Milking dynamics following individual quarter dry-off in Holstein cows in an automatic milking system
Bibliographic record
Abstract
Individual quarter dry-off (QDO) is a targeted management strategy used to address persistent intramammary infections that lead to chronic subclinical mastitis, as well as cases of clinical mastitis that are recurrent or unresponsive to treatment.Although the interest in the use of individual QDO as a non-antimicrobial strategy for mastitis control is growing, the impact of this management on subsequent milk production has not been widely explored.Moreover, detailed information on the individual performance of the remaining functional quarters, following QDO is scarce.The objective of this observational study was to investigate the effect of lactational QDO following clinical mastitis on short-term milk yield in the remaining individual quarters.This retrospective study was conducted in a commercial dairy farm located in northeast Colorado, USA, equipped with an automatic milking system.The analysis included 114 multiparous cows with one quarter dried off through abrupt cessation of milking following unresponsive clinical mastitis therapy.For comparison, one healthy control cow was matched to each affected cow based on DIM and parity number.Individual quarter milk yield of the remaining functional quarters and from control cows was collected for each milking visit from the on-farm management software and summed as a daily value per quarter for the 30 d following QDO.The herd average DIM at the peak of lactation (68 DIM) was considered to categorize the study cows based on their DIM at QDO into pre-peak and post-peak groups.All the analyses were conducted separately for these 2 stage of lactation groups and cows were also categorized based on their dry quarter location (DQL).Least squares means (SE) for daily average milk yield per functional quarter and per cow up to 30 d post QDO were calculated and compared among DQL groups (including matched control cows) using ANOVA for repeated measures analysis, with cow ID as the repeated statement, with compound symmetry selected as the covariance structure.Multivariable models included DQL as explanatory variable of interest and DIM at QDO and calving season as potential covariates.In addition, milk yield curves up to 30 d post QDO were built for milk yield per DQL using daily LSM calculated by repeated measures analysis.Cow-level milk yield was also compared between DQL groups, including unaffected control cows using t-test for repeated measures analysis.Differences in quarter milk yield were only identified for the pre-peak group (68 DIM).Milk yield from the left rear and right rear quarters was smaller in control cows than in cows with the right front quarter dried off.When total milk yield per cow was compared within the pre-peak group, control cows had greater yield than cows subjected to QDO of the right rear quarter.In the post-peak group, control cows had the highest milk yield compared with the 4 groups of cows with a dry quarter.In conclusion, following QDO, the levels of milk yield compensation in the remaining functional quarters were variable and smaller when QDO occurred post peak (>68 DIM).Nonetheless, in most cases the cow-level milk yield remained lower in 3-quarter cows compared with unaffected controls.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".