Fall-applied residual herbicides improve broadleaf weed management in ultra-early wheat (<i>Triticum aestivum</i> L.) production systems on the northern Great Plains
Bibliographic record
Abstract
Ultra-early spring wheat ( Triticum aestivum L.) planting systems based on soil temperature on the northern Great Plains have lower overall variability in grain yield, and can increase grain yield relative to current calendar date-based spring wheat planting systems used in the region. However, ultra-early planting when soils are cold (2 °C), and resulting early crop emergence, precludes most foliar pre-seeding weed control options. Field trials were conducted at three sites in western Canada from 2017 to 2019 to evaluate the crop safety, broadleaf weed efficacy, and growing system stability resulting from the inclusion of fall applications of soil-applied residual herbicides prior to planting wheat ultra-early the following spring. Flumioxazin (protoporphyrinogen oxidase inhibitor; Weed Science Society of America (WSSA) group 14) and pyroxasulfone (very long chain fatty acid synthesis inhibitor; WSSA group 15) were applied alone and in combination at multiple rates in the late fall prior to ground freeze. The following spring, hexaploid spring wheat was planted ultra-early, based on a soil temperature trigger of 2 °C, and later, triggered by a soil temperature of 8 °C. When planting was completed ultra-early, grain yield was greater, and variability of grain yield was lower. Herbicide treatments increased broadleaf weed control, and in some environments further increased grain yield and reduced grain yield variability without resulting in phytotoxicity. The ability to safely incorporate fall-applied residual herbicides into ultra-early spring wheat planting systems provides an option for growers to adopt ultra-early planting without negatively impacting weed management on their farms.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".