Enhancement of saccharification of corn stover by cellulolytic enzyme produced from biomass-degrading bacteria
Bibliographic record
Abstract
Enzymatic saccharification of corn stover can be enhanced by partially replacing commercial enzymes with bacterial crude enzyme extracts. Thus, in this study, three bacteria (Bacillus sp. A0, Bacillus sp. CH20S1, and Exiguobacterium sp. AS2B) were cultured in a media with corn stover as the substrate to produce crude enzyme extract and saccharify corn stover. The cultural conditions were monitored and optimized to maximize CMCase and xylanase activity in the crude enzyme extracts. After 72 h of hydrolysis of corn stover with diluted crude enzymes (DCE) from the three strains, reducing sugars ranging from 48.2 to 71.7 mg g-1 were released from non-pretreated and pretreated corn stover. Furthermore, the maximum reducing sugars of 316 and 321 mg g-1 were observed when 12 and 4 FPU g-1 of commercial cellulase were added to the DCE of the CH20S1 strain, respectively. It was shown that an effective combination of bacterial DCE with commercial enzymes could achieve higher saccharification of lignocellulosic biomass, which might be cost-efficient compared to their single-use. Overall, this study aims to show the enhanced enzymatic saccharification of corn stover.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".