Impact of timing of feed delivery on the behavior and productivity of dairy cows
Bibliographic record
Abstract
The objective of this work was to assess the effect of timing of feed delivery on the behavior and productivity of cows milked 3 times per day. Twelve lactating Holstein dairy cows (4 primiparous and 8 multiparous), milked 3 times per day (at 1400, 2100, and 0700 h), were individually assigned and exposed to each of 2 treatments (over 21-d periods) in a replicated crossover design. Treatments were the manipulation of timing of TMR delivery, 2 times per day, in relation to milking time: (1) feeding at milking time (at 1400 and 0700 h), and (2) feeding halfway between milking times (at 1730 and 1030 h). Milk production, feeding, sorting, and rumination behavior were monitored for each animal for the last 7 d of each treatment period. Milk samples were collected for 2 of the last 4 d of each period for milk component analysis. With a feed delivery delay, dry matter intake (DMI) tended to be lower (26.5 vs. 27.2 kg/d). Although no difference was found in feeding time (224.2 min/d), cows fed with a delay consumed their feed more slowly (0.12 vs. 0.13 kg of dry matter/min) in more frequent meals (10.0 vs. 9.1 meals/d), which were smaller in size (2.8 vs. 3.1 kg/meal) and tended to be shorter in duration (26.7 vs. 30.1 min/meal). Cows fed at milking sorted for long particles (102.3%), whereas cows fed with a delay did not sort for or against those particles. Cows sorted for medium particles to a similar extent (102.5%) on each treatment. Cows did not sort for or against short particles on either treatment. Sorting against fine particles was observed, to a similar extent (97.1%), on both treatments. Rumination time (8.9 h/d) and lying time (9.5 h/d) were similar between treatments. Cows without fresh feed at the 1400 h milking tended to stand for less time following that milking (71.0 vs. 94.0 min), whereas cows without fresh feed at the 0700 h milking stood for less time following that milking (66.3 vs. 87.8 min). No difference in this latency to lie down was seen at the 2100 h milking. Milk yield (48.0 kg/d), milk fat content (3.64%), and milk protein content (2.86%) were similar between treatments. Given the tendency for a difference in DMI and no change in yield, efficiency of production was improved with a feed delay (1.93 vs. 1.80 kg of milk/kg of DMI). These data suggest that moving the timing of feed delivery resulted in cows consuming their feed more slowly in smaller, more frequent meals, contributing to an improvement in efficiency of production.
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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".