Efficacy of Fall- and Spring-Applied Pyroxasulfone For Herbicide-Resistant Weeds in Field Pea
Bibliographic record
Abstract
Field trials were initiated in fall 2011 to determine the potential of pyroxasulfone to control acetolactate synthase (ALS) inhibitor-resistant weeds in field pea. Pyroxasulfone was applied in split-plot trials at five locations in western Canada using fall and PRE spring applications of 0 to 400 g ai ha−1. Trial locations were chosen with a range of soil organic matter content: 2.9, 4.3, 5.5, 10.5, and 10.6% at Scott, Kernen, Kinsella, Melfort, and Ellerslie, respectively. The herbicide dose required to reduce biomass by 50% (ED50) in false cleavers ranged between 53 and 395 g ha−1at Scott and Ellerslie, respectively. Wild oat ED50s varied between 0.54 g ha−1at Scott in the fall and 410 g ai ha−1in the spring at Melfort. ED50s for wild oat and false cleavers varied by 7.4- and 746-fold, respectively, depending primarily on the organic matter content at the trial location. The effect of application timing was not consistent. Significant yield reductions and pea injury occurred at 150 and 100 g ha−1and higher at Kernen and Scott, respectively. Low organic matter and high precipitation levels at these locations indicates increased herbicide activity under these conditions. Pyroxasulfone may allow control of ALS inhibitor-resistant false cleavers and wild oat; however, locations with high soil organic matter will require higher rates than those with low organic matter for similar control levels.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".