Integrated Management of Angular Leaf Spot (<i>Phaeoisariopsis griseola</i> (Sacc.) Ferr.) on Snap Beans in Ontario
Bibliographic record
Abstract
Angular leaf spot (ALS) caused by the fungus Phaeoisariopsis griseola (Sacc.) Ferr. was first observed and confirmed on snap beans growing in three commercial fields in southern Ontario during the 2000 growing season. The potential impact of this disease on the bean industry in Ontario is not known but this disease is severe in many other regions. The objective of this study was to develop a disease management strategy for ALS in Ontario by investigating the survival of P. griseola in Ontario, and assessing the influence of bean varieties and fungicides on disease development. P. griseola survived at least one winter on crop debris in Ontario and survived better on the soil surface in comparison to burial in soil at depths of 5 or 25 cm. Fifteen snap bean varieties were compared for susceptibility to ALS in a growth room, and nine varieties were compared in a naturally-infested field from 2001-2003. Most varieties reacted similarly to P. griseola in both environments. For example, the varieties Carlo, Storm, and Bush Blue Lake 47 were least susceptible whereas Gold Rush was most susceptible in field and growth room experiments. Boscalid, pyraclostrobin, pyramethanil, vinclozolin, and thiophanate-methyl were tested for effectiveness in managing ALS under field conditions. Overall, pyraclostrobin was most effective. Results indicate that an effective disease management strategy for ALS in snap bean in Ontario should include burying infested plant debris through deep plowing, crop rotation for two years, growing the least susceptible varieties, and applying a registered effective fungicide. Accepted for publication 13 October 2005. Published 29 November 2005.
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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 | 0.000 | 0.000 |
| 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".