Effects of <i>Ligustrum robustum</i> (Rxob.) Blume extract on the quality of peanut and palm oils during storage and frying process
Bibliographic record
Abstract
The potential uses of Ligustrum robustum (Rxob.) Blume extract as a natural antioxidant to protect the quality of different oils during storage and frying process were studied. The results showed that L. robustum extract has been shown to retard the decline in the quality of both oils based on the tests of acid value, peroxide value, p-anisidine value, color, volatile flavor, and fatty acid compositions, and the protective effect of L. robustum extract on the quality of peanut oil was better than that of palm oil. By the component analysis, L. robustum extract was found to have a total phenols content of 140.75 ± 1.52 mg/g, and ligurobustoside C was identified as the main phenolic compound. The thermogravimetric and differential scanning calorimetry results showed that L. robustum extract enhanced the oxidative stability of peanut and palm oils. In addition, Fourier transform infrared results indicated that L. robustum extract had protective effects on the C=C bond and ester bond of oil molecule. Moreover, by using electron spin resonance technique, L. robustum extract showed the ability to inhibit and scavenge alkyl-free radicals in both oils. The present results suggested that L. robustum extract may protect the quality of oils during the storage and frying process by inhibiting the oxidation of unsaturated fatty acids and might be a potential natural antioxidant in the food industry. PRACTICAL APPLICATIONS: The excellent antioxidant ability of Ligustrum robustum (Rxob.) Blume extract on the oxidation of different oils and its low price indicated that it could be used as a new low-cost natural antioxidant in oil processing.
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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".