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Record W1559379415 · doi:10.1111/1750-3841.12377

Assessment of the Antioxidant Capacity and Oxidative Stability of Esterified Phenolic Lipids in Selected Edible Oils

2014· article· en· W1559379415 on OpenAlexaff
Sarya Aziz, Sélim Kermasha

Bibliographic record

VenueJournal of Food Science · 2014
Typearticle
Languageen
FieldChemistry
TopicEdible Oils Quality and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsChemistryFood scienceAntioxidantFish oilPeroxide valueOxidative phosphorylationLipid oxidationLipaseChromatographyFish <Actinopterygii>Organic chemistryBiochemistryBiologyEnzyme

Abstract

fetched live from OpenAlex

The research work was aimed at the determination of the antioxidant capacity (AOC) and the oxidative stability of phenolic lipids (PLs), obtained by lipase-catalyzed transesterification of phenolic acids (PAs) with selected edible oils (EOs), including flaxseed (FSO), fish liver (FO), and krill (KO) oils. The statistical analyses (Tukey's test at P < 0.05) revealed that the difference in AOC between that of the esterified FSO (EFSO) and the esterified krill oil (EKO) containing PLs and their control trials of EOs was significant (P < 0.05). To evaluate the storage stability, the EOs and their esterified products were subjected to 2 oxidation treatments. The experimental findings showed that the esterified EOs had higher oxidative stability when they were subjected to light, oxygen, and agitation at 50 °C as compared to that of the EOs; however, only the esterified fish oil (EFO) showed a significant difference in its peroxide value, when the esterified EOs were placed in the dark at 25 °C. Overall, the phenolic mono- and diacyglycerols present in the EOs have shown to be potential antioxidants in improving the oxidative stability of the oil and enhancing its AOC.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.031
Threshold uncertainty score0.253

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.033
GPT teacher head0.289
Teacher spread0.256 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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