Different Ground Corn Particle Size in Supplements for Young Bulls Grazing During Intensive System Production
Bibliographic record
Abstract
Abstract We hypothesized that a decrease in flint corn particle size in the supplements of young bulls during grazing promotes better use of starch in the total gastrointestinal tract, with less starch lost in the feces, thus increasing growth performance. This experiment aimed to evaluate the effects of supplements with different ground corn particle sizes on the growth performance, economic analysis, intake and apparent digestibility of nutrients for beef cattle in Urochloa brizantha cv. Marandu pastures during the rainy-dry transition season. Sixty-four Nelore bulls, with an average age of 16 months and 303.6 ± 18.0 kg of body weight (BW), were distributed in a completely randomized design. The treatments were WG = whole grain (geometric mean particle size, dgw, 6.262 µm); CG = coarse ground grain (dgw, 2.882 µm); MG = medium ground grain (dgw, 1.011 µm); and FG = fine ground grain (dgw, 0.621 µm). The supplements with ground grain or whole grain were similar (P > 0.05) in terms of intake and the digestibility of dry matter (DM), forage, organic matter (OM), crude protein (CP), neutral detergent fiber corrected for ash and protein (NDFap), and total digestible nutrients (TDN). However, the starch digestion in the total tract was higher (P < 0.05) with ground grain than with whole grain. The different geometric mean particle sizes of the grain in the supplements were not sufficient to alter (P > 0.05) the starch digestion in the total tract. The starch fecal concentration decreased with ground grain compared with that for whole grain (P < 0.05). However, no differences in growth performance were observed among the treatments (P > 0.05). Supplementation with CG promoted a slightly greater net revenue (+ 11.51%) and return per ha (+ 12.8%) compared with WG, while MG and FG yielded worse economic results. Therefore, CG showed higher economic performance and efficiency utilization of starch, suggesting it is a better strategy for providing supplements to young grazing bulls.
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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".