Control of Glyphosate-Resistant Horseweed (<i>Conyza canadensis</i>) with Dicamba Applied Preplant and Postemergence in Dicamba-Resistant Soybean
Bibliographic record
Abstract
Herbicide-resistant crops, such as glyphosate-resistant (GR) soybean, allow for broad-spectrum, flexible weed control with minimal crop injury; however, the development of GR weeds, such as horseweed, has forced reliance on alternative herbicides for control of these weeds. While preplant (PP) herbicides provide excellent control of GR-horseweed, there are currently no POST herbicide control options within soybean. The objective of this study was to evaluate the efficacy of dicamba for the control of GR-horseweed when applied PP, POST, and sequentially in dicamba-resistant soybean. Dicamba applied PP at 600 g a.e. ha−1provided 90 to 100% control of GR-horseweed 8 wk after application (WAA) across three field trials conducted in Ontario in 2011 and 2012. Similarly, sequential applications provided 91 to 100% control. This technology provides a much-needed POST option of dicamba to be applied as a rescue treatment to control weed escapes caused by late emergence or poor initial control following a PP herbicide application.
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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 | 0.000 | 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".