Optimisation of extraction conditions for terpenoids in <i>Schizandra chinensis Baillon</i> using the response surface method
Bibliographic record
Abstract
Abstract Terpenoids, which are the major volatile compounds of Schizandra chinensis Baillon (Omija), are the main component of phytoncide. The purpose of the present study was to provide more ways to utilise Omija by optimising terpenoid extraction. The response surface method (RSM) was used to maximise the levels of monoterpene, which has substantial physiological activity and sesquiterpene, which has strong impacts on flavour. Central composite design was used to optimise the extraction pressure (X1: 0.01‐0.1 Mpa), ethanol concentration (X2: 0%‐50%), and sample concentration (X3: 0.01‐0.2 g/mL). Analysis of variance showed that X1, X2 and X3 affected total terpenoid levels (Y1) and monoterpene levels (Y2), whereas only X1 and X3 significantly affected sesquiterpene content (Y3) (P < .05). The optimal conditions based on the individual responses were as follows: Y1 and Y2, X1 = 0.07 Mpa, X2 = 36% and X3 = 0.17 g/mL; Y3, X1 = 0.10 Mpa, X2 = 50% and X3 = 0.20 g/mL.
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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 | 0.000 |
| 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".