Value-Added Potential of Expeller-Pressed Canola Oil Refining: Characterization of Sinapic Acid Derivatives and Tocopherols from Byproducts
Bibliographic record
Abstract
Valuable phenolic antioxidants are lost during oil refining, but evaluation of their occurrence in refining byproducts is lacking. Rapeseed and canola oil are both rich sources of sinapic acid derivatives and tocopherols. The retention and loss of sinapic acid derivatives and tocopherols in commercially produced expeller-pressed canola oils subjected to various refining steps and the respective byproducts were investigated. Loss of canolol (3) and tocopherols were observed during bleaching (84.9%) and deodorization (37.6%), respectively. Sinapic acid (2) (42.9 μg/g), sinapine (1) (199 μg/g), and canolol (344 μg/g) were found in the refining byproducts, namely, soap stock, spent bleaching clay, and wash water, for the first time. Tocopherols (3.75 mg/g) and other nonidentified phenolic compounds (2.7 mg sinapic acid equivalent/g) were found in deodistillates, a byproduct of deodorization. DPPH radical scavenging confirmed the antioxidant potential of the byproducts. This study confirms the value-added potential of byproducts of refining as sources of endogenous phenolics.
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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 | 0.000 |
| 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".