Efficacy of Trifluralin Compared to Ethalfluralin Applied Alone and Co-Applied with Halosulfuron for Weed Management in White Bean
Bibliographic record
Abstract
There are a limited number of herbicides registered for weed management in white bean production in Ontario, Canada. Five field experiments were completed in Ontario from 2016 to 2018 to compare the efficacy of trifluralin and ethalfluralin applied alone and in combination with halosulfuron, applied preplant incorporated (PPI), for weed control efficacy and white bean tolerance and seed yield. At 2 and 4 WAE, there was no white bean injury from the herbicide treatments evaluated. Trifluralin applied PPI provided up to 32%, 99%, 13%, 99%, 27%, 99% and 99% control of velvetleaf, redroot pigweed, common ragweed, common lambsquarters, wild mustard, barnyardgrass and green foxtail, respectively. Trifluralin and ethalfluralin provide similar control of velvetleaf, redroot pigweed, barnyardgrass and green foxtail control, however, ethalfluralin is slightly more efficacious on common ragweed, common lambsquarters and wild mustard. Halosulfuron (35 g∙ai∙ha−1), applied PPI, provided as much as 76%, 98%, 96%, 96%, 100%, 19% and 23% control of velvetleaf, redroot pigweed, common ragweed, common lambsquarters, wild mustard, barnyardgrass and green foxtail, respectively. Trifluralin (600 or 1155 g∙ai∙ha−1) + halosulfuron (35 g∙ai∙ha−1), applied PPI, provided up to 88%, 100%, 98%, 100%, 100%, 99% and 98% control of velvetleaf, redroot pigweed, common ragweed, common lambsquarters, wild mustard, barnyardgrass and green foxtail, respectively. Ethalfluralin (810 or 1080 ai∙ha−1) + halosulfuron (35 g∙ai∙ha−1) provided similar control. Weed interference decreased white bean seed yield 44% - 45% with trifluralin, 30% - 41% with ethalfluralin and 34% with halosulfuron. However, decreased weed interference with trifluralin and ethalfluralin applied in combination with halosulfuron resulted white bean seed yield that was similar to the weed-free control. Trifluralin or ethalfluralin co-applied with halosulfuron can be safely used in white bean production for the control of common annual grass and broadleaf weeds in Ontario.
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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".