Alternative Herbicides for Control of Glyphosate-Resistant Giant Ragweed in Nebraska
Bibliographic record
Abstract
Giant ragweed is an early emerging and one of the most competitive summer annual species found in many fields throughout North America. Extensive use of glyphosate in glyphosate-tolerant (GT) crops has evolved giant ragweed populations with glyphosate resistance. Field dose-response studies were conducted to determine the influence of growth stage on the level of glyphosate resistance in a suspected giant ragweed population. In addition, efficacy of alternative pre-plant, pre-emergence (PRE) and post-emergence (POST) herbicides were evaluated in corn and soybeans for glyphosate-resistant (GR) giant ragweed control. The field glyphosate dose-response studies confirmed that the suspected giant ragweed population were resistant ranging from 14- to 32-fold resistance depending on the growth stage of glyphosate application. The 10, 20 and 30 cm tall giant ragweed had 14, 17 and 32X resistance level, respectively. The dose-response studies indicated that the 10, 20, and 30 cm tall GR giant ragweed was controlled 90% with 214, 402 and 482 g ae ha-1 of dicamba, respectively, when tank-mixed with glyphosate (1060 g ae ha-1) 21 days after treatment (DAT). All evaluated pre-plant herbicides for corn provided ≥ 90% control of the GR giant ragweed at 30 DAT; among which the best control (100%) was achieved with pre-plant application of atrazine (2240 g ai ha-1), isoxaflutole (90 g ai ha-1), and premix of flumioxazin/pyroxasulfone (315 g ai ha-1). Herbicide combinations of different site of action provided greater than 90% control of the GR giant ragweed population in a PRE followed by POST herbicide program in corn and soybean, suggesting that alternative herbicide for giant ragweed control are available.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".