Effects of moisture, roller setting, and saponin-based surfactant on barley processing, ruminal degradation of barley, and growth performance by feedlot steers1
Bibliographic record
Abstract
Two experiments were conducted to study the effects of six processing techniques for barley grain in a 3 x 2 factorial arrangement of grain conditions and roller settings on ruminal degradation of the grain (Exp. 1) and on growth performance by 138 feedlot steers (n = 23 per treatment; Exp. 2). Dry barley (11% moisture, D barley), barley tempered to 20% moisture (M barley), and barley tempered with 60 mL/t of surfactant-based tempering agent (GrainPrep, Agrichem, Inc., Anoka, MN; MS barley), were each rolled at two roller settings selected from preliminary tests. The settings selected for the study were RD, the roller position that had yielded optimally processed D barley, and RMS, the setting that had yielded optimally processed MS barley. Setting RMS was tighter than RD. Barley rolled at the RMS setting was more extensively processed (i.e., had a lower [P < 0.001] processing index, PI), had lighter (P < 0.001) volume weight, thinner (P < 0.001) kernels, and fewer (P < 0.001) whole kernels compared with setting RD. Tempering did not affect (P > 0.05) PI, percentage of whole kernels, or kernel thickness at either roller setting. The processing characteristics of tempered barley were unaffected (P > 0.05) by surfactant. The extent of in situ DM disappearance (ISDMD) was higher (P < 0.01) in grain rolled at setting RMS compared with RD. At both roller settings, tempering reduced (P < 0.05) ISDMD between 4 and 24 h of ruminal incubation. Steers fed RMS-rolled barley had lower (P < 0.001) DMI, slightly lower (P = 0.084) ADG, but increased (P < 0.05) gain:feed (G:F) compared with steers fed RD-rolled barley. Tempering did not affect (P > 0.05) ADG, DMI, or G:F during backgrounding, but improved (P < 0.01) these variables during finishing. Surfactant improved (P < 0.05) G:F but not DMI or ADG. The improvement in G:F was most pronounced when setting RMS was used. The optimal PI values calculated from performance data were numerically greater for the backgrounding diet than for the finishing diet. Steers fed M or MS barley had heavier (P < 0.01) hot carcasses and thicker (P < 0.05) fat cover but lower (P < 0.05) dressing percentages than steers fed D. When the feed barley was rolled at setting RMS, steers fed MS barley produced heavier (P < 0.05) carcasses than those fed M. Tempering with or without surfactant increased performance by feedlot steers compared with not tempering. Diet composition and degree of barley processing mediated this effect.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".