Control of Volunteer Glyphosate-Resistant Corn in Soybean With Clethodim Plus Adjuvants
Bibliographic record
Abstract
In Ontario, volunteer glyphosate-resistant (GR) corn is one the most common annual grass escapes in GR soybean sprayed with glyphosate. Six field experiments were established in southwestern Ontario during 2021 and 2022 to determine volunteer GR corn control in soybean with glyphosate (900 g ae ha-1) + clethodim (45 g ai ha-1) plus three adjuvants. At 1, 2, and 4 WAA, there was no visible soybean injury from the herbicide treatments evaluated. At 1 WAA, glyphosate + clethodim controlled volunteer GR corn 23%; the addition of the adjuvants Amigo®, Journey HSOC®, and StrikeLock® at 0.5% v/v improved control to 45 to 49%; there was no statistical difference in volunteer corn control among the adjuvants evaluated. At 2 WAA, glyphosate + clethodim controlled volunteer GR corn 23%; the addition of the adjuvants Amigo®, Journey HSOC®, and StrikeLock® at 0.5% v/v improved the control to 73 to 79%; there was no statistical difference in volunteer corn control among the adjuvants evaluated. At 4 WAA, glyphosate + clethodim controlled volunteer GR corn 16%; the addition of the adjuvants Amigo®, Journey HSOC®, and StrikeLock® at 0.5% v/v improved the control to 91 to 95%; there was no statistical difference in volunteer corn control among the adjuvants evaluated. Volunteer corn interference reduced soybean yield by up to 23% in this trial (highest yielding treatment compared to the non-treated control). Reduced volunteer corn interference with clethodim increased soybean yield 13%. Reduced volunteer corn interference with clethodim plus an adjuvant increased soybean yield 27 to 31%. This study concludes that the addition of Amigo®, Journey HSOC®, or StrikeLock® to clethodim improves volunteer GR corn control resulting in a concomitant increase in soybean yield.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".