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Record W4400263964 · doi:10.5539/jfr.v13n2p19

Impact of Hulling and Heat Treatment on the Physicochemical Properties, Bioactivity and Bioavailability of Iron and Zinc of the G196 Soybean Variety Produced in Burkina Faso

2024· article· en· W4400263964 on OpenAlexvenueno aff
Elisabeth Rakisewendé Ouedraogo, Raymond Poussian Barry, Salamata Tiendrebeogo, Frédéric Anderson Konkobo, Sandrine Zongo, Edwige Noëlle Roamba, Kiessoun Konaté, Mamoudou H. Dicko

Bibliographic record

VenueJournal of Food Research · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsnot available
Fundersnot available
KeywordsSteamingRoastingBioavailabilityChemistryFood scienceZincPhytic acidWater contentSignificant differenceMoistureAnimal scienceMathematicsBiology

Abstract

fetched live from OpenAlex

This study delved into the impact of hulling and two types of heat treatment on the physicochemical, bioactive properties and bioavailability of the G196 soybean produced in Burkina, in order to not only find the optimal conditions for pre-treatment of seed, but also to guide their use in food formulations. Standard analytical methods were used for physicochemical and biochemical analyses. The results showed an increase in ash content by 0.04% as a result of seed shelling, while steaming led to a significant decrease in ash with a reduction rate by 0.06%; 0.08%; 0.25% after 20min, 40min and one hour, respectively. An average increase in total dry materials by 0.03% and reduction in moisture by 6.33% were observed after one hour of roasting. Additionally, shelling and steaming increased total carbohydrate contents. Roasting and steaming caused a significant reduction in protein, but an increase was observed after hulling. Carbohydrate levels decreased over the course of three roasting times. Regarding bioavailability, the zinc content improved after 40 minutes of roasting. Shelling also reduced the phytate content by 11.89%, while steaming significantly reduced the phytate, resulting in a drop in the phytate content by 17.18%; 18.02% and 19.71% after twenty, forty minutes and one hour, respectively. A significant reduction in phytate content by 26.64% after 40 minutes, and 46.46% after one hour was observed during heat treatment by roasting.

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)0.001
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 score0.141
Threshold uncertainty score0.121

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.099
GPT teacher head0.330
Teacher spread0.231 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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