Climatic and agronomic effects on leaf spots of spring wheat in the western Canadian Prairies
Bibliographic record
Abstract
Leaf spots (LS) of wheat continue to be widespread in western Canada. Most registered cultivars do not have a good level of resistance, thus it is important to evaluate the impact of agronomic practices. This study examined LS severity of spring wheat in a cropping sequence trial under conservation tillage, and compared it to results from two other agronomic trials conducted under different environmental conditions in the same area two decades earlier. In the present study, wheat grown after fallow generally had lower LS severity than wheat grown after another wheat crop, regardless of the sequence, with wheat grown after non-cereals (crop or green manure) having among the lowest disease levels. In most cases there were no differences in disease within phases of each sequence. Grain yield was highest in wheat grown after fallow or green manure than in wheat grown after another wheat, regardless of the sequence. Some of these results were different than those reported from studies conducted before, under conventional or conservation tillage, in particular in regards to disease levels after a fallow year, and the frequency of Pyrenophora tritici-repentis and Phaeosphaeria nodorum. Climatic conditions in the years of the present study (2010–2013) were different than when the previous studies were conducted (1993–1996), especially in regards to temperatures over the previous fall/winter and precipitation in the growing season, which were all higher in the most recent period. How these differences might have affected the survival and reproduction of the LS pathogens, and disease development, are discussed.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".