Rice fortification with zinc during parboiling may improve the adequacy of zinc intakes in Bangladesh
Bibliographic record
Abstract
BACKGROUND: Zinc deficiency is prevalent among children and women in Bangladesh and parboiled rice is the major staple food consumed. Parboiling offers an opportunity to increase the zinc and iron content of rice by adding fortificants to the soaking water. RESULTS: Rice zinc content increased with increasing amounts of zinc sulfate added to the parboil soaking water. Addition of 1300 mg zinc L(-1) increased raw polished rice zinc content from 16.6 to 44.9 mg kg(-1) and from 12.6 to 32.9 mg kg(-1) in the open and closed parboiling systems, equivalent to 170% and 161% increases, respectively. Retention of zinc after washing and cooking was 70-81% across all concentrations tested. Addition of iron-ethylenediaminetetraacetic acid and zinc sulfate together increased zinc, but not iron, content of polished rice. The simulated prevalence of inadequate zinc intake was reduced by more than half among children and nearly two-thirds among women if 50% of the population were to consume the 1300 mg zinc L(-1) parboiled fortified rice. CONCLUSION: Addition of zinc sulfate to soaking water during parboiling increases the zinc content of rice and, if found to be bioavailable, could substantially reduce the prevalence of inadequate zinc intake by children and women in Bangladesh.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".