Efficacy of Pre-Emergence and Post-Emergence Soybean Herbicides for Control of Glufosinate-, Glyphosate-, and Imidazolinone-Resistant Volunteer Corn
Bibliographic record
Abstract
Glyphosate-resistant corn and soybean are grown in rotations in the Midwest, including Nebraska. Volunteer corn is a problematic weed in soybean fields because it causes harvest problems, reduces yield and seed quality, and potentially harbors insects, pests, and diseases. Several pre-packaged herbicides have been registered in soybean in recent years, but response of volunteer corn to these herbicides has not yet been documented. Greenhouse experiments were conducted to evaluate the response of glufosinate-, glyphosate-, and imidazolinone-resistant volunteer corn to 20 pre-emergence (PRE) and 17 post-emergence (POST) soybean herbicides. Cumulative emergence of volunteer corn was not affected by PRE soybean herbicides compared with the nontreated control regardless of herbicide-resistant trait at 21 days after treatment (DAT). Although comparable with several other treatments, clomazone provided ? 90% control of glufosinate- and imidazolinone-resistant volunteer corn at 21 DAT. The POST soybean herbicides were applied when volunteer corn plants were at the 2 to 3 or 5 to 6 leaf stage. The ACCase-inhibiting herbicides, including clethodim, fenoxaprop plus fluazifop, fluazifop, quizalofop, and sethoxydim, provided ? 96 and ? 85% control of the 2 to 3 or 5 to 6 leaf stage volunteer corn, respectively, regardless of the herbicide-resistance trait at 28 DAT. Glyphosate tank mixed with acifluorfen, chlorimuron-ethyl, or imidazolinones usually provided > 83% control of glufosinate-and imidazolinone-resistant volunteer corn when sprayed at the 2 to 3 leaf stage at 28 DAT, but control was ? 71% for the 5 to 6 leaf stage volunteer corn. Similar results were usually reflected in volunteer corn biomass. It is concluded that PRE soybean herbicides partially controlled volunteer corn; therefore, ACCase inhibiting herbicides are the only highly effective option for soybean growers.
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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 | 0.001 |
| 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".