Two-Pass Weed Management with Preemergence and Postemergence Herbicides in Glyphosate-Resistant Soybean
Why this work is in the frame
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Bibliographic record
Abstract
There is little information on the efficacy and profitability of two-pass weed control strategies in soybean when a preemergence (PRE) residual herbicide is followed by glyphosate applied late postemergence (LPOST) under Ontario, Canada environmental conditions. Ten field trials were conducted during 2011-2013 in Ontario, Canada to determine the level of weed control, yield and net returns of various preemergence/postemergence programs in glyphosate-resistant soybean. Crop injury was 2% or less with the herbicides evaluated except for chlorimuron + flumioxazin (PRE) and pyroxasulfone + flumioxazin (PRE) which caused 4% and 7% visible injury in soybean, respectively. A single application of glyphosate resulted in variable weed control (73% - 98%) while the sequential application of glyphosate provided excellent weed control (98% - 100%). The control of all weeds 8 WAA after the LPOST glyphosate application was equivalent regardless of the PRE herbicide applied (96% - 100%). Soybean yield was equivalent to the weed free control regardless of the PRE herbicide applied. Soybean yield was lower than the sequential application of glyphosate with chlorimuron or pyroxasulfone/flumioxazin PRE fb glyphosate LPOST. Generally net return with the two-pass programs was equivalent to the sequential application of glyphosate. Net returns were lower than the sequential application of glyphosate with chlorimuron or s-metolachlor + flumetsulam followed by glyphosate LPOST. Based on these results, a sequential application of glyphosate or a two-pass program of a preemergence residual herbicide followed by glyphosate LPOST are the preferred weed management programs in glyphosate-resistant soybean. The two-pass programs have the potential to reduce selection pressure for glyphosate-resistant weeds.
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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 | 0.000 |
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 it