Virulence of <i>Puccinia coronata</i> var <i>avenae</i> f. sp. <i>avenae</i> (oat crown rust) in Canada during 2016 to 2020 and comparison of extensive vs intensive sampling methods
Bibliographic record
Abstract
Puccinia coronata var avenae f. sp. avenae (Pca), the causal fungus of crown rust of oats, is a significant threat to oat production in the eastern prairie region (Manitoba and eastern Saskatchewan; EPR), Ontario and Quebec (eastern Canada; EC), in Canada. Development of oat lines with effective resistance to Pca has been a priority for oat breeding programmes in Canada, and helped mitigate reductions in oat yield and quality. This requires knowledge of the virulence characteristics of the Pca population in Canada. Our objectives were to determine the incidence and severity of Pca in Canada, the presence and frequency of virulence and races in Pca populations and compare the traditional extensive sampling method (few isolates per field from many fields) to an intensive sampling method (many isolates per field from a few fields) for obtaining genetically diverse collections. The incidence and severity of crown rust of oat in Canada was lower in 2016 to 2020 than has been reported in previous years. Virulence to all the 24 Pc genes studied was observed over the 5 years in EC and the EPR. The most effective genes were Pc94, Pc98 and Pc101 in EC and Pc50, Pc96, Pc97 and Pc98 in the EPR. Approximately 81% of 424 races identified were of unique virulence phenotypes over the 5 years, indicating a highly variable Pca population in Canada. Races JTQG-91 and GTQG-91 were the most common races identified. Collections of Pca obtained using the extensive sampling method were observed to be more genetically diverse than collections obtained using the intensive sampling method in 2018 and 2020, but not in 2019.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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".