Broadleaf weed control and white clover response to florpyrauxifen-benzyl + 2,4-D and common pasture herbicides
Bibliographic record
Abstract
Abstract The combination of florpyrauxifen-benzyl + 2,4-D is a new, pre-packaged herbicide mixture for use in pastures and hayfields in the United States. Unlike many other pasture herbicides, florpyrauxifen-benzyl + 2,4-D is reported to preserve white clover. However, limited research exists on the efficacy of florpyrauxifen-benzyl + 2,4-D on common weed species and on the level of tolerance of white clover to it. Field trials were conducted in Virginia in 2018 to 2020 to evaluate control of various broadleaf weeds with florpyrauxifen-benzyl + 2,4-D compared to other commonly used herbicides. Field and greenhouse studies were also carried out to assess white clover tolerance. Weed species evaluated included bulbous buttercup, Canada thistle, horsenettle, and broadleaf plantain. Florpyrauxifen-benzyl + 2,4-D provided 75% to 99% control of all weeds 90 d after application except for horsenettle (56%), while causing the least white clover injury of any herbicide treatment that was evaluated. Spring herbicide applications resulted in greater bulbous buttercup control compared to fall applications, but florpyrauxifen-benzyl + 2,4-D provided greater than 81% control from both application timings. There were no differences in aboveground biomass between white clover varieties; however, all herbicides reduced white clover biomass compared to a nontreated control. This research suggests that florpyrauxifen-benzyl + 2,4-D can improve overall forage quality by controlling broadleaf weeds in mixed grass-legume stands while preserving white clover.
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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 | 0.000 |
| 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".