Pretreatment of Lodgepole Pine Killed by Mountain Pine Beetle Using the Ethanol Organosolv Process: Fractionation and Process Optimization
Bibliographic record
Abstract
Lodgepole pine ( Pinus contorta ) killed by mountain pine beetle ( Dendroctonus ponderosae ) (MPB-LPP) was evaluated for bioconversion to ethanol using the ethanol organosolv process. The pretreatment was optimized using an experimental matrix designed with response surface methodology. It was found that MPB-LPP was easy to pretreat and delignify, but gave low yields of substrate and carbohydrate as a result of excessive hydrolysis and subsequent decomposition of cellulose and hemicellulose during the pretreatment. The center-point conditions (170 °C, 60 min, 1.1% H 2 SO 4 and 65% ethanol) were close to the optimum for the recovery of glucose and ethanol organosolv lignin. At the center-point conditions, ∼75% of the cellulose present in the untreated wood was recovered in the substrate fraction, and approximately 79% of the lignin in the wood was recovered as ethanol organosolv lignin (EOL). The combined recovery of carbohydrate in the substrate and water-soluble fractions was ∼83% glucose, ∼46% mannose, ∼53% xylose, ∼78% galactose, and ∼55% arabinose. The lost carbohydrate was decomposed to furfural, hydroxymethylfurfural, and levulinic and formic acids. The substrate generated at center-point conditions from MPB-LPP was readily digestible. Cellulose-to-glucose conversion yields of ∼93% and ∼97% were achieved within 24 and 48 h, respectively, with 20 FPU of cellulase/g of cellulose.
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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".