The production of Chinese Baijiu relies on the synergistic metabolism of multi-species microbial communities in an open environment. Its intricate microbial succession and flavor formation mechanisms have long been considered complex systems that are difficult to fully deconstruct. Traditional culture-dependent techniques inherently fail to comprehensively capture the actual functional roles and dynamic regulation of “viable but non-culturable” (VBNC) microorganisms within this complex system. In recent years, the rapid advancement of multi-omics technologies has offered a novel perspective for elucidating the underlying fermentation mechanisms of Baijiu. This paper systematically reviews the recent progress in the application of metagenomics, metatranscriptomics, metaproteomics, and metabolomics in Baijiu research. Specific focus is placed on the unique contributions of these tools to resolving microbial community structural diversity, mining key functional genes and enzymes, uncovering microbial stress response mechanisms under environmental fluctuations, identifying phages and spoilage microorganisms, and tracing the metabolic pathways of flavor substances. Furthermore, the pivotal role of multi-omics integration strategies in constructing “microbe–metabolite” regulatory networks is highlighted. Finally, current challenges regarding standardization and data integration are discussed, with an outlook on leveraging omics big data to promote digital monitoring and intelligent brewing in the Baijiu industry.

Background: Qu was the core starter of traditional Chinese fermentation and had long relied on artisan experience, which led to limited batch stability and standardization. This review organized the preparation processes, microbial diversity, and application patterns of qu in foods from experience to science perspective. Methods: This work summarized typical process parameters for daqu, xiaoqu, hongqu, wheat bran or jiangqu, douchi qu, and qu for mold curd blocks used for furu. Parameters covered raw material moisture, bed thickness, aeration or turning, drying, final moisture, and classification by peak temperature. Multi-omics evidence was used to analyze the coupling of temperature regime, community assembly, and functional differentiation. Indicators for pigment or enzyme production efficiency and safety control such as citrinin in hongqu were included. Results: Daqu showed low, medium, and high temperature regimes. Thermal history governed differences in communities and enzyme profiles and determined downstream fermentation fitness. Xiaoqu rapidly established a three-stage symbiotic network of Rhizopus, Saccharomyces, and lactic acid bacteria, which supported integrated saccharification and alcohol fermentation. Hongqu centered on Monascus and achieved coordinated pigment and aroma formation with toxin risk control through programmed control of temperature, humidity, and final moisture. Wheat bran or jiangqu served as an enzyme production engine for salt-tolerant fermentation, and the combined effects of heat and humidity during the qu period, aeration, and bed loading determined hydrolysis efficiency in salt. Douchi and furu mold curd blocks used thin-layer cultivation and near-saturated humidity to achieve stable mold growth and reproducible interfacial moisture. Conclusions: Parameterizing and online monitoring of key variables in qu making built a process fingerprint with peak temperature, heating rate, and moisture rebound curve at its core. Standardization and functional customization guided by temperature regime, community, and function were the key path for the transition of qu from workshop practice to industry and from experience to science. This approach provided replicable solutions for flavor consistency and safety in alcoholic beverages, sauces, vinegars, and soybean products.

Traditional fermented foods and beverages (TFFB) rely on complex microbial communities that generate distinctive flavors, nutritional attributes, and cultural value, but spontaneous or empirically controlled fermentations often limit reproducibility. Defined microbial consortia (DMCs) provide a promising route for improving fermentation controllability and product consistency, although overly simplified starters may fail to reproduce the ecological robustness and sensory complexity of traditional systems. This review focuses on how multi-omics and culturomics can support rational DMC design in TFFB. We summarize how metagenomics, metatranscriptomics, metaproteomics, metabolomics, and culturomics reveal community structure, functional potential, active expression, metabolic output, and cultivable strain resources. Particular attention is given to translating multi-omics evidence into strain prioritization through the identification of keystone microorganisms that drive core fermentation functions and helper microorganisms that support ecological or metabolic stability. We further propose an Assembly-Assessment-Redesign (A-A-R) framework for iterative DMC optimization, linking strain selection, functional validation, performance evaluation, and consortium redesign. Finally, we discuss key challenges, including cross-omics integration, experimental verification of microbial functions, standardized validation criteria, and the transfer of laboratory-designed consortia to industrial fermentation systems.

Daqu functions as a core saccharifying and fermenting starter in Baijiu production and acts as a complex microecological reactor in open solid-state fermentation. The formation of Baijiu flavor is closely associated with microbial community assembly, enzymatic activities, and metabolic interactions occurring within Daqu. However, the open production environment also exposes the Daqu system to multiple external disturbances that may influence its microecological stability and fermentation performance. This review summarizes recent advances in understanding the microecology of Daqu, focusing on microbial succession, metabolic pathways related to flavor formation, and environmental factors affecting Daqu quality. Particular attention is given to how external disturbances during production and storage may influence microbial communities, enzymatic functions, and aroma compound formation. Based on current knowledge, a conceptual framework linking environmental factors, microbial community dynamics, metabolic activity, and flavor outcomes is proposed. In addition, strategies for maintaining microecological stability and ensuring flavor consistency are discussed, including environmental management, process optimization, physical control technologies, and integrated quality monitoring systems. Emphasis is placed on combining process control with modern analytical approaches such as multi-omics technologies and process analytical technologies (PAT) to improve traceability and precision management during Daqu production. Overall, this review provides a systematic perspective on the relationships among Daqu microecology, process conditions, and flavor formation and highlights future research directions for achieving stable and controllable Baijiu fermentation systems.

Flavor-relevant trace volatiles and microbial communities were examined in six sauce-aroma high-temperature Daqu samples. Headspace solid-phase microextraction coupled with gas chromatography–mass spectrometry (HS-SPME-GC-MS) quantified 210 trace volatile compounds across 14 chemical classes. Orthogonal partial least squares discriminant analysis (OPLS-DA) with variable importance in projection (VIP) screening was integrated with sensory scoring, correlation analysis, and molecular docking to an olfactory receptor model. Volatile profiles showed clear stratification in total abundance. Pyrazines dominated the high-total group. Tetramethylpyrazine served as a major driver. Sensory evaluation indicated that aroma explained overall quality best. (E)-2-pentenal and dimethyl trisulfide showed significant positive associations with aroma and overall scores. In the olfactory receptor, the polar residue module that provides directional constraints for Daqu odor activation was formed by Ser75, Ser92, Ser152, Ser258, Thr74, Thr76, Thr98, Thr200, Gln99, and Glu94. The hydrogen-bond or charge network was further reinforced by Arg150, Arg262, Asn194, His180, His261, Asp182, and Gln181. The core discriminant set comprised acetic acid, hexanoic acid, (E)-2-pentenal, nonanal, decanal, dimethyl trisulfide, trans-3-methyl-2-n-propylthiophane, 2-hexanone oxime, ethyl linoleate, propylene glycol, 2-ethenyl-6-methylpyrazine, 4-methylquinazoline, 5-methyl-2-phenyl-2-hexenal, and 1,2,3,4-tetramethoxybenzene. Sequencing revealed higher bacterial diversity than fungal. Bacillus and Kroppenstedtia were dominant bacterial genera. Aspergillus, Paecilomyces, Monascus, and Penicillium were major fungal genera. Correlation patterns suggested that Bacillus and Monascus were positively linked to acetic acid and 1,2,3,4-tetramethoxybenzene. Together, these results connected chemical fingerprints, sensory performance, receptor-level plausibility, and microbial ecology. Concrete targets are provided for quality control of high-temperature Daqu.

Traditional doubanjiang was investigated to identify endogenous peptides that may contribute to taste maintenance under salt-reduction conditions. Peptidomics identified 1230 peptides at −10logP ≥ 15. UMPred-FRL predicted 161 potential umami peptides, and molecular docking showed that 141 of these peptides could enter the binding site of the T1R1/T1R3 receptor. The successfully docked sequences were mainly short oligopeptides containing three to five amino acid residues. Based on docking scores, six representative candidate peptides were screened, namely EESP, SCPH, SSSGF, PDTE, SYH, and DYDS. Docking and MM-GBSA analyses suggested that these peptides mainly bound within the VFT cavity of T1R1/T1R3, and the interacting residues were dominated by polar residues such as Ser, Asn, Gln, and His and hydrophobic residues such as Tyr, Ile, Leu, and Val. MM-GBSA further suggested that vdW was the major favorable contributor, while Lipo supported complex stability. The umami thresholds of the six peptides ranged from 0.14 to 1.09 mmol/L. Experimental validation by threshold determination and sensory addition showed that all six peptides significantly increased saltiness, whereas their effects on umami differed. PDTE showed the strongest umami-enhancing effect, while SSSGF, SYH, and SCPH exhibited more pronounced saltiness synergy. These results suggest that the screened peptides do not necessarily amplify umami in complex food systems, but may contribute to taste maintenance under salt-reduction conditions through umami support, saltiness synergy, and taste-structure remodeling.