The Role of Ascospores and Conidia, in Relation to Weather Variables, in the Epidemiology of Stemphylium Leaf Blight of Onion
Bibliographic record
Abstract
Stemphylium leaf blight (SLB), caused by Stemphylium vesicarium, is an important foliar disease of onion in northeastern North America. The pathogen produces conidia and ascospores, but the relative contributions of these spore types to epidemics in onion is not known. Determining the abundance of ascospores and conidia during the growing season could contribute to a disease forecasting model. Airborne ascospores and conidia of S. vesicarium were trapped during the growing season of 2015 and 2016 at an onion trial in southern Ontario, Canada, using a Burkard 7-day volumetric sampler. Meteorological data were recorded hourly. Ascospore numbers peaked before the crop was planted and declined rapidly with time and at daily mean air temperatures >15°C. Conidia were present throughout the growing season and appear to be closely related to the development of SLB on onion. Daily spore concentrations were variable, but 59 to 73% of ascospores and approximately 60% of conidia were captured between 0600 and 1200 h. Spore concentrations increased 24 to 72 h after rainfall and precipitation and leaf wetness duration were consistently and positively associated with increases in numbers of conidia and subsequent SLB incidence. The first symptoms of SLB coincided with high numbers of conidia, rainfall, leaf wetness duration ≥8 h, and days with average daily temperature ≥18°C. The number of airborne ascospores was very low by the time SLB symptoms were observed. Ascospores may initiate infection on alternative hosts in early spring, while conidia are the most important inoculum for the epidemic on onions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".