Hay intake improves performance and rumen development of calves fed higher quantities of milk
Bibliographic record
Abstract
Research to date has suggested that access to forage before weaning can limit rumen development in calves, but no research has yet addressed the role of forage for calves fed higher quantities of milk. This study compared performance and rumen development of calves provided high volumes (equivalent to approximately 20% of calf birth weight) of milk with and without access to hay. At d 3 of age, individually housed calves were randomly assigned to treatment (either ad libitum access to chopped grass hay or no forage; n=15 calves per treatment, 10 heifers, and 5 bulls). All calves were provided ad libitum access to water and starter throughout the study. All calves were offered 8L of milk/d from a nipple bottle from d 3 to 35, 4 L/d from d 36 to 53, and 2L/d until weaning at d 56. Solid feed intake and growth parameters were monitored from d 3 to 70. At d 70, males from both treatments were slaughtered to measure rumen development parameters. Overall dry matter (DM) intake from solid feed did not differ between treatments before wk 5. However, during wk 6 to 10, calves fed forage consumed more total DM (starter plus hay) than did calves fed no forage. Hip and wither height, heart girth, and body barrel at d 3, 56, and 70 did not differ between treatments. Reticulorumen weight was heavier in calves fed hay versus those fed only starter (12.77±1.29 vs. 7.99±0.69 kg with digesta; 1.89±0.05 vs.1.60±0.09 kg without digesta). Body weight without digesta was similar in calves fed forage or no forage. Mean rumen pH was higher in calves fed hay compared with those fed no forage (5.49±0.08 vs. 5.06±0.04). In conclusion, provision of chopped hay to calves fed high volumes of milk can promote solid feed DM intake and rumen development without affecting BW gain.
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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".