Effect of tocopherols on the frying stability of regular and modified canola oils
Bibliographic record
Abstract
Abstract A study was conducted to compare the relationship between frying stability and levels and degradation rates of tocopherols in regular and three modified canola oils. Oils were heated at 175 ± 2°C for a total of 72 h, with french fries fried intermittently. Frying stability was compared based on the rates of formation of free fatty acids (FFA) and total polar compounds (TPC). Significant differences (P<0.05) were identified between oils using analysis of covariance and t‐tests for multiple comparisons. No significant differences were observed in the rates of FFA formation among the canola oils during frying. Nevertheless, regular canola (RCO) and high‐oleic, low‐linolenic acid canola (HOLLCO) oils produced less FFA compared to higholeic LLCO and HOCO both had significantly (P<0.05) faster rates of TPC formation compared to HOLLCO or RCO. HOLLCO with the highest level of tocopherols (893 mg/kg) exhibited a slow rate of degradation which accounted for a halflife of 48–60 h of frying. RCO, with a lower level of tocopherols (565 mg/kg), however, had the slowest degradation rate with a half‐liofe of >72 h. In contrast, HOCO and LLCO with 601 and 468 mg/kg tocopherols, respectively, both exhibited a half‐life for tocopherols of 3–6 h of frying. An inverse relatioship was observed between TPC formation and the reduction of tocopherol. Thus, the greater frying stability of RCO and HOLLCO appears to be affected far more by the rate of tocopherol degradation than by any changes in fatty acid composition.
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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 | 0.001 |
| 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".