Effect of Seeding Rate and Seed Treatment Fungicides on Agronomic Performance, Fusarium Head Blight Symptoms, and DON Accumulation in Two Winter Wheats
Bibliographic record
Abstract
Fusarium head blight (FHB), caused by Fusarium graminearum, is an important disease of wheat (Triticum aestivum). FHB reduces yield and quality, and the pathogen produces several toxins in the grain, the most important being deoxynivalenol (DON). In North America, the foliar fungicide tebuconazole is used to reduce FHB symptoms and DON accumulation. Because of the narrow window required for its application, uniform flowering of wheat is important. The objective of this study was to investigate the influence of variety, seeding rate, and seed treatment fungicides on the flowering period of winter wheat and their effect on FHB symptoms and DON accumulation. The seed of two winter wheat varieties (Pioneer 25W60 and Pioneer 25R57) was treated with Dividend XL (difeconazole+metalaxyl), Vitaflo 280 (thiram+carbathiin), Raxil (tebuconazole), and Baytan 30 (triadimenol) and planted at 320, 480, and 640 seeds per m2 for each treatment at Ridgetown, ON, Canada in 2000 and 2001. The plots were sprayed with tebuconazole at 50% anthesis and inoculated with F. graminearum 3 days later. Increased seeding rate increased the number of emerged plants, tillers, spikes per m2, and yield. All seed treatments, compared to nontreated controls, increased plant emergence and number of spikes per m2, and all except tebuconazole increased tillering and yield. Increased seeding rate decreased the length of flowering period. As flowering period increased, FHB index and DON level decreased, suggesting that greater infection was linked to more uniform flowering.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".