Untangling the chemistry of port wine aging with the use of GC-FID, multivariate statistics, and network reconstruction

Volatile Composition of Fortification Grape Spirit and Port Wine: Where Do We Stand?

Port wine's prominence worldwide is unequivocal and the grape spirit, which comprises roughly one fifth of the total volume of this fortified wine, is also a contributor to the recognized quality of this beverage. Nonetheless, information about the influence of the grape spirit on the final aroma of Port wine, as well as its volatile composition, is extremely limited. Moreover, the aroma characteristics of Port wines are modulated mainly by their volatile profiles. Hence, this review presents a detailed overview of the volatile composition of the fortification spirit and Port wine, along with the methodologies employed for their characterization. Moreover, it gives a general overview of the Douro Demarcated Region (Portugal) and the relevance of fortification spirit to the production of Port wine. As far as we know, this review contains the most extensive database on the volatile composition of grape spirit and Port wine, corresponding to 23 and 208 compounds, respectively. To conclude, the global outlook and future challenges are addressed, with the position of the analytical coverage of the chemical data on volatile components discussed as crucial for the innovation centered on consumer preferences.

Optimizing column-to-column retention time alignment in high-speed gas chromatography by combining retention time locking and correlation optimized warping

We examine and then optimize alignment of chromatograms collected on nominally identical columns using retention time locking (RTL), an instrumental alignment tool, and software-based alignment using correlation optimized warping (COW). For this purpose, three samples are constructed by spiking two sets of analytes into a base test mixture. The three samples are analyzed by high-speed gas chromatography with four nominally identical columns and identical separation conditions. The data is first analyzed without alignment, then using COW alone, then RTL alone, and finally with RTL followed by COW to correct the severe column-to-column misalignment. Principal component analysis (PCA) is used to investigate how well each alignment method clustered the chromatograms into the three sample classes via a scores plot without being compromised by the specific column(s) used. The degree-of-class separation (DCS) is used as a classification metric, measured as the Euclidian distance between the centroids of two clusters in PC space in the scores plot, normalized by their pooled variance. With no alignment, the average DCS between sample classes (DCS_sam) was 3.0, while the average DCS between the four nominally identical columns, i.e., column classes (DCS_col) was 76.1 (ideally the DCS_col should be 0), indicating the chromatograms were initially classified by the columns used. Using either COW or RTL alone also produced unsatisfactory results, with COW alone incorrectly aligning many peaks, leading to a DCS_sam of only 1.9 and DCS_col of 1.7, while RTL alone provided a DCS_sam of 4.7 and DCS_col of 4.2. Finally, using RTL followed by COW alignment, DCS_sam increased to 32.5, indicating successful classification by chemical differences between sample classes, while the DCS_col decreased to 0.4, indicating virtually no classification due to column-to-column differences, as desired. Thus, RTL provided a "first-order" correction of the initial retention mismatch observed for the nominally identical columns, while additional alignment via COW was required to optimize sample classification by PCA.

Metabolomic fingerprinting based on network analysis of volatile aroma compounds during the forced aging of Huangjiu: Effects of dissolved oxygen and temperature

Introduction

Huangjiu is an important Chinese alcoholic beverage, usually prepared from rice. Although its unique flavor improves with prolonged storage in traditional pottery jars, knowledge of the aging mechanism, necessary for commercialization of an optimum product, remains unclear.

Methods

Here, volatile aroma compounds from forced aged samples exposed to different temperatures and oxygen treatments were measured by GC/MS. After retention time alignment and normalization, the peak vectors were compared over storage time using Pearson's correlation, and a correlation network was established. Marker compounds, representative of traditionally aged Huangjiu, were then monitored and compared to similar compounds in the forced aged product.

Results and discussion

Correlation network analysis revealed the following: Temperature had little effect on most aroma compounds; alcohols, acids, and esters all increased with increasing dissolved oxygen, while polyphenols, lactones, and ketones were readily oxidized; aldehydes (e.g., furfural and benzaldehyde) were highly dependent on both temperature and dissolved oxygen. Dynamic changes in the targeted aging-markers showed that a higher initial oxygen concentration intensified the "aging-aroma" of Huangjiu in the early and middle stages of storage. Consequently, careful control of oxygen supplementation and storage temperature could be beneficial in controlling the desirable flavor of Huangjiu in the artificially aged product.

Discrimination of white wine ageing based on untarget peak picking approach with multi-class target coupled with machine learning algorithms

The complexity of the chemical reactions occurring during white wine storage, such as oxidation turns the capacity of prediction and consequently the capacity to avoid it extremely difficult. This study proposes an untarget methodology based on machine learning algorithms capable to classify wines according to their "oxidative-status". Instead of the most common approach in statistics using one class for classification, in this work eight classes were selected based on target oxidation markers for the extraction of relevant compounds. VIPS from OPLS-DA and mean decrease accuracy from random forest were used as feature selection parameters. Fifty-one molecules correlated with 5 classes, from which 23 were selected has having higher sensitivities (AUC > 0.85). For the first time to our knowledge hydroxy esters ethyl-2-hydroxy-3-methylbutanal and ethyl-2-hydroxy-4-methylpentanal were found to be correlated with oxidation markers and consequently to be discriminant of the wine oxidative status.

Oxygen-induced faults in bottled white wine: A review of technological and chemical characteristics

Several changes can take place in wine after blotting. Some of them lead to the desired evolution of wine being more complex, round and pleasant. However, unexpected changes can also occur ascribable to the premature wine oxidation (PremOx) arising when a wine, presumably with aging potential, results oxidized and often undrinkable. The complexity of PremOx, where aromas are also involved, makes difficult to identify all the oxidation products, and to predict its occurrence in wines. Despite most studies have been focused on the effect of time after wine bottling on PremOx as well as pinking phenomena, identification of pinking markers, reliable methods for their detection in wine, and correlations between markers and the wine-bottle-closure system are still unknown. This review aimed to highlight aspects PremOx-related, including wine-bottle-closure system, color change, with particular emphasis on pinking, and aroma decay based on the current knowledge becoming the bases for future perspectives.

Age-dependent characterization of volatile organic compounds and age discrimination in Chinese rice wine using an untargeted GC/MS-based metabolomic approach

An untargeted gas chromatography/mass spectrometry (GC/MS)-based metabolomics by XCMS-Online software combined with partial least squares regression (PLSR) was applied to characterize volatile organic compounds (VOCs) during Chinese rice wine aging and discriminate ages for the first time. Finally, seven different ages between 0 and 15 years were well discriminated by PLSR. Total 104 feature groups were isolated from all optimized candidate peaks, and 94 VOCs (including unknowns) were preliminarily identified as aging markers. Therein, alcohols, sulfides, phenols and their derivatives, small esters and acids exhibited significantly better discrimination of short-aged rice wines. Correspondingly, furans, aromatics, aldehydes, ketones, most esters and acids, discriminated the long-aged samples better. Meanwhile, the potential origins of certain VOCs were also proposed for further research. Overall, this untargeted GC/MS-based metabolomics coupled with PLSR was a feasible tool for a rapidly and globally age-dependent characterization of volatile metabolomic signals in Chinese rice wine and thus for age discrimination.

Characterization of volatile organic compounds as potential aging markers in Chinese rice wine using multivariable statistics

BACKGROUND

There is a close relationship between certain 'aging markers' in wine and the wine's age. This study aimed to characterize all extracted aging markers in Chinese rice wine and distinguish the ages of Chinese rice wine using principal component analysis (PCA) and cluster analysis (CA).

RESULTS

A total of 49 potential aging markers (P ≤ 0.05*) were extracted from 71 volatile organic compounds (VOCs) in Chinese rice wine across a range of seven different ages. Of all 49 extracted aging markers, all furans, 2/3 aldehydes and ketones maintained significantly increasing levels with age (P ≤ 0.01**), especially sotolon (0.981**) and acetophenone (0.951**). On the other hand, all sulfides decreased significantly (P ≤ 0.01**). Changes in vanillin, guaiacol, 4-vinylguaiacol (4-VG) and 4-ethylguaiacol (4-EG) also suggested a potential synthesis during the aging process. The results of PCA and CA demonstrated that Chinese rice wines with different ages could be clearly distinguished from each other, which was consistent with the evolution of the 49 aging markers during the aging process.

CONCLUSION

These 49 potential 'aging markers' successfully distinguished ages using PCA and CA. Our results therefore throw light on the characterization of VOCs during Chinese rice wine aging, and provide a quantitative basis for discriminating the ages of Chinese rice wine. © 2019 Society of Chemical Industry.

Quantitative and fingerprinting analysis of Atractylodes rhizome based on gas chromatography with flame ionization detection combined with chemometrics

This study assessed the feasibility of gas chromatography with flame ionization detection fingerprinting combined with chemometrics for quality analysis of Atractylodes rhizome. We extracted essential oils from 20 Atractylodes lancea and Atractylodes koreana samples by hydrodistillation. The variation in extraction yields (1.33-4.06%) suggested that contents of the essential oils differed between species. The volatile components (atractylon, atractydin, and atractylenolide I, II, and III) were quantified by gas chromatography with flame ionization detection and confirmed by gas chromatography with mass spectrometry, and the results demonstrated that the number and content of volatile components differed between A. lancea and A. koreana. We then calculated the relative peak areas of common components and similarities of samples by comparing the chromatograms of A. lancea and A. koreana extracts. Also, we employed several chemometric techniques, including similarity analysis, hierarchical clustering analysis, principal component analysis, and partial least-squares discriminate analysis, to analyze the samples. Results were consistent across analytical methods and showed that samples could be separated according to species. Five volatile components in the essential oils were quantified to further validate the results of the multivariate statistical analysis. The method is simple, stable, accurate, and reproducible. Our results provide a foundation for quality control analysis of A. lancea and A. koreana.

Chemiomics: network reconstruction and kinetics of port wine aging

Network reconstruction (NR) has proven to be useful in the detection and visualization of relationships among the compounds present in a Port wine aging data set. This view of the data provides a considerable amount of information with which to understand the kinetic contexts of the molecules represented by peaks in each chromatogram. The aim of this study was to use NR together with the determination of kinetic parameters to extract more information about the mechanisms involved in Port wine aging. The volatile compounds present in samples of Port wines spanning 128 years in age were measured with the use of GC-MS. After chromatogram alignment, a peak matrix was created, and all peak vectors were compared to one another to determine their Pearson correlations over time. A correlation network was created and filtered on the basis of the resulting correlation values. Some nodes in the network were further studied in experiments on Port wines stored under different conditions of oxygen and temperature in order to determine their kinetic parameters. The resulting network can be divided into three main branches. The first branch is related to compounds that do not directly correlate to age, the second branch contains compounds affected by temperature, and the third branch contains compounds associated with oxygen. Compounds clustered in the same branch of the network have similar expression patterns over time as well as the same kinetic order, thus are likely to be dependent on the same technological parameters. Network construction and visualization provides more information with which to understand the probable kinetic contexts of the molecules represented by peaks in each chromatogram. The approach described here is a powerful tool for the study of mechanisms and kinetics in complex systems and should aid in the understanding and monitoring of wine quality.