Pathotypes of Plasmodiophora brassicae causing damage to oilseed rape in the Czech Republic and Poland
Bibliographic record
Abstract
Winter oilseed rape (Brassica napus) is an important crop in the Czech Republic and Poland. Clubroot disease caused by the pathogen Plasmodiophora brassicae is a serious and still-growing problem for oilseed rape growers in both countries. The aim of this study was to evaluate the pathotype composition of P. brassicae populations from the Czech Republic and Poland, according to the three evaluation systems, and to determine soil inoculum loads for representative fields via traditional end-point PCR as well as quantitative PCR analysis. There were considerable differences between the populations of P. brassicae from both countries, and the number of pathotypes varied depending on the evaluation system and the threshold used to distinguish susceptible vs. resistant plant reactions. This is the first study comparing the effect of different thresholds. Using an index of disease (ID) of 25 % to distinguish susceptible vs. resistant reactions, there was a total of seven pathotypes identified based on the differentials of Williams, five with the system of Somé et al., and 18 with the European Clubroot Differential (ECD) set. However, based on a threshold of 50 %, there were nine pathotypes according to the evaluation system by Williams, four based on the differentials of Somé et al., and 15 with the ECD set. Changing of the thresholds led to the reclassification of some pathotypes. Several pathotypes were common in both countries. High amounts of pathogen DNA were found in many of the field soils analysed by quantitative PCR. There was a weak correlation between soil pH and infestation of P. brassicae for the Polish soils.
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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 | 0.002 | 0.001 |
| 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".