Optimization of Bioactive Polyphenols Extraction from Picea Mariana Bark
Bibliographic record
Abstract
Reported for its antioxidant, anti-inflammatory and non-toxicity properties, the hot water extract of Picea mariana bark was demonstrated to contain highly valuable bioactive polyphenols. In order to improve the recovery of these molecules, an optimization of the extraction was performed using water. Several extraction parameters were tested and extracts obtained analyzed both in terms of relative amounts of different phytochemical families and of individual molecules concentrations. As a result, low temperature (80 °C) and low ratio of bark/water (50 mg/mL) were determined to be the best parameters for an efficient polyphenol extraction and that especially for low molecular mass polyphenols. These were identified as stilbene monomers and derivatives, mainly stilbene glucoside isorhapontin (up to 12.0% of the dry extract), astringin (up to 4.6%), resveratrol (up to 0.3%), isorhapontigenin (up to 3.7%) and resveratrol glucoside piceid (up to 3.1%) which is here reported for the first time for Picea mariana. New stilbene derivatives, piceasides O and P were also characterized herein as new isorhapontin dimers. This study provides novel information about the optimal extraction of polyphenols from black spruce bark, especially for highly bioactive stilbenes including the trans-resveratrol.
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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".