Process Development for Double and Multiple Fortification of Salt with Ferric Pyrophosphate and Iron Absorption Enhancers
Bibliographic record
Abstract
A process was developed to fortify salt using ferric pyrophosphate (FePP), to treat micronutrient deficiencies (in iron, zinc, iodine, B9, B12) causing prenatal complications. Extrusion and microencapsulation produced premixes for double (DFS) and multiple-fortified salt (MFS). Reduction in colour-masking was predicted, since FePP is off-white. FePP is significantly less bioavailable than ferrous fumarate, therefore, absorption enhancers were utilized. Formulations developed by ETH Zurich were 1:citric acid (CA), trisodium citrate (TSC); 2:CA, sodium pyrophosphate; 3: reduced levels CA, TSC; 4: disodium EDTA. 25% titanium dioxide was required to colour-mask the extrudates. Soy stearin (SS) coating at 15% w/w prevented iodine loss (from iron-iodine interaction) in fortified salts. All samples made with University of Toronto retained >50%iodine at 25, 35, 45oC after 6 months. Pilot testing of the process at JVS Foods, Jaipur confirmed the laboratory results. With 10g salt consumption/day, DFS and MFS can deliver 50-200% RDA for the added micronutrients.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".