Combating a dynamic wheat rust population in Canada
Bibliographic record
Abstract
Wheat leaf rust, caused by Puccinia triticina Erikss., is one of the most common and damaging diseases of wheat in Canada and throughout the world. To understand the P. triticina population virulence analysis of the population in Canada has been conducted annually for over 80 years. The virulence profile of the P. triticina population and virulence to key resistance genes changes significantly over time, and differs between regions. Recently, genetic analysis via DNA sequencing of representative isolate from the P. triticina populations from 2018 to 2022 initially revealed three diverse groups in Canada. All isolates within group one had the same two mating type alleles, group two isolates all had a second combination of alleles, whereas group three isolates were partitioned into eight subgroups encompassing different genetic clades. A fourth distinct group was later found from British Columbia. To combat leaf rust, the resistance genes Lr2a, Lr13, Lr14a, Lr16, Lr21, and Lr34 have been used extensively in Canadian spring wheat cultivars. Lr34, Lr46, and Lr67 are unique among resistance genes in that they are non-race-specific, conditioning partial resistance to all isolates, while also providing resistance to other wheat diseases. Critically, Lr34 and Lr67 were demonstrated to confer resistance to Fusarium head blight. The complete picture underlying Lr34 functions is not fully understood, but only Lr34res lines accumulate the fungistatic compound 1- O- p-coumaroyl-3- O-feruloylglycerol. Lr34 also produces leaf tip necrosis; this is enhanced at low temperatures. Combinations of race-specific leaf rust resistance genes, with Lr34, Lr46, and/or Lr67, have the best potential to protect wheat from a dynamic Canadian leaf rust population.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".