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Record W1988051664 · doi:10.1002/cjce.22179

Oil extraction kinetics of hydrothermally pretreated canola seeds

2015· article· en· W1988051664 on OpenAlexvenueno aff
Valeria Zárate, Ethel E. Pérez, Guillermo H. Crapiste, Susana M. Nolasco, María B. Fernández

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2015
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsnot available
FundersConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsCanolaExtraction (chemistry)DiffusionScanning electron microscopeArrhenius equationHydrothermal circulationChemistryMaterials scienceYield (engineering)Analytical Chemistry (journal)ChromatographyChemical engineeringNuclear chemistryActivation energyComposite materialFood scienceOrganic chemistryThermodynamics

Abstract

fetched live from OpenAlex

In this work the kinetics of oil extraction from spring canola seeds subjected to a hydrothermal pretreatment with direct steam (393 K, 5 min) was studied. The differences between the seed internal structure generated by the application of this pretreatment and that of the untreated sample (ground sample) were observed by scanning electron microscopy. Oil from both samples was extracted with hexane at different times and temperatures using a stirred batch system. Oil yield increased up to 46 % due to the hydrothermal treatment. A model was proposed to explain the oil extraction process from hydrothermally pretreated and untreated canola seeds, taking into account two main mechanisms: a washing process of the surface oil from the seed, and a diffusion process. Parameters of the model were fitted, and values of the oil fraction extracted during the washing step (0.27 and 0.50 for untreated and hydrothermally treated canola seeds, respectively) and the effective diffusion coefficient (3.1–9.4.10‐12 m 2 s −1 ) were obtained. The latter value showed an Arrhenius‐type temperature dependence in the untreated sample, but the diffusion coefficient did not vary with temperature when oil diffusion was analyzed using hydrothermally pretreated seeds.

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 score0.011
Threshold uncertainty score0.399

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 head0.017
GPT teacher head0.218
Teacher spread0.202 · 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

Citations17
Published2015
Admission routes1
Has abstractyes

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