Optimal Fungicide Timing for Suppression of Typhula Blight under Winter Covers
Bibliographic record
Abstract
Core Ideas Winter covers increase snow mold severity on golf course turfgrass. Despite increased pressure, effective fungicides are available to limit disease to acceptable levels. Applying fungicides as a single application shortly before snow cover or splitting out into two applications are both effective at reducing snow mold. Synthetic covers are often used to protect high‐value golf course putting greens throughout much of North America and Scandinavia from injury during harsh winter conditions. However, these covers may trap heat and moisture at the turf surface and provide optimal conditions for snow mold development. This study was conducted to determine the most effective fungicide application strategy under both permeable and impermeable synthetic covers. Three different fungicide timings (early, late, and early + late) were tested under no cover, a permeable Evergreen (Hinspergers Poly Industries, Mississauga, ON) cover, and an impermeable GreenJacket cover (GreenJacket, Genoa City, WI) during the winters of 2011–2012 and 2012–2013 in Antigo, WI. Snow mold pressure appeared highest under the impermeable cover, though under all three cover treatments both the late and early + late fungicide timings provided excellent snow mold suppression. These results suggest that despite the increased disease pressure that may be observed under winter covers, excellent snow mold suppression can still be achieved with just one application of a highly efficacious fungicide mixture shortly prior to cover installation.
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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 | 0.000 |
| 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) | 0.006 | 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".