Study on the structure, stability characterization, and oxidative stability of a conjugated stabilized walnut oil emulsion using walnut protein isolate and gum Arabic
Bibliographic record
Abstract
Walnut oil (WO), often referred to as “Oriental olive oil," is renowned for its numerous biological benefits, including memory enhancement and the prevention of cardiovascular and cerebrovascular diseases. However, WO is prone to oxidation during processing, which leads to a decline in oil quality. Due to the weak functional properties of walnut protein isolate (WP), a WP-gum acacia (GA) conjugate (WP-GA) was prepared by modifying the WP surface to stabilize walnut oil emulsion. Results showed that WP-GA, at a concentration of 2 g/100 g protein, could form a stable and fully emulsified emulsion. Compared to the walnut protein-stabilized emulsion (WP-WO), the WP-GA conjugate-stabilized WO emulsion (WP-GA-WO) exhibited larger particle size, a higher absolute zeta potential, reduced turbidity, and a higher percentage of adsorbed protein. Rheological analysis revealed that WP-GA-WO had a higher energy storage modulus compared to WP-WO, indicating improved elasticity and viscosity due to glycosylation of the emulsion. Additionally, the WP-GA-WO emulsion demonstrated enhanced thermal, pH, ionic strength, salt stress, and storage stability, as evidenced by delayed oxidation of α-linolenic acid and linoleic acid. In vitro digestion assays showed that the WP-GA conjugate emulsion had better stability in gastric juices. These findings suggest potential applications for WP and GA in food-related fields. • WP and gum arabic (GA) can be conjugated to prepare high internal phase emulsions. • GA was selected for the first time for glycosylation of walnut protein (WP). • The emulsion of conjugate stabilization improves the stability of walnut oil. • After glycosylation of GA and WP, the function of WP was improved.
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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 | 0.001 | 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".