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Gaseous ozone treatment inactivates Listeria innocua in vitro

2007· article· en· W1545952088 on OpenAlexaff
Lihua Fan, Jun Song, K. B. McRae, Brad Walker, Deana V. Sharpe

Bibliographic record

VenueJournal of Applied Microbiology · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicListeria monocytogenes in Food Safety
Canadian institutionsMount Saint Vincent UniversityAgriculture and Agri-Food Canada
Fundersnot available
KeywordsOzoneListeriaAgarChemistryFood scienceInoculationIncubationListeria monocytogenesLog reductionBacteriaBiologyHorticultureBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

AIMS: To investigate the effects of ozone on inactivation of Listeria innocua on solid media. METHODS AND RESULTS: Suspensions of L. innocua ranging from 4.5 x 10(4 )- 6.4 x 10(4) CFU ml(-1) were inoculated onto potato dextrose agar (PDA, pH 5.6 and 6.8) and nutrient agar (NA, pH 6.0 and 6.8), then exposed to gaseous ozone. Variable factors included postinoculation standing time at 20 degrees C before exposure to ozone, ozone concentration, treatment duration and treatment temperature (5 or 20 degrees C). The interaction among ozone concentration, treatment duration, media and temperature in effecting changes in colony-forming units (CFU) was significant. The 100 nl l(-1) ozone treatment for 2 h reduced the microbial populations by 2-3 log CFU ml(-1). Cell viability decreased more rapidly on PDA than on NA. The average time to obtain a 2 log CFU ml(-1) reduction was 1.3 h at 20 degrees C and 2.5 h at 5 degrees C (P < 0.001). CONCLUSIONS: Gaseous ozone effectively inactivates L. innocua at concentrations of 50 and 100 nl l(-1) during short exposure times at both 5 and 20 degrees C. The Gompretz model can be utilized for determining the response of L. innocua to ozone over time. SIGNIFICANCE AND IMPACT OF THE STUDY: This study provides useful information on ozone inactivating Listeria spp., which may be imposed on ensuring quality and safety of horticultural produce and food products.

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 score0.068
Threshold uncertainty score0.716

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 head0.027
GPT teacher head0.292
Teacher spread0.266 · 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

Citations36
Published2007
Admission routes1
Has abstractyes

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