Potential of thin stillage as a low-cost nutrient source for direct cellulose fermentation by <i>Clostridium thermocellum</i>
Bibliographic record
Abstract
Utilization of thin stillage (TS), derived from grain-based ethanol production, was investigated as an alternative source for microbial growth nutrients during direct conversion of cellulose by <i>Clostridium thermocellum</i> DSM 1237. Fermentation end-products synthesized by <i>C. thermocellum</i> grown on media prepared with various concentrations (50-400 g/L) of TS were compared to those synthesized by <i>C. thermocellum</i> grown on reagent grade chemical (reference) medium. Cell-growth in TS media, monitored with the aid of quantitative polymerase chain reactions (qPCR) technique, showed prolonged growth with increasing TS concentration. Final fermentation end-product concentrations from TS media were comparable with those from the reference medium despite lower growth-rates. The volumetric H<sub>2</sub> production generated by <i>C. thermocellum</i> grown with medium containing a low concentration (50 g/L) of TS matched the volumetric H<sub>2</sub> production by <i>C. thermocellum</i> grown in the reference medium, while higher concentrations (200 g/L) of TS resulted in greater synthesis of ethanol. Supplementation of TS-media with Mg<sup>++</sup> enhanced ethanol production, while hydrogen production remained unchanged. These results suggest that TS, an attractive source of low-cost nutrients, is capable of supporting the growth of <i>C. thermocellum</i> and that high concentrations of TS favor synthesis of ethanol over hydrogen from cellulose.
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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 | 0.000 |
| 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".