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Record W1549801950 · doi:10.1155/2015/594238

Optimization of the Hydrolysis of Safflower Oil for the Production of Linoleic Acid, Used as Flavor Precursor

2015· article· en· W1549801950 on OpenAlexafffund
Marya Aziz, Florence Husson, Sélim Kermasha

Bibliographic record

VenueInternational Journal of Food Science · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsHydrolysisCandida rugosaChemistryLinoleic acidFlavorSubstrate (aquarium)ChromatographyLipaseEnzymatic hydrolysisOrganic chemistryFood scienceEnzymeFatty acidBiology

Abstract

fetched live from OpenAlex

Commercial lipases, from porcine pancreas (PPL), Candida rugosa (CRL), and Thermomyces lanuginosus (Lipozyme TL IM), were investigated in terms of their efficiency for the hydrolysis of safflower oil (SO) for the liberation of free linoleic acid (LA), used as a flavor precursor. Although PPL, under the optimized conditions, showed a high degree of hydrolysis (91.6%), its low tolerance towards higher substrate concentrations could limit its use for SO hydrolysis. In comparison to the other investigated lipases, Lipozyme TL IM required higher amount of enzyme and an additional 3 h of reaction time to achieve its maximum degree of SO hydrolysis (90.2%). On the basis of the experimental findings, CRL was selected as the most appropriate biocatalyst, with 84.1% degree of hydrolysis. The chromatographic analyses showed that the CRL-hydrolyzed SO is composed mainly of free LA.

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)0.002
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 score0.078
Threshold uncertainty score0.183

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0010.000
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 head0.019
GPT teacher head0.280
Teacher spread0.260 · 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

Citations26
Published2015
Admission routes2
Has abstractyes

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