Exploring the chemical and bioactive properties of <i>Hibiscus sabdariffa</i> L. calyces from Guinea-Bissau (West Africa)
Bibliographic record
Abstract
Different external factors influence the chemical characteristics of natural products, varying according to the geographic origin. The present study determined the nutritional and chemical composition of Hibiscus sabdariffa L. dried calyces (Guinea-Bissauan origin), as well as the phenolic composition, antioxidant, anti-inflammatory, cytotoxicity and antimicrobial activity of its infusion and hydroethanolic extracts. Among the chemical components, glucose and quinic acid showed the major concentration for sugars and organic acids, respectively. Palmitic acid and α-tocopherol were the most abundant lipophilic compounds. The individual phenolic compounds were analysed through HPLC-DAD-ESI/MS. Thirteen compounds were identified in the hydroethanolic extract, while twelve were identified in the infusion, 3-O-caffeoylquinic acid being the major non-anthocyanin compound. Three anthocyanins were identified, delphinidin-3-O-sambubioside being the most abundant. Both extracts showed promising results in all the bioactive assays. This study exhibited the beneficial properties of H. sabdariffa and also emphasized the potential applications of this plant in different industrial sectors.
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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) | 0.001 | 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".