Effects of Grain Processing, Forage to Concentrate Ratio, and Forage Particle Size on Rumen pH and Digestion by Dairy Cows
Bibliographic record
Abstract
Dietary factors that alter the intake of effective fiber were evaluated for their effects on rumen fermentation, digestion, and milk production using a double 4 x 4 quasi-Latin square design with a 2(3) factorial arrangement of treatments. The dietary factors were extent of barley grain processing, coarse (1.60 mm) or flat (1.36 mm); forage-to-concentrate (F:C) ratio, low (35:65) or high (55:45) (dry matter basis); and forage particle length, long (7.59 mm) or short (6.08 mm). Eight lactating cows with ruminal and duodenal cannulas were offered ad libitum access to a total mixed diet and milked twice daily. Dry matter intake was increased by increasing the extent of grain processing. Mean rumen pH was lower for cows fed flatly rolled barley than for cows fed coarsely rolled barley, whereas F:C ratio or forage particle size had no effect on rumen pH. Rumen pH was not correlated with effective NDF intake but tended to be correlated with digestibility of starch in the rumen. Total tract digestibilities of dry matter, organic matter, starch, and neutral detergent fiber were increased by feeding flatly rolled barley or low F:C ratio diets. Milk yield and milk protein content were higher in cows fed flatly rolled barley or low F:C ratio diets. Milk fat content tended to increase with high F:C ratio or long forage particle length but was reduced by feeding flatly rolled barley. In this study, extent of grain processing and intake of ruminal available starch were the most influential factors affecting milk production. Reducing the ratio of F:C improved total digestion and actual milk production. Forage particle length had minimal impact on digestibility and 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 | 0.001 | 0.001 |
| 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 | 0.001 | 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".