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Record W1941361595 · doi:10.1111/1750-3841.12065

Antimicrobial Effects of Allyl Isothiocyanate and Modified Atmosphere on <i>Pseduomonas Aeruginosa</i> in Fresh Catfish Fillet under Abuse Temperatures

2013· article· en· W1941361595 on OpenAlexfundno aff
Yu‐Hsin Pang, Shiowshuh Sheen, Siyuan Zhou, LinShu Liu, Kit L. Yam

Bibliographic record

VenueJournal of Food Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEssential Oils and Antimicrobial Activity
Canadian institutionsnot available
FundersMcMaster UniversityU.S. Department of Agriculture
KeywordsCatfishFillet (mechanics)Allyl isothiocyanateShelf lifeModified atmosphereAntimicrobialFood scienceBacterial growthChemistryBiologyFisheryMaterials scienceBacteriaFish <Actinopterygii>BiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The effects of allyl isothiocyanate (AIT; 18 and 36 μg/L) in vapor phase, modified atmosphere (MA; 49% CO2 , 0.5% O2 , and 50.5% N2 ), and their combinations on the growth behavior of Pseduomonas aeruginosa in fresh catfish fillet at different abuse temperatures (8, 15, and 20 °C) were evaluated in this study. Lag phase, maximum growth rate, and shelf life were used as parameters to analyze the antimicrobial effects. Both gaseous AIT and MA alone inhibited the growth potential of P. aeruginosa effectively, prolonging the shelf life by 1.5 to 3.4 times compared to the control at abuse temperatures between 8 and 20 °C. The synergistic effect was observed at 8 °C, extending the shelf life of fresh catfish by more than 6.5 times (≥ 550 h). In addition, the maximum growth rate decreased with decreasing storage temperature, but it was not significantly influenced by the addition of AIT or MA. Hence, the combination of AIT and MA may be used as an effective antimicrobial system to reduce the microbial risks due to temperature abuse and to improve the shelf life of fresh catfish fillet. The proper combination of AIT and MA may be further optimized for industrial applications.

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 score0.127
Threshold uncertainty score0.255

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 communication0.0000.001
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 head0.195
Teacher spread0.188 · 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

Citations23
Published2013
Admission routes1
Has abstractyes

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