Encapsulation of hydrophobic aroma in whey protein nanoparticles
Bibliographic record
Abstract
Aroma-loaded nanoparticles (d < 300 nm) were prepared by cross-linking denatured whey protein through pH-cycling. The effect of nanoparticulation conditions and aroma concentration on the physicochemical characteristics of nanoparticles and aroma release profile was studied. Better retention of aroma was observed when ethyl hexanoate was added before nanoparticle formation. The highest aroma retention was obtained for nanoparticles produced at pH 5.0 and 5.5 without calcium addition. These nanoparticles are characterized by a less compact and more porous internal structure allowing a higher loading of aroma. Increasing aroma concentration increased the diameter and the voluminosity of the aroma-loaded nanoparticles. The percentage of aroma retention showed an increase from 7% to 24% over the tested concentration range while the value averaged 2% for native or denatured whey protein. Encapsulation of ethyl hexanoate in whey protein nanoparticles reduced the mass transfer of aroma at the surface of the matrix and improved its retention.
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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) | 0.000 | 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".