Performance, feeding behaviour and rumen pH profile of beef cattle fed corn silage in combination with barley grain, corn or wheat distillers’ grain or wheat middlings
Bibliographic record
Abstract
Holtshausen, L., Beauchemin, K. A., Schwartzkopf-Genswein, K. S., González, L. A., McAllister, T. A. and Gibb, D. J. 2011. Performance, feeding behaviour and rumen pH profile of beef cattle fed corn silage in combination with barley grain, corn or wheat distillers’ grain or wheat middlings. Can. J. Anim. Sci. 91: 703–710. This study compared growth performance, feeding behaviour and ruminal pH profile of growing beef heifers fed a total mixed ration (TMR) containing corn silage and either [400 g kg−1 dry matter (DM)] barley grain (CTL), corn dried distillers’ grain with solubles (CDDGS), wheat dried distillers’ grain with solubles (WDDGS) or wheat middlings (WM). Eighty beef heifers (16 ruminally cannulated; 301±34 kg) were blocked by weight and randomly assigned to eight feedlot pens for a 70-d backgrounding study. Pens were randomly assigned to one of four dietary treatments and equipped with the GrowSafe feed intake system for determining individual feed intake and monitoring feeding behaviour. Dry matter intake (DMI) was lower (P<0.01) and average daily gain (ADG) tended to be lower for CTL (P=0.06) heifers as compared with heifers on other treatments. Feed conversion efficiency (i.e., gain to feed ratio; P=0.41) and feeding behaviour and ruminal pH profile measurements (P>0.05) did not differ among treatments. This study illustrates that barley grain can be replaced by corn dried distillers’ grain, wheat dried distillers’ grain or wheat middlings in diets fed to growing beef cattle without compromising feed conversion efficiency, adversely affecting feeding behaviour (e.g., decreased meal frequency and duration) or increasing the incidence of ruminal acidosis.
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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".