Effect of frequency of feed delivery on the behavior and productivity of lactating dairy cows
Bibliographic record
Abstract
The objective of this study was to determine the effect of feed delivery frequency on the behavioral patterns and productivity of lactating dairy cows. Twelve freestall-housed, lactating Holstein dairy cows, including 6 primiparous (PP) and 6 multiparous (MP), milked 3 ×/d (at 1400, 2200, and 0600 h), were exposed to each of 3 treatments (over 21-d periods) in a replicated Latin square design. Treatments included feed delivery frequency of (1) 1 ×/d (at 1400 h), (2) 2 ×/d (at 1400 and 2200 h), and (3) 3 ×/d (at 1400, 2200, and 0600 h). Milk production as well as feeding, lying, and rumination behaviors were electronically monitored for each animal for the last 7d of each treatment period. Milk samples were collected for the last 3d of each period for milk component analysis. Dry matter intake (DMI) varied with feed delivery frequency, with greatest DMI observed in cows fed 3 ×/d (27.8 kg/d) compared with those fed 2 ×/d (27.0 kg/d) or 1 ×/d (27.4 kg/d). Treatment had no effect on milk yield (41.3 kg/d) or efficiency of production (1.54 kg of milk/kg of DMI). Cows that did not receive delivery of feed following the 2200 h milking (treatment 1) and 0600 h milking (treatments 1 and 2) had lower DMI during the first hour after milking than those that received feed at all milkings (treatment 3). Total feeding time and meal frequency, size, and duration did not vary by treatment, but PP cows consumed smaller meals at a slower rate, resulting in lower DMI compared with MP cows. Primiparous cows consumed 50.1% and 26.1% less dry matter than MP cows during the first meal following the first and second milkings, respectively. Lying time did not vary by treatment, but PP cows spent more time lying (10.3 vs. 8.3h/d) than MP cows. Under 3 ×/d milking schedules, greater feed delivery frequency resulted in greater DMI as a function of increased DMI following the return from milking and the delivery of feed.
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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".