Comparison of ‘Beibinghong’ dry red wines from six producing areas based on volatile compounds analysis, mineral content analysis, and sensory evaluation analysis

Study on the Effect of Different Concentrations of SO2 on the Volatile Aroma Components of 'Beibinghong' Ice Wine

SO2 plays an important role in wine fermentation, and its effects on wine aroma are complex and diverse. In order to investigate the effects of different SO2 additions on the fermentation process, quality, and flavor of 'Beibinghong' ice wine, we fermented 'Beibinghong' picked in 2019. We examined the fermentation rate, basic physicochemical properties, and volatile aroma compound concentrations of 'Beibinghong' ice wine under different SO2 additions and constructed a fingerprint of volatile compounds in ice wine. The results showed that 44 typical volatile compounds in 'Beibinghong' ice wine were identified and quantified. The OAV and VIP values were calculated using the threshold values of each volatile compound, and t the effect of SO2 on the volatile compounds of 'Beibinghong' ice wine might be related to five aroma compounds: ethyl butyrate, ethyl propionate, ethyl 3-methyl butyrate-M, ethyl 3-methyl butyrate-D, and 3-methyl butyraldehyde. Tasting of 'Beibinghong' ice wine at different SO2 additions revealed that the overall flavor of 'Beibinghong' ice wine was the highest at an SO2 addition level of 30 mg/L. An SO2 addition level of 30 mg/L was the optimal addition level. The results of this study are of great significance for understanding the effect of SO2 on the fermentation of 'Beibinghong' ice wine.

Flavor Quality Analysis of Ten Actinidia arguta Fruits Based on High-Performance Liquid Chromatography and Headspace Gas Chromatography-Ion Mobility Spectrometry

Actinidia arguta is a fruit crop with high nutritional and economic value. However, its flavor quality depends on various factors, such as variety, environment, and post-harvest handling. We analyzed the composition of total soluble sugars, titratable acids, organic acids, and flavor substances in the fruits of ten A. arguta varieties. The total soluble sugar content ranged from 4.22 g/L to 12.99 g/L, the titratable acid content ranged from 52.55 g/L to 89.9 g/L, and the sugar-acid ratio ranged from 5.39 to 14.17 at the soft ripe stage. High-performance liquid chromatography (HPLC) showed that citric, quinic, and malic acids were the main organic acids in the A. arguta fruits. Headspace gas chromatography-ion mobility spectrometry (HS-GC-IMS) detected 81 volatile compounds in 10 A. arguta varieties, including 24 esters, 17 alcohols, 23 aldehydes, 7 ketones, 5 terpenes, 2 acids, 1 Pyrazine, 1 furan, and 1 benzene. Esters and aldehydes had the highest relative content of total volatile compounds. An orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor activity value (OAV) revealed that myrcene, benzaldehyde, methyl isobutyrate, α-phellandrene, 3-methyl butanal, valeraldehyde, ethyl butyrate, acetoin, (E)-2-octenal, hexyl propanoate, terpinolene, 1-penten-3-one, and methyl butyrate were the main contributors to the differences in the aroma profiles of the fruits of different A. arguta varieties. Ten A. arguta varieties have different flavors. This study can clarify the differences between varieties and provide a reference for the evaluation of A. arguta fruit flavor, variety improvement and new variety selection.

Comprehensive Evaluation of Ten Actinidia arguta Wines Based on Color, Organic Acids, Volatile Compounds, and Quantitative Descriptive Analysis

Actinidia arguta wine is a low-alcoholic beverage brewed from A. arguta with a unique flavor and sweet taste. In this study, the basic physicochemical indicators, color, organic acid, and volatile aroma components of wines made from the A. arguta varieties 'Kuilv', 'Fenglv', 'Jialv', 'Wanlv', 'Xinlv', 'Pinglv', 'Lvbao', 'Cuiyu', 'Tianxinbao', and 'Longcheng No.2' were determined, and a sensory evaluation was performed. The findings show that 'Tianxinbao' produced the driest extract (49.59 g/L), 'Kuilv' produced the most Vitamin C (913.46 mg/L) and total phenols (816.10 mg/L), 'Jialv' produced the most total flavonoids (477.12 mg/L), and 'Cuiyu' produced the most tannins (4.63 g/L). We analyzed the color of the A. arguta wines based on CIEL*a*b* parameters and found that the 'Kuilv' and 'Longcheng No.2' wines had the largest L* value (31.65), the 'Pinglv' wines had the greatest a* value (2.88), and the 'Kuilv' wines had the largest b* value (5.08) and C*ab value (5.66) of the ten samples. A total of eight organic acids were tested in ten samples via high-performance liquid chromatography (HPLC), and we found that there were marked differences in the organic acid contents in different samples (p < 0.05). The main organic acids were citric acid, quinic acid, and malic acid. The aroma description of a wine is one of the keys to its quality. A total of 51 volatile compounds were identified and characterized in ten samples with headspace gas chromatography-ion mobility spectrometry, including 24 esters, 12 alcohols, 9 aldehydes, 3 aldehydes, 2 terpenes, and 1 acid, with the highest total volatile compound content in 'Fenglv'. There were no significant differences in the types of volatile compounds, but there were significant differences in the contents (p < 0.05). An orthogonal partial least squares discriminant analysis (OPLS-DA) based on the odor activity value (OAV) showed that ethyl butanoate, ethyl pentanoate, ethyl crotonate, ethyl isobutyrate, butyl butanoate, 2-methylbutanal, ethyl isovalerate, and ethyl hexanoate were the main odorant markers responsible for flavor differences between all the A. arguta wines. Sensory evaluation is the most subjective and effective way for consumers to judge A. arguta wine quality. A quantitative descriptive analysis (QDA) of the aroma profiles of ten grapes revealed that the 'fruity' and 'floral' descriptors are the main and most essential parts of the overall flavor of A. arguta wines. 'Tianxinbao' had the highest total aroma score. The flavor and quality of A. arguta wines greatly depend on the type and quality of the A. arguta raw material. Therefore, high-quality raw materials can improve the quality of A. arguta wines. The results of the study provide a theoretical basis for improving the quality of A. arguta wines and demonstrate the application prospects of HS-GC-IMS in detecting A. arguta wine flavors.

Genome-wide transcriptome analysis uncovers gene networks regulating fruit quality and volatile compounds in mango cultivar 'Tainong' during postharvest

Mango is one of the most economically important fruit; however, the gene regulatory mechanism associated with ripening and quality changes during storage remains largely unclear. This study explored the relationship between transcriptome changes and postharvest mango quality. Fruit quality patterns and volatile components were obtained using headspace gas chromatography and ion-mobility spectrometry (HS-GC-IMS). The changes in mango peel and pulp transcriptome were analyzed during four stages (pre-harvesting, harvesting, maturity, and overripe stages). Based on the temporal analysis, multiple genes involved in the biosynthesis of secondary metabolites were upregulated in both the peel and pulp during the mango ripening process. Moreover, cysteine and methionine metabolism related to ethylene synthesis were upregulated in the pulp over time. Weighted gene co-expression network analysis (WGCNA) further showed that the pathways of pyruvate metabolism, citrate cycle, propionate metabolism, autophagy, and SNARE interactions in vesicular transport were positively correlated with the ripening process. Finally, a regulatory network of important pathways from pulp to peel was constructed during the postharvest storage of mango fruit. The above findings provide a global insight into the molecular regulation mechanisms of postharvest mango quality and flavor changes.

Widely Targeted Metabolomics Was Used to Reveal the Differences between Non-Volatile Compounds in Different Wines and Their Associations with Sensory Properties

In this study, metabolites from six varieties of wines, including 'Haasan' (A1), 'Zuoshaner' (A2), 'Beibinghong' (A3), 'Shuanghong' (A4), 'Zijingganlu' (A5), and 'Cabernet Sauvignon' (A6), were identified and quantified using widely targeted metabolomics analysis techniques. Based on the test results, 1172 metabolites were detected and classified into 18 categories. These include 62 amino acids, 178 alkaloids, 189 flavonoids, 106 phenols, 148 terpenoids, etc. Comparing the differential metabolites between the comparison groups of each variety, differences between varieties based on P-values and VIP values were shown. Among these differential metabolites, Trimethoprim and Crotonoside were screened out as core differential metabolites. Multiple comparisons also screened the biomarkers for each species. We used widely targeted metabolomics to reveal the differences between non-volatile compounds in different wines and their associations with sensory properties. We also used the simultaneous weighted gene co-expression network analysis (WGCNA) to correlate metabolites with sensory traits, including color difference values and taste characteristics. Two of the six key modules were screened by WGCNA for relevance to sensory traits (brown module and turquoise module). This study provides a high-throughput method for linking compounds to various sensory characteristics of food, opening up new avenues for explaining differences in different varieties of wine.

Characterization of the Key Aroma Volatile Compounds in Nine Different Grape Varieties Wine by Headspace Gas Chromatography-Ion Mobility Spectrometry (HS-GC-IMS), Odor Activity Values (OAV) and Sensory Analysis

During this study, the physicochemical properties, color, and volatile aroma compounds of the original wines produced from the grape varieties ‘Hassan’, ‘Zuoshaner’, ‘Beibinghong’, ‘Zuoyouhong’, ‘Beta’, ‘Shuanghong’, ‘Zijingganlu’, ‘Cabernet Sauvignon’, and ‘Syrah’ were determined and sensory evaluation was performed. Results indicated that ‘Hassan’ contained the most solids, ‘Zuoshaner’ produced the most total acid, residual sugar, total anthocyanin, and total phenol, and ‘Shuanghong’ produced the most tannin. Calculation of the chroma and hue of the wines according to the CIEL*a*b* parameters revealed that the ‘Cabernet Sauvignon’ wines were the brightest of the nine varieties and that the ‘Zuoshaner’ wines had the greatest red hue and yellow hue and the greatest saturation’. A total of 52 volatile compounds were identified and quantified in nine wine samples by HS-GC-IMS analysis, with the most significant number of species detected being 20 esters, followed by 16 alcohols, 8 aldehydes, four ketones, one terpene, and one furan, with the highest total volatile compound content being ‘Beta’. A total of 14 volatile components with OAV (odor activity value) >1 were calculated using the odor activity value (OAV) of the threshold of the aromatic compound, and the OPLS-DA analysis was performed by orthogonal partial least squares discriminant analysis (OPLS-DA) using the OAV values of the compounds with OAV values >1 as the Y variable. The VIP (Variable Importance in Projection) values of six compounds, ethyl isobutyrate, ethyl hexanoate-D, 2-methylpropanal, ethyl octanoate, ethyl butanoate-D, and Isoamyl acetate-D, were calculated to be higher than one between groups, indicating that these six compounds may influence aroma differences. It is essential to recognize that the results of this study have implications for understanding the quality differences between different varieties of wines and for developing wines that have the characteristics of those varieties.

Validation Study on the Simultaneous Quantitation of Multiple Wine Aroma Compounds with Static Headspace-Gas Chromatography-Ion Mobility Spectrometry

A new quantitative method based on static headspace-gas chromatography-ion mobility spectrometry (SHS-GC-IMS) is proposed, which enables the simultaneous quantitation of multiple aroma compounds in wine. The method was first evaluated for its stability and the necessity of using internal standards as a quality control measure. The two major hurdles in applying GC-IMS in quantitation studies, namely, nonlinearity and multiple ion species, were also investigated using the Boltzmann function and generalized additive model (GAM) as potential solutions. Metrics characterizing the model performance, including root mean squared error, bias, limit of detection, limit of quantitation, repeatability, reproducibility, and recovery, were investigated. Both nonlinear fitting methods, Boltzmann function and GAM, were able to return desirable analytical outcomes with an acceptable range of error. Potential pitfalls that would cause inaccurate quantitation, that is, effects of ethanol content and competitive ionization, were also discussed. The performance of the SHS-GC-IMS method was subsequently compared against that of a currently established method, namely, GC-MS, using commercial wine samples. These findings provide an initial validation of a GC-IMS-based quantitation method, as well as a starting point for further enhancing the analytical scope of GC-IMS.