Glyphosate-Resistant Canada Fleabane Control in Winter Wheat with Postemergence Herbicides
Bibliographic record
Abstract
In recent years, there has been a rapid increase in the number of herbicide-resistant weeds, including glyphosate-resistant (GR) biotypes in Ontario, Canada. A total of six field experiments were conducted over a two-year period (2018 and 2019) to determine the control of GR Canada fleabane ( Conyza canadensis (L.) Cronq.) with currently available herbicides for winter wheat in Ontario. Winter wheat was not injured with any of the herbicides evaluated. Among herbicides evaluated, pyrasulfotole/bromoxynil (preformulated), 2,4-D ester, halauxifen, fluroxypyr/halauxifen (preformulated) + MCPA, pyrasulfotole/bromoxynil/fluroxypyr (preformulated), pyrasulfotole/bromoxynil/thiencarbazone (preformulated), pyrasulfotole/bromoxynil/thiencarbazone + MCPA, and fluroxypyr/halauxifen + pyroxsulam + MCPA controlled GR Canada fleabane 94–100% at 8 weeks after application (WAA) and reduced density 95–100% and biomass 97–100%. Reduced GR Canada fleabane interference with pyrasulfotole/bromoxynil/thiencarbazone + MCPA increased winter wheat yield 27% compared to the weedy control. GR Canada fleabane interference had no adverse effect on winter wheat yield with all other treatments. Based on these results, herbicide treatments that include 2,4-D, pyrasulfotole, or halauxifen can adequately control GR Canada fleabane in winter wheat.
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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 | 0.000 | 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) | 0.000 | 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".