Limpograss [Hemarthria altissima] Silage and Protein Supplementation as an Alternative Feed Option for Growing Heifers in North Florida
Bibliographic record
Abstract
Limpograss (Hemarthria altissima) is a warm-season perennial grass that has the potential to feed livestock during scarcity periods. This study evaluated the intake, nutrient digestibility, and animal performance of beef heifers fed ‘Gibtuck’ limpograss silage combined with different levels of a range cube supplementation. Twenty-four heifers (330 ± 16 kg live weight) were submitted to four different treatments with 6 replicates: (1) control, no supplementation + limpograss silage ad libitum; (2) 1.4 kg of supplement + limpograss silage ad libitum; (3) 2.8 kg of supplement + limpograss silage ad libitum; and (4) 4.2 kg of supplement + limpograss silage ad libitum. The apparent total tract digestibility of dry matter, organic matter, and crude protein showed a positive quadratic effect with increasing supplementation levels (p = 0.001, p = 0.002, and p < 0.0001, respectively). Overall, the supplement improved diet digestibility and total DM intake but reduced silage intake, indicating a combined effect (substitutive and additive effect) of the protein supplement. The increasing level of protein supplement increased the average daily gain with a quadratic effect (p ≤ 0.0001). Limpograss silage associated with supplementation can improve diet digestibility and increase the animal performance of growing heifers, providing an alternative for livestock in North Florida.
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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".