins; climatic conditions, such as temperature and precipitation, imposed a greater impact on metabolite levels than the cultivars. By orthogonal partial least-squares-discrimination analysis (OPLS-DA), 20 metabolites that contributed to the discrimination were screened, including primary metabolites (sucrose, D-fructose, D-mannose, D-glucose, inositol, maleic acid, citric acid, malic acid, L-threonic acid, L-proline, L-phenylalanine), secondary metabolites (chlorogenic acid, α- and β-4,8,13-duvatriene-1,3-diol, nicotine, quinic acid), and four unknown metabolites. The results suggest that metabolic profiling using GC-MS combined with multivariate analysis can be used to discriminate tobacco leaf of different geographical origins and to provide potential indicators of tobacco origins.

Application of one- and two-dimensional NMR spectroscopy for the characterization of Protected Designation of Origin Lambrusco wines of Modena

Lambrusco is a Protected Designation of Origin (PDO) red wine of Modena (Italy) produced according to the production regulation (Decreto Ministeriale (DM) July 27, 2009; GU no. 184-187-188, 13/08/2009). Here the use of (1)H NMR spectroscopy as molecular fingerprints of several PDO Lambrusco wines was proposed to serve as indicators of authenticity and quality control. Application of partial least squares discriminant analysis (PLS-DA) revealed a good varietal discrimination by analyzing the low-frequency spectral region. This model explains 68.8% of the variance for the Y vector (classification factor: varietal source). In particular, the signals of 2,3-butanediol, lactic, succinic and malic acids, and threonine were found to be the most statistically significant variables in the model. These findings seem to be very promising in the attempt to extend the study to geographical discrimination.

(1)H-NMR-based metabolomic analysis of the effect of moderate wine consumption on subjects with cardiovascular risk factors

Moderate wine consumption is associated with health-promoting activities. An H-NMR-based metabolomic approach was used to identify urinary metabolomic differences of moderate wine intake in the setting of a prospective, randomized, crossover, and controlled trial. Sixty-one male volunteers with high cardiovascular risk factors followed three dietary interventions (28 days): dealcoholized red wine (RWD) (272mL/day, polyphenol control), alcoholized red wine (RWA) (272mL/day) and gin (GIN) (100mL/day, alcohol control). After each period, 24-h urine samples were collected and analyzed by (1) H-NMR. According to the results of a one-way ANOVA, significant markers were grouped in four categories: alcohol-related markers (ethanol); gin-related markers; wine-related markers; and gut microbiota markers (hippurate and 4-hydroxphenylacetic acid). Wine metabolites were classified into two groups; first, metabolites of food metabolome: tartrate (RWA and RWD), ethanol, and mannitol (RWA); and second, biomarkers that relates to endogenous modifications after wine consumption, comprising branched-chain amino acid (BCAA) metabolite (3-methyl-oxovalerate). Additionally, a possible interaction between alcohol and gut-related biomarkers has been identified. To our knowledge, this is the first time that this approach has been applied in a nutritional intervention with red wine. The results show the capacity of this approach to obtain a comprehensive metabolome picture including food metabolome and endogenous biomarkers of moderate wine intake.

Effects of different vinification technologies on physical and chemical characteristics of Sauvignon blanc wines

In order to investigate the effects of cryomaceration and reductive vinification on chemical and physical indices and on antioxidant compounds of Sauvignon blanc wines, four wine-making procedures were applied: traditional white vinification, skin cryomaceration, vinification in a reductive environment, and a combination of the last two procedures. Significant differences were highlighted by both conventional analyses and NMR spectroscopy. The strongest changes were for organic acid concentrations (tartaric, in particular) and phenolic content. Cryomaceration caused a strong precipitation of tartaric acid, which may be desired if grapes have high acidity values. Cryomaceration protected those flavans reactive with vanillin from the action of oxidative enzymes. Vinification in a reductive environment, alone or combined with a cryomaceration step, gave wines with the highest solids content and caused a greater extraction of phenolic compounds from skins compared to traditional winemaking or cryomaceration alone, due to SO(2) solubilisation. Grape oenological expression can be strongly affected by the application of the investigated wine-making procedures.

HRMAS-NMR spectroscopy and multivariate analysis meat characterisation

¹H-High resolution magic angle spinning-nuclear magnetic resonance spectroscopy was employed to gain the metabolic profile of longissimus dorsi and semitendinosus muscles of four different breeds: Chianina, Holstein Friesian, Maremmana and Buffalo. Principal component analysis, partial least squares projection to latent structure - discriminant analysis and orthogonal partial least squares projection to latent structure - discriminant analysis were used to build models capable of discriminating the muscle type according to the breed. Data analysis led to an excellent classification for Buffalo and Chianina, while for Holstein Friesian the separation was lower. In the case of Maremmana the use of intelligent bucketing was necessary due to some resonances shifting allowed improvement of the discrimination ability. Finally, by using the Variable Importance in Projection values the metabolites relevant for the classification were identified.

Traceability of Italian garlic (Allium sativum L.) by means of HRMAS-NMR spectroscopy and multivariate data analysis

(1)H High Resolution Magic Angle Spinning-Nuclear Magnetic Resonance (HRMAS-NMR) spectroscopy was used to analyse garlic (Allium sativum L.) belonging to red and white varieties and collected in different Italian regions, in order to address the traceability issue. 1D and 2D NMR spectra, performed directly on untreated small pieces of garlic, so without any sample manipulation, allowed the assignment of several compounds: organic acids, sugars, fatty acids, amino acids and the nutritionally important fructo-oligosaccharides and allyl-organosulphur compounds. Application of Partial Least Squares projections to latent structures-Discrimination Analysis provided an excellent model for the discrimination of both the variety and, most important, the place origin, allowing the identification of the metabolites contributing to such classifications. The presence of organosulphurs, allicin and some allyl-organosulphurs found by HRMAS-NMR, was confirmed also by SPME-GC-MS; 11 molecules were identified, containing from one up to three sulphur atoms and with and without allyl moieties.

Chemical profile of white wines produced from 'Greco bianco' grape variety in different Italian areas by nuclear magnetic resonance (NMR) and conventional physicochemical analyses

In this study the characterization of white wines produced from the monovarietal 'Greco bianco' grape variety is presented for the first time. A total of 40 commercial wines, from two different southern Italian regions, Calabria and Campania, from the same grape variety and two different vintages, were investigated. The analyses were performed by means of chromatographic methods, conventional analyses, and nuclear magnetic resonance (NMR) spectroscopy. No differentiation was observed according to the year of production but a significant discrimination was achieved using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). In particular, PLS-DA allowed the selection of compounds (total acidity; citric, malic, succinic, and lactic acids; total polyphenol index; glucose and proline/arginine ratio) useful for differentiating the studied wines on the basis of geographical origin.

Advantage of Applying OSC to (1)H NMR-Based Metabonomic Data of Celiac Disease

BACKGROUND

Celiac disease (CD) is a disorder associated with body reaction to gluten. After the gluten intake, an immune reaction against the protein occurs and damages villi of small intestine in celiac patients gradually.

OBJECTIVES

The OSC, a filtering method for minimization of inter- and intra-spectrometer variations that influence on data acquisition, was applied to biofluid NMR data of CD patients.

PATIENTS AND METHODS

In this study, metabolites of total 56 serum samples from 12 CD patients, 15 CD patients taking gluten-free diet (GFD), and 29 healthy cases were analyzed using nuclear magnetic resonance (NMR) and associated theoretical analysis. Employing ProMetab (version ProMetab_v3_3) software, data obtained from NMR spectra were reduced and orthogonal signal correction (OSC) effect on celiac disease metabonomics before and after the separation by principle component analysis (PCA) was investigated.

RESULTS

The three groups were separated by OSC and findings were analyzed by partial least squares discriminant analysis (PLS-DA) method. Root mean square error of calibration (RMSEc) and correlation coefficient of calibration (Rc) for PLS-DA referred to an efficient group separation filtered by OSC.

CONCLUSIONS

The applied leave-one-out cross-validation to PLS-DA method performed along with OSC confirmed validation of data analysis. Finally four metabolites are introduced as CD biomarkers.

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.

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.

Metabolomics: a second-generation platform for crop and food analysis

The combined factors of financial and food security, a rapidly increasing population and the associated requirement for food generated sustainably in a changing environment have brought food swiftly to the top of most government agendas. The consequence of this is that we need to produce more food at an equivalent or higher quality with lower inputs. These aims are achievable using conventional breeding, but not in the required timelines, and thus state-of-the-art genetic and analytical technologies are coming to the forefront. The concept of metabolomics, underpinned by mainstream (GC–MS, LC–MS, NMR) and specialist (MALDI-TOF-MS) analytical technologies addressing broad chemical (class) targets and dynamic ranges, offers significant potential to add significant value to crop and food science and deliver on future food demands. Metabolomics has now found a home in the food analytical toolbox with raw material quality and safety the major quality areas, although, as we will show, it is translating beyond this into food storage, shelf-life and post-harvest processing.

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.

Metagenomic analysis of kimchi, a traditional Korean fermented food

Kimchi, a traditional food in the Korean culture, is made from vegetables by fermentation. In this study, metagenomic approaches were used to monitor changes in bacterial populations, metabolic potential, and overall genetic features of the microbial community during the 29-day fermentation process. Metagenomic DNA was extracted from kimchi samples obtained periodically and was sequenced using a 454 GS FLX Titanium system, which yielded a total of 701,556 reads, with an average read length of 438 bp. Phylogenetic analysis based on 16S rRNA genes from the metagenome indicated that the kimchi microbiome was dominated by members of three genera: Leuconostoc, Lactobacillus, and Weissella. Assignment of metagenomic sequences to SEED categories of the Metagenome Rapid Annotation using Subsystem Technology (MG-RAST) server revealed a genetic profile characteristic of heterotrophic lactic acid fermentation of carbohydrates, which was supported by the detection of mannitol, lactate, acetate, and ethanol as fermentation products. When the metagenomic reads were mapped onto the database of completed genomes, the Leuconostoc mesenteroides subsp. mesenteroides ATCC 8293 and Lactobacillus sakei subsp. sakei 23K genomes were highly represented. These same two genera were confirmed to be important in kimchi fermentation when the majority of kimchi metagenomic sequences showed very high identity to Leuconostoc mesenteroides and Lactobacillus genes. Besides microbial genome sequences, a surprisingly large number of phage DNA sequences were identified from the cellular fractions, possibly indicating that a high proportion of cells were infected by bacteriophages during fermentation. Overall, these results provide insights into the kimchi microbial community and also shed light on fermentation processes carried out broadly by complex microbial communities.

NMR analysis of seven selections of vermentino grape berry: metabolites composition and development

The goal of this work was to study via NMR the unaltered metabolic profile of Sardinian Vermentino grape berry. Seven selections of Vermentino were harvested from the same vineyard. Berries were stored and extracted following an unbiased extraction protocol. Extracts were analyzed to investigate variability in metabolites concentration as a function of the clone, the position of berries in the bunch or growing area within the vineyard. Quantitative NMR and statistical analysis (PCA, correlation analysis, Anova) of the experimental data point out that, among the investigated sources of variation, the position of the berries within the bunch mainly influences the metabolic profile of berries, while the metabolic profile does not seem to be significantly influenced by growing area and clone. Significant variability of the amino acids such as arginine, proline, and organic acids (malic and citric) characterizes the rapid rearrangements of the metabolic profile in response to environmental stimuli. Finally, an application is described on the analysis of metabolite variation throughout the physiological development of berries.

Nutrimetabolomics: development of a bio-identification toolbox to determine the bioactive compounds in grape juice

BACKGROUND

Grape juice and related products have previously been associated with many health benefits, such as protection against cardiovascular disease. Current consensus is that the polyphenols are the likely bioactive species in these products.

RESULTS

Extracts of commercially available grape juices exhibited biological antioxidant activities ranging from 19.30 to 3099.51 µM trolox equivalents, as determined by cell-based assay in which J774 macrophages were stimulated with lipopolysaccaride at a concentration of 100 µg/ml for 1 h. Partial least-squares regression was then used to determine covariance between the antioxidant activity and 400 MHz (1)H NMR spectral profiles using models with R(2)X and R(2)Y values of 0.64 and 0.95, respectively, using three latent variables: the Q(2)(cum) was 0.63. Hydroxycinnamic acids and their derivatives were identified as being the most positively correlated with the antioxidant activity.

CONCLUSION

The work presented here describes a strategy for the bioinformatic linkage of plant metabolomic data with in vitro biological activity as an initial step towards determining structure-activity relationships.

Geographical and climatic dependencies of green tea (Camellia sinensis) metabolites: a (1)H NMR-based metabolomics study

The effects of climatic conditions on green tea metabolites in three different growing areas of Jeju Island, South Korea, were investigated through global metabolite profiling by (1)H nuclear magnetic resonance (NMR) spectroscopy. Pattern recognition methods, such as principal component analysis (PCA) and orthogonal projection on latent structure-discriminant analysis (OPLS-DA), revealed clear discriminations of green teas from the three different growing areas. Variations of theanine, isoleucine, leucine, valine, alanine, threonine, glutamine, quinic acid, glucose, epicatechin (EC), epigallocatechin (EGC), epigallocatechin-3-gallate (EGCG), and caffeine levels were responsible for the discriminations. Green teas grown in an area with high temperature, long sun exposure time, and high rainfall had higher levels of theanine but lower levels of isoleucine, leucine, valine, alanine, EC, EGC, EGCG, and caffeine than those grown in areas with relatively low temperature, short sun exposure time, and low rainfall. These results indicate that high temperature, long sun exposure, and high preciptation stimulate theanine synthesis in green tea during the spring season. This study highlights how metabolomics coupled with multivariate statistical analysis can illuminate the metabolic characteristics of green tea associated with climatic variables, thereby allowing for the assessment of quality strategy in green tea production.

Discrimination of the geographical origin of beef by (1)H NMR-based metabolomics

The geographical origin of beef is of increasing interest to consumers and producers due to "mad cow" disease and the implementation of the Free Trade Agreement (FTA). In this study, (1)H NMR spectroscopy coupled with multivariate statistical analyses was used to differentiate the geographical origin of beef samples. Principal component analysis (PCA) and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) showed significant separation between extracts of beef originating from four countries: Australia, Korea, New Zealand, and the United States. The major metabolites responsible for differentiation in OPLS-DA loading plots were succinate and various amino acids including isoleucine, leucine, methionine, tyrosine, and valine. A one-way ANOVA was performed to statistically certify the difference in metabolite levels. The data suggest that NMR-based metabolomics is an efficient method to distinguish fingerprinting difference between raw beef samples, and several metabolites including various amino acids and succinate can be possible biomarkers for discriminating the geographical origin of beef.

Nuclear magnetic resonance and chemometrics to assess geographical origin and quality of traditional food products

In this globalization era, the opening of the markets has put at almost everybody's disposal a wide variety of foods, allowing everybody to taste food flavors and aromas from different nations. Notwithstanding this opportunity, countries try to preserve their markets by developing protection policies. A few countries have adopted different denominations to label their "typical food" products in order to give them additional value. Besides, the term "typical food" is widely thought of as something anchored to the local traditions, with geographical meaning and made with typical raw materials. Then a "typical food" starts to be considered "traditional" when it is made following specific and old recipes. As a matter of fact, these products acquire particular organoleptic characteristics that are not reproducible when produced in different places. In this review, NMR studies coupled to multivariate statistical analysis are presented with the aim of determining geographical origin and key quality characteristics.

Evidence of metabolic transformations of amino acids into higher alcohols through (13)C NMR studies of wine alcoholic fermentation

Because the metabolite transformations in wine fermentation processes play a crucial role in the organoleptic and hygienic quality of wines, the nuclear magnetic resonance (NMR) technique is presented as a significant tool to follow metabolic pathways. In this paper, we investigated the transformation of several amino acids into their corresponding higher alcohols during the alcoholic fermentation, showing that the amino acids are totally consumed in the first stages of the process.

Modeling relationships among active components in black raspberry (Rubus occidentalis L.) fruit extracts using high-resolution (1)H nuclear magnetic resonance (NMR) spectroscopy and multivariate statistical analysis

A process was developed to ascertain the bioactive components of black raspberry (Rubus occidentalis L.) fruit extracts by relating chemical constituents determined by high-field nuclear magnetic resonance (NMR) spectroscopy to biological responses using partial least-squares regression analysis. To validate our approach, we outlined relationships between phenolic signals in NMR spectra and chemical data for total monomeric anthocyanin (TMA) content and antioxidant capacity by the ferric-reducing antioxidant power (FRAP) and 2,2-diphenyl-1-picrylhydrazyl (DPPH) assays. Anthocyanins, cyanidin 3-O-rutinoside (Cy 3-rut), cyanidin 3-O-(2(G))-xylosylrutinoside (Cy 3-xylrut), and cyanidin 3-O-glucoside (Cy 3-glc), were significant contributors to the variability in assay results, with the two most important NMR bins corresponding to the methyl peaks in Cy 3-rut (6''') and/or Cy 3-xylrut (6(IV)). Many statistically important bins were common among assay models, but differences in structure-activity relationships resulted in changes in bin ranking. The specificity of these results supported the application of the process to investigate relationships among health-beneficial natural products and potential biological activity.

Correlation between sensory evaluation scores of Japanese sake and metabolome profiles

The aim of this study was to explore the association between taste and metabolite profiles of Japanese refined sake. Nontarget metabolome analysis was conducted using capillary electrophoresis mass spectrometry. Zatsumi, an unpleasant not clear flavor, and sweetness, bitterness, and sourness were graded by four experienced panelists. Regression models based on support vector regression (SVR) were used to estimate the relationships among sensory evaluation scores and quantified metabolites and visualized as a nonlinear relationship between sensory scores and metabolite components. The SVR model was highly accurate and versatile: the correlation coefficients for whole training data, cross-validation, and separated validation data were 0.86, 0.73, and 0.73, respectively, for zatsumi. Other sensory scores were also analyzed and modeled by SVR. The methodology demonstrated here carries great potential for predicting the relevant parameters and quantitative relationships between charged metabolites and sensory evaluation in Japanese refined sake.