Aroma Release from Solid Droplet Emulsions: Effect of Lipid Type
Bibliographic record
Abstract
Abstract Aroma compounds partition between the different phases of a food emulsion and the headspace but only those in the headspace are perceived. Phase transitions in the lipid droplets profoundly affect the position of the partitioning equilibria and hence headspace aroma concentration. The release of four volatile aroma compounds (ethyl butanoate, pentanoate, heptanoate and octanoate) from eicosane, hydrogenated palm fat or Salatrim ® emulsions stabilized with sodium caseinate were investigated as a function of fat crystallization, particle size and droplet concentration. For all compounds, the headspace aroma concentration in equilibrium with solid droplet emulsions was significantly higher than that in equilibrium with liquid droplet emulsions. The partitioning of volatile aroma compounds from emulsion does not depend on the type of liquid lipid, however, the interactions between solid lipid droplets and aroma compounds are significantly influenced by the nature of the crystalline fat. Notably, partitioning into the headspace was much lower for solid triglyceride droplet emulsions than for solid alkane emulsions. It was proposed that both residual liquid lipid in solid triglycerides and aroma co‐crystallization with solid lipid could be responsible for higher aroma absorption by solid triglycerides.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".