Extraction of natural antioxidants from Moroccan saffron (Crocus sativus L.) using ultrasound-assisted extraction: An optimization approach with box-behnken design
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Bibliographic record
Abstract
There is increasing evidence of protective health effects of natural antioxidants, such as those contained in saffron ( Crocus sativus L.), but it is challenging to extract polyphenols, which are the purported antioxidants with conventional techniques. This study developed an ultrasound-assisted extraction technique to improve the efficiency of phenolic compound extraction and assess the antioxidant activity of saffron. A response surface methodology, utilizing a Box-Behnken design, was employed to optimize three key extraction parameters: solid-to-liquid ratio, temperature, and extraction time for both saffron stigmas and corms. The total phenolic content and antioxidant activity were analyzed using the Folin-Ciocalteu and the 2,2-Diphenyl-1-picrylhydrazyl (DPPH) assays, respectively. The optimal extraction conditions for stigmas were a solid/liquid ratio of 40 mg/30 mL, with an extraction temperature of 50 °C for 15 min, resulting in a total phenolic content yield of 118.55 mg GAE/g DM and an IC 50 value of 0.023 mg/mL. For optimal conditions when extracting from corms, the extraction time was extended to 45 min, resulting in a total phenolic content of 21.18 mg GAE/g DM and a IC 50 value of 1.02 mg/mL. Results were consistent with predicted values provided by the quadratic model, which confirmed the efficacy of the Box-Behnken design in maximizing the extraction of polyphenol content from C. sativus . Although UAE has been refined at the laboratory level, additional research is needed to assess its feasibility and efficiency on an industrial scale. Exploring large-scale UAE systems, evaluating cost-effectiveness, and identifying potential adaptations for commercial production would be highly beneficial.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it