The inheritance of leaf rust resistance in the wheat cultivars ‘Superb’, ‘McKenzie’ and ‘HY644’
Bibliographic record
Abstract
Understanding the genetic resistance to wheat leaf rust, caused by Puccinia triticina, in Canadian wheat cultivars is critical for maximizing resistance in future-bred cultivars. This knowledge also helps to predict the impact of changes in virulence to specific resistance genes within the P. triticina population. ‘Superb’ and ‘McKenzie’ are two of the most popular high-yielding wheat cultivars in Canada. ‘HY644’ has moderate resistance to Fusarium head blight (caused primarily by Fusarium graminearum). All three of these cultivars have been used extensively as parents in Canadian wheat breeding programmes. To analyze the nature of resistance in these cultivars, they were crossed and then backcrossed to the susceptible cultivar ‘Thatcher’. The BC1F3 populations were inoculated at the seedling and adult plant stages with various P. triticina races to determine the number and identity of the resistance genes in each cultivar. Allelism tests, to confirm the postulated genes, were performed by crossing each cultivar to the ‘Thatcher’ isolines containing the postulated genes and analyzing the F2 progeny for rust resistance. ‘Superb’ was demonstrated to have genes Lr2a and Lr10, ‘McKenzie’ had Lr10, Lr13, Lr16 and Lr21, and ‘HY644’ had Lr1, Lr17, Lr34 and an unknown resistance gene.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".