Profiles of Phenolic Acids and Flavan-3-ols for Select Chinese Red Wines: A Comparison and Differentiation According to Geographic Origin and Grape Variety

Could Collected Chemical Parameters Be Utilized to Build Soft Sensors Capable of Predicting the Provenance, Vintages, and Price Points of New Zealand Pinot Noir Wines Simultaneously?

Soft sensors work as predictive frameworks encapsulating a set of easy-to-collect input data and a machine learning method (ML) to predict highly related variables that are difficult to measure. The machine learning method could provide a prediction of complex unknown relations between the input data and desired output parameters. Recently, soft sensors have been applicable in predicting the prices and vintages of New Zealand Pinot noir wines based on chemical parameters. However, the previous sample size did not adequately represent the diversity of provenances, vintages, and price points across commercially available New Zealand Pinot noir wines. Consequently, a representative sample of 39 commercially available New Zealand Pinot noir wines from diverse provenances, vintages, and price points were selected. Literature has shown that wine phenolic compounds strongly correlated with wine provenances, vintages and price points, which could be used as input data for developing soft sensors. Due to the significance of these phenolic compounds, chemical parameters, including phenolic compounds and pH, were collected using UV-Vis visible spectrophotometry and a pH meter. The soft sensor utilising Naive Bayes (belongs to ML) was designed to predict Pinot noir wines' provenances (regions of origin) based on six chemical parameters with the prediction accuracy of over 75%. Soft sensors based on decision trees (within ML) could predict Pinot noir wines' vintages and price points with prediction accuracies of over 75% based on six chemical parameters. These predictions were based on the same collected six chemical parameters as aforementioned.

The Biogeography of Fungal Communities Across Different Chinese Wine-Producing Regions Associated With Environmental Factors and Spontaneous Fermentation Performance

Chinese Marselan grapes are believed to possess the potential to become a characteristic regional variety, whose quality is internationally recognized. The fermentation-related mycobiota from six climatically diverse Marselan-producing regions in China were analyzed via high-throughput sequencing (HTS), while the influence of environmental factors was evaluated as well. The results implied that the phyla Ascomycota and genus Aureobasidium dominated the fungal communities in 166 Marselan must and fermented samples. Significant differences were detected in the fungal microbiota from the regions, as well as the wineries, while these discrepancies decreased as the fermentation progressed. Moreover, the discrepancy in fungal communities between the wineries exceeded the variation involving the regions. Geoclimatic elements (Gc) and physicochemical indexes (Pi) exerted a significant effect on the fungal must consortium, explaining 58.17% of the taxonomic information. Furthermore, a correlation was proposed between the spontaneous fermentation performance and their association with fungal taxonomic composition. In addition to depicting a fundamental landscape of fungal biogeography patterns across Chinese main wine-producing regions, we firstly proposed the correlation between the must polyphenol content and fungal microbiota, which may provide a new strategy for harnessing autochthonous “microbial terroir.”

A fundamental landscape of fungal biogeographical patterns across the main Chinese wine-producing regions and the dominating shaping factors

The microbial terroir plays an indispensable role in the formation of regional wine characteristics. A fundamental landscape of the fungal biogeographical patterns across Chinese wine-producing regions was obtained by characterizing the fungal communities in spontaneous fermentation. After confirming the established national microbial terroir, the fungal heterogeneity was evaluated at different geographical levels. The result showed that the variation between the wineries was more evident than at a regional level. Moreover, the microbial comparability from various regions with similar climates or wineries within the same regions was revealed. Further discriminant analysis determined the specific fungal biomarkers in different regions, while the associated reverse identification model displayed reliable accuracy (>70%). Correlation analysis illustrated the primary role of the geoclimatic factors (>41%) in shaping the fungal geographical patterns, and the relationship between the microbiome and spontaneous fermentation performance. In addition to expanding the knowledge regarding wine microbes, these findings provided a new benchmark for harnessing the microbial terroir to enhance regional wine expression.

Identification of Tentative Traceability Markers with Direct Implications in Polyphenol Fingerprinting of Red Wines: Application of LC-MS and Chemometrics Methods

This study investigated the potential of using the changes in polyphenol composition of red wine to enable a more comprehensive chemometric differentiation and suitable identification of authentication markers. Based on high performance liquid chromatography-mass spectrometry (HPLC-MS) data collected from Feteasca Neagra, Merlot, and Cabernet Sauvignon finished wines, phenolic profiles of relevant classes were investigated immediately after vinification (Stage 1), after three months (Stage 2) and six months (Stage 3) of storage, respectively. The data were subjected to multivariate analysis, and resulted in an initial vintage differentiation by principal component analysis (PCA), and variety grouping by canonical discriminant analysis (CDA). Based on polyphenol common biosynthesis route and on the PCA correlation matrix, additional descriptors were investigated. We observed that the inclusion of specific compositional ratios into the data matrix allowed for improved sample differentiation. We obtained simultaneous discrimination according to the considered oenological factors (variety, vintage, and geographical origin) as well as the respective clustering applied during the storage period. Subsequently, further discriminatory investigations to assign wine samples to their corresponding classes relied on partial least squares-discriminant analysis (PLS-DA); the classification models confirmed the clustering initially obtained by PCA. The benefits of the presented fingerprinting approach might justify its selection and warrant its potential as an applicable tool with improved authentication capabilities in red wines.

Polyphenols, L-Ascorbic Acid, and Antioxidant Activity in Wines from Rose Fruits (Rosa rugosa)

The aim of the present study was to determine the influence of the winemaking process on the antioxidant potential and content of phenolic compounds and L-ascorbic acid in wines from the fruits of Rosa rugosa. The results obtained in this study clearly indicate that the fruits of the Rosa rugosa are a desirable raw material for the production of fruit wine. The parameters of the technological process of producing wines from rose fruits had a diversified influence on the tested quality characteristics. Aged wines contained phenolics levels of 473–958 mg/100 mL GAE. The final concentrations of ascorbic acid ranged from 61 to 155 mg/100 mL for the different variants of the wine. Wines revealed high antioxidant activity in assay with DPPH. On the basis of the obtained results, it can be assumed that all the applied variants of the winemaking process are suitable for rose fruit wine. Each variant ensured at least the stability of the antioxidant capacity.

Real wine or not? Protecting wine with traceability and authenticity for consumers: chemical and technical basis, technique applications, challenge, and perspectives

Wine is a high-value alcoholic beverage welcomed by consumers because of its flavor and nutritional value. The key information on wine bottle label is the basis of consumers' choice, which also becomes a target for manufacturers to adulterate, including geographical origin, grape variety and vintage. With the improvement of wine adulteration technology, modern technological means are needed to solve the above mentioned problems. The chemical basis of wine determines the type of technique used. Detection technology can be subdivided into four groups: mass spectrometry techniques, spectroscopic techniques, chromatography techniques, and other techniques. Multivariate statistical analysis of the data was performed by means of chemometrics methods. This paper outlines a series of procedures for wine classification and identification, and classified the analytical techniques and data processing methods used in recent years with listing their principles, advantages and disadvantages to help wine researchers choose appropriate methods to meet the challenge and ensure wine traceability and authenticity.

Phenolic Compounds as Markers of Wine Quality and Authenticity

Targeted and untargeted determinations are being currently applied to different classes of natural phenolics to develop an integrated approach aimed at ensuring compliance to regulatory prescriptions related to specific quality parameters of wine production. The regulations are particularly severe for wine and include various aspects of the viticulture practices and winemaking techniques. Nevertheless, the use of phenolic profiles for quality control is still fragmented and incomplete, even if they are a promising tool for quality evaluation. Only a few methods have been already validated and widely applied, and an integrated approach is in fact still missing because of the complex dependence of the chemical profile of wine on many viticultural and enological factors, which have not been clarified yet. For example, there is a lack of studies about the phenolic composition in relation to the wine authenticity of white and especially rosé wines. This review is a bibliographic account on the approaches based on phenolic species that have been developed for the evaluation of wine quality and frauds, from the grape varieties (of V. vinifera and non vinifera), to the geographical origin, the vintage year, the winemaking process, and wine aging. Future perspectives on the role of phenolic compounds in different wine quality aspects, which should be still exploited, are also outlined.

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

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

Letting wine polyphenols functional: Estimation of wine polyphenols bioaccessibility under different drinking amount and drinking patterns

Effects of drinking amount and patterns of wine on the digestive characteristics and bioaccessibility of wine polyphenols under in vitro gastrointestinal digestion were investigated. Wine polyphenols released well during mouth and stomach digestion, and the release rates in the "serum-available" fraction, "colon-available" fraction, and after the colon were much lower. Red wine showed a higher biological activity than white wine, but white wine had a better bioaccessibility than red wine, especially under binge drinking. The bioaccessibility of most polyphenols decreased as the drinking amount increased, indicating that drinking larger volumes of wine did not increase the bioaccessibility of polyphenols. Additionally, the relevant biological activities did not increase as the drinking amount increased. Drinking after a meal showed significantly better results than drinking before a meal in most of the tests. Hence, in order to let wine polyphenols play its functional for human health, there still need a moderate consumption amount of wine and drinking after meal is better.

Food fingerprints - A valuable tool to monitor food authenticity and safety

In recent years, food frauds and adulterations have increased significantly. This practice is motivated by fast economical gains and has an enormous impact on public health, representing an important issue in food science. In this context, this review has been designed to be a useful guide of potential biomarkers of food authenticity and safety. In terms of food authenticity, we focused our attention on biomarkers reported to specify different botanical or geographical origins, genetic diversity or production systems, while at the food safety level, molecular evidences of food adulteration or spoilage will be highlighted. This report is the first to combine results from recent studies in a format that allows a ready overview of metabolites (<1200 Da) and potentially molecular routes to monitor food authentication and safety. This review has therefore the potential to unveil important aspects in food adulteration and safety, contributing to improve the current regulatory frameworks.

Effects of Copper Pollution on the Phenolic Compound Content, Color, and Antioxidant Activity of Wine

The effects of copper pollution on the polyphenol content, color, and antioxidant activity of wine, as well as correlations among these factors, were investigated. Copper had clear influences on wine polyphenol content. At low copper concentrations, the concentrations of nearly all polyphenols increased, and the antioxidant activity values of the wine also increased. When the copper concentration reached the lowest level of the medium copper range (9.6~16 mg/L), most of the indices also improved. When the copper concentrations reached the latter part of the medium copper range (19.2 and 22.4 mg/L), many of the tested indices began to decrease. Furthermore, when the copper concentration reached the high ranges (32, 64, and 96 mg/L), the polyphenol content, CIELAB color parameters, and antioxidant activity of wine were substantially decreased, indicating the need to control increasing copper content in grape must.

Profile of Polyphenol Compounds of Five Muscadine Grapes Cultivated in the United States and in Newly Adapted Locations in China

Polyphenol compositions and concentrations in skins and seeds of five muscadine grapes (cv. “Noble”, “Alachua”, “Carlos”, “Fry”, and “Granny Val”) cultivated in the United States (Tallahassee-Florida, TA-FL) and South China (Nanning-Guangxi, NN-GX and Pu’er-Yunnan, PE-YN) were investigated, using ultra performance liquid chromatography tandem triple quadrupole time-of-flight mass spectrometry (UPLC Triple TOF MS/MS). Fourteen ellagitannins were newly identified in these muscadine grapes. The grapes grown in NN-GX accumulated higher levels of ellagic acid, methyl brevifolin carboxylate, and ellagic acid glucoside in skins, and penta-O-galloyl-glucose in seeds. In PE-YN, more flavonols were detected in skins, and higher contents of flavan-3-ols, ellagic acid, and methyl gallate were identified in seeds. Abundant seed gallic acid and flavonols were found among the grapes grown in TA-FL. Based on principal component analysis (PCA) of 54 evaluation parameters, various cultivars grown in different locations could be grouped together and vice versa for the same cultivar cultivated in different regions. This is the result of the interaction between genotype and environmental conditions, which apparently influences the polyphenol synthesis and accumulation.