Weed Control, Environmental Impact, and Economics of Weed Management Strategies in Glyphosate-Resistant Soybean
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
With the number of glyphosate-resistant weed species increasing in North America and a lack of new herbicide chemistries being developed, growers are shifting toward using older herbicides that are more expensive and may be less environmentally friendly. Therefore, to determine which weed management strategies are most cost effective and have the lowest impact on the environment we evaluated the efficacy, environmental impact, and the profitability of several weed management strategies in glyphosate-resistant soybean over a 3-yr period (2007 to 2009) at three locations in southwestern Ontario, Canada. No visible injury to soybean was observed with the herbicide treatments evaluated. A sequential application of glyphosate consistently provided high levels of weed control (99 to 100%) at 56 d after treatment in comparison with one- or two-pass herbicide programs. Soybean yield did not differ between the two-pass herbicide programs and glyphosate applied early POST; however, a yield benefit was found with a sequential application of glyphosate or a PRE herbicide followed by glyphosate compared with glyphosate applied only at late POST. The two-pass herbicide programs had higher environmental impact (EI) (> 23) than the one-pass herbicide programs (< 15), except when imazethapyr was followed by or tank-mixed with glyphosate, which had an equivalent EI (∼ 14) to the one-pass herbicide programs. Not surprisingly because of the low purchase price of glyphosate, gross margins were highest for treatments that included glyphosate. However, to reduce the selection pressure on glyphosate-resistant weed biotypes, to reduce environmental impact, and to increase gross margins a combination of glyphosate with another mode of action would be most beneficial. In this study glyphosate + imazethapyr was the best alternative to a sequential two-pass glyphosate program.
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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) | 0.000 | 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) | 0.000 | 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 it