Optimization of Liquid Fermentation Process for Improved Exo-Polysaccharides Production by Kombucha ZJU1
Bibliographic record
Abstract
In order to improve exo-polysaccharides production by Kombucha ZJU1, the optimization of liquid fermentation process for cell growth and Exo-Polysaccharide (EPS) production by Kombucha ZJU1 was conducted with Response Surface Methodology (RSM). A Fractional Factorial Design (FFD) and Central Composite Design (CCD) were applied to optimize the main factors that affect EPS production during fermentation. Both the concentration of brown sugar and inoculation level significantly affected EPS production by Kombucha ZJU1 through FFD experiment. The optimized fermentation process was derived from the predicted model using central composite design as follows: 280 g/L brown sugar, 4 g/L Pu-erh tea, 1 g/L KH2PO4 and 1 g/L (NH<sub>4</sub>)<sub>2</sub> SO<sub>4</sub>, initial pH unadjusted, the culture medium was inoculated with 1.95% (v/v) Kombucha ZJU1, the cell age was 5 days, then incubated at a temperature of 30±1°C for 6 days on the rotary shaker. The predicted maximal EPS concentration was 2.66 g/L using this optimized fermentation process, which was of value to further work.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".