Antioxidant Activity of a Oryzanols Concentrate by Differential Scanning Calorimetry
Bibliographic record
Abstract
Oryzanols are natural antioxidants that are found in appreciable amounts in rice bran oil. However, by chemically refining the crude rice bran oil they are lost during the chemical neutralization step leaving the oil refined with very little oryzanols. The chemical neutralization leaves a residue called "soapstocks" where most of these antioxidants are found. From the soapstocks and by relatively simple procedures it is possible to obtain a oryzanols concentrate which may contain 33% of them. However, its antioxidant power has been little studied in oils compared to other natural antioxidants. Therefore, the present work gives information about the antioxidant power of a concentrate of oryzanols compared to natural antioxidants such as tocopherol and synthetic antioxidants such as butylhydroxytoluene (BHT) added in oils with different degrees of unsaturation and without antioxidants. The results determined by the differential scanning calorimetry method show that the antioxidant power was variable according to the method used. The tocopherol protected the oils from the oxidation at 130°C (soybean and high oleic sunflower) better than the oryzanols concentrate by the isothermal method. When the non-isothermal method was used it was found that the-tocopherol protected soybean oil better than oleic high sunflower oil compared to the oryzanols concentrate. However, when comparing BHT with oryzanols concentrate, BHT generally had a lower protection in both oils and both methods. These results show that the oryzanols concentrate has a protective effect of the oxidation of the studied oils, however, this could depend on the degree of the oil unsaturation.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".