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Record W4402015551 · doi:10.3389/fmicb.2024.1404795

Tracking the microbial communities from the farm to the processing facility of a washed-rind cheese operation

2024· article· en· W4402015551 on OpenAlexafffund
Tara Wilson, Myra Siddiqi, Yueqi Xi, Gisèle LaPointe

Bibliographic record

VenueFrontiers in Microbiology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProbiotics and Fermented Foods
Canadian institutionsUniversity of Guelph
FundersDairy Farmers of Ontario
KeywordsBiologyMilkingFood science16S ribosomal RNALactoseContaminationBacteriaMicrobiologySerial dilutionLeuconostocAmpliconLactobacillusPolymerase chain reactionAnimal scienceEcologyGene

Abstract

fetched live from OpenAlex

Milk residue and the accompanying biofilm accumulation in milking systems can compromise the microbial quality of milk and the downstream processes of cheese production. Over a six-month study, the microbial ecosystems of milk (n = 24), tap water (n = 24) and environmental swabs (n = 384) were cultured by plating decimal dilutions to obtain viable counts of total aerobic mesophilic lactose-utilizing bacteria (lactose-M17), lactic acid bacteria (MRS), yeasts and molds (Yeast, Glucose, Chloramphenicol (YGC) medium). Viable aerobic lactose-M17 plate counts of milk remained well below 4.7 log CFU/ml over five of the months, except for 1 week in November where milk at the facility exceeded 5 log CFU/ml. Swab samples of the farm milking equipment showed consistent viable counts after sanitation, while the bulk tank swabs contained the lowest counts. Viable counts from swabs of the facility were generally below the detection limit in the majority of samples with occasional residual contamination on some food contact surfaces. Extracted DNA was amplified using primers targeting the V3–V4 region of the 16S rRNA gene, and the amplicons were sequenced by MiSeq to determine the shared microbiota between the farm and the processing facility (8 genera). Culture independent analysis of bacterial taxa in milk, water and residual contamination after sanitation with swab samples revealed the shared and distinct microbiota between the sample types of both facilities. Amplicon sequence variants (ASVs) of the V3–V4 region of the 16S rRNA gene revealed that the microbiota of milk samples had lower diversity than water or environmental swabs (279 ASVs compared to 3,444 in water and 8,747 in environmental swabs). Brevibacterium and Yaniella (both Actinomycetota) were observed in all sampling types. Further studies will include whole genome sequencing of Brevibacterium spp. isolates to determine their functionality and diversity within the system.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.223
Teacher spread0.204 · 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 designObservational
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

Citations7
Published2024
Admission routes2
Has abstractyes

Explore more

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