Effects of grain source and marginal change in lucerne hay particle size on feed sorting, eating behaviour, chewing activity, and milk production in mid‐lactation Holstein dairy cows
Bibliographic record
Abstract
This study investigated the effects of grain source and lucerne hay (LH) particle length on eating behaviour, chewing activity, and milk production of lactating dairy cows. Eight Holstein dairy cows (175 ± 21 days in milk) were used in a replicated 4 × 4 Latin square design with four 21-days periods. The experiment was a 2 × 2 factorial arrangement of treatments with barley grain alone or equal blend of barley and maize grains combined with short (15 mm) and long (30 mm) LH. Diets were fed ad libitum as total mixed ration with a concentrate to forage ratio of 60:40. Interactions between grain source and LH particle length on feed particle distributions, sorting index, chewing activity, and milk production were minimal. Partially replacing barley grain with maize in the diet overall did not change diurnal distributions of particles retained on the sieves of Penn State Particle Separator but reduced the proportion of particles on 1.18-sieve and increased that of particles on pan (p < 0.05). Grain source did not affect sorting index and chewing activity. However, feeding long LH increased (p < 0.01) intakes of long particles retained on 19- and 8-mm of sieve, prolonged (p < 0.05) eating time, and lowered eating rate (p < 0.05). Interestingly, cows fed with long LH ate more coarse particle during critical-early time post feeding (i. e. 1.5 h), where eating time increased and eating rate decreased (p < 0.05). Increasing particle length of dietary LH tended to increase milk fat-to-protein ratio (p = 0.08). The results suggested that the increased eating time and decreased eating rate as a result of marginally increasing LH particle length would be beneficial to alleviate reduction of ruminal pH and milk fat percentage following the ingestion of highly fermentable diets.
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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".