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Record W2090771391 · doi:10.1007/s11746-000-0151-0

Antioxidant activity of crude tannins of canola and rapeseed hulls

2000· article· en· W2090771391 on OpenAlexaff
Ryszard Amarowicz, M. Naczk, Fereidoon Shahidi

Bibliographic record

VenueJournal of the American Oil Chemists Society · 2000
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsMemorial University of NewfoundlandSt. Francis Xavier University
Fundersnot available
KeywordsCanolaRapeseedTanninChemistryDPPHFood scienceAntioxidantBotanyOrganic chemistryBiology

Abstract

fetched live from OpenAlex

Abstract The antioxidant activity of crude tannins of canola and rapeseed hulls was evaluated by β‐carotene‐linoleate, α,α‐diphenyl‐β‐picrylhydrazyl (DPPH) radical, and reducing power assays. Crude tannins were extracted from three samples of Cyclone canola (high‐tannin) hulls and Kolner, Ligaret, and Leo Polish rapeseed (low‐tannin) hulls with 70% (vol/vol) acetone. The total phenolic content in crude tannin extracts ranged between 128 and 296 mg of sinapic acid equivalents per 1 g of extract. The ultraviolet spectra of methanolic solution of canola extracts showed two absorption maxima (282 and 309 nm), whereas those of rapeseed extracts exhibited a single maximum (326 nm). Crude tannins isolated from canola hulls exerted significantly (P<0.025) greater antioxidant activity than those from rapeseed in all three assays. The scavenging effect of all crude tannins, at a dose of 1 mg, on the DPPH radical ranged from 35.2 to 50.5%. The reducing power of Cyclone canola hull extracts on potassium ferricyanide was significantly (P≤0.0025) greater than that of rapeseed hull extracts, and the observed data correlated well (r=0.966; P=0.002) with the total content of phenolics present.

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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.251
Teacher spread0.244 · 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

Citations193
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Oil Chemists SocietySame topicPhytochemicals and Antioxidant ActivitiesFrench-language works237,207