Impact of <i>Brassica napus–Leptosphaeria maculans</i> interaction on the emergence of virulent isolates of <i>L. maculans</i> , causal agent of blackleg disease in canola
Bibliographic record
Abstract
Abstract Canola ( Brassica napus ) is the major oilseed crop in Canada. Blackleg ( Leptosphaeria maculans ) causes yield losses annually, with a larger impact in the last two decades caused by breakdown of resistance in growers’ fields. A 4‐year small‐plot field study from 2014 to 2017 in Manitoba investigated the impact of the B . napus–L . maculans interaction on the emergence of virulent isolates towards specific R genes. Doubled haploid B . napus ‘Topas’ introgression lines carrying single R genes were used, with a 2‐year canola–wheat rotation. Blackleg incidence was reduced by 40% in 2017 compared to 2014 for all R genes tested except Rlm4 . In 2017, disease severity was reduced between 21% and 52% compared to 2014 for all R genes tested except Rlm2 . There was a significant shift from AvrLm2 and AvrLm4 to virulent alleles avrLm2 and avrLm4 , respectively, which led to the gain of virulence toward Rlm2 and Rlm4 Topas introgression lines within a year. Sequencing of the AvrLm2 gene of isolates from 2014 and 2015 revealed a shift of AvrLm2 to avrLm2 allele due to accumulation of point mutations. Masking of AvrLm3 phenotype by the presence of the AvrLm4‐7 allele was also confirmed by analysing phenotypes and genotypes of the isolates collected from 2014 to 2017. Based on these and previous findings, we demonstrate the need for an epidemiological model that takes into account complex molecular mechanisms allowing plant breeders to select appropriate R genes, including balanced cultivar rotation strategies to maintain blackleg resistance in the Canadian Prairies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".