Protein–Protein Multilayer Oil-in-Water Emulsions for the Microencapsulation of Flaxseed Oil: Effect of Whey and Fish Gelatin Concentration
Bibliographic record
Abstract
The impact of whey protein isolate (WPI) and fish gelatin (FG) deposited sequentially at concentrations of 0.1, 0.5, and 0.75% on the surface of primary oil-in-water emulsions containing 5% flaxseed oil stabilized with either 0.5% fish gelatin or whey protein, respectively, was investigated. The results revealed that the adsorption of WPI/FG or FG/WPI complexes to the emulsion interface led to the formation of oil-in-water (o/w) emulsions with different stabilities and different protection degrees of the flaxseed oil. Deposition of FG on the WPI primary emulsion increased the particle size (from 0.53 to 1.58 μm) and viscosity and decreased electronegativity (from -23.91 to -11.15 mV) of the complexes. Different trends were noted with the deposition of WPI on the FG primary emulsion, resulting in decreasing particle size and increasing electronegativity and viscosity to a lower extent. Due to the superior tension-active property of WPI, the amount of protein load in the WPI primary emulsion as well as in WPI/FG complex was significantly higher than the FG counterparts. A multilayer emulsion made with 0.5% WPI/0.75% FG exhibited the lowest oxidation among all of the multilayered emulsions tested (0.32 ppm of hexanal) after 21 days, likely due to the charge effect of FG that may prevent pro-oxidant metals to interact with the flaxseed oil.
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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 | 0.000 |
| 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 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".