Identification and quantification of canolol and related sinapate precursors in Indian mustard oils and Canadian mustard products
Bibliographic record
Abstract
Abstract Canadian condiment yellow mustard seeds (also called white), oriental and brown mustard seeds and flour extracts and commercially produced Indian mustard oils were examined for bioactive phenolics primarily to identify the antioxidant properties. Phenolic compounds, namely sinapic acid, sinapoyl glucose and canolol, were quantified using high‐performance liquid chromatographic (HPLC) coupled with a diode array detector (DAD). Canolol was detected and confirmed in trace amounts for the first time in commercial oils that had not been preheated specific for canolol production, most likely due to heat applied during processing. Sinapic acid, sinapine and canolol derived from unheated/unroasted mustard seeds and canola extracts were confirmed utilizing HPLC‐DAD, ultra‐performance liquid chromatography‐tandem‐mass spectrometry (UPLC‐tandem‐MS) and nuclear magnetic resonance (NMR) spectroscopy. Practical applications:Oilseeds canola and mustard contain significant amounts of phenolic compounds, principally sinapic acid derivatives. The level and functionality of these phenolic is highly influenced by the processing conditions. In the current study, the phenolic composition of some commercial mustard seed, oil, meal and flour samples were profiled with special focus on the occurrence of canolol, the decarboxylation product of sinapic acid. This study suggests that optimizing the crushing, pressing, or extraction steps during processing is crucial to enrich mustard and canola products with benefits associated with these bioactives, especially canolol. The existence of sinapic acid derivatives was confirmed in the 70% aqueous methanolic extracts of commercial mustard products such as deheated mustard flour and oil. Extracts of mustard, in addition to canola, contain significant amounts of phenolics, mainly sinapine. Traditional ghani pressing, cold pressing and/or screw expeller pressing hold potential for enriching mustard and sinapate‐rich oil with benefits associated with canolol.
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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 | 0.001 | 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".