Cultivar Response of Seeded Bermudagrass to Leaf Spot and the Influence of Nitrogen on Disease Severity
Bibliographic record
Abstract
Seeded bermudagrass [Cynodon dactylon (L.) Pers.] cultivars are currently replacing hybrid‐bermudagrass and cool‐season turfgrasses in some golf course renovations, home lawns, and athletic fields. Leaf spot, a destructive disease of bermudagrass, is caused by a fungal complex consisting of Bipolaris and Exserohilum spp. that infect leaves, stems, and stolons resulting in leaf blight and melting‐out. A three‐year field study was conducted to determine the response of seven seeded bermudagrass cultivars to leaf spot and the influence of nitrogen on leaf spot severity. Princess‐77, Riviera, and Yukon were determined to have improved field tolerance to leaf spot. Transcontinental and Savannah cultivars displayed moderate disease response while Nu‐Mex Sahara and Arizona Common had poor field tolerance to leaf spot. Seeded bermudagrass cultivars with poor field tolerance to leaf spot displayed increased leaf spot severity in response to high nitrogen (2.0 lb N per 1000 ft2 per month). Leaf spot severity of Arizona Common increased at the highest nitrogen level. Nitrogen levels did not influence leaf spot severity in seeded bermudagrass cultivars that had improved field tolerance. Princess‐77, Riviera, and Yukon had the lowest leaf spot severity throughout the growing season each year of the three‐year study.
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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".