Invited review: Effect of udder health management practices on herd somatic cell count
Bibliographic record
Abstract
A systematic review of the scientific literature on relationships between management practices used on dairy farms and herd somatic cell count (SCC) was undertaken to distinguish those management practices that have been consistently shown to be associated with herd SCC from those lacking evidence of association. Relevant literature was identified using a combination of database searches (PubMed, Medline, CAB, Agricola, and Web of Science) and iterative screening of references. To be included in the review, a manuscript had to be published after 1979 in French, English, or Dutch; study design had to be other than case report or case series; herds studied had to be composed of ≥ 40 milking cows producing on average ≥ 7,000kg of milk in 305 d; interventions studied had to be management practices applied at the herd level and used as udder health control strategies; and SCC had to be measured using electronic cell counting methods. The 36 manuscripts selected were mainly observational cross-sectional studies; 8 manuscripts dealt exclusively with automatic milking systems and 4 with management of calves and heifers and its effect on SCC in early lactation heifers. Most practices having consistent associations with SCC were related to milking procedures: wearing gloves during milking, using automatic take-offs, using postmilking teat dipping, milking problem cows last, yearly inspection of the milking system, and use of a technique to keep cows standing following milking; all were consistently associated with lower herd SCC. Other practices associated with lower SCC were the use of a freestall system, sand bedding, cleaning the calving pen after each calving, surveillance of dry-cow udders for mastitis, use of blanket dry-cow therapy, parenteral selenium supplementation, udder hair management, and frequent use of the California Mastitis Test. Regarding SCC of heifers, most of the consistent associations reported were related to interventions made during the peripartum period. Studies on automatic milking systems have frequently reported elevation of the herd SCC following transition to the new system. These elevations seemed to be mediated both by the lack of monitoring of chronically infected cows and by an elevated incidence of intramammary infections. By assembling the results reported in many different studies, this review generates a more comprehensive understanding of the management practices influencing SCC and highlights areas of SCC control knowledge that lack evidence of effectiveness.
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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 | 0.008 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.006 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".