Antioxidant Activity of Spray-Dried Extracts of Psidium guajava Leaves
Bibliographic record
Abstract
Antioxidants from Psidium guajava leaves were extracted with 70% ethanol in water. The extractive solution was concentrated and submitted to spray drying in the presence of technological adjuvants at a proportion of 8 % wet base. Three distinct technological adjuvants were evaluated: β-cyclodextrin (βCD-80), maltodextrin DE10:Aerosil® (MA-80 - 7:1), and maltodextrin DE10:Encapsia®:Aerosil® (MDEA-80 - 5:2:1). The antioxidant activity of the concentrated extract and spray-dried powders was assessed by three antioxidant assays, namely: the2,2'-azinobis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radical scavenging, ferric reducing antioxidant power (FRAP), and oxygen radical absorption capacity (ORAC). The 1,1-diphenyl-2-picrylhydrazyl radical (DPPH) scavenging capacity was determined previously. The spray-dried powders exhibited strong antioxidant activity (IC50 value = 7.96 to 9.76 μg/mL – DPPH method; 3,125.1 to 3,406.0 μM TE/g dry weight – ABTS method; 4,210 to 4,540 μM FeSO4 E/g – FRAP method; 1,820-2,020 μM TE/g – ORAC method). The technological adjuvants did not significantly interfere with the antioxidant activity of the dried products, regardless the type of antioxidant assay used. The results here reported strongly evidenced that the concentrated and spray-dried extracts of Psidium guajava are rich sources of natural antioxidants with potential application in food, pharmaceutical, and cosmeceutical products.
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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 | 0.000 | 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".