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Record W2158488917 · doi:10.5539/sar.v3n1p50

Marketed and Original Shea Butters of Côte d’Ivoire: Physicochemical and Biochemical Characterization and Evaluation of the Potential Utilizations

2014· article· en· W2158488917 on OpenAlexvenueno aff
Rose-Monde Mégnanou, Lessoy T. Zoué, Sebastien Niamké

Bibliographic record

VenueSustainable Agriculture Research · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAfrican Botany and Ecology Studies
Canadian institutionsnot available
Fundersnot available
KeywordsUnsaponifiableFood scienceChemistryStearic acidFatty acidOrganic chemistry

Abstract

fetched live from OpenAlex

<p>Many standards constitute shea butter trading conditions, but the exploitation of this greasy product is submitted to other industrial exigencies. The aim of this study was to characterize and evaluate the utilization potentiality of the artisanal shea butter produced in Côte d’Ivoire, on the basis of the industrials exigencies. Hence, both beige and yellow artisanal (original and market) shea butters were collected and analyzed. The refractive indexes (1.46 ± 0.00) did not vary while specific gravity at 40 °C (0.86 ± 0.00 - 0.92 ± 0.00), unsaponifiable matter (1.80 ± 0.01 - 3.76 ± 0.02%) and pH values (5.39 - 6.69) showed significant differences from a sample to another. The viscosity was very high at 40 °C (86.78 ± 0.89 - 130.10 ± 0.26 mPas) and decreased with the temperature increasing (40 to 65 °C). The UV-Vis spectrum showed a very weak absorption from 300 to 400 nm (UV-B and UV-A domains) while the near infra-red (NIR) one, revealed peaks at 450 and 700 nm for yellow shea butters only and peaks at 1200, 1400, 1725 and 2150 nm for all the samples. The fatty acids profile highlighted four main fatty acids (palmitic, stearic, oleic and linoleic acids); saturated fatty acids (56.00 ± 0.20 - 63.00 ± 0.20%) were the most important. All these interesting characteristics should arouse attention for using traditional shea butters in food, cosmetic and pharmaceutical industries.</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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.285

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 studies0.0000.001
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 head0.020
GPT teacher head0.271
Teacher spread0.252 · 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

Citations5
Published2014
Admission routes1
Has abstractyes

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