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Record W1979547707 · doi:10.5539/jfr.v4n3p138

Desorption Isotherms and Isosteric Heats of Fermented Cocoa Beans (Theobroma cocoa)

2015· article· en· W1979547707 on OpenAlexvenueno aff
Djedjro Clément Akmel, Kouassi E. Kakou, Kisselmina Youssouf Kone, Nogbou Emmanuel Assidjo, Patrice Lucien Kouamé

Bibliographic record

VenueJournal of Food Research · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsTheobromaDesorptionChemistryWater contentMoistureCOCOA BEANWater activityGravimetric analysisFermentationThermodynamicsFood scienceAdsorptionOrganic chemistryBotanyPhysics

Abstract

fetched live from OpenAlex

<p>Water desorption isotherms of fermented cocoa beans from Ivory Coast were determined using the gravimetric static method of saturated salts solutions at 30 °C, 40 °C and 60 °C, and isosteric heats of desorption were calculated from Clausius-Clapeyron equation. The experimental data were fitted to several isotherm equations. The best fittings were obtained for the BET equation for aw<0.50 (with an average mean relative deviation (MRD) value of 1.56%) and for the Harkins-Jura equation for aw?0.50 (with an average value MRD equation of 4.17%). The isotherms obtained at 30 °C and 40 °C are practically coincident and overlapped for aw below 0.40. Fermented cocoa beans presented a monolayer moisture content of 0.083 dry basis (d.b.) at 30 °C and this value decreases with increasing temperature. The net isostheric heats of desorption for fermented cocoa beans for the temperature range studied (30-60 °C) were estimated as a function of moisture content. The maximum net isosteric heat of desorption for fermented cocoa beans was estimated at around 13.51 kJ/mol corresponding to a moisture content value of 2.85%. The energy requirement for maintaining the moisture content low of 8.7% (d.b.) or 8% wet basis (w.b.) for safe storage of this product or for reducing the moisture content during drying was estimated at around 9.58 kJ/mol.</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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.111

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 head0.142
GPT teacher head0.332
Teacher spread0.190 · 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

Citations11
Published2015
Admission routes1
Has abstractyes

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