Antioxidant compounds, antioxidant activities, and mineral contents among underutilized vegetables
Bibliographic record
Abstract
Natural sources may be a method to introduce antioxidants in the human diet. Portulaca oleracea L., Peperomia pellucida L., and Trianthema portulacastrum L are underutilized leafy vegetables. The plants may be sources for total phenolic (TPC), total flavonoid (TFC), total carotenoid (TCC), and β-carotene but information is lacking. Antioxidant activity, ferric reducing antioxidant power (FRAP), and 1,1-diphenyl-2-picrylhydrazyl (DPPH), and macro- and microminerals contents were investigated in P. oleracea, P. pellucida and T. portulacastrum. Trianthema portulacastrum had the highest TPC (1.34 ± 0.13 mg∙g−1), TFC (0.58 ± 0.08 mg∙g−1), TCC (0.14 ± 0.01 mg∙g−1), and β-carotene (0.94 ± 0.18 mg∙g−1) values. The antioxidant activity and FRAP assay were highest in P. oleracea (0.91 ± 0.09 mg∙g−1); the DPPH assay for P. pellucida was highest (IC50 = 7 µg∙mL−1). The amount of K was highest in P. oleracea (55.470 ± 0.481 g∙kg−1). The amount of Mn was highest in P. pellucida (0.251 ± 0.002 g∙kg−1). The individual underutilized vegetables may be able to supply some antioxidant compounds and mineral contents for the human diet.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".