Insights into fighting against blackleg disease of Brassica napus in Canada
Bibliographic record
Abstract
Blackleg disease, caused by the ascomycete fungal pathogen Leptosphaeria maculans, is a devastating disease of canola (Brassica napus) in Australia, Canada and Europe. Although cultural strategies such as crop rotation, fungicide application, and tillage are adopted to control the disease, the most promising disease control strategy is the utilisation of resistant canola varieties. However, field populations of L. maculans display a high evolutionary potential and are able to overcome major resistance genes within a few years, making disease control relying on resistant varieties challenging. In the early 1990s, blackleg resistance gene Rlm3 was introduced into Canadian canola varieties and provided good resistance against the fungal populations until the early 2000s, when moderate to severe blackleg outbreaks were observed in some areas across western Canada. However, the breakdown of Rlm3 resistance was not reported until recently, based on studies on R genes present in Canadian canola varieties and the avirulence allele frequency in L. maculans populations in western Canada. The fact that Rlm3 was overcome by the evolution of fungal populations demands canola breeding programs in Canada to be prepared to develop canola varieties with diversified and efficient R genes. In addition, frequent monitoring of fungal populations can provide up-to-date guidance for proper resistance genes deployment. This literature review provides insights into the outbreaks and management of blackleg disease in Canada.
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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 | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".