Early Postemergence Herbicide Tank-Mixtures for Control of Waterhemp Resistant to Four Herbicide Modes of Action in Corn
Bibliographic record
Abstract
Multiple-herbicide-resistant (MHR) waterhemp has been confirmed and is difficult to control for growers in Ontario, Canada and in the Midwestern United States. The objective of this study was to evaluate early post-emergence (EPOST) herbicides for control of MHR waterhemp in field corn. Five field trials were conducted over a two-year period (2019, 2020) at sites on Walpole Island, ON and near Cottam, ON, Canada. Thirteen herbicide tank-mixtures containing multiple modes-of-action (MOA) were applied EPOST to 5 cm MHR waterhemp in field corn. Control of MHR waterhemp varied by site due to variable plant density, plant biomass, and number of herbicide-resistant individuals across research sites and years. Control of MHR waterhemp ranged from 90% to 100% with glyphosate + S-metolachlor/mesotrione/ bicyclopyrone/atrazine, glyphosate/2,4-D choline + rimsulfuron + mesotrione + atrazine, glyphosate + S-metolachlor/atrazine/mesotrione, glyphosate + mesotrione + atrazine, glyphosate/S-metolachlor/mesotrione + atrazine, glyphosate + S-metolachlor/mesotrione/bicyclopyrone, glyphosate/2,4-D choline + rimsulfuron + mesotrione, and glyphosate + pyroxasulfone + dicamba/atrazine at 4, 8, and 12 WAA. Control of MHR waterhemp ranged from 70% to 100% with glyphosate + topramezone/dimethenamid-P + dicamba/atrazine, glyphosate + isoxaflutole + atrazine, and glyphosate + tolpyralate + atrazine at 4, 8, and 12 WAA. Control of MHR waterhemp was similar for all herbicide programs, except glyphosate + dicamba/atrazine and glyphosate + S-metolachlor/atrazine which resulted in the lowest control at three of five sites that ranged from 63% to 89% and 61% to 76%, respectively. Crop injury was ≤10% for herbicide programs tested, except 28% to 31% corn injury with glyphosate/2,4-D choline + rimsulfuron + mesotrione + atrazine; however, without effect on corn grain yield. Corn yield was comparable with all herbicide programs evaluated in this study. It is concluded that there are herbicide programs that provide control of emerged and full-season residual control of MHR waterhemp in field 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 | 0.000 | 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 | 0.001 | 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".