Yiyuan Chen

This study aimed to identify umami peptides in non-alcoholic beer and clarify their potential contribution to taste reconstruction and aftertaste improvement. Peptides were profiled by RPLC-Q-TOF-MS and screened using machine learning prediction, molecular docking, MM-GBSA analysis, and sensory validation. Under the criteria of −10logP ≥ 15 and ALC ≥ 90.00%, 2081 peptides were identified. Among them, 122 potential umami peptides were predicted, and 117 peptides were successfully docked with the T1R1/T1R3 umami receptor. The docked peptides were mainly short to medium oligopeptides, especially tetrapeptides and pentapeptides, which accounted for 40.17% and 35.90%, respectively. Based on docking score, structural diversity, and peptide length distribution, CTGAA, IDQILG, KDTHP, QRQ, and EITGR were selected as representative candidates. These peptides showed favorable receptor binding, mainly supported by hydrogen bonding, electrostatic interactions, and local hydrophobic contacts. Sensory validation further showed that the 5 peptides improved umami and aftertaste cleanliness to different degrees. Umami intensity increased by 7.58% to 22.73%, while aftertaste cleanliness increased by 5.80% to 17.39%. Among them, CTGAA showed the strongest umami enhancement, and QRQ produced the greatest improvement in aftertaste cleanliness. These results suggest that selected umami peptides may contribute to flavor reconstruction in non-alcoholic beer by enhancing umami perception and improving aftertaste quality.

Beer consumption behaviors within China exhibited significant regional heterogeneity. To elucidate the specific differences in beer consumer behaviors across different regions and their influencing factors, this study systematically analyzed the sensory preference characteristics of consumers in the Chinese beer market based on machine learning methods, and further revealed the core driving mechanisms influencing their consumption behaviors. By integrating consumer data from different regions, a comprehensive dataset was constructed encompassing sensory attribute evaluations (bitterness, malt flavor, hop aroma, smoothness of mouthfeel, foam characteristics, etc.) and other dimensional consumption behavior variables (brand, beer packaging, etc.). Utilizing an ensemble learning framework (LightGBM), Support Vector Machine (SVM), and decision tree models for feature mining, the study identified important factors influencing the consumption behaviors of Chinese beer consumers. Specifically, consumers in mature and upgrading markets placed greater emphasis on the overall drinking experience and drinkability when purchasing beer, whereas consumers in scale-dominant and mainstream competitive markets considered foam persistence, fineness, and light brown color as core quality indicators. Conversely, consumers in potential growth and emerging cultivation markets demonstrated strong brand orientation. This indicated that the factors influencing beer consumption behaviors varied significantly across regions. Through a data-driven paradigm, this study revealed the underlying regional mechanisms behind consumption decisions in different regional beer markets in China, providing a theoretical foundation and empirical support for cross-regional product customization, precision marketing, and resource optimization.

Alcoholic beverages held significant importance in global dietary cultures. Their consumption was subject to the combined influence of sociocultural, economic, and psychological factors. As one of the world’s major alcohol consumption markets, China exhibited increasingly diverse drinking patterns, yet research on drinking behaviors based on the Chinese population remained relatively limited. This study employed a questionnaire-based survey to collect data. A total of 2119 Chinese adult alcohol consumers were recruited between October 2024 and April 2025. The sample encompassed individuals with diverse demographic backgrounds, including variations in gender, age, education level, monthly income, and occupation. Based on this dataset, multivariate logistic regression analysis was applied to systematically examine the key factors influencing drinking frequency among Chinese adult drinkers. The study found that the majority of drinkers in China engaged in low- to moderate-frequency drinking, with significant variations observed across different demographic groups: women aged 31–50 showed a higher proportion of high-frequency drinking, while individuals over 50 experienced a notable decline in drinking frequency. Individuals with smoking habits and higher stress levels were more likely to engage in high-frequency drinking. In contrast, those who report higher subjective well-being tended to exhibit moderate-frequency drinking patterns, characterized by moderate but non-excessive consumption. This study constructed a multi-dimensional profile of alcohol consumption behavior in China, thereby providing precise guidance for future product positioning and development, promoting high-quality development in the alcoholic beverage industry, and offering a scientific basis for advocating a culture of moderate and healthy drinking.

In this study, inter-brand variations in volatile flavor compound profiles of four lager beers were systematically investigated by integrating sensory evaluation with GC-MS, GC×GC-TOF-MS, and GC-O-MS. A total of 594 volatile compounds were identified, of which 71 with odor activity values (OAV) ≥ 1 were found to contribute directly to aroma expression. Additionally, 59 compounds with taste activity values (TAV) ≥ 1 were identified and may also contribute to taste perception. Furthermore, 53 aroma-active compounds were confirmed through GC-O-MS, providing additional evidence for their sensory contribution. Partial least squares discriminant analysis (PLS-DA), correlation analysis, and flavor addition experiments revealed brand-specific differential flavor compounds. Ultimately, twenty key differential flavor compounds, encompassing esters, alcohols, aromatic compounds, acids, lactones, and others, were confirmed to contribute to fruity, floral, burnt, and sweet notes. Phenethyl alcohol, with concentrations varying from 1377.1 mg/L in QD to 3297.5 mg/L in HR, showed a more than 2.4-fold difference across brands and was strongly associated with fruity (r = 0.553) and floral (r = 0.564) aroma. These compounds acted in combination to shape distinct aroma profiles. This study provides a molecular-level basis for understanding lager beer flavor and offers practical guidance for targeted flavor modulation in brewing.

Pale lager dominates global beer markets. However, rising living standards and changing consumer expectations have reshaped sensory preferences, highlighting the importance of understanding consumers’ true sensory priorities. In this study, a twenty-eight-item questionnaire, refined through multiple rounds of optimization, was distributed across China and yielded 1837 valid responses. Spearman correlation analysis and partial least-squares regressions showed that educational background and spending willingness exerted the strongest independent effects on sensory priorities. A hybrid analytic hierarchy process–entropy weight method–Delphi procedure was then applied to quantify sensory attribute importance. Results indicated that drinking sensation (30.92%) emerged as the leading driver of pale lager choice, followed by taste (26.60%), aroma (24.77%), and appearance (17.71%), confirming a flavor-led and experience-oriented preference structure. Weighting patterns differed across drinking-frequency cohorts: consumers moved from reliance on overall mouthfeel, through heightened sensitivity to negative attributes, to an eventual focus on subtle hedonic details. Based on these findings, a new sensory evaluation scale was developed and validated against consumer preference rankings, showing significantly stronger alignment with consumer preferences (ρ = 0.800; τ = 0.667) than the traditional scale. The findings supply actionable metrics and decision tools for breweries, supporting applications in product development, quality monitoring, and targeted marketing.

Baijiu is popular with a long history and balanced flavor. Flavor type is the most widely used classification mode for Baijiu. However, the evolutionary relationships of Baijiu flavor types and the differential markers between flavor types are still unclear, significantly impacting the development of the Baijiu industry. In this study, a total of 319 trace components were identified using gas chromatography–olfactometry–mass spectrometry and gas chromatography–mass spectrometry. Among them, 91 trace components with high odor active values or taste active values were recognized as flavor components. Then random forests were conducted to screen differential markers between the derived and basic flavor types, while a principal component analysis assessed their effectiveness in distinguishing the flavor types of Baijiu. Finally, 19 differential markers (including 3-methylbutyric acid, pentanoic acid, 2-butanol, 2,3-butanediol, ethyl pro-panoate, isobutyl acetate, ethyl butanoate, ethyl hexanoate, ethyl heptanoate, ethyl lactate, ethyl 2-hydroxy butanoate, isopentyl hexanoate, ethyl nonanoate, isopropyl myristate, ethyl tetradecanoate, ethyl benzoate, 2,4-di-t-butylphenol, 2-methylbutanal and 3-octanone) were screened and proven to effectively reveal the evolution of Baijiu flavor types; these were further verified as key differential markers using addition tests and a correlation analysis.

The storage process of Baijiu is an integral part of its production (the quality undergoes substantial changes during the aging process of Baijiu). As the storage time extends, the flavor compounds in Baijiu tend to undergo coordinated transformation, thereby enhancing the quality of Baijiu. Among them, long-chain fatty acid ethyl esters (LCFAEEs) were widely distributed in Baijiu and have been shown to have potential contributions to the quality of Baijiu. However, the current research on LCFAEEs in Baijiu predominantly focuses on the olfactory sensation aspect, while there is a lack of systematic investigation into their influence on taste and evaluation after drinking Baijiu during the aging process. In light of this, the present study investigates the distribution of LCFAEEs in Baijiu over different years. We have combined modern flavor sensory analysis with multivariate chemometrics to comprehensively and objectively explore the influence of LCFAEEs on Baijiu quality. The results demonstrate a significant positive correlation between the concentration of LCFAEEs and the fruity aroma (p < 0.05, r = 0.755) as well as the aged aroma (p < 0.05, r = 0.833) of Baijiu within a specific range; they can effectively reduce the off-flavors and spicy sensation of Baijiu. Furthermore, additional experiments utilizing a single variable suggest that LCFAEEs were crucial factors influencing the flavor of Baijiu, with Ethyl Palmitate (EP) being the most notable LCFAEE that merits further systematic investigation.