Impact of endogenous canola phenolics on the oxidative stability of oil‐in‐water emulsions
Bibliographic record
Abstract
Abstract The aim of this study was to evaluate the antioxidative effect of phenolics naturally present in canola seeds and meal. Individual phenolics were extracted from ground, defatted canola seeds, and meal. Fractionated extracts rich in sinapic acid, sinapine, or canolol as well as a non‐fractionated extract were used. These extracts (100 and 350 µM) were evaluated as antioxidants in stripped canola oil‐in‐water (o/w) emulsion. For comparison, the antioxidative effect of phenolic standards for sinapic acid and sinapine (as sinapine thiocyanate) and butylated hydroxytoluene (BTH) as a positive control were also evaluated. The concentration of lipid hydroperoxides and selected volatiles measured at different time points was used to evaluate the antioxidative effect. Moreover, the properties of extracts and corresponding phenolic standards were evaluated in three different in vitro antioxidant assays. All extracts and standard antioxidants had radical scavenging activity and reducing power. The antioxidant standards and extracts inhibited lipid oxidation in the emulsions compared to no antioxidant added. At 100 µM the effectiveness of the extracts was as follows: sinapine>whole extract>sinapic acid>canolol>Con2 (no antioxidant). At 350 µM the ranking was as follows: canolol ≥ sinapine ≥ whole extract ≥ sinapic acid > Con2. Sinapine and sinapic acid extracts were more efficient antioxidants than the corresponding pure standards. However, the most efficient antioxidant in this study was BHT. The differences in effectiveness may be ascribed to mainly the different chain attached to the phenolic ring, which results in different polarity and thus different location in the emulsions. Practical applications: The result showed stronger antioxidant activity of canola extracts than phenolic standards. Therefore, these canola extracts can be used for protecting canola oil emulsion or other emulsions against lipid oxidation. However, the results indicate that the antioxidant activity of the extracts rich in sinapine and canolol had a concentration‐sensitive effect. In order to get the best antioxidative effect, optimization of the concentration to be used for each specific application is necessary.
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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) | 0.000 | 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) | 0.002 | 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".