Carboxylic acid ester hydrolysis rate constants for food and beverage aroma compounds
Bibliographic record
Abstract
Abstract Aroma compounds in the Flavornet database were screened for potentially hydrolysable carboxylic acid ester functionalities. Of 738 aroma compounds listed in this database, 140 molecules contain carboxylic acid ester groups that may be amenable to hydrolysis in various food and beverage products. Acid‐ (kA) and base‐ (kB) catalysed and neutral (kN) hydrolysis rate constants in pure water at 25°C were calculated for these aroma compounds. Where available, good agreement between theoretical and experimental hydrolytic half‐lives was obtained at various pH values. Wide ranges and broad frequency distributions for kA, kB, and kN are expected among the various hydrolyzable aroma compounds, with calculated kA ranging from 3.7 × 10‐8 to 4.7 × 10‐4 M‐1 s‐1, calculated kB ranging from 4.3 × 10‐4 to 43 M‐1 s‐1, and calculated kN ranging from 4.2 × 10‐17 to 7.6 × 10‐9 M‐1 s‐1. The resulting hydrolytic half‐lives also range widely, from 10 days to 370 years at pH 2.8, 18 days to 4,900 years at pH 4.0, 1.8 days to 470 years at pH 7.0, and 26 minutes to 5.1 years at pH 9.0. The findings illustrate the importance of considering abiotic hydrolysis and matrix pH when modelling the evolution of sensory characteristics for foods and beverages with carboxylic acid ester based aroma compounds. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".