Performance and nitrogen use efficiency in mid-lactation dairy cows fed timothy cut in the afternoon or morning
Bibliographic record
Abstract
Shifting cutting from morning to afternoon has been shown to increase the concentration of nonstructural carbohydrates in forages. We hypothesized that, compared with a total mixed ration containing timothy baleage and silage cut in the morning (a.m.-cut TIM), a total mixed ration containing timothy baleage and silage cut in the afternoon (p.m.-cut TIM) would improve animal performance and N use efficiency in mid-lactation Holstein cows due to enhanced supply of ruminal fermentable energy. The objective of this study was to compare the effects of p.m.- versus a.m.-cut TIM on milk yield, concentrations and yields of milk components, ruminal metabolism, and plasma concentrations of AA in mid-lactation Holstein cows. Ten (6 ruminally cannulated) primiparous cows averaging 139±13 d in milk and 550±56 kg of body weight, and 6 (2 ruminally cannulated) multiparous cows averaging 128±11 d in milk and 632±57 kg of body weight at the beginning of the experiment, were used in a crossover design. Each period lasted 21 d with 14 d for diet adaptation and 7 d for data and sample collection. The concentration of nonstructural carbohydrates (water-soluble carbohydrates plus starch) was numerically greater in the p.m.- versus the a.m.-cut TIM and averaged 13.2±1.06% and 12.2±1.13%, respectively. Treatment × parity effects were observed for milk urea N, feed efficiency, and milk N efficiency, whereas parity effects were observed for nutrient intake, milk yield, and plasma concentration of several essential and nonessential AA. Intakes of dry matter (19.3 versus 18.6 kg/d) and nonstructural carbohydrates (2.56 versus 2.31 kg/d), and yields of 4% fat-corrected milk (23.1 versus 22.2 kg/d), energy-corrected milk (25.0 versus 24.1 kg/d), milk fat (0.91 versus 0.88 kg/d), and milk protein (0.77 versus 0.73 kg/d) were all greatest with feeding p.m.-cut TIM. Milk yield (23.5 versus 22.7 kg/d) tended to increase in cows fed p.m.-cut TIM. The ruminal fermentation profiles and plasma concentrations of AA were mostly unaffected by treatments. However, ruminal valerate (1.01 versus 1.17 mol/100 mol) and plasma Gly (172 versus 188 µM) were lowest with feeding p.m.-cut TIM. Overall, feeding mid-lactation dairy cows a total mixed ration that consisted of p.m.-cut timothy baleage and silage significantly increased dry matter intake and yields of milk, milk fat, and milk protein.
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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".