Relationship Between Efficacy of Fusarium Head Blight Chemical Control and Deoxynivalenol Contamination on Wheat Kernels
Bibliographic record
Abstract
In field experiment carried out in the 2018 growing season we tried to show the inverse relation between the efficacy of fusarium head blight (FHB) chemical control and the deoxynivalenol (DON) concentration in harvested kernels. The wheat cultivar Tbio Mestre was established under no-till in soybean residues and in winter rotation with black oats. The leaf rust and yellow spot control was performed during the vegetative stage by spraying the whole experimental area with three applications of epoxiconazole + krezoxim methyl (0.7 L/ha). The most potent fungicides metconazole + pyraclostrobin (1.0 L/ha) + mancozeb (2.0 kg/ha), prothioconazole + trifloxystrobin (0.4 L/ha) and pydiflumetofen (1.0 L/ha) were compared to control FHB. Disease incidence in spikes, incidence in spikelets, or spikes severity, grain weight and yield were evaluated. DON concentration was. Using the most efficient technology available for FHB control, the hypothesis of the inverse relationship between disease intensity occurring naturally in spikes, and deoxinivalenol (DON) concentration in the harvested grains was confirmed. DON concentration in unsprayed grains was 3,675 and in the best treatments 821 to 1,067 ppb.
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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 | 0.000 | 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".