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Record W2790008772 · doi:10.3382/ps/pex457

Protein hydrolysate from turkey meat and optimization of its antioxidant potential by response surface methodology

2018· article· en· W2790008772 on OpenAlexaff
Daoying Wang, Fereidoon Shahidi

Bibliographic record

VenuePoultry Science · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsMemorial University of Newfoundland
FundersNatural Science Foundation of Jiangsu Province
KeywordsHydrolysateDPPHABTSAntioxidantChemistryFood scienceHydrolysisResponse surface methodologyEnzymatic hydrolysisIngredientBiochemistryChromatography

Abstract

fetched live from OpenAlex

The objective of this research was to optimize antioxidant potential of hydrolyzed protein using Flavourzyme assisted hydrolysis of turkey meat and compare the antioxidant activity of hydrolysates from turkey meat, chicken, and beef. Response surface methodology (RSM) was used to determine the optimal Flavourzyme hydrolysis conditions for preparation of hydrolysate from turkey meat, which were at a temperature of 50.09°C, pH of 5.42, and processing time of 1.08 hours. For comparison, antioxidant activities of the hydrolysate from turkey meat, chicken, and beef under the optimum conditions were determined using reducing power, 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radical cation, hydroxyl radical, and 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging activities. The antioxidant activity of turkey meat and chicken meat was significantly higher than that of beef (P < 0.05). Therefore Flavourzyme could be regarded as an effective hydrolytic enzyme for preparation of antioxidant hydrolysate from turkey meat, indicating the potential use of it as a functional food ingredient with shelf-life extension purposes.

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)0.001
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 score0.013
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.017
GPT teacher head0.276
Teacher spread0.258 · 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

Citations26
Published2018
Admission routes1
Has abstractyes

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