Attenuation of sinapic acid and <scp>sinapine‐derived flavor‐active</scp> compounds using a <scp>factorial‐based</scp> pressurized <scp>high‐temperature</scp> processing
Bibliographic record
Abstract
Abstract De‐oiled canola meals are sources of protein‐containing flavor‐active phenolic compounds. Conventional canola oil processing utilizes an excess amount of solvents and is associated with the release of high‐intensity bitter flavor‐active phenolic compounds, limiting the use of the canola meal. Recent advances in the extraction and isolation of the bitter favor‐active phenolic compounds from canola by‐products produce protein isolates, however, would benefit the industry by producing a side‐stream ingredient rich in phenolics. High temperature and pressure‐aided processing, namely the accelerated solvent extraction (ASE) was investigated to extract the flavor‐active bitter molecules from the canola meal. The extractability of flavor‐active phenolic compounds including the major sinapates, kaempferol derivatives, and other thermo‐generative compounds including thomasidioc acid (TA) was evaluated. The effects of temperature, solvent extractant and concentration, and the particle size of the meal were examined on the extraction efficiency of these phenolic compounds. Extraction temperature (180°C) was the primary determinant (p < 0.05) for the attenuation of major sinapates including sinapine and sinapic acid. Both ethanol and methanol extractants at a concentration of 70% (v/v) significantly (p < 0.05) extracted the flavor‐active phenolic compounds. The pressurized high temperature through optimized ASE conditions attenuated the bitter undesirable flavor‐active phenolic molecules from canola meal, thereby facilitating a potential value‐added phenolic‐rich by‐product.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| 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".