MétaCan
Menu
Back to cohort
Record W2991018403 · doi:10.1017/s1751731119002787

Bacterial concentrations in bedding and their association with dairy cow hygiene and milk quality

2019· article· en· W2991018403 on OpenAlexaffabout
I. Robles, D.F. Kelton, Herman W. Barkema, Greg Keefe, Jean‐Philippe Roy, M.A.G. von Keyserlingk, T.J. DeVries

Bibliographic record

Venueanimal · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsCegep de Saint HyacintheUniversity of British ColumbiaUniversity of Prince Edward IslandUniversity of CalgaryUniversity of Guelph
Fundersnot available
KeywordsBeddingUdderStrawAnimal scienceManureVeterinary medicineMastitisEnvironmental scienceBiologyAgronomyMedicineMicrobiologyBotany

Abstract

fetched live from OpenAlex

Comparison of bacterial counts (BCs) among common bedding types used for dairy cows, including straw, is needed. There is concern that the microbial content of organic bedding is elevated and presents risks for dairy cow udder health and milk quality. The objectives of this study were to investigate: (1) % DM and BCs (Streptococcus spp., all gram-negatives and specifically Klebsiella spp.) in different types of bedding sampled, and to investigate housing and farm management factors associated with % DM and BCs; (2) if bedding type was associated with hygiene of cow body parts (lower-legs, udder, upper-legs and flank) and housing and management factors associated with hygiene and (3) bedding types associated with higher BCs in cow milk at the farm level and bulk tank milk and management factors that were associated with highest BCs. Seventy farms (44 free-stall and 26 tie-stall) in Ontario, Canada were visited 3 times, 7 days apart from October 2014 to February 2015. At each visit, composite samples of unused and used bedding were collected for % DM determination and bacterial culture. Used bedding samples were collected from the back third of selected stalls. Data were analyzed using multivariable linear mixed models. Bedding classification for each farm were: new sand (n = 12), straw and other dry forage (n = 33), wood products (shavings, sawdust; n = 17) and recycled manure solids (RMSs)-compost, digestate (n = 8). In used bedding, across all bedding samples, sand was driest, compared to straw and wood, and RMS; higher % DM was associated with lower Streptococcus spp. count. Streptococcus spp. and all Gram-negative bacteria counts increased with increasing days since additional bedding was added. Gram-negative bacteria counts in used bedding varied with type: RMS = 16.3 ln colony-forming units (cfu)/mL, straw = 13.8 ln cfu/mL, new sand = 13.5 ln cfu/mL, and wood = 10.3 ln cfu/mL. Klebsiella spp. counts in used bedding were lower for wood products (5.9 ln cfu/mL) compared to all other bedding types. Mean cow SCC tended to be higher on farms with narrower stalls. Farms with mattress-based stalls had a higher prevalence of cows with dirty udders compared to those using a deep bedding system (often inorganic sand). Wider stalls were associated with lower bulk milk bacteria count. Lower % DM of used bedding was associated with higher bulk milk bacteria count. In conclusion, bedding management may have a profound impact on milk quality, bacterial concentrations in the bedding substrates, and cow hygiene.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.343
Threshold uncertainty score0.247

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 head0.020
GPT teacher head0.236
Teacher spread0.216 · 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 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

Citations60
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueanimalSame topicMilk Quality and Mastitis in Dairy CowsFrench-language works237,207