Time of Feed Delivery Affects the Feeding and Lying Patterns of Dairy Cows
Bibliographic record
Abstract
The objective of this experiment was to determine whether it is the return from milking or delivery of fresh feed that has the greater effect on the daily patterns of feeding and lying behavior of dairy cattle. Forty-eight lactating Holstein cows were subjected to each of 2 treatments in a 2 x 2 cross-over design replicated over time. The treatments were 1) milking and feed delivery times coinciding and 2) feed delivery 6 h after milking. Cows were milked twice daily at 0500 and 1700 h. An electronic monitoring system was used to measure the time spent at the feed alley. Time-lapse video was used to quantify the lying time and incidence of aggressive displacements of the cows at the feed alley. Cows increased their total daily feeding time by 12.5% when fed 6 h after milking. This change was driven by an 82% increase in feeding time during the first hour immediately following the delivery of fresh feed and a 26% decrease in feeding time during the first hour after milking. The delivery of feed 6 h after milking did not change the daily lying time of the cows, but did decrease the latency to lie down after milking by 20 min. The reduction in feeding time after milking and decreased latency to lie down resulted in a tendency for less aggressive interactions at the feed alley after the cows returned from milking. These results indicate that the delivery of fresh feed has a greater impact on stimulating feeding behavior than does the return from milking and that changes in feeding management can affect both the feeding and lying behavior of dairy 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 | 0.000 | 0.000 |
| 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".