Annual ryegrass control prior to seeding corn with glyphosate plus group 2 herbicides
Bibliographic record
Abstract
Abstract Control of fall‐seeded annual ryegrass ( Lolium multiflorum Lam) cover crops with spring‐applied herbicides prior to seeding corn ( Zea mays L.) has been variable. Improved herbicide options are needed in order to increase the consistency of annual ryegrass termination prior to seeding corn. Four field experiments were conducted over a 2‐yr period (2018, 2019) in Ontario, Canada, to evaluate the control of fall‐seeded annual ryegrass cover crops with various corn herbicides, applied prior to seeding corn in the spring. Based on visual estimates, glyphosate alone controlled annual ryegrass 80% at 6 weeks after application (WAA). Acetolactate synthase (ALS) inhibitor herbicides, foramsulfuron, nicosulfuron, rimsulfuron, and nicosulfuron/rimsulfuron controlled annual ryegrass 82, 71, 88, and 88%, respectively, at 6 WAA. The tankmix of glyphosate with foramsulfuron, nicosulfuron, rimsulfuron, or nicosulfuron/rimsulfuron controlled annual ryegrass 94–98% at 6 WAA. Glyphosate reduced annual ryegrass density 73%; in contrast, foramsulfuron, nicosulfuron, rimsulfuron, and nicosulfuron/rimsulfuron did not reduce annual ryegrass density compared to the weedy control. The tankmix of glyphosate plus an ALS inhibitor herbicide reduced annual ryegrass density 88−94%. Reduced annual ryegrass interference with glyphosate applied alone resulted in an increase in corn yield of 86% compared to the control. Reduced annual ryegrass interference with foramsulfuron, nicosulfuron, rimsulfuron, and nicosulfuron/rimsulfuron applied alone resulted in an increase in corn yield 61, 61, 93, and 91%, and 98, 105, 95, and 98% when co‐applied with glyphosate, respectively. The tankmix of glyphosate with an ALS inhibitor herbicide resulted in excellent (>90%) annual ryegrass control and increased corn yield.
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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 | 0.000 | 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) | 0.000 | 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".