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Retention of Antioxidant Capacity of Vacuum Microwave Dried Cranberry

2010· article· en· W2003480176 on OpenAlexaff
Gwen J. Leusink, David D. Kitts, Parastoo Yaghmaee, T.D. Durance

Bibliographic record

VenueJournal of Food Science · 2010
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAntioxidant capacityMicrowaveChemistryFood scienceAntioxidantBiochemistryComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

In this study, cranberries were dried by vacuum-microwave drying (VMD), freeze-drying (FD), or hot air-drying (AD), to compare the effects of different drying processes on both physical changes as well as the retention of bioactive components in dried samples. Total porosity (%) and average pore radius of dehydrated cranberries were greater using VMD compared to FD and AD (P < 0.05). Crude methanol cranberry powdered extracts were fractionated by solid phase extraction (SPE) into organic acid-, total phenolics-, anthocyanin-, or proanthocyanidin-enriched extracts, respectively. The chemical composition of the 60% acidified methanol fractions contained cyanidin-3-galactoside, cyanidin-3-arabinoside, peonidin-3-galactoside, and peonidin-3-arabinoside, as assessed by HPLC. Antioxidant activities of cranberry fractions were measured using chemical ORAC and ABTS methods. The 60% acidified methanol fraction had a significantly higher (P < 0.05) antioxidant potential than the other chemical fractions, which was largely attributed to the relatively higher anthocyanin content. In general, vacuum-microwave drying and freeze-drying resulted in similar retention of anthocyanins and antioxidant activity, which were both relatively higher (P < 0.05) than that recovered from cranberries dried by hot air drying.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.027
GPT teacher head0.268
Teacher spread0.241 · 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

Citations81
Published2010
Admission routes1
Has abstractyes

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