Weed Control in Soybean with Imazethapyr Applied Alone or in Tank Mix with Saflufenacil/Dimethenamid-P
Bibliographic record
Abstract
Saflufenacil/dimethenamid-P is a relatively new prepackaged herbicide mixture that has the potential to provide enhanced weed control in soybean when tank-mixed with reduced doses of imazethapyr. Six field experiments were conducted over a 3-yr period (2011, 2012, and 2013) near Ridgetown and Exeter, Ontario, Canada, to determine the dose of imazethapyr, applied PRE, that must be added to saflufenacil/dimethenamid-P (245 g ai ha−1) to provide effective weed control in soybean. The predicted dose of imazethapyr PRE for 80% control of common lambsquarters, common ragweed, green foxtail, and velvetleaf 8 wk after soybean emergence (WAE) was 66, 180, 137, and 48 g ai ha−1, respectively. In contrast, when tank-mixed with saflufenacil/dimethenamid-P (245 g ha−1), the dose of imazethapyr PRE needed for 80% control of common lambsquarters, common ragweed, green foxtail, and velvetleaf was reduced to 11, 80, 48, and 18 g ha−1, respectively. The control of common lambsquarters, common ragweed, green foxtail, and velvetleaf was improved by 21, 23, 34, and 27%, respectively when saflufenacil/dimethenamid-P (245 g ha−1) was added to imazethapyr PRE. Imazethapyr at 104 g ha−1resulted in soybean yield that was 95% of the weed-free control; however, when tank-mixed with saflufenacil/dimethenamid-P (245 g ha−1) only 54 g ha−1of imazethapyr was required for the same yield level. Based on this study, PRE application of saflufenacil/dimethenamid-P with reduced doses of imazethapyr has the potential to improve soybean yield and provide acceptable weed control (≥ 80%); however, the extent that imazethapyr dose can be reduced is dependent upon weed community composition.
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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".