Competition for feed affects the feeding behavior of growing dairy heifers
Bibliographic record
Abstract
The objective of this study was to determine how competition for feed influences the feeding behavior of young, growing dairy heifers. Thirty-six prepubertal Holstein heifers (231.5 +/- 12.1 d old, weighing 234.7 +/- 24.0 kg), consuming a total mixed ration ad libitum, were assigned to 1 of 2 treatments: noncompetitive (1 heifer/feed bin), or competitive (2 heifers/feed bin). After 7 d of treatment adaptation, dry matter intake and feeding behavior were monitored for 7 d for each animal. Fresh feed and orts were sampled on the last 3 d of the treatment period from each bin and were subjected to particle size analysis. The particle size separator consisted of 3 screens (18, 9, and 1.18 mm) and a bottom pan resulting in 4 fractions (long, medium, short, and fine). Sorting activity for each fraction was calculated as the actual intake expressed as a percentage of the predicted intake. There was no difference in sorting behavior or dry matter intake between the treatments. Overall, the heifers sorted against long particles (94%), and sorted for medium (102%) and short (103%) particles. The competitively fed heifers tended to have 10% shorter feeding times, particularly at peak feeding periods. The competitively fed heifers also consumed 9% fewer meals per day, although the duration of these meals were 10% longer, and tended to be 13% larger. Competition for feed also tended to increase the day-to-day variation in feeding time, meal duration, and meal size. It can be concluded that competition for feed for growing dairy heifers alters feeding patterns, reduces access to feed, particularly during periods of peak feeding activity, and tends to increase day-to-day variation in feeding behavior.
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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 | 0.000 |
| 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".