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Record W2802288979 · doi:10.1094/asbcj-2015-0726-01

Dissolved Carbon Dioxide Selects for Lactic Acid Bacteria Able to Grow in and Spoil Packaged Beer

2015· article· en· W2802288979 on OpenAlexaff
Jordyn Bergsveinson, Anna Redekop, Sheree Zoerb, Barry Ziola

Bibliographic record

VenueJournal of the American Society of Brewing Chemists · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFermentation and Sensory Analysis
Canadian institutionsUniversity of SaskatchewanRoyal University Hospital
Fundersnot available
KeywordsFood spoilageBacteriaLactic acidFood scienceBrewingHop (telecommunications)BiologyCarbon dioxideFermentationBiotechnologyChemistryEcologyComputer scienceGenetics

Abstract

fetched live from OpenAlex

Lactic acid bacteria (LAB) are frequently found as beer-spoilage organisms (BSOs). Correctly identifying a LAB as a BSO is problematic, given that there are few known genetic markers that distinguish beer-spoiling from non-beer-spoiling LAB. Currently, genes purported to participate in hop-tolerance mechanisms are heavily relied upon to indicate LAB isolates with the potential to spoil beer, even though these genes do not consistently correlate with beer-spoilage. Though the presence of hops certainly is a significant physiological stress for bacteria in beer, we demonstrate here that the presence of CO2 dissolved in beer is a strong selective pressure for true LAB beer-spoilage ability (i.e., the ability to grow in and spoil a finished and packaged beer). We screened 20 LAB for their capability to survive and grow in gassed beer at 22 and at 30°C, and discuss the results in relation to ethanol and hop tolerance. Functional gene comparisons of nine dissolved CO2-tolerant and nontolerant genomesequenced isolates reveal potential metabolic pathways of interest for further study, specifically those that deal with cell dormancy and stress responses. These results further our understanding of LAB BSOs and have implications for how best to analyze these bacteria in laboratory settings and to test for these bacteria in the brewery.

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)0.001
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
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.253
Teacher spread0.226 · 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

Citations13
Published2015
Admission routes1
Has abstractyes

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Same venueJournal of the American Society of Brewing ChemistsSame topicFermentation and Sensory AnalysisFrench-language works237,207