Effect of feed type and method of presentation on feeding behavior, intake, and growth of dairy calves fed a high level of milk
Bibliographic record
Abstract
The objective of this study was to assess the effect of different feed types and method of feed presentation in the first 12 wk of life on the feeding behavior, intake, and growth of calves fed a high milk level. Forty-eight neonatal Holstein calves were individually housed and randomly assigned to 1 of 4 treatments and fed solid feed ad libitum: silage-based total mixed ration (TMR), concentrate (CON), and chopped hay and concentrate presented in 2 manners: mixed (MIX) or separate (SEP). All calves were offered 12 L/d of acidified milk replacer (1.8 kg of dry matter) until d 38 at which time step-down weaning by 1 L/d began. At d 50 calves no longer received milk, and all calves on SEP and CON treatments were offered the MIX diet until the end of the trial, whereas TMR and MIX calves did not change feeds. Feed intakes were recorded daily, and calves were weighed twice per week. Rumination time was observed on the last 3 d of alternate weeks (wk 3, 5, 7, 9, and 11) for 1h beginning at 1500 h. Time spent feeding was determined for the last 2 d of alternate weeks. In the preweaning stage (d 1-37) average daily gain was similar for all calves (1.1 kg/d). The TMR calves had lower average daily gain than calves on the other 3 treatments during both the weaning (d 38-49; 0.2 vs. 0.7 kg/d) and postweaning (d 50-84; 0.5 vs. 1.2 kg/d) stages. This result is related to the lower dry matter intake of calves fed TMR in comparison with MIX, SEP, and CON calves in the weaning (0.2 vs. 0.5 kg/d) and postweaning (1.8 vs. 2.8 kg/d) stages. Given dry matter content of the feeds (TMR=52%, other diets=89%), the as-fed intake of the calves was similar across treatments in all 3 stages. Calves offered hay in addition to concentrate showed no difference in concentrate intake in the first 7 wk of life. Interestingly, TMR calves spent more time feeding during the postweaning stage than MIX, SEP, and CON calves (308 vs. 194 min/d) and exhibited a slower feeding rate postweaning (5.9 vs. 14.4 g of dry matter per minute). It appears that during weaning, and postweaning, calves fed TMR were attempting to maximize their nutrient intake but were unable to match that of calves in other treatments because of the high moisture content of their feed, and thus were unable to achieve similar average daily gain. Additionally, growth and total intake throughout the preweaning and weaning stages were similar for calves fed chopped hay along with concentrate and those not offered hay, suggesting no detrimental effect of feeding forage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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) | 0.000 | 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 teacher head, 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".