Postemergence Herbicide Applications Impact Canada Thistle Control and Spring Wheat Yields
Bibliographic record
Abstract
Canada thistle ( Cirsium arvense L.) growing in spring wheat ( Triticum aestivum ) is difficult to control for several reasons. First, it is a perennial weed that has an extensive root system. Second, the cash‐crop wheat prevents the use of many chemicals, and third, Canada thistle is becoming resistant to many single action herbicides. The objective of this study was to evaluate the effect of postemergence herbicide applications on Canada thistle control growing in a spring wheat field. Replicated studies conducted in Russia between 2015 and 2017 evaluated the impact of different herbicide mixtures on Canada thistle control. The formulated mixtures of (iodosulfuron/mesosulfuron/antidote mefenpyr‐diethyl) mixed with triasulfuron and metsulfuron and triasulfuron + metsulfuron increased wheat yields 48 to 60% and provided the greatest (>85%) Canada thistle suppression in all experiments. Generally, (aminopyralid/florasulam), triasulfuron and (2,4‐D/florasulam) provided little control. It can be concluded that in all treatments, the herbicide mixtures did not provide 100% control, and therefore care must be used to prevent the creation of herbicide resistant Canada thistle. Core Ideas Formulated mixtures of herbicides containing (iodosulfuron/mesosulfuron/antidote mefenpyr‐diethyl) and triasulfuron plus metsulfuron provided the most effective Canada thistle suppression. Canada thistle was better controlled at the early stage of spring wheat. Herbicide mixtures containing multiple modes of action was more effective than a single mode of action herbicide in the control of Canada thistle in 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) | 0.001 | 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 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".