Effects of <i>Daqu</i> properties on the microbial community and their metabolites in fermented grains in Baijiu fermentation system
Bibliographic record
Abstract
Daqu is the natural starter for Nong-flavor Baijiu brewing. The effects of Daqu properties on the microbial community succession and their metabolites in fermented grains (FG) during Baijiu brewing were determined. These results showed that the effect of Daqu on the bacterial communities was stronger than that of the fungal communities. Compared with the conventional Daqu (DZ), Taikong (TK), and Qianghua (QH), Daqu significantly enhanced the content of volatile metabolites (especially esters) and ethanol when they were used, respectively, for FG fermentation. In the second round of fermentation, the relative abundance of Lactobacillus decreased, the content of lactic acid decreased, and that of caproic acid increased. In particular, the abundance of Lactobacillus was also reduced by 20% in FGs of the second round when TK Daqu was used than that in the respective first round. Partial least squares structural equation model analysis also showed that physicochemical parameters and Daqu properties significantly affected FG community structure and metabolism. This study provides a theoretical basis for further study on the effect of high-quality Daqu on the quality of fresh Baijiu and lays an important theoretical foundation for the stabilization of the Baijiu fermentation system based on Daqu.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".