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Record W2014938883 · doi:10.1021/jf900489d

Antioxidant Activity of Hazelnut Skin Phenolics

2009· article· en· W2014938883 on OpenAlexaff
Cesarettin Alasalvar, Magdalena Karamać, Agnieszka Kosińska, Anna Rybarczyk, Fereidoon Shahidi, Ryszard Amarowicz

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2009
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsChemistryAcetoneDPPHTanninAntioxidantProanthocyanidinChromatographySolventMethanolExtraction (chemistry)AbsorbanceCondensed tanninSephadexPhenolsPolyphenolFood scienceOrganic chemistry

Abstract

fetched live from OpenAlex

Phenolic compounds were extracted from hazelnut skin using 80% (v/v) aqueous acetone or methanol. The crude extracts were applied onto a Sephadex LH-20 column for two fractionations (Fr. I and Fr. II). Fr. I consisting of low-molecular-weight phenolics was eluted by ethanol, whereas Fr. II consisting of tannins was obtained using acetone/water (1:1, v/v) as the mobile phase. UV spectra of phenolic compounds present in the crude extracts and their fractions exhibited a maximum absorbance at 282 nm. The crude extracts and their fractions were examined for phenolic and condensed tannin contents as well as total antioxidant activity (TAA), antiradical activity against the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical, and reducing power. Results of these assays showed higher values when Fr. II containing tannins was tested, followed by crude extract, and Fr. I. Both 80% acetone and methanol were capable of extracting phenolics, but 80% acetone was a more effective solvent for the extraction of condensed tannins (p < 0.05). These results suggest that hazelnut skin can be considered as a value-added byproduct for use as dietary antioxidants.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.210
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

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 head0.009
GPT teacher head0.223
Teacher spread0.214 · 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

Citations158
Published2009
Admission routes1
Has abstractyes

Explore more

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