Effect of fungicide combinations for FHB control on disease incidence, grain yield and quality of winter wheat, spring wheat and barley
Bibliographic record
Abstract
This study investigates the effects of timing of fungicide applications alone or in combinations on Fusarium head blight (FHB), seed deoxynivalenol (DON) concentrations, dominant leaf diseases, grain yield, and thousand-kernel weight in winter wheat, spring wheat, and barley in the Atlantic region of Canada. The experiments were conducted for 3 yr (2010–2012), with fungicide treatment as the main factor. Selected commercially available fungicide treatments were applied at two timings: (i) Zadoks growth stage (ZGS) 39: check, propiconazole + trifloxystrobin (125 g ha−1), propiconazole (125 g ha−1), and pyraclostrobin (100 g ha−1); and (ii) ZGS 60: check, prothioconazole (200 g ha−1), prothioconazole + tebuconazole (200 g ha−1), and metaconazole (90 g ha−1). Results show that a single fungicide application was not sufficient to achieve a high yield with good seed quality. Reduction of visual FHB infection due to fungicide applications did not guarantee a reduction in seed DON concentrations. Fungicide application pyraclostrobin at ZGS 39 and prothioconazole + tebuconazole at ZGS 60 was the best treatment, consistently providing the highest crop yield and seed quality, including lowered DON.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".