Multiple herbicide-resistant waterhemp control with Group 15 herbicides
Bibliographic record
Abstract
Abstract Waterhemp has evolved resistance to seven herbicide modes of action in the United States and to five in Canada, which limits weed control options for producers. The objective of this research was to quantify the level and duration of residual control of multiple herbicide-resistant (MHR) waterhemp with five Group 15 herbicides (acetochlor, dimethenamid-p, flufenacet, pyroxasulfone, and S -metolachlor) applied preemergence in a non-crop area. Four field trials were conducted over a 2-yr period (2021, 2022) in southwestern Ontario, Canada. By 4 wk after application (WAA) 91% of waterhemp had emerged in the nontreated control area. The numerical control of waterhemp with all Group 15 herbicides, with the exception of pyroxasulfone, was greatest at 4 WAA, then control declined. Flufenacet provided the lowest waterhemp control; dimethenamid-p and S -metolachlor provided intermediate control, and acetochlor and pyroxasulfone provided the highest control. Waterhemp control with pyroxasulfone peaked at 6 WAA with 99% and declined to 77% at 12 WAA. Flufenacet (low and high rates) was predicted to reduce waterhemp emergence by 50% for 42 to 44 d after application (DAA). Dimethenamid-p, S -metolachlor, and acetochlor (both formulations and three rates) were predicted to reduce waterhemp emergence by 80% for 36, 43, and 33 to 51 DAA, respectively; in contrast, pyroxasulfone was predicted to reduce waterhemp emergence by 80% for 82 DAA. This study concludes that of the Group 15 herbicides evaluated, flufenacet provides the lowest and shortest residual control of waterhemp, and pyroxasulfone provides the highest and longest residual control of waterhemp.
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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 | 0.001 |
| 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 | 0.001 |
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".