What Are the Most Efficacious Herbicides Applied Preplant for Control of Multiple-Herbicide-Resistant Canada Fleabane in Corn?
Bibliographic record
Abstract
New weed management strategies are needed to effectively control multiple-herbicide-resistant (MHR) Canada fleabane in corn. Five experiments were established in growers’ corn fields with confirmed MHR Canada fleabane to determine the efficacy of various herbicides applied preplant (PP). In 2021 environments, glyphosate + isoxaflutole + atrazine, glyphosate + isoxaflutole/diflufenican + atrazine, glyphosate + S-metolachlor/atrazine/mesotrione/bicyclopyrone, glyphosate + mesotrione + atrazine, glyphosate/dicamba + isoxaflutole/diflufenican, glyphosate/dicamba + isoxaflutole/diflufenican + atrazine, and glyphosate + saflufenacil/dimethenamid-p provided excellent control (90-100%) of MHR Canada fleabane but glyphosate + S-metolachlor/mesotrione/bicyclopyrone and glyphosate + S-metolachlor/atrazine/mesotrione controlled MHR Canada fleabane 77-84% and 87-96%, respectively at 4, 8, and 12 weeks after application (WAA). Herbicide tankmixes evaluated reduced MHR Canada fleabane density and biomass 91-100%. In 2022 environments, all glyphosate tankmixes evaluated provided 97-100% control, 99-100% density reduction, and 100% biomass reduction of MHR Canada fleabane in corn. In 2021 and 2022 environments MHR Canada fleabane interference reduced corn yield 41 and 32%, respectively; reduced MHR Canada fleabane interference with all herbicide treatments resulted in corn yield similar with the weed-free control. Results of this study indicate that glyphosate + isoxaflutole + atrazine, glyphosate + isoxaflutole/diflufenican + atrazine, glyphosate + S-metolachlor/atrazine/mesotrione/bicyclopyrone, glyphosate + mesotrione + atrazine, glyphosate/dicamba + isoxaflutole/diflufenican, glyphosate/dicamba + isoxaflutole/diflufenican + atrazine, and glyphosate + saflufenacil/dimethenamid-p provide excellent and consistent control of MHR Canada fleabane. However, glyphosate + S-metolachlor/atrazine/mesotrione and glyphosate + S-metolachlor/mesotrione/bicyclopyrone do not provide consistent control of MHR Canada fleabane in corn.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".