Gas chromatography (GC) and gas chromatography-mass spectrography (GC-MS) were used to identify and quantitate the volatile substances in Maotai-flavoured baijiu produced by two different processes. A discriminant model was established based on odor activity value (OAV) by chemometrics and the key differential substances were identified. The results showed that the contents of volatile compounds in baijiu made from ground sorghum were lower than those in baijiu made from whole sorghum, but the proportions of esters, acids and aromatic compounds were higher, indicating that baijiu quality may be related to the proportion of each compound. Baijiu blends at different ratios were prepared to validate the applicability of the proposed model, four-fifths of which were used as training set, and the remaining one-fifth were used as testing set. The overall accuracy rate was 93.33%, indicating that the model could discriminate the two baijiu samples. The distribution of 9 different proportions of mixed samples in the model showed that it could also be used for preliminary identification of mixed samples, which verified the applicability of the model. In addition, 14 potential differential compounds were identified, and their effectiveness in discriminating the two processes was confirmed by the clustering heatmap. Among these compounds, the variable importance in the projection (VIP) value of furfural was the highest, and the OAV of furfural differed greatly between the two baijiu samples, indicating that furfural may be an important substance causing the difference between the baijiu samples.

To evaluate the application potential of Wickerhamomyces anomalus (Wa) K-008 in mixed culture fermentation and its interaction mechanism with Saccharomyces cerevisiae (Sc) ZM-005 in co-fermentation, pure and mixed culture fermentations of the two strains were carried out. The biomass, glucose consumption, ethanol production and fermentation rate were measured during the fermentation process. It was found that after 24 hours of mixed culture fermentation, Wa showed growth arrest and cell death, while the growth of Sc was not significantly affected by the presence of Wa. We preliminarily ruled out that the early death phenomenon was due to Wa autolysis or apoptosis. By analyzing the fermentation supernatant as well as evaluating the ethanol tolerance, we found that the death of Wa at the early stage of fermentation was not due to the lack of nutrients or the toxic effect of Sc. The mixed culture fermentations with high concentrations of viable, broken or dead cells of Sc indicated that cell death in Wa at the early stage was due to the high concentration of live Sc cells in the system but not dead or broken Sc cells. Furthermore, to verify the mechanism of action, the Sc and Wa cells were separated by dialysis to avoid contact between each other. It was found that both Sc and Wa could grow normally in the mixed culture system. In summary, the growth arrest and death of Wa at the early stage of mixed culture fermentation may be caused by the high concentration of live Sc cells through a cell-to-cell contact mechanism.

The microbial community structure and diversity of Jiang-flavor Daqu (TS, WS, WM, MH and DJ) from different areas of Maotai town were analyzed by using the third-generation nanopore sequencing platform, and its physicochemical indexes and characteristic flavor substances were measured. The results showed that there were some similarities and differences between Daqu in different areas of Maotai town. In terms of microbial community structure, Bacillus, Saccharopolyspora, Weissella, Staphylococcus and Streptomyces were the common dominant bacterial genera in the five Daqu samples. Among them, Bacillus was the absolute dominant bacteria in MH and DJ. Aspergillus and Penicillium were the common dominant fungal genera, and the proportions of Lichtheimia and Saccharomycopsis in TS, WM and MH were significantly higher than those in DJ and WS. Compared with TS and WM, network correlation analysis showed that MH, DJ and WS had stronger interactions among dominant bacteria. In addition, redundancy analysis (RDA) showed that Weissella was positively correlated with esterification power, liquefaction power, saccharification power, acetic acid, ethyl acetate, ethyl lactate and n-pentanol. Lichtheimia was positively correlated with liquefaction power, saccharification power, acetic acid, isovaleric acid, 2,3-butanediol, phenylacetaldehyde and dibutyl phthalate. Saccharomycopsis was positively correlated with esterification power and ethyl acetate. Bacillus was positively correlated with 2,3,5,6-tetramethylpyrazine, propionic acid, isovaleric acid, dibutyl phthalate, 2,3-butanediol and phenacetaldehyde.