Effects of feeding Fermenten on ruminal fermentation in lactating Holstein cows fed two dietary sugar concentrations
Bibliographic record
Abstract
This study was conducted to determine the effects of feeding Fermenten (Church and Dwight Co., Princeton, NJ) with or without dietary sucrose on ruminal fermentation, apparent total-tract nutrient digestibility, and nutrient utilization. Eight ruminally cannulated Holstein cows (163 +/- 55 d in milk; mean +/- standard deviation) were used in a replicated 4 x 4 Latin square design with a 2 x 2 factorial arrangement of treatments. Experimental diets were formulated with and without Fermenten (0 vs. 3.3% of dietary DM) at 2 dietary sugar concentrations (2.8 vs. 5.7%). Dietary treatment did not affect dry matter intake or apparent total-tract nutrient digestibility. Feeding Fermenten did not affect ruminal pH, but high-sugar diets tended to increase the daily minimum pH (5.61 vs. 5.42) and mean pH (6.17 vs. 6.30) compared with low-sugar diets. Ruminal ammonia concentration tended to be greater for cows fed Fermenten compared with control (18.1 vs. 15.9 mg/dL), but was not affected by dietary sugar concentration. Significant interactions between Fermenten and dietary sugar concentration were detected for some milk production responses. Fermenten treatment numerically increased milk fat yield (0.92 vs. 0.82 kg/d), 4% fat-corrected milk yield (24.3 vs. 21.9 kg/d), and milk energy output (18.2 vs. 16.4 Mcal/d) compared with control for cows fed low-sugar diets, but not for cows fed high-sugar diets. Increasing dietary sugar concentration did not enhance the effects of Fermenten, providing no support for the theory that synchronizing the availability of N and fermentable energy in the rumen improves nutrient utilization in lactating dairy cows.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".