Bioaugmented Hydrogen Production from Lignocellulosic Substrates Using Co-Cultures of Shigella flexneri str. G3 and Clostridium acetobutylicum X9
Bibliographic record
Abstract
Bioaugmented fermentation of cellulosic substrates to produce biohydrogen via co-culture of isolated strains was investigated. Two mesophilic anaerobic bacterial strains, known for their ability to hydrolyze cellulosic substrates, were taken in consideration: Shigella flexneri str. G3, which shows high cellulolytic activity but cannot ferment oligosaccharides to bioenergy, and Clostridium acetobutylicum X9, able to convert microcrystalline cellulose into hydrogen. The ability of the selected strains to effectively convert different cellulosic substrates to hydrogen was tested on carboxymethyl cellulose (AVICEL), as well as pretreated lignocellulosic material such as Bermuda grass, corn stover, rice straw, and corn cob. Results showed that co-culture of Shigella flexneri str G3 and Clostridium acetobutylicum X9 efficiently improved cellulose hydrolysis and subsequent hydrogen production from carboxymethyl cellulose. Hydrogen production yield was enhanced from 0.65 mol H2 (mol glucose)−1 of the X9 single culture to approximately 1.5 mol H2 (mol glucose)−1 of the co-culture, while the cellulose degradation efficiency increased from 50% to 95%. Co-culture also efficiently improved hydrogen production from natural lignocellulosic materials (which was up to 4-5 times higher than mono-culture with X9), with the highest performance of 24.8 mmol L-1 obtained on Bermuda grass. The results demonstrate that co-culture of S. flexneri G3 and C. acetobutylicum X9 was capable of efficiently enhance cellulose conversion to hydrogen, thus fostering potential biofuel applications under mesophilic conditions.
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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 | 0.001 | 0.001 |
| 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".