Synergistic effects of rosemary, sage, and citric acid on fatty acid retention of palm olein during deep‐fat frying
Bibliographic record
Abstract
Abstract A study to optimize the use of oleoresin rosemary extract, sage extract, and citric acid in refined, bleached, and deodorized (RBD) palm olein during deep‐fat frying of potato chips was performed using response surface methodology. Results showed that the natural antioxidants used in this study retarded oil deterioration, as evidenced by retention of fatty acid profiles. The linoleic to palmitic (C18∶2/C16∶0) ratio was chosen as the parameter for optimizing the use of natural antioxidants in RBD palm olein during deep‐fat frying. Linoleic (R2=0.946) and palmitic (R2=0.825) acids were found to be the most important dependent variables, giving highest R2 values to various antioxidant treatments after 25 h of frying. All three antioxidants had independent significant (P<0.05) effects on the C18∶2/C16∶0 ratio. In fact, significant effects on the C18∶2/C16∶0 ratio of RBD palm olein were also given by a second‐order form. A combination of 0.076% oleoresin rosemary extract, 0.066% sage extract, and 0.037% citric acid produced the optimal retention of the essential fatty acid C18∶2. In addition, a synergistic effect among these antioxidants on the fatty acid ratio of RBD palm olein was found.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 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".