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Record W2969111365 · doi:10.1111/1750-3841.14730

Technology for Triple Fortification of Salt with Folic Acid, Iron, and Iodine

2019· article· en· W2969111365 on OpenAlexaff
Oluwasegun Modupe, Kiruba Krishnaswamy, Levente L. Diósady

Bibliographic record

VenueJournal of Food Science · 2019
Typearticle
Languageen
FieldNursing
TopicChild Nutrition and Water Access
Canadian institutionsUniversity of Toronto
FundersBill and Melinda Gates Foundation
KeywordsIodineFortificationFolic acidChemistrySalt (chemistry)FerrousPopulationMicronutrientIodised saltFood fortificationFood scienceIodine deficiencyMedicineOrganic chemistryInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

As many of the maternal and child health complications result from folic acid, iron, and iodine deficiencies; it makes sense to combat these simultaneously. We have developed cost-effective technology to deliver these three micronutrients simultaneously through salt. Our goal was to retain at least 70% of the micronutrients during 6 months of storage. The fortified salt was formulated by spraying a solution that contained 2% iodine and 0.5% or 1% folic acid onto salt and adding encapsulated ferrous fumarate. The formulated triple fortified salt contained 1,000 ppm iron, 50 ppm iodine, and 12.5 or 25 ppm folic acid. The spray solution and the salt were stored for 2 and 6 months respectively at 25, 35, and 45 °C 60 to 70% relative humidity. Even at 45 °C, over 70% of both iodine and folic acid were retained in the salt. The best formulation based on the color of the salt and stability of iodine and folic acid contained 12.5 ppm folic acid, 50 ppm iodine, and 1,000 ppm iron. These results indicate that iron, iodine, and folic acid can be simultaneously delivered to a vulnerable population through salt using the technology described. Also, the quality control of the process can be developed around pteroic acid that was detected as a primary degradation product of folic acid. PRACTICAL APPLICATION: The technology developed is already transferred to India for industrial scale up. When fully operational, the technology will simultaneously solve iron, iodine, and folic acid deficiencies in vulnerable populations at a very low cost.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.130

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.274
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2019
Admission routes1
Has abstractyes

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