Deciphering the core microbes and their interactions in spontaneous Baijiu fermentation: A comprehensive review

The spontaneous Baijiu fermentation system harbors a complex microbiome that is highly dynamic in time and space and varies depending on the Jiuqu starters and environmental factors. The intricate microbiota presents in the fermentation environment is responsible for carrying out various reactions. These reactions necessitate the interaction among the core microbes to influence the community function, ultimately shaping the distinct Baijiu styles through the process of spontaneous fermentation. Numerous studies have been conducted to enhance our understanding of the diversity, succession, and function of microbial communities with the aim of improving fermentation manipulation. However, a comprehensive and critical assessment of the core microbes and their interaction remains one of the significant challenges in the Baijiu fermentation industry. This paper focuses on the fermentation properties of core microbes. We discuss the state of the art of microbial traceability, highlighting the crucial role of environmental and starter microbiota in the Baijiu brewing microbiome. Also, we discuss the various interactions between microbes in the Baijiu production system and propose a potential conceptual framework that involves constructing predictive network models to simplify and quantify microbial interactions using co-culture models. This approach offers effective strategies for understanding the core microbes and their interactions, thus beneficial for the management of microbiota and the regulation of interactions in Baijiu fermentation processes.

Current situation, trend, and prospects of research on functional components from by-products of baijiu production: A review

In the present scenario marked by energy source shortages and escalating concerns regarding carbon dioxide emissions, there is a growing emphasis on the optimal utilization of biomass resources. Baijiu, as the Chinese national spirit, boasts remarkably high sales volumes annually. However, the production of baijiu yields various by-products, including solid residues (Jiuzao), liquid wastewater (Huangshui and waste alcohol), and gaseous waste. Recent years have witnessed dedicated research aimed at exploring the composition and potential applications of these by-products, seeking sustainable development and comprehensive resource utilization. This review systematically summarizes recent research, shedding light on both the baijiu brewing process and the bioactive compounds present baijiu production by-products (BPBPs). The primary focus lies in elucidating the potential extraction methods and applications of BPBPs, offering a practical approach to comprehensive utilization of by-products in functional food, medicine, cosmetic, and packaging fields. These applications not only contribute to enhancing production efficiency and mitigating environmental pollution, but also introduce innovative concepts for the sustainable advancement of associated industries. Future research avenues may include more in-depth compositional analysis, the development of utilization technologies, and the promotion of potential industrialization.

Selection of initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu

The initial microbial community is critical for the production of volatile metabolites during traditional food fermentations. Selection of the initial community plays an important role in improving the quality of fermented foods. Here, we used high-throughput amplicon sequencing combined with multivariate statistical methods to explore the microbial succession in stacking and alcoholic fermentation stages in sesame flavor-type baijiu making. We proposed a selection strategy for the initial microbial community in the alcoholic fermentation stage, which determined the quality of baijiu. Results suggested that the microbial composition statistically differed between stacking and alcoholic fermentation stages (ANOSIM, Bacteria: R = 0.60, P = 0.001; Fungi: R = 0.53, P = 0.001). Microbial succession drove metabolic succession (Bacteria: r = 0.87, P < 0.05; Fungi: r = 0.56, P < 0.05) in alcoholic fermentation. The fermentation time of stacking fermentation determined the initial community for alcoholic fermentation, and it can be used as a criterion for selection of the initial microbial community for alcoholic fermentation. The succession distance of the microbial community was varied and reached the highest (Bacteria: 0.048, Fungi: 0.064) at 30 h in stacking fermentation. When we selected 30 h as stacking fermentation time, the concentration (4.58 mg/kg) and diversity (0.61) of volatile metabolites were highest at the end of alcoholic fermentation. This work developed a succession distance-guided approach to select the initial microbial community for the alcoholic fermentation of sesame flavor-type baijiu. This approach can be used to improve the quality of baijiu.

Acidity drives volatile metabolites in the spontaneous fermentation of sesame flavor-type baijiu

Environmental factors play an important role in contributing to intricate compositional dynamics and volatile metabolites in food fermentation. However, our understanding of which and how environmental factors affect volatile metabolites during sesame flavor-type baijiu fermentation is poor. Here, we examined the effects of environmental factors on the bacterial and fungal community to determine how changes in representative factors impact the microbial structure, diversity, and volatile metabolites in three fermentations. Results showed that bacterial community (ANOSIM: R = 0.79, P = 0.001), fungal community (ANOSIM: R = 0.65, P = 0.001), and volatile metabolites (ANOSIM: R = 0.84, P = 0.001) were significantly different in three fermentations. Acidity, ethanol, and moisture negatively impacted bacterial composition and diversity (P < 0.05). The fungal diversity and structure were positively and significantly affected by acidity (path coefficient, b = 0.54 for diversity, b = 0.35 for structure, P < 0.05). The fungal community rather than the bacterial community was the strongest driver of volatile metabolites. Fungal structure and diversity were equally important for the composition and content of volatile metabolites (structure: b = 0.50, diversity: b = 0.56, P < 0.05). 66 % of variations in volatile metabolites could be explained. Altogether these results indicated that acidity strongly drove volatile metabolites by modulating fungal structure and diversity. This work provides insights into managing volatile metabolites by regulating initial acidity in sesame flavor-type baijiu fermentation.

Applications and prospects of the automation of compound flavor baijiu production by solid-state fermentation

Baijiu, the national liquor of China, is produced using traditional solid-state fermentation (SSF). SSF automation during compound flavor baijiu (CFB) production can considerably reduce labor intensity and required manpower, improve the working environment, decrease costs, and increase efficiency. The approaches for SSF automation in CFB production can provide a reference for the automation of SSF in other industries. Therefore, this review compares the traditional and automated processes for jiuqu starter production, SSF, and solid-state distillation during baijiu brewing. Furthermore, specific applications of automation technology and equipment are summarized for each process. The problems and challenges associated with the automation of the process are then detailed and future development directions are proposed. Thus, this review provides an overall introduction to and insight into the developments and challenges in the automation of the CFB brewing process, helping to promote automation in the brewing of other baijiu flavor classes and SSF products.

A flavoromics strategy for the differentiation of different types of Baijiu according to the non-volatile organic acids

Non-volatile organic acids (NVOAs) in 12 main flavor types of Baijiu were analyzed by a derivatization method combined with GC-MS and 38 NVOAs were quantified. Meanwhile, a flavoromics strategy based on the contents of NVOAs in the 12 flavor types of Baijiu was successfully used to the differentiation of Baijiu. PLS-DA models (explained variation, predictive capability) were used to consider different categories: fermentation process (0.931, 0.870), starter (0.921, 0.834), fermentation container (0.899, 0.810) and raw material (0.951, 0.909). Based on the selected categories, suitable separations were achieved, and the classification ability of these models were nearly 100%. As a result, the model demonstrated its ability to perfectly distinguish different types of Baijiu. Seventeen potential markers were identified by variable importance in projection method and were further processed using heatmap and hierarchical cluster analysis, indicating that the NVOAs had great discrimination power to differentiate Baijiu.

Furfural and organic acid targeted carbon dot sensor array for the accurate identification of Chinese baijiu

Baijiu quality control has always been a major challenge for researchers. In this paper, taking furfural which is closely related to baijiu brewing process and organic acids related to baijiu fermentation process and microorganism types as the main discriminating factors, a carbon dot (CDs) sensor array targeting furfural and organic acids was constructed to identify 41 kinds of baijiu. Through the fluorescence response investigation of CDs synthesized by isomers of benzenediol, aminophenol, and phenylenediamine to different baijiu, two CDs synthesized by meta-benzene substitutions containing -NH₂ were selected to build a fluorescence sensor array. Due to the aggregation-induced enhancement effect between furfural and the CDs, and the protonation of organic acid and the CDs, different fluorescence changes were observed, the sensor array combined with partial least squares regression could quantitatively analyze furfural and organic acids. What is more, semi-quantitative analysis of furfural and lactic acid in baijiu was performed. Owing to the interaction of the two CDs with furfural and organic acids in baijiu, the sensor array could accurately identify different baijiu through linear discriminant analysis. This sensor array has potential applications in the quantitative analysis of flavor substances in other alcoholic beverages, moreover, this method could provide a quick response and practical tool for real-time quality control monitoring in the baijiu industry.