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Record W2124818288 · doi:10.3168/jds.2012-6408

Genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins

2013· article· en· W2124818288 on OpenAlexafffundabout
A. Koeck, F. Miglior, J. Jamrozik, D.F. Kelton, Flávio S. Schenkel

Bibliographic record

VenueJournal of Dairy Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsKetosisAbomasumLactationIce calvingAnimal scienceHerdBiologyDairy cattleEndocrinologyRumenFood scienceGeneticsPregnancyDiabetes mellitus

Abstract

fetched live from OpenAlex

The aim of this study was to investigate the genetic associations of ketosis and displaced abomasum with milk production traits in early first lactation of Canadian Holsteins. Health data recorded by producers were available from the national dairy cattle health system in Canada. Test-day records of milk, fat, and protein yields were obtained from the routine milk recoding scheme. Ketosis and displaced abomasum were defined as binary traits (0 = healthy; 1 = sick) based on whether or not the cow had at least 1 case of the respective disease in the period from calving to 100 d after calving. Mean frequencies of ketosis and displaced abomasum were 4.1 and 2.7%, respectively. The following milk production traits were considered: milk yield, fat percentage (Fat%), protein percentage (Prot%), fat-to-protein (F:P) ratio, and F:P ratio >1.5. The trait F:P ratio >1.5 was scored as 1 or 0, based on whether or not the cow had an F:P ratio >1.5. For milk production traits, the first (5-30 d in milk) and the second (31-60 d in milk) test days were considered. Data were analyzed using bivariate linear animal models. Average heritabilities of 0.02 and 0.04 were obtained for ketosis and displaced abomasum, respectively. For milk production traits, the lowest heritabilities were obtained for F:P >1.5 (0.04 to 0.08), whereas the highest estimates were found for Prot% (0.27 to 0.38). Ketosis and displaced abomasum were genetically uncorrelated with milk yield in early lactation. Moderate favorable correlations were found between metabolic diseases and milk composition traits. Ketosis was significantly correlated with Fat% (0.33), F:P ratio (0.30), and F:P ratio >1.5 (0.35) at the first test day, whereas all genetic correlations with milk composition traits at the second test day were not significant and close to zero. Significant favorable genetic correlations were also found between displaced abomasum and F:P ratio (0.26), F:P ratio >1.5 (0.25) and Prot% (-0.19) at the first test day. Also, Prot% at the second test day was significantly correlated (-0.16) with displaced abomasum. Overall, a higher Fat% and F:P ratio and a lower Prot% at the first test day were associated with an increased susceptibility to metabolic diseases. As genetic correlations between metabolic diseases and F:P ratio were far from unity, dairy producers should be encouraged to keep accurate and complete health data. This will be expected to yield to more accurate genetic evaluations for metabolic diseases.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.214
Teacher spread0.196 · 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

Citations59
Published2013
Admission routes3
Has abstractyes

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