Subcritical water extraction of hydrolyzed proteins from canola meal: Optimization of recovery and physicochemical properties
Bibliographic record
Abstract
The aim of the study was to valorize hot-pressed canola meal using subcritical water extraction (SWE). Response surface methodology with a 3×3 face-centered central composite design was used to understand the interaction between extraction temperature (200-250°C), time (20-30 min) and feed concentration (5-20%) at 4 MPa pressure and their effects on the protein yield, degree of hydrolysis (DH), interfacial tension (IFT) and phenolic content. The extracts displayed a maximum protein yield of 68.9 wt% and a maximum DH of 14.1%. SDS-PAGE analysis confirmed the hydrolysis of proteins into smaller peptides. The extracted protein significantly reduced the IFT to a minimum of 4.0 mN/m. The extracts were also rich in phenolic compounds, leading to a high level of antioxidative properties. Regression equations were created to optimize the extraction process for desirable properties of the hydrolysates. Overall, the study provides valuable insights into SWE’s potential for significant value addition to canola meal.
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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) | 0.000 | 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 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".