Udder health in Canadian dairy heifers during early lactation
Bibliographic record
Abstract
Mastitis is the most prevalent and costly disease in dairy cattle worldwide, with implications for animal health and welfare as well as production and economics. Nonlactating heifers are an often-neglected group of animals concerning mastitis management, as they are assumed to be free of mastitis. An observational field study was conducted between 2007 and 2008 on 91 dairy herds across Canada, representative of provincial averages of bulk milk somatic cell count (BMSCC) and barn type. The aims of that study were to (1) estimate in early-lactating heifers overall and pathogen-specific incidence rate of clinical mastitis (IRCM), prevalence of intramammary infection (IMI), and prevalence of subclinical mastitis (SCM; defined as SCC ≥200,000 cells/mL); (2) compare these udder health parameters between heifers and multiparous cows; and (3) determine regional patterns and variations in these udder health parameters across BMSCC categories. During the first day of lactation, IRCM was higher in heifers than in multiparous cows (99 vs. 48 cases per 10,000 quarter-days at risk, respectively). Clinical mastitis affected 4% of heifers (0.73 cases per 100 quarters) in the first 30 d after calving, with the most common pathogens isolated being Staphylococcus aureus and Escherichia coli, whereas S. aureus and non-aureus staphylococci were the most commonly isolated pathogens in multiparous cows. The IRCM in heifers was highest in Ontario heifers, but overall IRCM did not vary by BMSCC category and it was only higher in multiparous cows than heifers in high-BMSCC Ontario herds. Intramammary infections were present in 33% of heifer quarters, with non-aureus staphylococci the most commonly isolated group of bacteria in both heifers (26% of quarters) and multiparous cows (18% of quarters). Pathogen-specific prevalence of IMI did not differ between heifers and multiparous cows, but we noted regional differences and differences across BMSCC categories in pathogen-specific prevalence of IMI. Prevalence of SCM in heifers was 13.6% and was lowest in Alberta herds. In all regions, SCM prevalence was higher in multiparous cows than in heifers. In conclusion, udder health of Canadian dairy heifers was similar to that of other countries, demonstrating the importance of the issue. Differences between heifers and multiparous cows early in lactation highlighted the need for management practices to target the precalving period in heifers, when exposure to risk factors differs from that in lactating cows.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".