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Record W2140409095 · doi:10.5539/jfr.v3n5p49

Mass Transfer During Osmotic Dehydration of Chub Mackerel Cylinders in Ternary Solution

2014· article· en· W2140409095 on OpenAlexvenueno aff
Gerardo Checamarev, Marı́a Isabel Yeannes, A.E. Bevilacqua, M. R. Casales

Bibliographic record

VenueJournal of Food Research · 2014
Typearticle
Languageen
FieldEngineering
TopicFreezing and Crystallization Processes
Canadian institutionsnot available
FundersUniversidad Nacional de Mar del PlataConsejo Nacional de Investigaciones Científicas y Técnicas
KeywordsOsmotic dehydrationChemistryThermodynamicsDehydrationMass transferTernary operationDiffusionAnalytical Chemistry (journal)CylinderChromatographyPhysicsBiochemistryGeometryMathematics

Abstract

fetched live from OpenAlex

<p>In the analysis, design and optimization of an osmotic dehydration process is important to know the kinetic of water loss and solutes gain. In this study, the mass transfer during osmotic dehydration of chub mackerel (<em>Scomber japonicus</em>) cylinders in ternary solution glycerol/salt/water was analyzed. The models of Zugarramurdi & Lupín and Azuara were used to describe mass transfer and to estimate equilibrium values. The radial effective diffusion coefficient was estimated using the analytical solution of Fick's second law. Diffusion coefficients were determined for a finite cylinder, for an infinite cylinder considering only the first term of the series and considering higher order terms of the series. The profiles of water and solutes during the osmotic dehydration were calculated by using the estimated water and solutes diffusivities. According to the results obtained, using three terms in the analytical solution of the Fick's second law is appropriate to determine the diffusion coefficients. The diffusion coefficient for infinite cylinder were 2.63×10<sup>-6</sup>, 4.11×10<sup>-6</sup> and 4.25×10<sup>-6</sup> cm<sup>2</sup>/s for water loss, salt and glycerol gain respectively. For a finite cylinder these values were 2.30×10<sup>-6</sup>, 3.67×10<sup>-6</sup> and 3.78×10<sup>-6</sup> cm<sup>2</sup>/s respectively. All the models proposed were in agreement with experimental data for solutes gain ((0.967<R<sup>2</sup><sub>adj</sub><0.986); (0.0016<<em>RMSE</em><0.039) and (4.17<<em>P</em><10.0)). The model based on the solution of Fick’s Law for an infinite cylinder with higher order terms was the best fit for water loss and solutes gain. The equilibrium values estimated with Azuara model agree with the experimental (0<relative error<9.8). Water and solute distributions as a function of time and location in the radial direction were plotted.</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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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 head0.032
GPT teacher head0.270
Teacher spread0.239 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2014
Admission routes1
Has abstractyes

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