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Record W4280515125 · doi:10.18697/ajfand.108.20500

Impact of fermentation and incorporation of cashew flour on the micronutrient and macronutrient contents of millet flour sold on the market: Case of the city of Yamoussoukro

2022· article· en· W4280515125 on OpenAlexfundno aff
Traoré Sékou, Koffi David AKAKI, KY Koné, D Soro

Bibliographic record

VenueAfrican Journal of Food Agriculture Nutrition and Development · 2022
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsnot available
FundersAgence Française de DéveloppementInternational Development Research Centre
KeywordsFood scienceFermentationMicronutrientChemistryWheat flourNutrientMoistureFortificationWeaningMathematicsAnimal scienceBiology

Abstract

fetched live from OpenAlex

The weaning period of an infant, which should begin from 7 months, is characterized by the gradual change from a liquid to a solid diet. After 6 months, the nutrients contained in breast milk are no longer sufficient to meet the growing demands of the infant. This is the ideal period for the introduction of a complementary food to make up for any deficiencies. To contribute to this situation, two groups, each consisting of five combinations of millet flour, enriched with cashew flour were formulated. The samples M100A0 (Unenriched millet flour), M92,5A7,5, M85A15, M77, 5A22,5 and M70A30 were enriched with 7.5%, 15%, 22,5% and 30% downgraded cashew flour, respectively. The samples MF100A0 (Unenriched fermented millet flour), MF92, 5A7,5, MF85A15, MF77, 5A22,5 and MF70A30 were constructed in a corresponding manner, the only difference being that the millet flour was fermented. After analyses of the different formulations, the best proportions of proteins were observed in MF70A30, MF77, 5A22, 5 and M70A30, which were 13.13%, 12.25% and 12.25%, respectively. Samples M70A30 and M77,5A22,5 exhibited the best iron contents of 8.44 ppm and 8.12 ppm, respectively. The protein contents of the unfortified samples M100A0 and MF100A0 were 7.53% and 6.13% respectively. Formulations MF70A30, M77,5A2,5 and M70A30 with levels of 1.06 ppm, 0.98 ppm and 0.98 ppm, respectively, gave the best zinc contents. The moisture contents of the formulated samples had minimal changes. They varied between 6.16 ± 0.06% and 7.6 ± 0.99% for unfermented samples, and between 6.35 ± 0.32% and 7.0 ± 0.02% for fermented samples. The humidity values of the two groups of samples were not significantly different at P≤0.05. These low moisture contents in the flours are important for better preservation. At the end of this study, certain formulations were selected because of their good nutritional profile. Thus the formulations M70A30 composed of 70% millet flour and 30% cashew flour and MF70A30 composed of 70% fermented millet flour and 30% cashew flour present the best options and could be used as quality infant flours. Key words : complementary food, infant, cashew kernel, weaning, millet flour

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 score0.155
Threshold uncertainty score0.272

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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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