Enzymatic hydrolysis of corn crop residues with high solid loadings: New insights into the impact of bioextrusion on biomass deconstruction using carbohydrate-binding modules
Bibliographic record
Abstract
Lignocellulosic biomass is a sustainable source of renewable substrate to produce low carbon footprint energy and materials. Biomass conversion is usually performed in two steps: a biomass pretreatment for improving cellulose accessibility followed by enzymatic hydrolysis of cellulose. In this study we investigated the efficiency of a bioextrusion pretreatment (extrusion in the presence of cellulase enzyme) for production of reducing sugars from corn crop agricultural residues. Our results demonstrate that bioextrusion increased the reducing sugar conversion yield by at least 94% at high solid/liquid ratio (14%-40%). Monitoring biomass surface with carbohydrate-binding modules (FTCM-depletion assay) revealed that well known negative impact of high solid/liquid ratio on conversion yield is not due to the lack of exposed cellulose which was abundant under such conditions. Bioextrusion was found to be less efficient on alkaline pretreated biomass but being a mild and solvent limiting pretreatment, it might help to minimize the waste stream.
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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".