Use of a plant‐derived enzyme template for the production of the green‐note volatile hexanal
Bibliographic record
Abstract
Hexanal is a key organoleptic element of green-note that is found in both fragrances and flavors. We report a novel process for the production of hexanal using immobilized enzyme templates extracted from different plant sources in combination with hollow-fiber ultrafiltration for in situ separation. Enzyme templates, known to be responsible for the synthesis of hexanal from linoleic acid (18:2), were isolated from naturally enriched tissues including carnation petals, strawberry and tomato leaves. These templates were immobilized in an alginate matrix and used as a biocatalyst in a packed-bed bioreactor. Continuous product recovery was achieved using a hollow-fiber ultrafiltration unit. The effects of pH, reaction temperature, and substrate and enzyme concentrations were studied and their effects on hexanal generation identified and optimized. Utilizing optimized conditions, hexanal production 112-fold higher than endogenous steady-state levels in a corresponding amount of plant tissue could be achieved over a 30-minute period. Based on the reactor studies, product inhibition also appears to be an important factor for bioreactor-based hexanal production.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".