In order to identify the age of Luzhou-flavor base baijiu, headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) was used to create a fingerprint of the volatile composition of Luzhou-flavor base baijiu, and the eXtreme Gradient Boosting (XGBoost) algorithm was used to establish a regression model. Feature selection was conducted via a combination of variable importance evaluation using the extremely randomized trees, and F_regression and mutual_info_regression in the sklearn feature selection module. The coefficient of determination (R²) of the proposed regression model was 0.987, demonstrating good predictive reliability. This study provides a new idea for the identification of baijiu age.

In this study, the effects of different concentrations and types of organic acids in the medium on the fermentation characteristics of three high-performance strains of Lactobacillus isolated from fermented grains for vinegar brewing were investigated, and their fermentation performances in 12 typical fruit and vegetable juices were compared. The results showed that L. rhamnosus LR-S, L. plantarum LP-D and L. plantarum LP-F had good tolerance to malic acid, citric acid and tartaric acid, respectively, and were consequently superior in fermenting fruit and vegetable juices containing each of these organic acids as the major one. Sequential inoculation of two strains was suitable for raw materials with complicated organic acid composition such as mulberry juice. These results prove the necessity of developing targeted stress-resistant strains according to the characteristics of fruits and vegetables, and that sequential inoculation is an effective method to improve the fermentation performance of lactic acid bacteria on fruits and vegetables.

Gas chromatography-mass spectrometry (GC-MS) and electronic tongue were used to quantitatively determine the volatile compounds and taste indices of 21 Jiang-flavor baijiu samples of different grades. These samples were differentiated by chemometrics, and key differential compounds among grades were identified. Finally, a discriminant model was established by machine learning. The results showed that there were differences in the contents of volatile compounds in Jiang-flavor baijiu of three grades, indicating the feasibility of further discriminant analysis. The total content of flavor compounds in second-grade baijiu (4908 mg/L) was significantly lower than that in premium-grade (6583 mg/L) and first-grade baijiu (8254 mg/L), while the proportion of several esters responsible for floral and fruity aromas in total esters showed a decreasing trend as the grade decreased. Partial least squares-discriminant analysis (PLS-DA) identified 16 key differential compounds represented by ethyl palmitate and acetic acid. The results of electronic tongue showed that the taste indexes of premium-grade baijiu were more consistent, with lower bitterness and astringency aftertaste. The taste indexes of second-grade baijiu showed significant intersample differences. Principal component analysis (PCA) showed clear discrimination of Jiang-flavor baijiu of different grades according to their taste indexes. The above results provide a basis for the establishment of Jiang-flavor baijiu quality system. Four discriminant models were established based on 25 differential compounds and taste indexes identified. The accuracy of all models was higher than 90%, and the support vector machine (SVM) model performed best, with an accuracy of 100%.

The organic acids and microbial community structure of fermented grains in the dominant stacking fermentation rounds for sauce-flavor Baijiu production (i.e., the 2nd and 3rd rounds corresponding to the 3rd and 4th rounds of base liquor) were analyzed using high-performance liquid chromatography (HPLC) and high-throughput sequencing, and the interaction between them was investigated. The results revealed that lactic acid, acetic acid, and succinic acid were the primary organic acids present in fermented grains at mean values of 32.70, 4.87 and 1.93 mg/g, respectively. In total, 8 dominant bacterial genera and 7 dominant fungal genera (average relative abundance > 1%) were identified across the two fermentation rounds. The dominant bacterial genera were Virgibacillus, Kroppenstedtia and Bacillus. The dominant fungal genera were Monascus, Thermomyces and Thermoascus. Principal coordinate analysis (PCoA) revealed that there was a significant difference in the structure of bacteria community between the second and third rounds of stacking fermentation, while the difference in the structure of fungal community was not significant. Co-occurrence network analysis showed that the bacterial-fungal (55.60%), bacterial-bacterial (50.57%), and fungal-fungal (91.67%) networks were mainly positively correlated, and there were more unknown interactions between bacterial communities. Mantel test analysis showed a significantly positive correlation between acidity and bacterial community structure (P < 0.01), and succinic acid was highly correlated with both bacterial and fungal community succession (P < 0.01). Spearman’s correlation analysis revealed that the bacterial community had a more significant correlation with organic acids than the fungal community, while the fungal community showed a negative correlation with most organic acids. Nine organic acids citric acid were positively correlated with Oceanobacillus, Bacillus, and Sphingobacterium but negatively correlated with Thermoactinomyces. The results of this study can provide a theoretical basis for the production of high-quality sauce-flavor Baijiu.