Milk production and efficiency of utilization of nitrogen, metabolizable protein, and amino acids are affected by protein and energy supplies in dairy cows fed alfalfa-based diets
Bibliographic record
Abstract
Alfalfa has a lower fiber digestibility and a greater concentration of degradable protein than grasses. Dairy cows could benefit from an increased digestibility of alfalfa fibers, or from a better match between nitrogen and energy supplies in the rumen. Alfalfa cultivars with improved fiber digestibility represent an opportunity to increase milk production, but no independent studies have tested these cultivars under the agroclimatic conditions of Canada. Moreover, decreasing metabolizable protein (MP) supply could increase N use efficiency while decreasing environmental impact, but it is often associated with a decrease in milk protein yield, possibly caused by a reduced supply of essential AA. This study evaluated the performance of dairy cows fed diets based on a regular or a reduced-lignin alfalfa cultivar and measured the effect of energy levels at low MP supply when digestible His (dHis), Lys (dLys), and Met (dMet) requirements were met. Eight Holstein cows were used in a double 4 × 4 Latin square design, each square representing an alfalfa cultivar. Within each square, 4 diets were tested: the control diet was formulated for an adequate supply of MP and energy (AMP_AE), whereas the 3 other diets were formulated to be deficient in MP (DMP; formulated to meet 90% of the MP requirement) with deficient (94% of requirement: DMP_DE), adequate (99% of requirement: DMP_AE), or excess energy supply (104% of requirement; DMP_EE). Alfalfa cultivars had no significant effect on all measured parameters. As compared with cows receiving AMP_AE, the dry matter intake of cows fed DMP_AE and DMP_EE was not significantly different but decreased for cows fed DMP_DE. The AMP_AE diet provided 103% of MP and 108% of NE L requirements whereas DMP_DE, DMP_AE, and DMP_EE diets provided 84, 87, and 87% of MP and 94, 101, and 107% of NE L requirements, respectively. In contrast to design, feeding DMP_EE resulted in a similar energy supply compared with AMP_AE, although MP supply has been effectively reduced. This resulted in a maintained milk and milk component yields and improved the efficiency of utilization of N, MP, and essential AA. The DMP diets decreased total N excretion, whereas DMP_AE and DMP_EE diets also decreased milk urea-N concentration. Reducing MP supply without negative effects on dairy cow performance is possible when energy, dHis, dLys, and dMet requirements are met. This could reduce N excretion and decrease the environmental impact of milk production.
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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".