Blackleg (Leptosphaeria maculans) Severity and Yield Loss in Canola in Alberta, Canada
Bibliographic record
Abstract
Blackleg, caused by Leptosphaeria maculans, is an important disease of oilseed rape (Brassica napus L.) in Canada and throughout the world. Severe epidemics of blackleg can result in significant yield losses. Understanding disease-yield relationships is a prerequisite for measuring the agronomic efficacy and economic benefits of control methods. Field experiments were conducted in 2013, 2014, and 2015 to determine the relationship between blackleg disease severity and yield in a susceptible cultivar and in moderately resistant to resistant canola hybrids. Disease severity was lower, and seed yield was 120%-128% greater, in the moderately resistant to resistant hybrids compared with the susceptible cultivar. Regression analysis showed that pod number and seed yield declined linearly as blackleg severity increased. Seed yield per plant decreased by 1.8 g for each unit increase in disease severity, corresponding to a decline in yield of 17.2% for each unit increase in disease severity. Pyraclostrobin fungicide reduced disease severity in all site-years and increased yield. These results show that the reduction of blackleg in canola crops substantially improves yields.
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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 | 0.001 | 0.000 |
| 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".