Efficacy of tiafenacil applied preplant alone or mixed with metribuzin for glyphosate-resistant horseweed control in soybean
Bibliographic record
Abstract
Abstract Tiafenacil is a recently developed protoporphyrinogen IX oxidase (PPO)-inhibiting herbicide from the pyrimidinedione chemical class that is proposed for use as a preplant (PP) burndown in soybean. Glyphosate-resistant (GR) horseweed is a troublesome weed often found in no-till systems that can dramatically reduce soybean yield; control in soybean has been variable. Five field experiments were conducted over 2019 and 2020 in commercial soybean fields with GR horseweed to determine the biologically effective dose (BED) of tiafenacil and tiafenacil + metribuzin and to compare their efficacy to currently accepted industry standard herbicide treatments in identity-preserved (IP, non-GMO), GR, and glyphosate/dicamba-resistant (GDR) soybean systems. There was no soybean injury with treatments evaluated. The calculated doses of tiafenacil for 50%, 80%, and 95% control of GR horseweed control were 21, 147, and >200 g ai ha −1 , respectively, at 8 wk after application (WAA). Lower doses were calculated with the addition of metribuzin (400 g ai ha −1 ) to tiafenacil for 50% and 80% control, with no dose of tiafenacil + metribuzin providing 95% control. Tiafenacil + metribuzin at 25 + 400 and 50 + 400 g ai ha −1 controlled GR horseweed 88% and 93%, respectively, which was similar to the industry standards of saflufenacil + metribuzin (25 + 400 g ai ha −1 ) and glyphosate/dicamba + saflufenacil (1,200/600 + 25 g ai ha −1 ) that provided 98% and 100% control, respectively, at 8 WAA. This study presents the potential utility of tiafenacil + metribuzin as a GR horseweed management strategy in soybean.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".