Response of dry beans to tiafenacil applied preemergence
Bibliographic record
Abstract
Abstract Tiafenacil is a new nonselective, protoporphyrinogen IX oxidase–inhibiting pyrimidinedione herbicide that is under consideration for registration to control grass and broadleaf weeds in corn, soybean, wheat, cotton, and other crops prior to crop emergence. The sensitivity of dry beans to tiafenacil is not known. Four field experiments were completed at Exeter and Ridgetown, ON, Canada, during the 2019 and 2020 growing seasons, to determine the sensitivity of azuki, kidney, small red, and white beans to tiafenacil applied preemergence (PRE) at 12.5, 25, 50, and 100 g ai ha−1. Tiafenacil applied at 100 g ai ha−1 caused 5% or less injury to azuki, kidney, small red, and white beans: 0% to 3% injury to azuki bean; 1% to 5% injury to kidney bean; and 1% to 4% injury to both small red bean and white bean. Tiafenacil applied PRE at 12.5, 25, 50, and 100 g ai ha−1 caused up to 1%, 4%, 4%, and 5% visible dry bean injury, respectively, but had no negative effect on other measured growth parameters including seed yield. Crop injury was generally greatest when tiafenacil was appled at the 100 g ai ha−1 rate in dry beans. Generally, kidney, small red, and white bean were more sensitive to tiafenacil than azuki bean. Dry bean injury was persistent and increased with time with the greatest injury observed 8 wk after emergence. Tiafenacil applied PRE can be a useful addition to the current strategies to control grass and broadleaf weeds, especially glyphosate-resistant horseweed and amaranth species prior to bean emergence.
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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) | 0.001 | 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 | 0.001 |
| 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".