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Record W2143290245 · doi:10.1139/w08-003

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

2008· article· en· W2143290245 on OpenAlexvenueno aff
Sarika Kuhar, Lavanya M. Nair, Ramesh Chander Kuhad

Bibliographic record

VenueCanadian Journal of Microbiology · 2008
Typearticle
Languageen
FieldEngineering
TopicBiofuel production and bioconversion
Canadian institutionsnot available
Fundersnot available
KeywordsPhanerochaeteLigninChemistryHydrolysisFood scienceChrysosporiumFermentationHydrolysateEthanol fuelNuclear chemistryBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

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).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.285

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.006
GPT teacher head0.163
Teacher spread0.156 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations123
Published2008
Admission routes1
Has abstractyes

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