Tea-flavored liquor can often represent one of the most favorite alcoholic beverages in recent years. A combination of tea and liquor flavors can be produced after raw material preparation, tea maceration, sugar supplementation, alcoholic fermentation, distillation, aging, and blending. However, its aroma profile is characterized by pronounced complexity and variability. Substantial challenges also remained to accurately assess and then predict the aroma quality. In this study, an explainable machine learning (ML) framework was developed to predict the sensory quality grades of the tea-flavored liquor. The key volatile compounds were identified under quality differentiation. A total of 110 tea-flavored liquor samples were taken after identification. A tasting panel was selected for the standardized protocols of the sensory assessment. Each sample was assigned to one of three predefined quality grades (Grade A, high quality; Grade B, medium quality; Grade C, low quality) after evaluation. The aroma compound profiles of the tea-flavored liquor were then determined using headspace solid phase micro-extraction-gas chromatography-mass spectrometry (HS–SPME–GC–MS). Furthermore, the 13 ML models were benchmarked. The performance of the model was assessed using accuracy, precision, recall, F1-score, and the area under the receiver operating characteristic curve (AUC). Shapley Additive exPlanations (SHAP) were employed to quantify the contribution rates of the aroma compounds to the predictions, in order to enhance the model interpretability. According to the sensory evaluation, 28 samples were classified as Grade A, 42 as Grade B, and 40 as Grade C. Among the 32 volatile aroma compounds, 24 exhibited significant differences (P < 0.05) over the three quality grades, including 10 terpenes, 10 esters, and 4 higher alcohols. The samples of the RANK A and RANK B grades also displayed broadly similar aroma profiles, whereas most compounds in the RANK C were presented at significantly lower concentrations. Among the 13 ML models, the Radial Support Vector Machine (Radial SVM) achieved the best performance in the prediction, with an AUC of 0.92 and all accuracy, precision, recall, and F1-score values exceeding 0.8. The SHAP analysis further revealed that the terpenes constituted the largest subgroup among the top 20 most influential compounds, followed by 7 esters and 3 higher alcohols. Key aroma compounds contributed to the prediction, including linalool (floral), anethole (spicy), methyl salicylate (mint-like), nerol (floral), ethyl undecanoate (fruity), and isoamyl alcohol (alcoholic). Linalool, anethole, methyl salicylate, and ethyl undecanoate greatly contributed to the sensory quality of the tea-flavored liquor. While the nerol similarly shared a positive correlation, where its contribution rate followed a complex, nonlinear trend: Its positive influence first increased, then diminished as the concentrations rose. There was a synergistic interaction between esters and other terpene compounds at the lower concentrations. Collectively, the sensory perception of nerol was amplified after interaction. By contrast, the isoamyl alcohol was accumulated to diminish the overall aroma quality of the tea-flavored liquor. In conclusion, an accurate and interpretable ML model can be expected to identify the volatile compounds most critical to quality differentiation, particularly for the sensory quality grading of tea-flavored liquor. These findings can provide a scientific basis for the targeted optimization of the production, quality control, and flavor enhancement in the tea-flavored liquor. Future work can be expected to focus on the interactions among key aroma compounds, in order to enrich the theoretical foundation of the flavor chemistry in alcoholic beverages.

In order to find out the differences in the microbial community structure in Qula at different altitudes of Tibet, a total of 40 yak Qula samples were collected from three groups at low, middle and high altitude for high-throughput sequencing. The results showed that there were differences in microbial community diversity among the different groups of samples. With the increase in altitude, the diversity and richness of bacterial flora in Qula samples showed a downward trend, and so did the abundance of fungal flora, while the diversity of fungal flora did not change significantly. The samples from the low, middle and high altitude groups contained 2411, 1391 and 1197 bacterial operational taxonomic units (OTUs), respectively, and 715 bacterial OTUs were common to the three groups; the dominant bacterial genera identified were Lactococcus and Lactobacillus, with an average relative abundance of 34.0% and 18.4%, respectively. The samples from the low, middle and high altitude groups contained 801, 343 and 399 fungal OTUs, and 173 fungal OTUs were common to the three groups; the dominant fungal genus identified was Geotrichum, with an average relative abundance of 33.8%. The results of this study can provide a theoretical basis for the selection and utilization of characteristic microbial resources in Qula.

In order to improve the ability to produce ethyl acetate, Nakazawaea ishiwadae GDMCC 60786 was mutagenized by atmospheric and room-temperature plasma (ARTP), ethyl methanesulfonate (EMS) and nitrosoguanidine (NTG). The mutants were sequentially screened by using a plate medium containing tributyrin, shake flask fermentation and addition of substrate. The genetic stability, hemolytic activity and in vitro drug resistance of the selected mutant were evaluated. Mutant N5, which was found to be able to produce a high yield of ethyl acetate, had good genetic stability and in vitro safety. After five successive passages, the average production of ethyl acetate was 764.54 mg/L, and the glucose conversion rate was 38.22%, which were 2.90 times and 25.03% higher than those observed with the original strain, respectively. When ethanol was used as a supplementary carbon source, the yield of ethyl acetate was 1426.81 mg/L; however, upon the addition of acetic acid, N5 did not grow and lost the ability to produce esters, indicating that the strain was more tolerant to ethanol than acetic acid. Meanwhile, the activities of esterase, acetyl-CoA and alcohol acyltransferase in N5 cells were measured to reach a maximum value after 24 h. In summary, this study successfully constructed a set of suitable mutagenesis system for this strain.