Effects of partial replacement of corn grain with lactose in calf starters on ruminal fermentation and growth performance
Bibliographic record
Abstract
The objective of this study was to evaluate effects of partial replacement of dry ground corn with lactose in calf starters on dry matter intake, growth rate, ruminal pH, and volatile fatty acid profile. Sixty Holstein bull calves were raised on a high plane of nutrition program until 55 d of age. Calves were fed texturized calf starters containing 30.1% steam-flaked grains and lactose at 0 (control), 5, or 10% (n = 20 for each treatment) on a dry matter basis. All calves were fed treatment calf starters ad libitum from d 7 and kleingrass hay from d 35. Ruminal pH was measured continuously immediately after weaning (d 55–62) for 15 calves (n = 5 per treatment), and 3 wk after weaning (d 77 to 80) for the other 45 calves (n = 15 per treatment). Dry matter intake, growth performance, and ruminal pH variables were not affected by treatment. However, according to Spearman's correlation coefficient ( r s ) analyses, lactose intake was positively correlated with dairy minimum ruminal pH ( r s = 0.306) for the data collected from d 77 to 80. Similarly, hay intake was not affected by treatment, but positively correlated with daily mean ( r s = 0.338) and maximum ruminal pH ( r s = 0.408) and negatively correlated with duration pH <5.8 ( r s = −0.329) and area pH <5.8 ( r s = −0.325), indicating that the variation in hay intake among animals might have masked treatment effects on ruminal pH. Ruminal molar ratio of acetate was higher (45.2 vs. 40.6%), and that of propionate was lower in 10% lactose than control (35.3 vs. 40.2%) for ruminal fluid collected on d 80; however, molar ratio of butyrate was not affected by treatment. These results indicate that lactose inclusion in calf starters up to 10% of dry matter might not affect dry matter intake and growth performance of calves, but that greater lactose and hay intake might be associated with higher ruminal pH.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".