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Record W2094261244 · doi:10.3390/antiox3030544

Endogenous Phenolics in Hulls and Cotyledons of Mustard and Canola: A Comparative Study on Its Sinapates and Antioxidant Capacity

2014· article· en· W2094261244 on OpenAlexafffund
Shyamchand Mayengbam, Ayyappan Appukuttan Aachary, Usha Thiyam‐Holländer

Bibliographic record

VenueAntioxidants · 2014
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversity of Manitoba
FundersCanola Council of CanadaUniversity of Manitoba
KeywordsCanolaChemistryCotyledonAntioxidantDPPHBrassicaFood scienceHigh-performance liquid chromatographyBotanyChromatographyBiochemistryBiology

Abstract

fetched live from OpenAlex

Endogenous sinapic acid (SA), sinapine (SP), sinapoyl glucose (SG) and canolol (CAN) of canola and mustard seeds are the potent antioxidants in various lipid-containing systems. The study investigated these phenolic antioxidants using different fractions of canola and mustard seeds. Phenolic compounds were extracted from whole seeds and their fractions: hulls and cotyledons, using 70% methanol by the ultrasonication method and quantified using HPLC-DAD. The major phenolics from both hulls and cotyledons extracts were SP, with small amounts of SG, and SA with a significant difference of phenolic contents between the two seed fractions. Cotyledons showed relatively high content of SP, SA, SG and total phenolics in comparison to hulls (p < 0.001). The concentration of SP in different fractions ranged from 1.15 ± 0.07 to 12.20 ± 1.16 mg/g and followed a decreasing trend- canola cotyledons > mustard cotyledons > mustard seeds > canola seeds > mustard hulls > canola hulls. UPLC-tandem Mass Spectrometry confirmed the presence of sinapates and its fragmentation in these extracts. Further, a high degree of correlation (r = 0.93) was noted between DPPH scavenging activity and total phenolic content.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.974

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.092
GPT teacher head0.301
Teacher spread0.209 · 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

Citations38
Published2014
Admission routes2
Has abstractyes

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