PSXII-19 Effects of Feeding Hybrid Rye Grain as a Replacement for Barley Grain on Feed Intake, Growth Performance and Carcass Characteristics of Finishing Beef Cattle
Bibliographic record
Abstract
Abstract The objective of this study was to evaluate effects of increasing hybrid rye as a replacement for barley grain on feed intake, growth performance, and carcass characteristics for growing and finishing cattle. Commercial steers (n = 360) with an initial body weight (BW) of 348 ± 6.6 kg were stratified by BW and randomly assigned to 1 of 24 pens (15 steers/pen) for growing (n = 8; 65 d) phase and re-randomized for the finishing (n = 6; 118 d) phase. The control diet (BCON) for the growing phase included 60.2% barley grain, 28.0% barley silage, 7.0% corn silage, 3.4% oat hulls, with the remainder as mineral, vitamins, and urea. Hybrid rye was then included by replacing 50 or 100% of the barley grain (DM basis). Treatments for the finishing phase included a control containing 10% hay, 85.2% barley grain, with the remainder coming from mineral and vitamins (FCON). Hybrid rye grain was included by replacing 33 (33R), 67 (67R), and 100% (100R) of the barley grain (DM basis). Data were analyzed using the MIXED procedure for each phase independently with carcass data analyzed using the GLIMMIX procedure of SAS (SAS version 9.4; SAS Institute, Inc. Cary, NC). There was no effect of hybrid rye inclusion on DMI or G:F during the growing phase, but ADG increased quadratically (P = 0.04) with 50% rye having the greatest value. During finishing, DMI decreased linearly as hybrid rye inclusion increased (P = 0.03). Average daily gain was quadratically affected (P = 0.03) with an initial increase from FCON to 33% rye followed by a decrease with increasing rye grain inclusion, but G:F was not affected (0.148 kg BW/kg DMI). There was no effect of hybrid rye inclusion on hot carcass weight, dressing percentage, back-fat thickness, ribeye area, marbling score, and yield score. Increasing the inclusion of hybrid rye quadratically (P < 0.01) increased the proportion of severe liver abscesses with an average of 34.6% severely abscessed livers when hybrid rye grain was included compared with 11.1% for FCON. Partial replacement of barley grain with hybrid rye may improve ADG without affecting DMI or G:F during the growing phase. However, replacing barley grain in finishing diets with hybrid rye decreases DMI, increases risk for severe liver abscesses, but does not affect feed conversion suggesting hybrid rye could replace up to 33% of the barley grain.
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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) | 0.001 | 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 | 0.001 |
| 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".