Short communication: Limit feeding dairy heifers: Effect of feed bunk space and provision of a low-nutritive feedstuff
Bibliographic record
Abstract
The objectives of this study were to examine the behavioral effects of providing limit-fed dairy heifers an increased amount of feed bunk space compared with recommended feed bunk allowance, and to determine if the effects of provision of extra bunk space would be comparable to those seen when limit-fed heifers are provided a low-nutritive feedstuff. Twelve Holstein dairy heifers (381.1 ± 44.8 d of age, 417.3 ± 47.9 kg), divided into groups of 4, were exposed to each of 3 treatments using a 3 × 3 Latin square design with 7-d periods. The treatments were (1) 0.68 m of feed bunk space/heifer (TMR-0.68), (2) 0.34 m of feed bunk space/heifer (TMR-0.34), and (3) 0.34 m of feed bunk space/heifer with an additional 0.34 m of feed bunk space available for free-choice straw (TMR-S). The total mixed ration was fed once daily at a restricted level (1.83% of body weight) and contained (dry matter basis) 19.9% alfalfa/grass haylage, 20.1% corn silage, 49.6% high-moisture corn, and 10.4% protein supplement. Group dry matter intake (DMI) was recorded daily. Behavior at the feed bunk was recorded for the last 4 d of each treatment period. Due to the provision of straw, DMI was highest on the TMR-S treatment compared with the other treatments (9.4 vs. 7.8 kg/d). Heifers spent the most time feeding when on the TMR-S treatment (147.7 min/d), with no difference in feeding time between the limit-fed TMR treatments (64.5 min/d). Within the TMR-S treatment, feeding time on the straw was 76.9 min/d; thus, the rate of consumption of only the TMR was similar across all treatments. Unrewarded time at the feed bunk (when no feed was present) did not differ between treatments. Heifers did not differ in competitive behavior when on the limit-fed TMR treatments (13.1 displacements/heifer per day). However, while on the TMR-S treatment, heifers displaced each other more frequently (23.8 displacements/heifer per day) than while on the other 2 treatments. Overall, results suggest that neither increased feed bunk space nor provision of straw will reduce competition for, or slow consumption rates of, a limit-fed TMR. The provision of straw alongside a limit-fed TMR did increase DMI, which would contribute to further rumen fill, and allowed heifers to increase their time spent feeding throughout the day.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".