Effect of Late-Season Herbicide Applications on Inflorescence and Seed Production of Glyphosate-Resistant Giant Ragweed (<i>Ambrosia trifida</i>)
Bibliographic record
Abstract
Giant ragweed is one of the most competitive annual broadleaf weeds in corn and soybean crop production systems in the United States and eastern Canada. Management of giant ragweed has become difficult due to the evolution of resistance to glyphosate and/or acetolactate synthase (ALS)-inhibitor herbicides and giant ragweed’s ability to emerge late in the season, specifically in the eastern Corn Belt. Late-season herbicide application may reduce seed production of weed species; however, information is not available about late-season herbicide applications on giant ragweed seed production. The objective of this study was to evaluate the effect of single or sequential late-season applications of 2,4-D, dicamba, glyphosate, and glufosinate on inflorescence injury and seed production of glyphosate-resistant (GR) giant ragweed under greenhouse and field conditions (bare ground study). Single and sequential applications of glufosinate resulted in as much as 59 and 60% injury to giant ragweed inflorescence and as much as 78 and 75% reduction in seed production, respectively, under field and greenhouse conditions. In contrast, single or sequential applications of 2,4-D or dicamba resulted in ≥ 96% inflorescence injury and reduction in seed production in the field as well as in greenhouse studies. The results indicated that 2,4-D or dicamba are effective options for reducing seed production of glyphosate-resistant giant ragweed even if applied late in the season. Targeting weed seed production to decrease the soil seedbank will potentially be an effective strategy for an integrated management of GR giant ragweed.
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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".