Investigation of tension wood formation and 2,6-dichlorbenzonitrile application in short rotation coppice willow composition and enzymatic saccharification
Bibliographic record
Abstract
BACKGROUND: Short rotation coppice willow is a potential lignocellulosic feedstock in the United Kingdom and elsewhere; however, research on optimising willow specifically for bioethanol production has started developing only recently. We have used the feedstock Salix viminalis × Salix schwerinii cultivar 'Olof' in a three-month pot experiment with the aim of modifying cell wall composition and structure within the stem to the benefit of bioethanol production. Trees were treated for 26 or 43 days with tension wood induction and/or with an application of the cellulose synthesis inhibitor 2,6-dichlorobenzonitrile that is specific to secondary cell walls. Reaction wood (tension and opposite wood) was isolated from material that had received the 43-day tension wood induction treatment. RESULTS: Glucan content, lignin content and enzymatically released glucose were assayed. All measured parameters were altered without loss of total stem biomass yield, indicating that enzymatic saccharification yield can be enhanced by both alterations to cell wall structure and alterations to absolute contents of either glucan or lignin. CONCLUSIONS: Final glucose yields can be improved by the induction of tension wood without a detrimental impact on biomass yield. The increase in glucan accessibility to cell wall degrading enzymes could help contribute to reducing the energy and environmental impacts of the lignocellulosic bioethanol production process.
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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) | 0.000 | 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) | 0.001 | 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".