Microbiota stratification and succession of amylase‐producing <i>Bacillus</i> in traditional Chinese Jiuqu (fermentation starters)
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Jiuqu are vital saccharifying and fermenting agents for Chinese fermented foods. Natural ventilation during Jiuqu fermentation causes changes in temperature, oxygen and moisture content, resulting in mass and heat gradients from the outer to inner areas of Jiuqu blocks. In the present study, microbiota stratification in Jiuqu was investigated by single molecule real-time sequencing and culture isolation. The contributors of Bacillus to amylase activity of Jiuqu and the dynamics of their biomass during Jiuqu fermentation were also analyzed. RESULTS: The dominant orders, genera and species between the inner and outer layers of Huangjiu qu (HJQ) were similar, although they displayed greater variance in two layers of Baijiu qu (BJQ). Bacillus possessed the highest diversity (including 27 species) in Jiuqu. Bacillus licheniformis, Bacillus altitudinis, Bacillus subtilis, Bacillus amyloliquefaciens and Bacillus megaterium were most prevalent in HJQ, whereas B. licheniformis, B. amyloliquefaciens and Bacillus cereus were dominant in BJQ. Isolates of B. amyloliquefaciens, B. subtilis and B. cereus exhibited high activities of amylase and glucoamylase. Quantification of Bacillus members possessing genes of α-amylase revealed that B. cereus and B. licheniformis were the most dominant microbes to secret α-amylase in Jiuqu and their biomass were increasing during Jiuqu fermentation. CONCLUSION: The present study demonstrates the microbial distribution in different layers of Jiuqu and clarifies the Bacillus species processing the activity of α-amylase. These results will help industries control the quality of Jiuqu by rationally selecting starters and optimizing their microbiota. © 2020 Society of Chemical Industry.
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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 | 0.000 | 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 it