Evaluation of five fungicide application timings for control of leaf-spot diseases and fusarium head blight in hard red spring wheat
Bibliographic record
Abstract
The optimum timing of fungicide applications for control of leaf-spot diseases in hard red spring wheat (HRSW) is reported to be at Zadok's growth stage 39 (GS 39; flag leaf collar visible), while the optimum timing for suppression of fusarium head blight (FHB) is at GS 60 (beginning of anthesis). The objectives of this research were the following: (i) to compare five different timings of fungicide applications for control of common leaf-spot diseases and FHB and (ii) to evaluate whether the tested HRSW cultivars could be grouped based on their disease ratings to formulate recommendations for the use of fungicides. Across cultivars, the optimum timing of a fungicide application to control leaf diseases was at GS 60 rather than at GS 39. Waiting until flowering did not sacrifice control of the leafspot diseases or grain yield. The application of one half of the labeled rate of Stratego at GS 15 (fifth leaf unfolded) in combination with the labeled rate of Folicur at GS 60 tended to provide the best control of the leaf-spot diseases and greatest improvement in grain yield and grain quality. The average increase in grain yield with this combination of fungicide treatments was 11%, 31%, and 16% across varieties in 2001, 2002, and 2003, respectively. When the leafspot diseases developed early, as was the case in 2002, a single application at GS 60 was less effective than applications both at GS 15 and GS 60 for cultivars that were rated more susceptible to leaf-spot diseases. Even when differences were detected for disease severity of the leaf-spot diseases at GS 85 (soft dough), no differences were detected for grain yield, grain volume weight, grain protein, or kernel weight between cultivars that were rated more susceptible to the leaf-spot diseases versus those that were rated more resistant.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".