Tolerance of White Bean to Tiafenacil Herbicide Mixtures and Control of Multiple Herbicide-Resistant Horseweed With Tiafenacil Herbicide Mixtures
Bibliographic record
Abstract
There is limited information on the tolerance of white bean to tiafenacil herbicide mixtures applied preplant (PP) and the efficacy of tiafenacil herbicide mixtures applied PP to control multiple herbicide-resistant (MHR) horseweed. The objective aim of this research was to ascertain the tolerance of white beans to tiafenacil herbicide mixtures and determine if MHR horseweed control with tiafenacil can be improved by adding herbicide partners in a surrogate soybean crop. During 2021 and 2022 four experiments were performed to determine the tolerance of white bean to tiafenacil herbicide mixtures and five experiments were conducted to determine MHR horseweed control with tiafenacil mixtures in ON, Canada. All tiafenacil mixtures evaluated except those that included 2,4-D ester caused minimal (≤ 4%) white bean injury and had no adverse effect on white bean stand, dry biomass, height, maturity (as measured by seed moisture (SM) content at harvest), or yield. Glyphosate + tiafenacil + 2,4-D ester and glyphosate + tiafenacil + bromoxynil + 2,4-D ester caused up to 8% white bean injury but had no adverse effect on white bean stand, dry biomass, height, maturity, or yield. Glyphosate + tiafenacil or co-applied with bromoxynil, metribuzin, or 2,4-D controlled MHR horseweed 23-75%, reduced density up to 62% and reduced biomass up to 56%; consequently, horseweed interference with these tiafenacil mixtures resulted in soybean yield comparable to the non-treated (weedy) control. Glyphosate + tiafenacil + halauxifen-methyl and the co-application of glyphosate + tiafenacil + bromoxynil with metribuzin, halauxifen-methyl, or 2,4-D ester controlled MHR horseweed 73-94%, reduced density up to 79%, and reduced biomass up to 86%. Reduced MHR horseweed interference with the aforementioned tiafenacil mixtures resulted in soybean yield comparable to the weed-free control. In conclusion, all tiafenacil mixtures evaluated except those that contained 2,4-D ester can be safely used in white bean. Glyphosate + tiafenacil + halauxifen-methyl and the co-application of glyphosate + tiafenacil + bromoxynil with metribuzin, halauxifen-methyl, or 2,4-D ester provided the most consistent control of MHR horseweed.
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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".