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Record W4393098483 · doi:10.1016/j.psj.2024.103687

Role of marination, natural antimicrobial compounds, and packaging on microbiota during storage of chicken tawook

2024· article· en· W4393098483 on OpenAlexaff
Tareq M. Osaili, Anas A. Al‐Nabulsi, Fayeza Hasan, Dinesh Kumar Dhanasekaran, Leila Cheikh Ismail, Farah Naja, Hadia Radwan, Amin N. Olaimat, Mutamed Ayyash, Arisha Ali, Reyad S. Obaid, Richard A. Holley

Bibliographic record

VenuePoultry Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Quality and Safety Studies
Canadian institutionsUniversity of Manitoba
FundersUniversity of Sharjah
KeywordsMarinationAntimicrobialFood scienceChemistryMicrobiologyBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the antimicrobial effect of marination, natural antimicrobials, and packaging on the microbial population of chicken tawook during storage at 4°C. Chicken meat was cut into 10 g cubes and marinated. The chicken was then mixed individually with 0.5% or 1% (w/v) vanillin (VA), β-resorcylic acid (BR), or eugenol (EU), and stored under aerobic (AP) or vacuum (VP) packing at 4°C for 7 d. The marinade decreased microbial growth as monitored by total plate count, yeast and mold, lactic acid bacteria, and Pseudomonas spp. by about 1 log cfu/g under AP. The combination of marinade and antimicrobials under AP and VP decreased growth of spoilage-causing microorganisms by 1.5 to 4.8 and 2.3 to 4.6 log cfu/g, respectively. Change in pH in VP meat was less than 0.5 in all treated samples including the control. Marination decreased the lightness of the meat (L*) and significantly (p < 0.05) increased the redness (A*) and yellowness (B*). Overall acceptability was highest for marinated samples with 0.5% BR.

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 score0.860
Threshold uncertainty score0.190

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.007
GPT teacher head0.213
Teacher spread0.206 · 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

Citations4
Published2024
Admission routes1
Has abstractyes

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