Evaluation of foliar fungicide application methods on soybean
Bibliographic record
Abstract
A field trial was conducted at Fargo, North Dakota, in 2005 and 2006 to evaluate different fungicide application methods on soybean (Glycine max). Kromekote® paper cards were placed in the upper and lower canopy of soybean plants, and tebuconazole fungicide mixed with a blue dye was sprayed with different application methods at the R5 developmental stage. The applications were made with a conventional sprayer with Turbo TeeJet® 110015 flat-fan nozzles at 276 kPa liquid pressure, a conventional sprayer with XR TeeJet® 80015 flat-fan nozzles at 276 kPa liquid pressure, an AirJet® bifluid nozzle spray system with liquid pressure at 276 kPa and air pressure at both 76 and 48 kPa, or an air-assisted spray system with liquid pressure at both 221 and 83 kPa. An untreated control was also included to evaluate the effect of tebuconazole on soybean yield. Dye-sensitive Kromekote paper cards were analyzed to determine the percent coverage and the volume median diameter (VMD) of the droplets. Significant (P ≤ 0.05) interactions between year and application method were detected, most likely resulting from differences in plant height and development between the years. Droplet coverage in the upper canopy did not differ in either year among the application methods. Most application methods provided similar droplet coverage in the lower canopy in 2005, but the conventional sprayer with XR TeeJet 80015 flat-fan nozzles provided the greatest coverage in the lower canopy in 2006. Correlation analysis indicated that droplet coverage in the lower canopy increased with increased VMD of the droplets in 2005 (R = 0.91), and that yield increased with increased fungicide coverage in 2006 (R = 0.85). Visible symptoms of foliar fungal diseases were not present in either year, and tebuconazole had no effect on soybean yield, compared with the untreated control in either year.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".