0073 Association between rumination behavior, milk yield, and milk composition in dairy cows kept on commercial farms
Bibliographic record
Abstract
Automatic sensors are able to give an accurate indication of the duration of time that dairy cows spend ruminating, allowing for collection of rumination data on cows kept in commercial environments. The objective of this study was to associate rumination behavior with milk yield and milk composition for lactating dairy cows kept in commercial operations. In this study, 8 commercial dairy farms in Eastern Ontario, Canada, were recruited for participation. Selection criteria included: free-stall housing, parlor milking, >90 lactating cows in the herd, primarily have Holstein-Friesian genetics, participated in a DHI program, and fed a TMR. Chosen farms had a mean herd size of 187 cows (range: 95 to 419 cows), mean adjusted 305-d milk yield of 11,228 kg (range: 9787 to 13,006 kg), and a geometric mean annual bulk milk SCC of 162,000 cells/mL (range: 145,000 to 172,000 cells/mL). Rumination time for 30 cows/herd was monitored using an automated rumination monitoring system. In total, the rumination activity of 240 lactating Holstein cows (57 ± 29 DIM) was monitored for 6 d and associated, in a multivariable general linear mixed model, with their production data (as measured by the closest in time DHI test, on average ± 3.5 d from the day of rumination sensor placement), controlling for farm, parity, DIM, body condition score, and dietary (TMR) characteristics (nutrient content and particle size). Across cows, rumination time averaged 506 ± 85 min/d (mean ± SD), milk yield averaged 44.7 ± 10.2 kg/d, milk fat averaged 3.69 ± 0.54%, and milk protein averaged 2.97 ± 0.24%. Rumination time increased with cow parity (P < 0.001) and tended (P = 0.09) to be positively associated with the percentage of long particles (>19 mm) in the TMR fed to the cows (+10.0 ± 5.5 min/d rumination time per 5% increase in long particles). Milk yield increased with cow parity (P < 0.001), milking 3 vs. 2 (+4.5 ± 2.3 kg/d; P = 0.05), and was positively associated with rumination time (+0.2 ± 0.07 kg milk per 10 min increase in rumination time per d; P = 0.01). Rumination activity was not associated with milk fat content, and tended (P = 0.08) to be quadratically associated with milk protein content. In summary, the results of this study demonstrate that rumination time, as measured on lactating cows on commercial dairy farms, could indicative of milk yield; however, it showed less consistent association with milk components.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".