Pretreatment of lignocellulosic material with fungi capable of higher lignin degradation and lower carbohydrate degradation improves substrate acid hydrolysis and the eventual conversion to ethanol
Bibliographic record
Abstract
Phanerochaete chrysosporium, Pycnoporus cinnabarinus,and fungal isolates RCK-1 and RCK-3 were tested for their lignin degradation abilities when grown on wheat straw (WS) and Prosopis juliflora (PJ) under solid-state cultivation conditions. Fungal isolate RCK-1 degraded more lignin in WS (12.26% and 22.64%) and PJ (19.30% and 21.97%) and less holocellulose in WS (6.27% and 9.39%) and PJ (3.01% and 4.58%) after 10 and 20 days, respectively, than other fungi tested. Phanerochaete chrysosporium caused higher substrate mass loss and degraded more of holocellulosic content (WS: 55.67%; PJ: 48.89%) than lignin (WS: 18.89%; PJ: 20.20%) after 20 days. The fungal pretreatment of WS and PJ with a high-lignin-degrading and low-holocellulose-degrading fungus (fungal isolate RCK-1) for 10 days resulted in (i) reduction in acid load for hydrolysis of structural polysaccharides (from 3.5% to 2.5% in WS and from 4.5% to 2.5% in PJ), (ii) an increase in the release of fermentable sugars (from 30.27 to 40.82 g L(-1) in WS and from 18.18 to 26.00 g L(-1) in PJ), and (iii) a reduction in fermentation inhibitors (total phenolics) in acid hydrolysate of WS (from 1.31 to 0.63 g L(-1)) and PJ (from 2.05 to 0.80 g L(-1)). Ethanol yield and volumetric productivity from RCK-1-treated WS (0.48 g g(-1) and 0.54 g L(-1) h(-1), respectively) and PJ (0.46 g g(-1) and 0.33 g L(-1) h(-1), respectively) were higher than untreated WS (0.36 g g(-1) and 0.30 g L(-1) h(-1), respectively) and untreated PJ (0.42 g g(-1) and 0.21 g L(-1) h(-1), respectively).
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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) | 0.001 | 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".