Natural Antioxidant Activity and Compounds Content from Wastes of Euterpe edulis Berries
Bibliographic record
Abstract
The Euterpe edulis (Juçara) is native to Brazil, which berries and wastes present high antioxidant content. Therefore, in this study, microwave-assisted extraction (MAE) was investigated for antioxidant compounds extraction from E. edulis waste and maximized antioxidant activities using response surface methodology coupled with a central composite design. Three factors were observed: microwave power (400/500/600 W), exposition time (30/60/90 sec) and ethanol concentration solvent (40/60/80%). The extracts were characterized by determination of total phenolic (TPC), flavonoids (TFC), monomeric anthocyanins (TAC), tannins content (TTC), and in vitro antioxidant assay (AA%). The yield of TPC, TFC, TAC, and TTC varied at 595.43-2171.34 mg GAE.100 g DM-1, 137.36-251.24 mg QE.100 g DM-1, 179.32-354.38 mg C-3-GE.100 g DM-1 and 0.23-1.00 µg TAE.100 g DM-1, respectively. The optimal MAE parameters for TPC was microwave power 668.18 W, exposition time 110.45 s and aqueous ethanol concentration 93.64%, for TFC same parameters observed; though for TAC the different parameters were 532.28 W, and for TTC 9.55 s. However, for antioxidant activity, the parameters were 668.18 W, 110.45 s time and 64.41% of aqueous ethanol solvent. Therefore, this methodology was successfully applied for optimal extraction of total phenolics, flavonoids, monomeric anthocyanins and tannins from juçara waste and obtain optimal antioxidant activity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 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".