Quantifying Yield Losses in Canola (Brassica napus) Caused by Verticillium longisporum
Bibliographic record
Abstract
Verticillium stripe, a soilborne disease of canola (Brassica napus) caused by Verticillium longisporum, was first identified on the Canadian Prairies in 2014. Despite its increasing incidence, the impact of this disease on canola yields has not been quantified. To address this gap, the relationship between Verticillium stripe severity and yield was investigated in two canola hybrids, ‘45H31’ and ‘CS2000’, at two infested field sites near St. Albert, Alberta, in 2020 and 2021. In 2020, a year with above-average rainfall, both hybrids developed moderate levels of the disease, whereas in 2021, a drought year, symptoms and signs of infection were milder. Regression analysis indicated that seed yield per plant declined with increasing Verticillium stripe severity in both years of the study. In both hybrids, the relationship between disease severity and yield was best explained by second-degree quadratic equations. Although single-plant seed yield declined by up to 80% with increasing Verticillium stripe severity, these reductions did not translate into significant yield losses at the plot level, suggesting that losses experienced by individual plants were offset by reduced competition among the surviving plants. These results underscore the complexity of assessing disease impacts solely based on symptom severity.
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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 | 0.001 | 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".