Effect of Seed Treatment on Early Season Brown Spot Caused by <i>Septoria glycines</i> of Soybean
Bibliographic record
Abstract
Early season brown spot caused by Septoria glycines was compared in Illinois, Indiana, Iowa, Michigan, and Ontario, Canada, soybean fields planted with differing commercial seed treatments. Seed treatments that included fluopyram significantly reduced brown spot (P < 0.001). A greenhouse mist chamber experiment revealed that fluopyram seed treatment reduced the Area Under Disease Progress Curve of brown spot over a 6-week period (P < 0.001). Brown spot severity was unaffected by plant age at inoculation for the control treatment without fluopyram (P = 0.911); however, severity increased with plant age at inoculation for the fluopyram treatment (P = 0.009). The sensitivity of two S. glycines isolates to fluopyram was assessed by determining the effective concentration required to reduce its colony diameter growth in culture by 50% (EC50). Both isolates had an EC50 of 0.41 μg/ml of fluopyram. These results demonstrate that fluopyram seed treatment is effecttive at controlling early season brown spot in soybean. Accepted for publication 19 September 2016.
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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".