Screening of ligninolytic fungi for biological pretreatment of lignocellulosic biomass
Bibliographic record
Abstract
To identify white rot fungi with high potential in biological pretreatment of lignocellulosic biomass, preliminary screening was carried out on plates by testing different strains for their ability to oxidize guaiacol and decolorize the dyes azure B and Poly R-478. Of the 86 strains screened, 16 were selected for secondary screening for their ligninolytic ability; however, low manganese peroxidase activity and no lignin peroxidase activity were detected. Strain BBEL0970 proved to be the most efficient in laccase production and was subsequently identified as Trametes versicolor by analysis of the ribosomal DNA internal transcribed spacer gene sequence. In combining laccase production with biological pretreatment, the replacement of glucose with barley straw significantly improved the laccase activity by up to 10.3 U/mL, which provided evidence toward potential utilization of barley straw in laccase production by BBEL0970. Simultaneously, comparison by thermogravimetric analysis of the untreated and pretreated barley straw in liquid fermentation of laccase also demonstrated the high potential of BBEL0970 in biological pretreatment of lignocellulosic biomass. This work sheds light on further exploration on the integrated process of low-cost laccase production and efficient biological pretreatment of barley straw by T. versicolor BBEL0970.
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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".