1 Molecular marker analysis of Lr34 in Canada Western Red
Bibliographic record
Abstract
The leaf rust resistance gene Lr34 is an important component of the leaf rust resistance in Canadian wheat cultivars. It has provided effective resistance since it was incorporated into the cultivar Glenlea, registered in 1972. The Canada Western Red Spring (CWRS) wheat class is the predominant wheat class in Canada. The objective of this study was to analyze the molecular marker profiles of an historic collection of CWRS cultivars for microsatellite markers closely linked to Lr34. Cultivars released from 1900 to 2004 were included in the collection. These results were compared with genetic analyses of the leaf rust resistance in selected cultivars and with field leaf rust severity for these cultivars. Laura, registered in 1986, was the first major CWRS cultivar to carry Lr34, but since that time it has been incorporated into many of the leading CWRS cultivars. The cultivars Katepwa, AC Barrie, and Superb which were the most popular cultivars in the 1980s, 1990s and 2000s, respectively, all had the susceptible allele at the Lr34 locus. Even though these cultivars had other genes for leaf rust resistance, they were overcome by the Puccinia triticina population and they suffered significant losses due to leaf rust. If Lr34 had been present in these cultivars the losses would have been reduced. Determining the presence of Lr34 in CWRS cultivars will help ensure that this important resistance gene is incorporated into future CWRS cultivars.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.001 | 0.001 |
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".