Seeding date and location affect winter wheat infection by common bunt (<i>Tilletia tritici</i> and <i>T. laevis</i>) in western Canada
Bibliographic record
Abstract
Gaudet, D. A., Puchalski, B. J., Despins, T., McCartney, C., Menzies, J. G. and Graf, R. J. 2013. Seeding date and location affect winter wheat infection by common bunt (Tilletia tritici and T. laevis) in western Canada. Can. J. Plant Sci. 93: 483–489. The majority of western Canadian winter wheat varieties are susceptible to common bunt (Tilletia tritici and T. laevis) and the risk to production, particularly in Saskatchewan and Manitoba, where the majority of production occurs, is unknown. Inoculated trials were employed to determine the effects of fall seeding date on bunt infection levels on one resistant and two susceptible winter wheat varieties at three locations in western Canada during three growing seasons from 2007/2008 to 2009/2010. Among the three locations, average infection levels were highest in Lethbridge, AB, followed by Glenlea, MB, and Saskatoon, SK. Later seeding resulted in high infection levels at all three locations in the susceptible varieties, particularly in Lethbridge, but high infection levels were observed in the earliest seeded treatments at both the Saskatchewan and Manitoba locations. The resistant variety Blizzard consistently exhibited infection levels of less than 3% infection across all environments. In a second test at conducted at Lethbridge, 10 of the 11 currently grown winter wheat varieties were susceptible to common bunt. These results indicate that there is a general risk of common bunt infection to winter wheat production across western Canada and that control measures must be taken until resistant varieties are developed.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".