Stemphylium Leaf Blight: A Re-Emerging Threat to Onion Production in Eastern North America
Bibliographic record
Abstract
Stemphylium leaf blight (SLB), caused by Stemphylium vesicarium, is a foliar disease of onion worldwide, and has recently become an important disease in the northeastern United States and Ontario, Canada. The symptoms begin as small, tan to brown lesions on the leaves that can progress to defoliate plants. Crop loss occurs through reduced photosynthetic area, resulting in smaller, lower-quality bulbs. Leaf necrosis caused by SLB also can compromise bulb storage, as green leaves are required for the uptake of sprout inhibitors applied prior to harvest. The pathogen can overwinter on infested onion residue and infected volunteer plants. Asymptomatic weedy hosts near onion fields may also be a source of inoculum. Production of ascospores of the teleomorph (Pleospora allii) peaks in early spring in northeastern North America, often before the crop is planted, and declines rapidly as daily mean air temperatures rise. Conidia are usually present throughout the growing season. Application of fungicides is a standard practice for management of the complex of fungi that can cause foliar diseases of onion in this region. Recent assessments have shown that populations of S. vesicarium in New York and Ontario are resistant to at least three single-site mode-of-action fungicides. Three disease prediction systems have been developed and evaluated that may enable growers to reduce the frequency and/or number of fungicide applications, but the loss of efficacious fungicides due to resistance development within S. vesicarium populations threatens sustainability. The lack of commercially acceptable onion cultivars with sufficient resistance to reduce the number of fungicides for SLB also limits the ability to manage SLB effectively. Integrated disease management strategies for SLB are essential to maintain profitable, sustainable onion production across eastern North America.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".