Weed control, environmental impact and profitability of reduced rates of imazethapyr in combination with dimethenamid in dry beans
Bibliographic record
Abstract
Field experiments were conducted from 2003 to 2005 in Ontario to determine if reduced rates of imazethapyr (< 75 g a.i. ha-1) tank-mixed with dimethenamid applied preemergence (PRE) can be used as a feasible weed management strategy for broad-spectrum weed control in white and kidney beans (Phaseolus vulgaris L.). There was no injury in white or kidney bean with the imazethapyr plus dimethenamid tank-mix treatments evaluated. The rate of imazethapyr required to provide adequate control of green foxtail [Setaria viridis (L.) P. Beauv.], lamb’s-quarters (Chenopodium album L.), common ragweed (Ambrosia artemisiifolia L.), wild mustard (Sinapis arvensis L.), and redroot pigweed (Amaranthus retroflexus L.) tended to be reduced when tankmixed with dimethenamid at 1000 g ha-1. There was no adverse effect on the yield of white and kidney beans at the highest rate (75 g a.i. ha-1) of imazethapyr evaluated. Although both herbicides are considered reduced risk, the environmental impact of imazethapyr (75 g a.i. ha-1) was seven times less than that of dimethenamid (1000 g a.i. ha-1). The addition of reduced rates of imazethapyr to dimethenamid did not significantly increase environmental impact (EI) vs. dimethenamid alone. Profit margins were greater when dimethenamid was tank-mixed with imazethapyr than for applications of imazethapyr alone. Across all treatments, profit margins were maximized at an imazethapyr rate of 60 g a.i. ha-1 for white bean and an imazethapyr rate of between 60 and 75 g a.i. ha-1 for kidney bean. However, the profit-maximizing rates of imazethapyr tended to be higher for treatments without dimethenamid than for treatments where dimethenamid was tank-mixed with imazethapyr. Key words: Dimethenamid, environmental impact quotient (EIQ), imazethapyr, Montcalm, OAC Thunder, Phaseolus vulgaris L., profit margin
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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 | 0.001 | 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".