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

Wine metabolome and sensory analyses demonstrate the oenological potential of novel grapevine genotypes for sustainable viticulture in warm climates

BACKGROUND

Genetic breeding is essential to develop grapevine genotypes adapted to warm climates and resistant to pathogens. Traditionally cultivated Vitis vinifera is susceptible to biotic and abiotic stresses. Winemakers and consumers, however, perceive wines from non-vinifera or hybrid cultivars as inferior. In this study, sensory analyses and comprehensive metabolite profiling by targeted and untargeted approaches were used to investigate the oenological potential of wines from grapes of genotypes developed throughout four breeding cycles to improve climate adaptation, sugar contents and berry color.

RESULTS

Novel genotypes had higher yields and the wines exhibited increased contents of polyphenols, including anthocyanins. Volatile monoterpenes in the wines decreased throughout breeding cycles in the absence of selective pressure. Polyphenol contents were higher in intermediate wines, with hydroxytyrosol contents reaching up to three times reported values. Mouthfeel attributes astringency, leafy taste, flavor and body, and persistency showed significant correlation with untargeted features. Supervised model-based analyses of the metabolome effectively discriminate wines from distinct genetic origins.

CONCLUSION

Taken together, the results demonstrate the potential of novel grapevine genotypes to a more sustainable viticulture and quality wine production in warm climates. Comprehensive metabolite profiling of the wines reveals that genotype clustering is dependent on the chemical class and that traits not submitted to selective pressure are also altered by breeding. Supervised multivariate models were effective to predict the genetic origin of the wines based on the metabolic profile, indicating the potential of the technique to identify biomarkers for wines from sustainable genotypes. © 2024 Society of Chemical Industry.

HRMAS 1H NMR and CPMAS 13C NMR spectroscopies coupled with chemometrics for the metabolomic investigation of commercial teas

In this study, the metabolome of different types of tea (i.e., black, green and earl grey) is explored by means of HRMAS 1H (i.e., semisolid state) NMR and CPMAS 13C (i.e., solid state) NMR spectroscopies. By elaborating the metabolomic data with unsupervised and supervised chemometric tools (PCA, PLS-DA), it was possible to set up classification models with the aim to discriminate the different types of tea as based on differences in their chemical composition. Both the applications of the NMR spectroscopies also allowed to obtain information about the metabolic biomarkers leading the differentiation among teas. These were mainly represented by phenolic compounds. Also, some non-phenolic compounds, such as amino acids, carbohydrates, and terpenoids, played important roles in shaping tea quality. The findings of this study provided useful insights into the application of solid and semisolid state NMR spectroscopies, in combination with chemometrics, in the context of food authentication and traceability.

Metabolic Profiling and Stable Isotope Analysis of Wines: Pilot Study for Cross-Border Authentication

Globalization and free market dynamics have significantly impacted state economies, particularly in the wine industry. These forces have introduced greater diversity in wine products but have also heightened the risk of food fraud, especially in high-value commodities like wine. Due to its market value and the premium placed on quality, wine is frequently subject to adulteration. This issue is often addressed through regulatory trademarks on wine labels, such as Protected Designation of Origin (PDO) and Protected Geographic Indication (PGI). In this context, the metabolic profiles (organic acids, carbohydrates, and phenols) and stable isotope signatures (δ13C, δ18O, D/HI, and D/HII) of red and white wines from four agroclimatically similar regions were examined. The study explored how factors such as grape variety, harvest year, and geographical origin affect wine composition, with a particular focus on distinguishing samples from cross-border areas. Multivariate statistical analysis was used to assess the variability in wine composition and to identify distinct groups of samples. Preliminary results revealed that organic acids and volatile compounds were found in lower concentrations than carbohydrates but were significantly higher than phenols, with levels ranging between 1617 mg/L and 6258 mg/L. Carbohydrate content in the wines varied from 8285 mg/L to 14662 mg/L. Principal Component Analysis (PCA) indicated certain separation trends based on the variance in carbohydrates (e.g., fructose, glucose, galactose) and isotopic composition. However, Discriminant Analysis (DA) provided clear distinctions based on harvest year, variety, and geographical origin.

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.

Macroscopic and microscopic analysis of the effects of moisture content and dry density on the strength of loess

To clarify the impact of moisture content and dry density on the strength of loess, the remolded loess samples with different moisture content and dry density were prepared, and the influence of moisture content and dry density on loess strength was explored from the macro level by direct shear test without suction control. On this basis, the mechanism of the influence of moisture content and dry density on loess strength was explored from the micro level by nuclear magnetic resonance method. The research results indicate that: In the case of low water content, there are peak points in the stress-strain curve of remolded loess, exhibiting strain softening characteristics. In the case of high water content, there is no obvious peak in the stress-strain curve, exhibiting strain hardening characteristics. Moisture has a significant impact on the shear strength of remolded loess. As the moisture content of the soil sample increases, the cohesion decreases significantly, and the change in internal friction angle is not obvious. As the moisture content continues to increase, the free water content continues to increase. Free water will continuously soften the soil particle structure, reduce the bonding force between soil particles, and cause the cohesion to decrease with the increase of moisture content. The change in dry density also has a significant impact on the shear strength parameters of remolded loess. As the dry density of the soil sample increases, the cohesion increases. The smaller the dry density, the larger the pore ratio, and the looser the contact between soil particles, weakening the bonding effect. The larger the pore ratio, the more bound water is converted to free water, and the strong bonding force between the water film and soil particles disappears. Both of these microscopic factors can lead to a decrease in cohesion with a decrease in dry density.

Soil effect on proanthocyanidins composition of red and white wines obtained from Nero d'Avola and Grillo Vitis vinifera L. Cultivars

In this study, the effects of the main soil chemical-physical parameters (i.e. texture, pH, total carbonates, cation exchange capacity, electric conductivity, organic matter and mineral endowment) on proanthocyanidin composition of Nero d'Avola red wines and Grillo white wines were investigated. Monomer proanthocyanidins (i.e. (+)-catechin and (-)-epicatechin) and oligomer proanthocyanidins (i.e. B1, B2, B3 and B4 dimers and C1 trimer), as well as proanthocyanidins subunit composition, percentage of galloylation, percentage of prodelphinidins and mean degree of polymerization, were studied for each wine. Results highlighted that the proanthocyanidins composition of both red and white wines is greatly affected by soil. In particular, the proanthocyanidins composition of Nero d'Avola red wines appeared to be affected by the soil physical-chemical parameters related to nutrients dynamics (CEC, EC, pH, organic matter, mineral endowment), whereas the proanthocyanidins composition of Grillo white wines was mainly influenced by the soil texture, that modulates soil water dynamics.

Sur lies élevage practice to modulate the features of red wines from calcareous soils with different textures

BACKGROUND

In Sicilian calcareous soils, red wines often display unripeness and bitterness features. To enhance wine quality, we employed the 'sur lies élevage' technique, involving prolonged contact of dead yeast cells with the wine to favor the extraction of yeast cellular components through cell lysis. The 7 month treatment utilized two types of Chardonnay lies: fresh and previously matured. To overcome challenges in retrieving lies from red winemaking, we have recovered the lies from a white winemaking. Additionally, the lies underwent a preliminary passage on a red wine to minimize color adsorption on yeast cell walls.

RESULTS

The sur lies treatment effectively reduced astringency, bitterness, and brown pigment in wines, with partial removal of red color. It successfully eliminated quercetin aglycone and induced remarkable changes in the aromatic profile, showing increased ethyl esters and relative fatty acids. Sensory evaluations revealed sur lies-treated wines had fruitier and more complex characteristics compared to untreated wines. Matured lies had a greater impact on enhancing fruitiness than fresh lies.

CONCLUSIONS

The treatments mitigated the unripeness and bitterness of studied wines. Sur lies treatment improved the aromatic profile, leading to fruitier and more complex notes, enhancing overall sensory quality. Matured lies showed greater efficacy in elevating fruitiness than fresh lies. These findings highlight the value of the sur lies technique in enhancing the quality and sensory attributes of Nero d'Avola and Syrah wines from Sicilian calcareous soils. © 2023 Society of Chemical Industry.

Direct Identification and Quantitation of Protein Peptide Powders Based on Multi-Molecular Infrared Spectroscopy and Multivariate Data Fusion

Given that protein peptide powders (PPPs) from different biological sources were inherited with diverse healthcare functions, which aroused adulteration of PPPs. A high-throughput and rapid methodology, united multi-molecular infrared (MM-IR) spectroscopy with data fusion, could determine the types and component content of PPPs from seven sources as examples. The chemical fingerprints of PPPs were thoroughly interpreted by tri-step infrared (IR) spectroscopy, and the defined spectral fingerprint region of protein peptide, total sugar, and fat was 3600-950 cm^-1, which constituted MIR finger-print region. Moreover, the mid-level data fusion model was of great applicability in qualitative analysis, in which the F1-score reached 1 and the total accuracy was 100%, and a robust quantitative model was established with excellent predictive capacity (R_p: 0.9935, RMSEP: 1.288, and RPD: 7.97). MM-IR coordinated data fusion strategies to achieve high-throughput, multi-dimensional analysis of PPPs with better accuracy and robustness which meant a significant potential for the comprehensive analysis of other powders in food as well.

Widely Targeted Metabolomics Reveals the Effects of Soil on the Metabolites in Dioscorea opposita Thunb

Chinese yam (Dioscorea opposita Thunb. cv. Tiegun), a type of homologous medicinal plant, mainly grows in sandy soil (SCY) and loessial soil (LCY). However, the effects of the soil on the metabolites in SCY and LCY remain unclear. Herein, this study aims to comprehensively elucidate the metabolites in SCY and LCY. A UPLC-MS/MS-based, widely targeted metabolomics approach was adapted to compare the chemical composition of SCY and LCY. A total of 988 metabolites were detected, including 443 primary metabolites, 510 secondary metabolites, and 35 other compounds. Notably, 177 differential metabolites (classified into 12 categories) were identified between SCY and LCY; among them, 85.9% (152 differential metabolites) were upregulated in LCY. LCY significantly increased the contents of primary metabolites such as 38 lipids and 6 nucleotides and derivatives, as well as some secondary metabolites such as 36 flavonoids, 28 phenolic acids, 13 alkaloids, and 6 tannins. The results indicate that loessial soil can improve the nutritional and medicinal value of D. opposita.