PSXIV-2 Inclusion of a Slow-Release Nitrogen Ingredient Associated Or Not with Monensin on Performance, Metabolism, and Carcass Parameters of Finishing Beef Cattle Fed High Starch Diets
Bibliographic record
Abstract
Abstract This study aimed to assess the effects of a slow-released nitrogen (N) ingredient in association or not with monensin on the performance, metabolism, and carcass parameters of finishing young bulls. To investigate these outcomes, 112 Nellore young bulls (380 kg ± 16.2) were used in a 2 × 2 factorial arrangement. The young bulls were allocated to 28 feedlot pens (four animals per pen) and fed a finishing high starch (51% starch) corn grain and corn silage-based diet. The following treatments were randomly assigned to the experimental units: 1) Control (CON, n = 7), finishing diet without additives; 2) Monensin-enriched diet (MON, n = 7), monensin (Rumensin, Elanco Animal Health, Greenfield, IN) provided at a level of 30 mg per kg of dry matter (DM); 3) Gradual-N-release enriched diet (SRN, n = 7), slow-N-release supplement (Timafeed Boost, Roullier Group, Saint-Malo, France) provided at a dose of 250 g per animal per day; or 4) Monensin + SRN diet (MON + SRN, n = 7), monensin (30 mg per kg of DM) associated with the SRN (250 g per animal per day). The experimental period comprised 102 days, with the first 15 days designated for diet adaptation. The average daily gain (ADG) over the experimental period was reduced for young bulls fed SRN + MON (P = 0.02) compared with those fed only SRN. Young bulls fed MON had greater DMI during the finishing phase than MON × SRN (P = 0.03). Overall, young bulls fed CON diet had greater day-by-day dry matter intake (DMI) variation than other treatments (P ≤ 0.05). The SRN inclusion in the diet improved feed efficiency by 5.7% (P = 0.04). Young bulls fed diets without SRN inclusion tended to have higher blood urea concentration (P = 0.06). Blood D-lactate and glucose levels were similar between treatments (P ≥ 0.21). The SRN use tended to increase (P = 0.09) DM digestibility (5.6% increase). The microbial crude protein was reduced by MON + SRN association (P = 0.02) compared with other treatments. The hot carcass weight was greater for the SRN group compared with MON × SRN (P = 0.02). The use of SRN in the diet increased (P ≤ 0.04) total and daily carcass gain, carcass yield, and biological efficiency. In summary, although additional studies are suggested, these data indicate that the association between SRN and monensin might require careful consideration when used in finishing diets. The SRN inclusion in finishing diets without monensin shows important potential for increasing animal performance and efficiency.
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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".