Optimization of process parameters in supercritical <scp>CO<sub>2</sub></scp> extraction of rose essential oil: Evaluation of phenolic, flavonoid, and antioxidant profiles
Bibliographic record
Abstract
Abstract This study explores the optimization of supercritical CO2 extraction parameters (pressure, temperature, and flow rate) to maximize the yield and bioactive content in rose essential oil. Experiments covered a pressure range of 20–30 MPa, temperatures of 40–60°C, and flow rates from 2 to 6 mL/min, aiming to elucidate the effects of these variables on extraction outcomes. Findings indicate that a pressure of 20 MPa, temperature range of 40–50°C, and flow rate of 2–4 mL/min achieved optimal extraction, enhancing both yield and bioactive compound solubility. These specific conditions preserved high levels of phenolic and flavonoid compounds, directly boosting the antioxidant potency of the oil. The non‐linear interaction of each parameter highlights the critical balance needed for efficient extraction. This optimized process not only improves the economic viability of rose essential oil production by maximizing bioactive yields but also supports applications in therapeutic and cosmetic fields due to the oil's enriched antioxidant profile.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".