Incidence of metabolic disorders and reproductive performance following a short (35-d) or conventional (60-d) dry period management in commercial Holstein herds
Bibliographic record
Abstract
A total of 850 Holstein cows from 13 commercial dairy herds were involved in the present study to compare the effects of 2 different dry period (DP) management strategies on health and reproductive parameters. Cows were assigned to either a short (SDP; 35-d) or a conventional (CDP; 60-d) DP management within each herd, based on previous 305-d milk yield, parity (414 primiparous and 436 multiparous), and estimated calving interval. Cows assigned to CDP were fed a dry cow ration from dry-off until 21 d prepartum, and were then switched to a precalving ration. Cows assigned to SDP were fed the precalving ration throughout their DP. Rations were specific to each herd. A significant treatment × parity interaction was found for culling rate. Dry period management did not affect culling rate for second-lactation cows but a significantly higher culling rate occurred in multiparous CDP cows compared with SDP (42.6 vs. 31.6% ± 3.7 for CDP and SDP, respectively). Management used in the DP did not affect incidence of severe ketosis, displaced abomasum, milk fever, and mastitis, although incidence of these metabolic disorders were lower in second-lactation than third- or greater-lactation cows. The incidence of mild ketosis (evaluated by milk ketone concentration) was lower following SDP, probably as a result of better energy balance. On the other hand, the incidence of retained placenta was higher in multiparous cows assigned to SDP, but the reason for this increase remains unclear. Nevertheless, this did not lead to increased incidence of metritis. Moreover, DP management did not influence reproductive measures, including days in milk at first breeding, number of breedings per conception, as well as conception rates at first and second services. Regarding days open, overall, all 13 herds were not significantly affected by treatment, but 1 herd clearly showed opposite results to the 12 others. Our results indicate that a short DP management strategy could facilitate transition from one lactation to the next by decreasing the incidence of mild ketosis, with no major negative effects on other health parameters and reproduction. The variation in results observed among herds suggests that other management practices influence the response observed following a short or conventional DP, emphasizing the need for other field studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".