Effects of particle size and moisture levels in mixed rations on the feeding behavior of dairy heifers
Bibliographic record
Abstract
Two experiments on replacement heifers (175±12 days of age) assessed the effects of forage particle length and moisture on feeding behavior. Both experiments used a replicated 3×3 Latin square design, with nine heifers per replication and three periods of 9 days each. Each group of nine heifers was housed in one pen with access to three electronic feed bins. In Experiment 1, hay chopped at different lengths was incorporated into three total mixed rations (TMR) all having the same ingredient and nutrient composition but differing in the percentage of long particles (>19 mm): 60% (Short), 64% (Medium) and 72% (Long). In Experiment 2, heifers were fed a TMR with the same ingredient and nutrient composition but differing in moisture content: 65% DM (Dry), 50% DM (Moderate), and 35% DM (Wet). In both experiments, feeding behavior during the last 5 days of each period was analyzed using a mixed model accounting for the fixed effects of treatment and period, and the random effects of replication and animal. In Experiment 1, dry matter intake (DMI) and eating rate (DMI/min) tended to increase, whereas daily eating time decreased as the feed particle size decreased. Heifers fed the Long diet selected in favor of long particles (>19 mm) and against Short (1.18 to 8 mm) and fine (<1.18 mm) particles; heifers fed the Short diet selected against long particles and in favor of short and fine particles. Heifers fed the Medium diet showed a preference for medium particles with no preference for the other particle sizes. In Experiment 2, heifers fed the Dry diet tended to consume more feed than those fed the Moderate and Wet diets, with no differences in feeding behavior or sorting activity. In conclusion the Medium diet minimized sorting without reducing eating rates and intake, and adding water to TMR to achieve a dry matter less than 65% tended to decrease DMI without reducing sorting.
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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 | 0.000 | 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) | 0.000 | 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".