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Folic acid stability in the presence of various formulation components including iron compounds in fortified extruded Ultra Rice<sup>®</sup> over prolonged storage at 40 °C and 60% relative humidity (RH)

2011· article· en· W1522215782 on OpenAlexafffund
Yao Li, Levente L. Diósady, Shirley Jankowski

Bibliographic record

VenueInternational Journal of Food Science & Technology · 2011
Typearticle
Languageen
FieldMedicine
TopicFolate and B Vitamins Research
Canadian institutionsUniversity of Toronto
FundersRyerson UniversityPATH
KeywordsFolic acidFortificationFood fortificationFood scienceChemistryFortified FoodFerricVitaminVitamin CBiochemistryMedicineOrganic chemistry

Abstract

fetched live from OpenAlex

Summary Ultra Rice ® , a reconstituted rice product made by extrusion, has been successfully formulated for the fortification of market rice with vitamin A, iron and vitamin B 1 . As folic acid deficiency is a major health problem in areas targeted by Ultra Rice ® technology, including India, Colombia and Brazil, it seems logical to incorporate folic acid into the existing formulation. The effects of various iron compounds on the storage stability of folic acid were studied. Four commercial ferric pyrophosphate compounds were chosen as iron sources and were added at different concentrations. A food‐grade whitener (TiO 2 ) was also tested for its effects on folic acid stability and product colour. Folic acid was generally stable in the prepared rice formulations under high temperature and humidity (40 °C, 60%RH) – with the best sample retaining 95% and &gt;75% of folic acid after 3 and 9 months of storage, respectively. The work demonstrated that folic acid fortification of rice through Ultra Rice ® technology is technically feasible.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.083
GPT teacher head0.337
Teacher spread0.255 · 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 designObservational
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

Citations22
Published2011
Admission routes2
Has abstractyes

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