Evaluation of disease, yield and economics associated with fungicide timing in Canadian Western Red Spring wheat
Bibliographic record
Abstract
Protection from fungal plant pathogens is key for optimizing the yield and quality of wheat (Triticum aestivum L.). However, current grower practices and historical research do not always align with respect to optimum fungicide timing to maximize disease control, yield, quality, and profitability of Canadian Western Red Spring (CWRS) wheat. Six fungicide treatments were evaluated at eight site–years across Alberta in 2018 and 2019 to determine the optimum time for fungicide application. The treatments included early fungicide applications at BBCH 22–23 (herbicide timing), early- to mid-season application at BBCH 30–32 (plant growth regulator timing), ‘traditional’ timing at BBCH 39–45 (flag leaf), and head timing at BBCH 61–63 (Fusarium head blight timing) and were compared with a non-treated control. Yield responses to fungicide treatments occurred at 50% of the site–years when disease pressure was 32% higher than in non-responsive site–years. Responsive site–years were characterized by higher relative humidity (65.4%–74.0%) and an average 273 mm of precipitation. At responsive site–years, McFadden leaf spot disease severity ratings were 50% greater in early August when fungicides were applied at BBCH 22–23 and 30–32 versus at BBCH 39–45. At responsive sites, yield and thousand-kernel weight were 9.3% and 5.2%, higher, respectively, for fungicide applications at BBCH 39–45 and BBCH 61–63 compared with fungicide applications at BBCH 22–23 and BBCH 30–32. The most economically beneficial practices were applications of propiconazole, benzovindiflupyr and azoxystrobin (Trivapro A+B) at BBCH 39–45 or prothioconazole and tebuconazole (Prosaro XTR) at BBCH 61–63 when environmental conditions were conducive for disease development.
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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 | 0.000 |
| 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".