Jiawen Duan

Empty cup aroma is a distinctive quality attribute of soy sauce aroma type baijiu (SSB), but the compounds responsible for its long persistence and their changes over time are still not well understood. Previous studies have mainly focused on key empty cup odourants at single time points. In this study, a typical commercial SSB was selected and monitored for 30 days using aroma extract dilution analysis (AEDA), time-resolved odour monitoring, residue peak area analysis and correlation with boiling point. AEDA revealed 65 aroma-active regions, including 63 in SSB, 36 in the empty cup and 34 shared by both. After emptying, the flavour dilution profile changed markedly: fruity esters and volatile aldehydes became less prominent, whereas sotolon showed the highest FD factor in the empty cup (FD 2048), and several acids and pyrazines also became prominent. The number of detectable regions increased from 43 at 0 h to 49 at 6 h, and then gradually decreased to 14 at day 30. Persistence was strongly correlated with boiling point (Spearman’s ρ = 0.7465, p < 0.0001, n = 32). Peak area profiles also showed two general patterns. Low-boiling esters, aldehydes and dimethyl trisulfide decreased rapidly, whereas organic acids, pyrazines, phenylethyl alcohol, γ-nonanolactone and ethyl hexadecanoate showed delayed maxima or non-monotonic changes. These results suggest that persistent empty cup aroma is not simply a residual form of the original baijiu aroma but develops through selective retention and temporal shifts in the contribution of different odourants.

Daqu is not only a crucial starter in the production of baijiu, but it is also an important source of flavoring substances, so maintaining a stable quality is an important part of improving the quality of baijiu. Nonetheless, since the production of daqu is still a natural fermentation process, which is influenced by seasonal factors, the rapid testing of daqu quality is a problem that must be solved. In this study, headspace solid-phase microextraction technology (HS-SPME) was used to explore the volatile components in daqu, and a total of 115 volatile components were extracted. By constructing an untargeted statistical model, the variation in volatile compounds in dissimilar production processes of daqu was studied, and the differences between different maturation stages and the correlations between volatile compounds were analyzed. Subsequently, six compounds, including ethyl acetate, ethanol, phenylethanol, (R,R)-2,3-butanediol, ethyl caproate, and 2,3-butanediol, were further screened out by partial least squares discrimination analysis (PLS-DA), and the symbolic combination of daqu’s maturity was speedily judged in accordance with the changes in marker compound concentrations to lay the foundation for the mechanization of baijiu production.