Physiological specialization of <i>Puccinia triticina</i>, the causal agent of wheat leaf rust, in Canada in 2011
Bibliographic record
Abstract
Leaf rust collections were made across Canada in 2011 and 287 single-pustule isolates were tested for virulence on 16 standard differential lines and two additional lines containing Lr21 and LrCen, respectively. Of the 70 different virulence phenotypes found in Canada during 2011, the most common were TDBJ (12.5%), TDBG (10.5%) and MLDS (7.7%), which is similar to the findings from 2010. Three isolates from Alberta each had a unique virulence phenotype. From Manitoba and Saskatchewan, 33 virulence phenotypes were found among 216 isolates, with the most common being TDBJ (16.7%), TDBG (13.9%), MLDS and TBBG (both at 9.3%). There were 29 virulence phenotypes among 47 isolates from Ontario, with MBTN (25.5%), MCTN (8.5%) predominating. Ten virulence phenotypes were found from 11 isolates in Quebec, and six virulence phenotypes among 10 isolates from Prince Edward Island. Compared with 2010, there were increases in the frequencies of virulent isolates in Canada to Lr2a, Lr2c, Lr16, Lr26, Lr3ka, Lr11 and Lr30 while there were declines in the frequencies of virulent isolates to Lr9, Lr24, Lr10 and Lr14a. When a group of 161 representative isolates were tested on five adult plant differentials, all isolates were avirulent to Lr22a, most were virulent to Lr12, Lr13 and Lr37, while only 16 were virulent to Lr35. When this same group of isolates was tested on 12 additional lines at the seedling stage, all isolates were avirulent to Lr19, Lr32, Lr29 and Lr52 and virulent to Lr15, while they differed in their reactions to Lr2b, Lr3bg, Lr14b, Lr20, Lr23, Lr25 and Lr28. Virulence for Lr21 was detected for the first time in Canada from five different virulence phenotypes, though at a low frequency (3.8%). This finding has implications for wheat breeding in Canada, since Lr21 had been completely effective since its release in the cultivar ‘AC Cora’ in 1994.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".