Characterization, fermentation, and volatile profile of distilled beverages produced from defective maple syrup
Bibliographic record
Abstract
In this work, maple syrups with various flavor defects were physically and chemically characterized and assessed for their fermentative potential in alcoholic beverage production. The flavor defective maple syrups, as well as a control sample, were analyzed for soluble solids, pH, density, viscosity, transmittance, color (L, a*, b*), moisture, ash content, sugar profile, organic acids, and ethanol concentration. The defective maple syrups were fermented using Saccharomyces cerevisiae at 30°C for 204 hours. Maple syrups known for having flavor defects also have several differences in composition when compared to the regular commercial one (including but not limited to pH, viscosity, and color). In addition, the content of glucose, fructose, and sucrose occurred in different proportions, which is related to the types of defects. Overall, the amount of ethanol produced by VR1, VR11, VR4 Acid , VR5, and VR6 2 was statistically equal to that of the control (normal commercial maple syrup) with a fermentation efficiency of 95.15%. The faster fermentation kinetics for the VR1 and VR4 Acid shows the potential of these VRs for industrial processes. After distillation, the volatile profile of the defective maple syrups – VR1, VR11, VR4 Old, VR5, VR6 1 , and VR6 2 – were similar to the regular ones suggesting that defective maple syrups are suitable for producing distilled beverages with a desirable volatile composition.
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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".