307 Effect of Feeding Distilllers Grain from Wheat on Growth Performance of Growing and Finishing Beef Cattle
Bibliographic record
Abstract
Abstract The uniqueness of wheat-based distiller grain (wDG) with high protein and digestible fibre gives great feeding opportunities for cattle as energy, protein or fiber source. This abstract summarizes recent research findings on the use of wDG in beef cattle diets. For growing beef cattle, steers fed diets (forage:concentrate, 55:45) with increasing replacement of barley grain with wDG from 0, 8, 16, 24 to 32% (DM basis) linearly (P < 0.01) increased average daily gain (ADG) from 1.09 to 1.28 kg/d and DM intake (DMI) from 7.26 to 7.94 kg/d without affecting gain:feed (0.158). By comparing protein source of canola meal and corn DG in diets containing 60% of silage and 40% of barley grain, steers fed wDG diet had similar ADG (1.46 kg/d) with corn DG (1.51 kg/d), and had no differences in gain:feed (0.178) with canola meal (0.183). For finishing beef cattle, with increasing wDG from 10, 20 to 40% in the place of barley grain of finishing diets, the DMI linearly (P < 0.01) increased from 10.2 to 10.9 kg/d, whereas, the gain:feed linearly (P < 0.01) decreased from 0.172 to 0.159 without altering the ADG (1.74 kg/d). The wDG was also suggested to be fed as fiber source to replace roughage in finishing diet. Entirely substitution of wDG for roughage of finishing diet decreased (P < 0.01) ruminal pH from 5.95 to 5.75 of beef heifers; however, the ADG and gain:feed of steers were not affected. The results suggested that although substitution of wDG for roughage in finishing diets may increase the incidence of ruminal acidosis, this outcome does not appear to adversely impact the performance of the cattle. The wDG can be successfully incorporated to substitute a portion of grain or roughage within growing and finishing diets with minimal or no adverse impact on cattle growth performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".