Umami taste in lager beer not only determined body fullness and the backbone of aftertaste, but also affected the controllability and interpretability of flavor expression across the entire brewing process. Based on stage-wise sampling, peptidomic profiles were established on wort fermentation day 0, day 1, day 3, and day 9. A total of 25,592 peptides were identified by reversed-phase liquid chromatography–quadrupole time-of-flight mass spectrometry (RPLC-QTOF-MS). Molecular informatics screening was performed using UMPred-FRL (a feature representation learning-based meta-predictor for umami peptides) and TastePeptides-Meta (a one-stop platform for taste peptides and prediction models), yielding 7255 potential umami peptides. From these, 145 peptides were further selected for molecular docking. In addition, 6 representative umami peptides were selected for receptor-level validation and structural analysis. Mechanistically, the umami receptor taste receptor type 1 member 1/taste receptor type 1 member 3 (T1R1/T1R3) belonged to class C G protein-coupled receptor (GPCR) and relied on the extracellular Venus flytrap (VFT) domain for ligand capture. Ligand-induced VFT conformational convergence transmitted changes to the transmembrane region and triggered signal transduction. Docking and energy decomposition indicated that the ionic group primarily contributed to orientation and anchoring. Salt-bridge or hydrogen-bond networks were formed around Lys228, Arg240, Glu206, Asp210, Asn141, and Gln138, thereby reducing conformational freedom. Meanwhile, hydrophobic side chains obtained major binding gains within a hydrophobic microenvironment formed by Val135, Ile137, Leu165, Tyr166, Trp78, and His79. These results reflected a synergistic mode in which charge pairing enabled positioning and hydro-phobic complementarity promoted VFT closure. To experimentally confirm sensory relevance, 6 representative peptides were individually spiked into 4 brewing-stage beer samples, which produced a clear stratification pattern across stages. Notably, peptides with favorable docking-derived binding propensity did not necessarily enhance umami perception, and several longer peptides showed persistent negative sensory shifts, supporting that binding affinity alone could not be treated as a proxy for perceived umami in the beer matrix. At the node level, the cumulative abundance of umami peptides showed a significant positive correlation with umami scores, with a Pearson correlation coefficient of r = 0.963 and p = 0.037. This result indicated good linear consistency between umami peptide content and the upward shift in umami taste in lager beer. Umami peptide clusters were further proposed as a more appropriate functional unit, and an umami peptide cluster database spanning the full process was constructed. This database provided a reusable resource for process control and flavor prediction.

Despite increasing interest in beer-derived umami peptides, their formation during lager beer fermentation and their potential roles in receptor recognition and sensory perception remain insufficiently understood. Therefore, this study combined peptidomics, in silico screening, receptor-oriented analysis, and sensory evaluation to investigate the dynamic changes in umami-related peptides throughout lager beer fermentation and to explore their possible sensory relevance. Peptide profiles varied markedly across the fermentation process, indicating continuous proteolysis and dynamic restructuring of the peptide pool. From these profiles, candidate umami peptides were screened, and representative short peptides with plausible receptor-binding characteristics were selected for further evaluation. These peptides showed measurable taste activity and were mainly associated with modulation of the umami–bitterness–aftertaste dimension, whereas their effects on aroma and overall balance were limited. In addition, the abundance of umami-related peptides was positively associated with perceived umami intensity. Overall, the results suggest that fermentation-derived peptides may contribute to taste perception in lager beer and provide a basis for further studies on flavor-oriented brewing and process regulation.

As Feng-flavor Baijiu increasingly shifts toward consumer-oriented product development, clarifying consumers’ shared sensory priorities and age-related differences is essential for aligning its traditional style with evolving market demands. This study collected 1523 questionnaires across China, of which 1357 valid responses were analyzed. A hierarchical sensory system comprising three primary dimensions—aroma, taste, and drinking perception—and 24 secondary attributes was evaluated using hierarchical weighting, a proportional sensory flavor wheel, machine learning, and SHAP interpretation. Drinking perception received the highest weight (35.23%), although it was only slightly higher than aroma (33.54%) and taste (31.22%). Jiuhai aroma, sweetness, comfort, and purity were identified as the leading attributes within their respective dimensions. Machine learning further identified purity, persistence, saltiness, comfort, and harmony as attributes with relatively high contributions to age-group classification. Age-group differences were not concentrated in any single sensory attribute but were reflected in the classification information jointly provided by multiple sensory attributes. Descriptive group comparisons showed decreasing trends in the relative weights of saltiness and sourness across the 18–30-, 31–45-, and ≥46-year groups, although neither difference remained statistically significant after Benjamini–Hochberg correction. Comfort, bitterness, and honey aroma were relatively more prominent in the ≥46-year group, whereas grain aroma was relatively more prominent in the 31–45-year group. Sweetness and Jiuhai aroma had relatively high overall weights but contributed less to age-group classification, suggesting that they may represent more broadly shared sensory priorities across age groups. These findings identify candidate sensory priorities and segmentation indicators for subsequent validation using actual products, consumer liking tests, and ideal-intensity assessments.