Wetness duration, temperature and cultivar affect floral infection by <i>Botrytis cinerea</i> in alfalfa
Bibliographic record
Abstract
Blossom blight of alfalfa, caused by Botrytis cinerea and Sclerotinia sclerotiorum, can be an important constraint to alfalfa seed production on the Canadian Prairies. Botrytis cinerea is the predominant pathogen in rain-fed production areas across the northern Prairie region. This study assessed the optimum conditions for infection of alfalfa florets by B. cinerea, and susceptibility in alfalfa based on cultivar and flower colour/orientation. The disease reaction of the cultivars was assessed in detached and intact inflorescences inoculated under controlled conditions and in field trials. The optimum temperature for infection was 20°C, with a minimum of 12 h of surface wetness. Increased duration of surface wetness generally increased infection, except at 30°C, where continued exposure to high temperature reduced infection. There were small but consistent differences in flower infection among cultivars, which were consistent across the testing protocols (detached inflorescence, whole-plant and field). Upward-facing inflorescences had a lower incidence of infection than downward-facing inflorescences. Also, purple florets were slightly less susceptible relative to white/yellow florets, but in only one of the three cultivars assessed. Knowledge of infection requirements from this study can be used to improve management of blossom blight, but the differences among cultivars were generally too small to have an important impact on disease management in the field.
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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 | 0.001 | 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".