Optimization of Extraction of Phenolic Compounds from Flax Shives by Pressurized Low-Polarity Water
Bibliographic record
Abstract
Pressurized low-polarity water (PLPW) extraction of phenolic compounds from flax shive was investigated using statistically based optimization and the "one-factor-at-a-time" method. Extraction variables examined using central composite design (CCD) included temperature, flow rate, and NaOH concentration of the extracting water. Extraction of phenolic compounds including p-hydroxybenzaldehyde, vanillic acid, syringic acid, vanillin, acetovanillone, and feruric acid was affected by temperature and NaOH concentration; and extraction of all phenolic compounds, except ferulic acid, increased with temperature and NaOH concentration of the extracting water. Flow rate had little effect on concentration of phenolic compounds at equilibrium, but the extraction rate at the early phase was higher for higher flow rates. The mechanism of PLPW extraction of flax shive phenolics was also investigated using a two-site kinetic model and a thermodynamic model. To determine the extraction mechanism, flow rate was varied from 0.3 to 4.0 mL/min while temperature and NaOH concentration were fixed at 180 degrees C and 0.47 M, respectively. The flow rate tests showed the extraction rates of total phenolic (TP) compounds increased with flow rate and can be described by a thermodynamic model. The results from the thermodynamic model demonstrated that a K(D) value of 30 agreed with the experimental data in the flow rate range of 0.3-4.0 mL/min. When the effect of the three independent variables was evaluated simultaneously using CCD, a maximum TP concentration of 5.8 g/kg of dry flax shive (DFS) was predicted from the combination of a high temperature (230.5 degrees C), a high initial concentration of NaOH (0.63 M), and a low flow rate (0.7 mL/min). Maximum TP concentration of 5.7 g/kg of DFS was obtained from extraction conditions of 180 degrees C, 0.3 or 0.5 mL/min, and 0.47 M NaOH at equilibrium. A second-order regression model generated by CCD predicted a maximum TP concentration of 5.8 g/kg of DFS under the same extraction conditions, which is well matched with the results from experimental data.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".