Antioxidative Polyphenols of Canola Meal Extracted by High Pressure: Impact of Temperature and Solvents
Bibliographic record
Abstract
Canola meal, a by-product of oil pressing, is a rich source of phenolic antioxidants. However, its use in the food and feed sector is still limited by the need for greener, sustainable, and more cost-effective extraction methods. This study used accelerated solvent extraction (ASE) to enhance the extraction efficiency of the phenolic antioxidants. The high selectivity and short extraction time associated with ASE were ideal for obtaining high yields of these antioxidants. The structure-based activity of phenolic compounds may be influenced by the high pressure and temperature of the greener ASE process. The present study evaluated the effect of temperature (140, 160, and 180 °C) and pressure (1,500 psi) on the extraction and yield of phenolic compounds from canola meal as well as the solvent type (ethanol and methanol) and concentration (30%, 40%, 60%, and 70% v/v). Antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazyl, ferric reducing/antioxidant power assay, and ion-chelating activity. The highest yield of phenolic compounds was obtained with 70% methanol (20.72 ± 1.47 mg SAE/g DM [milligrams of sinapic acid equivalents per gram of dry matter]) and 70% ethanol (24.71 ± 2.77 mg SAE/g DM) at 180 °C temperature. A similar trend was observed for the antioxidant activity of the extracts and their total flavonoid content. The structure-based antioxidant activity of the extracts examined increased with the increase in the percentage of the extracting solvent (P > 0.05). This study established ASE as an efficient green method for extracting phenolic compounds from canola meal, with potential application for the production of natural bioactive compounds from underutilized agricultural by-products. PRACTICAL APPLICATION: ASE is an efficient eco-friendly method for extracting phenolic compounds from agricultural by-products such canola meal. Under the conditions of high pressure and temperature, ASE significantly improved the yields of phenolic compounds, sinapine, sinapic acid, and canolol. Under these conditions, water, as an extractant, was not effective in extracting sianpine. Moreover, it was much less effective than both 70% ethanol and 70% methanol in extracting sinapine or canolol. These phenolic compounds are of great interest as natural antioxidants for enhancing the shelf life of food products. They also represent new sources of neutraceuticals for improving human health.
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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 | 0.000 | 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) | 0.000 | 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".