Halauxifen-methyl controls glyphosate-resistant horseweed (<i>Conyza canadensis</i>) but not giant ragweed (<i>Ambrosia trifida</i>) in winter wheat
Bibliographic record
Abstract
Abstract Horseweed is a competitive summer or winter annual weed that produces up to 230,000 small seeds per plant that are capable of traveling more than 500 km via wind. Giant ragweed is a tall, highly competitive summer annual weed. Glyphosate-resistant (GR) horseweed and GR giant ragweed pose significant challenges for producers in the United States and Ontario, Canada. It is thought that an integrated weed management (IWM) system involving herbicide rotation is required to control GR biotypes. Halauxifen-methyl is a new selective broadleaf POST herbicide registered for use in cereal crops; there is limited information on its efficacy on horseweed and giant ragweed. The purpose of this research was to determine the efficacy of halauxifen-methyl applied POST, alone and in a tank mix, for the control of GR horseweed and GR giant ragweed in wheat across southwestern Ontario. For each weed species, an efficacy study consisting of six field experiments was conducted over a 2-yr period (2018, 2019). At 8 wk after application (WAA), halauxifen-methyl, fluroxypyr/halauxifen-methyl, fluroxypyr/halauxifen-methyl + MCPA EHE, fluroxypyr + MCPA ester, 2,4-D ester, clopyralid, and pyrasulfotole/bromoxynil + ammonium sulfate controlled GR horseweed >95%. Fluroxypyr and MCPA provided only 86% and 37% control of GR horseweed, respectively. At 8 WAA, fluroxypyr, fluroxypyr/halauxifen-methyl, fluroxypyr/halauxifen-methyl + MCPA EHE, fluroxypyr + MCPA ester, fluroxypyr/halauxifen-methyl + MCPA EHE + pyroxsulam, 2,4-D ester, clopyralid, and thifensulfuron/tribenuron + fluroxypyr + MCPA ester controlled GR giant ragweed 87%, 88%, 90%, 94%, 96%, 96%, 98%, and 93%, respectively. Halauxifen-methyl and pyroxsulam provided only 45% and 28% control of GR giant ragweed, respectively. Halauxifen-methyl applied alone POST in the spring controlled GR horseweed but not GR giant ragweed in winter wheat.
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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 | 0.000 |
| 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 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".