Effects of Lasalocid or Monensin Supplementation on Digestion, Ruminal Fermentation, Blood Metabolites, and Milk Production of Lactating Dairy Cows
Bibliographic record
Abstract
Six ruminally fistulated midlactating multiparous Holstein cows were used in a double 3 x 3 Latin square design (35-d periods) to study the effects of lasalocid (LAS) and monensin (MON) supplemented at 24 mg/ kg of dry matter on digestion, ruminal fermentation, blood metabolites, and milk production. Cows were blocked according to milk production and fed a red clover silage-based total mixed ration (17.8% crude protein) without supplementation or supplemented with LAS or MON. Daily dry matter intake, milk production, and milk fat and protein concentrations were similar among treatments and averaged 23.5 kg, 36.6 kg, 3.36%, and 3.38%, respectively. Rumen lipogenic:glucogenic volatile fatty acids and NH(3)-N concentration were lower, and apparent digestibility of dry matter, organic matter, crude protein, and gross energy were higher with than without ionophore supplementation. Compared with LAS, MON increased concentrations of plasma urea-N and milk urea-N, and excretion of urinary urea-N and total N. Monensin also decreased N retention and tended to reduce plasma concentration of nonessential AA in comparison with LAS. Both ionophores reduced daily fecal excretion of N by 13 g compared with the control, but MON increased daily losses of urinary N by 36 g compared with LAS. Results from this study suggest that postabsorptive metabolism of N might be altered by the type of ionophore fed.
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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) | 0.001 | 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".