Efficacy of Blackleg Major Resistance Genes in B. napus in Germany
Bibliographic record
Abstract
Leptosphaeria maculans is one of the major pathogens of oilseed rape (B. napus). It causes blackleg disease, which accounts for significant yield losses worldwide. Using cultivars that harbor major resistance (R) genes is one of the most effective control methods. However, the efficacy of major R genes is related to the frequency of the corresponding avirulence (Avr) genes in a L. maculans population. In this paper, we report the Avr profiles of L. maculans populations and the ratio of its mating types in Northern and Central regions of Germany. Eleven Avr genes in five-hundred and seventy-four isolates were characterized either by applying cotyledon tests on a B. napus differential set or by amplifying avirulence gene-specific PCR markers. Fifty-two races were determined, among which the most dominant race was Avrlm6, -7, -11, AvrlepR1, -R2. Results showed that the resistance gene Rlm2 is 100% ineffective, some other major R genes such as Rlm1, Rlm3, Rlm4 and LepR3 are partially effective (with corresponding Avr frequencies ≤ 42%), while LepR1, LepR2, Rlm6, Rlm11 and Rlm7 can still provide relatively effective resistance in the German fields investigated (with corresponding Avr frequencies of 63–100%). Sexual reproduction is a factor that enhances the potential of L. maculans to evolve under selection pressure. Mating types of the L. maculans populations did not deviate from the ratio of 1:1 in the examined regions, indicating that sexual reproduction and ascospores play central roles in the L. maculans lifecycle. Overall, this study provides an important dataset for the establishment of a strategic plan to preserve the efficacies of major R genes in Germany by applying cultivar rotations of oilseed rape.
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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 | 0.000 | 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".