This study was designed to systematically identify novel umami peptides in lager beer, clarify their molecular interactions with the T1R1/T1R3 receptor, and determine their specific effects on multidimensional sensory attributes. The peptides were characterized by LC-MS/MS combined with de novo sequencing, and 906 valid sequences were obtained. Machine-learning models (UMPred-FRL, Tastepeptides-Meta, and Umami-MRNN) predicted 76 potential umami peptides. These candidates were docked to T1R1/T1R3 with the CDOCKER protocol, producing 57 successful complexes. Six representative peptides—KSTEL, DELIK, DIGISSK, IEKYSGA, DEVR, and PVPL—were selected for 100 ns molecular-dynamics simulations and MM/GBSA binding-energy calculations. All six peptides stably occupied the narrow cleft at the T1R1/T1R3 interface. Their binding free energies ranked as DEVR (−44.09 ± 5.47 kcal mol⁻¹) < KSTEL (−43.21 ± 3.45) < IEKYSGA (−39.60 ± 4.37) ≈ PVPL (−39.53 ± 2.52) < DELIK (−36.14 ± 3.11) < DIGISSK (−26.45 ± 4.52). Corresponding taste thresholds were 0.121, 0.217, 0.326, 0.406, 0.589, and 0.696 mmol L⁻¹ (DEVR < KSTEL < IEKYSGA < DELIK < PVPL < DIGISSK). TDA-based sensory validation with single-factor additions showed that KSTEL, DELIK, DEVR, and PVPL increased umami scores by ≈21%, ≈22%, ≈17%, and ≈11%, respectively, while DIGISSK and IEKYSGA produced marginal changes (≤2%). The short-chain peptides thus bound with high affinity to T1R1/T1R3 and improved core taste and mouthfeel but tended to amplify certain off-flavors, and the long-chain peptides caused detrimental impacts. Future formulation optimization should balance flavor enhancement and off-flavor suppression, providing a theoretical basis for targeted brewing of umami-oriented lager beer.

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.

Lager beer has the characteristics of a refreshing aroma, clean and less intense taste, as well as a low alcohol degree, which is suitable for daily drinking. This study aimed to clarify the relationship between important flavor compounds and flavor profiles for lager beer. Headspace solid-phase microextraction, solvent-assisted flavor evaporation combined with comprehensive two-dimensional gas chromatography–mass spectrometry, gas chromatography–mass spectrometry, and gas chromatography-olfactometry–mass spectrometry were applied for the qualitative and quantitative analysis of the trace components in lager beer. Furthermore, the recombination experiment was successfully applied to simulate the flavor profile, and the omission experiment was conducted to study the effects of flavor compounds on the flavor profile. A total of nine compounds were identified as the key flavor compounds, and their contribution to the flavor characteristics of lager beer was verified according to validation experiments. It was found that the influence of the key flavor compounds on the sensory attributes such as malty aroma, fruity aroma, sweetness, and bitterness varied with their concentration. These findings might provide ideas for the research regarding the flavor compounds and flavor profile of lager beer, and contribute to the development of different types of beer in the future.

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.

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.

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.