Bioethanol Production as an Alternative End for Maple Syrups with Flavor Defects
Bibliographic record
Abstract
The purpose of this paper is to demonstrate the validity of an alternative route to valorize declassified maple syrups affected by flavor defects such as ropy maple syrup (RMS) and buddy maple syrup (BMS) as feedstocks for ethanol production. An acid hydrolysis treatment (0.1 M, 0.5 M, 5 M, and 10 M) was performed on the RMS to break the polysaccharide chains which are responsible for the flavor defect. The sugars and inhibitors composition of these hydrolysates were analyzed by ion chromatography and ion exclusion chromatography, respectively. Maple syrup samples were fermented by Saccharomyces cerevisiae for 96 h at 30 °C, and ethanol content was measured to determine the kinetic parameters of the process. RMS and BMS demonstrated a good potential to be used as feedstocks to produce ethanol achieving high efficiencies (RMS: 90.08%; BMS: 93.34%). The acid hydrolysis (25 min, 50 °C, with the addition of 5 M sulfuric acid solution) was effective to maximize ethanol production when using RMS as feedstock. To the best of our knowledge, it is the first time that such an approach is used to valorize declassified maple syrups.
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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".