Characterization of Free and Bound Monoterpene Alcohols during Riesling Fermentation

Caffrey, Andrew; Lerno, Larry; Zweigenbaum, Jerry; Ebeler, Susan E.

doi:10.1021/acs.jafc.1c01216

Cited by 3 publications

(2 citation statements)

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“…The correlation between VOC concentrations in grapes and wines may help us to discover the difference in metabolism during fermentation in non-smoke-tainted wine and smoke-tainted wine. Although several studies compared the VOC concentrations before and after fermentation, , it is difficult to observe the VOC concentration changes for different grape varieties during fermentation due to limited data set size or to correlate the VOC concentrations with smoke sensory attributes without smoke taint index information. In this study, a complete data set that combines VOC concentrations of wine and grape samples from different varieties and smoke taint index is prepared, and it allows us to discover the VOC composition changes and the correlation between VOC concentrations and smoke taint index and to apply predictive modeling of the smoke taint index at the same time.…”

Section: Discussionmentioning

confidence: 99%

Volatile Organic Compound-Based Predictive Modeling of Smoke Taint in Wine

Tan,

Neupane,

Wen

et al. 2024

J. Agric. Food Chem.

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Smoke taint in wine has become a critical issue in the wine industry due to its significant negative impact on wine quality. Data-driven approaches including univariate analysis and predictive modeling are applied to a data set containing concentrations of 20 VOCs in 48 grape samples and 56 corresponding wine samples with a taster-evaluated smoke taint index. The resulting models for predicting the smoke taint index of wines are highly predictive when using as inputs VOC concentrations after log conversion in both grapes and wines (Pearson Correlation Coefficient PCC = 0.82; R 2 = 0.68) and less so when only grape VOCs are used (Pearson Correlation Coefficient PCC = 0.76; R 2 = 0.56), and the classification models also show the capacity for detecting smoke-tainted wines using both wine and grape VOC concentrations (Recall = 0.76; Precision = 0.92; F1 = 0.82) or using only grape VOC concentrations (Recall = 0.74; Precision = 0.92; F1 = 0.80). The performance of the predictive model shows the possibility of predicting the smoke taint index of the wine and grape samples before fermentation. The corresponding code of data analysis and predictive modeling of smoke taint in wine is available in the Github repository ().

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Section: Discussionmentioning

confidence: 99%

Volatile Organic Compound-Based Predictive Modeling of Smoke Taint in Wine

Tan,

Neupane,

Wen

et al. 2024

J. Agric. Food Chem.

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“…This event suggested an occurrence of the hydrolysis process of mango glycosides by yeast glucosidases enzyme. This process cleaves the glycosidic bond of terpene glycosides and then releases volatile aglycone and sugar moiety ( 47 ).…”

Section: Discussionmentioning

confidence: 99%

Metabolic profiles alteration of Southern Thailand traditional sweet pickled mango during the production process

et al. 2022

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Sweet pickled mango named Ma-Muang Bao Chae-Im (MBC), a delicacy from the Southern part of Thailand, has a unique aroma and taste. The employed immersion processes (brining 1, brining 2, and immersion in a hypertonic sugar solution, sequentially) in the MBC production process bring changes to the unripe mango, which indicate the occurrence of metabolic profiles alteration during the production process. This occurrence was never been explored. Thus, this study investigated metabolic profile alteration during the MBC production process. The untargeted metabolomics profiling method was used to reveal the changes in volatile and non-volatile metabolites. Headspace solid-phase micro-extraction tandem with gas chromatography quadrupole time of flight (GC/QTOF) was employed for the volatile analysis, while metabolites derivatization for non-volatile analysis. In conclusion, a total of 82 volatile and 41 non-volatile metabolites were identified during the production process. Terpenes, terpenoids, several non-volatile organic acids, and sugars were the major mango metabolites that presented throughout the process. Gamma-aminobutyric acid (GABA) was only observed during the brining processes, which suggested the microorganism’s stress response mechanism to an acidic environment and high chloride ions in brine. Esters and alcohols were abundant during the last immersion process, which had an important role in MBC flavor characteristics. The knowledge of metabolites development during the MBC production process would be beneficial for product development and optimization.

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