Grazing intensity effects on sward responses of UF Riata Bahiagrass
Bibliographic record
Abstract
Abstract Bahiagrass ( Paspalum notatum Flüggé) is a rhizomatous, perennial, warm‐season forage widely grown in the southeastern United States "UF Riata" bahiagrass is more upright growing with greater herbage production when days are shorter compared with most other cultivars. Lesser daylength sensitivity extends the grazing season, but in combination with more upright growth may negatively affect persistence under grazing, especially if out‐of‐season herbage production interferes with normal reserve storage. This 3‐year study investigated above and belowground sward responses of UF Riata bahiagrass to three levels of post‐grazing herbage mass (HM) (500 [heavy grazing, HG], 1500 [moderate grazing], or 2500 [light grazing, LG] kg DM ha −1 , where DM is dry matter) imposed by mob stocking every 14 days. Total herbage accumulation (HA) and HA rate were not affected by treatment. Crude protein (CP) was affected by treatment × grazing cycle × year, whereas in vitro digestible organic matter concentrations were affected by treatment × year and grazing cycle × year. Root–rhizome biomass (12,940–9230 kg OM ha −1 , where OM is organic matter) and soil cover percentage (97%–93%) decreased linearly as grazing intensity increased from LG to HG. Proportion of non‐planted grasses was 34% and 17% in HG and LG swards, respectively. Proportion of non‐grass weeds increased across treatments from 2% to 22% over the years. Moderate grazing could maintain similar CP to HG, and similar root–rhizome biomass to LG. Thus, considering both sward persistence and forage nutritive value, a target post‐grazing HM of ≈1500 kg DM ha −1 is recommended when UF Riata pastures are grazed every 2 weeks.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".