MétaCan
Menu
Back to cohort
Record W2149221630 · doi:10.5539/jfr.v2n5p66

Effect of Nut Treatments on Shea Butter Physicochemical Criteria and Wrapper Hygienic Quality Influence on Microbiological Properties

2013· article· en· W2149221630 on OpenAlexvenueno aff
Rose-Monde Mégnanou, Sebastien Niamké

Bibliographic record

VenueJournal of Food Research · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRoastingFood scienceMathematicsChemistryNutPeroxideAnimal scienceBiologyPhysics

Abstract

fetched live from OpenAlex

<p>The increasing importance of traditional shea butter led to standards criteria establishment. Nevertheless, criteria are difficultly achieved because traditional processes are generally uncontrolled. In this study, optimal processing conditions in order to get shea butter in conformity with standard were determined. Hence, the drying duration and mode, the kernel quality and roasting time were varied. The wrapper hygienic quality effect was also considered. Resulting shea butters of each variation was analyzed and the ANOVA test performed on characteristics to evaluate variations effects. The peroxide index increased continuously (2.79 ± 0.05 to 10.30 ± 0.05 mEg O<sub>2</sub>/kg) from the first week to the fourth sun drying week, while unsapnifiable matter decreased (17.60 ± 0.05 to 1.55 ± 0.05%). Both peroxide and acid index were higher after five minutes of roasting than they were before; and shea butter conserved in sterile wrapper was germs free, compared to other wrappers. Moreover, the process taking into account all these optimal conditions conduced to shea butter with moisture (0.15%), acid (11.94 mg KOH/g), peroxide (2.79 ± 0.05 mEg O<sub>2</sub>/kg), saponifiable (196.10 ± 0.15 mg KOH/g), refractive (1.465 ± 0.005) index and melting point (35.0 ± 0.1 °C) conforming to international standard. Moreover, it was heavy metal and germs free, and its unsapnifiable content (17.61 ± 0.25%) was high.</p>

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.589
Threshold uncertainty score0.166

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 head0.083
GPT teacher head0.349
Teacher spread0.267 · 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

Citations8
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Food ResearchSame topicAfrican Botany and Ecology StudiesFrench-language works237,207