Short communication: Feeding method affects the feeding behavior of growing dairy heifers
Bibliographic record
Abstract
There is limited information available on what is the most appropriate feeding method for growing dairy heifers. The objective of this study was to determine the effect of feeding method on the feeding behavior and diet selection of growing dairy heifers. Six prepubescent Holstein heifers (158.2 +/- 4.0 d old, weighing 168.2 +/- 15.7 kg), fed once per day for 1.0 kg/d of growth, were subjected to each of 3 treatments in 3 successive 7-d treatment periods using a replicated 3 x 3 Latin square design. Treatments consisted of feeding 2.02 kg/d dry matter of grain concentrate and ad libitum chopped grass hay as: 1) choice (grain concentrate and hay in separate feed bins), 2) top-dressed ration (grain concentrate placed on top of the hay in one feed bin), and 3) total mixed ration (TMR, grain concentrate mixed with hay in one feed bin). Dry matter intake (DMI) and feeding behavior were monitored for 7 d for each animal on each treatment, and feed sorting was monitored for the last 3 d of each treatment period. The provision of grain concentrate and hay in either a choice or top-dressed situation resulted in young dairy heifers rapidly consuming the grain concentrate portion of their ration in very few, large meals before consuming the hay portion of their ration. The provision of the 2 ration ingredients as a TMR increased the distribution of DMI over the day and reduced the amount of sorting (against long forage particles, and for short grain concentrate particles) by heifers. These results suggest that the provision of a TMR to growing dairy heifers, as opposed to feeding concentrate and hay as either a choice or top-dressed, promotes a more balanced intake of nutrients across 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 | 0.001 |
| 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) | 0.002 | 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".