The effect of minor components on canola oil oxidation: Oxidation kinetics explained by molecular interactions
Bibliographic record
Abstract
This study investigates the effect of various minor components (MCs) on the oxidation kinetics and molecular self-assembly in stripped canola oil during thermal and photo oxidation processes using experimental and simulation tools. The peroxide value (PV) and fatty acid content were measured to evaluate the formation of oxidation products and the consumption rate of unsaturated fatty acids. In the thermal oxidation experiment, adding MCs slightly increased the oxidation rate, while in the photo oxidation experiment, stearic acid (SA) and glycerol monostearate (GMS) significantly decreased it. GMS demonstrated a pronounced ability to self-assemble and form molecular organizations during photo oxidation, resulting in lower critical micelle concentration (CMC) values of lipid hydroperoxides (LOOHs) and reduced oxidation rates. These GMS self-assemblies seem to scatter light, thus decreasing absorbed energy during photo oxidation, leading to lower oxidation rates. SA exhibited the highest surface activity, effectively lowering the LOOH CMC and facilitating the formation of stable reverse micelles at lower concentrations. Interestingly, the addition of MCs did not influence the tendency of LOOHs to form hydrogen bonds with water, suggesting that the lower CMC resulted from the formation of mutual reverse micelles of MCs and LOOHs. Meso-phase formation was observed at very high PVs, indicating a high concentration of secondary oxidation products, which also possess surface activity. These findings underscore the importance of molecular interactions in oxidation stability, providing insights for improving edible oil preservation.
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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) | 0.001 | 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".