Evaluation of pyraclostrobin as a component in seed and foliar fungicides for the management of blackleg (<i>Leptosphaeria maculans</i>) of canola (<i>Brassica napus</i>)
Bibliographic record
Abstract
Infection by Leptosphaeria maculans (Desm.) Ces. & de Not., the causal agent of blackleg of canola (Brassica napus L.), can result in seedling death, foliar lesions, and the development of stem cankers on adult plants. Strobilurin fungicides such as pyraclostrobin are popular, as they are effective against a broad range of fungal pathogens, have novel target specificity, and translaminar activity within the plant. The seed treatment Prosper FX (carbathiin + trifloxystrobin + metalaxyl) and an experimental formulation BAS 720 F (pyraclostrobin + fluxapyroxad + metalaxyl) were evaluated for their efficacy in managing blackleg when applied alone or in combination with the foliar fungicides Priaxor (pyraclostrobin + fluxapyroxad) or Tilt 250 EC (propiconazole). Experiments were conducted with the blackleg-susceptible cultivar ‘Westar’ and the moderately resistant cultivar ‘Dekalb 73-15 RR’ under greenhouse and field conditions in 2012 and 2013. In one greenhouse trial, all fungicide treatments significantly reduced stem blackleg severity on ‘73-15’ and ‘Westar’ compared with the inoculated–untreated controls. During 3 of 4 site-years, the combination of the experimental seed treatment BAS 720 F and Priaxor significantly reduced stem disease severity relative to the inoculated–untreated control by 60%–77% for ‘73-15’ and by 50%–75% for ‘Westar’. This treatment also resulted in a significant yield increase relative to the inoculated–untreated control in ‘Westar’ in 2 site-years by 24% and 56%. The results of the study suggest a reduction in blackleg symptoms and improved yields when canola is treated with a combination of seed and foliar fungicides, especially when cropping a susceptible cultivar.
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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 | 0.000 | 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".