Enzymatic Saccharification of Canola Straw and Oat Hull Subjected to Microwave-Assisted Alkali Pretreatment
Bibliographic record
Abstract
Pretreatment of lignocellulosic biomass is a critical step in removing substrate-specific barriers to the cellulolytic enzyme attack. The study compared the effectiveness of microwave-assisted alkali pretreatment and alkali treatment in the enzymatic saccharification of canola straw and oat hull. Microwave pretreatments were employed by immersing the biomass in dilute alkali solutions (NaOH and KOH) at concentrations of 0, 0.75, and 1.5% (w/v) for microwave-assisted heating times of 6, 12, and 18 min. Alkali treatments were carried out using the same procedure but by soaking and without microwave heating. The highest glucose yields after enzymatic saccharification of both canola straw and oat hull were obtained when these feedstocks were ground using 1.6 mm hammer mill screen size and subjected to microwave-assisted alkali pretreatment using 1.5% and 0.75% NaOH for 18 min, respectively. SEM analysis indicated a more significant modification in the structure of biomass samples subjected to microwave-assisted alkali pretreatment compared to untreated and alkali-treated biomass samples. Results indicated that microwave-assisted alkali pretreatment with short residence time is effective in improving the glucose yield of canola straw and oat hull during enzymatic saccharification.
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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 | 0.001 |
| 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 | 0.001 |
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".