Extraction Optimization of <i>Arctium lappa</i> L. Polysaccharides by Box–Behnken Response Surface Design and Their Antioxidant Capacity
Bibliographic record
Abstract
Abstract Arctium lappa L is a good source of polysaccharides in addition to its nutrient content and health benefits. In this study, a Box–Behnken response surface design is used to optimize the extraction conditions of A. lappa L. polysaccharides (ALP) in hot water. The influence of different degreasing methods on polysaccharide yield is investigated for the first time and their antioxidant activity compared. The effects of liquid‐to‐solid ratio (10:1 to 30:1), extraction temperature (60–100°C) and extraction time (1–3 h) on the ALP yield are analyzed. Under the optimal extraction conditions (extraction temperature 71.12°C, extraction time 2.51 h, liquid‐to‐solid ratio 16.20:1), Derringer's desirability prediction tool obtains the highest extraction yield of polysaccharides (9.73%), which is confirmed through validation experiments. In addition, the 2,2‐diphenyl‐1‐picrylhydrazyl, 2,2‐azinobis (3‐ethylbenzothiazoline‐6‐sulfonic acid) diammonium salt), andoxygen radical antioxidant capacity values of the optimized ALP are 232.23 ± 4.19, 407.84 ± 1.48, and 2932.54 ± 145.29 µmol Trolox g –1 , respectively, indicating that ALP has potential antioxidant capacity. Therefore, ALP can be used as a functional food ingredient or nutraceutical.
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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 | 0.001 | 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) | 0.001 | 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 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".