Evaluating the potential of Hibiscus sabdariffa beverage to address the prevalence of iron deficiency in sub-Saharan Africa
Bibliographic record
Abstract
The potential of Hibiscus sabdariffa L. beverage as a dietary iron source for sub-Saharan Africans was investigated. The target was to provide 6 mg of iron through 250 mL of the beverage daily. However, the iron content of the dried hibiscus calyces was determined to be 9.73 ± 0.31 mg/100 g and from that only ∼30% was extractable, resulting in 0.93 ± 0.19 mg Fe/250 mL of the selected beverage formulation. Therefore, ferrous sulphate was explored as a fortificant. The beverage contains polyphenols which could form non-absorbable chelation complexes with iron during digestion. Subsequently, the effect of polyphenols on the bioaccessibility of native and added iron was assessed using spectrophotometric methods. The presence of iron-polyphenol complexes in samples of the unfortified and fortified beverages, adjusted to pH 6.5 (pH at site of iron absorption in the gut) was established. However, only ∼25% of the added iron was found to be bound in the complex. It was shown that the viability of H. sabdariffa L. beverage as an iron source is impacted by extraction losses and the inhibitory effect of polyphenols. Nonetheless, if iron-polyphenol complexation was reduced/prevented then, a fortified hibiscus beverage could be a useful iron source.
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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".