Biologically Effective Dose of Diflufenican for the Control of Multiple Herbicide-Resistant Waterhemp in Soybean
Bibliographic record
Abstract
Waterhemp biotypes have evolved resistance to Weed Science Society of America (WSSA) Herbicide Groups 2, 5, 9, 14, and 27 in Ontario Canada, are present in 15 counties, spanning a distance of 800 km across southern Ontario, and cause an average soybean yield loss of 42%. Five field experiments were established in growers’ fields in southwestern Ontario to determine the biologically effective doses of diflufenican (Group 12) applied preemergence (PRE) to control multiple herbicide-resistant waterhemp in soybean. The calculated diflufenican doses to elicit 50, 80, and 95% control of MHR waterhemp were 71, 164, and 304 g ai ha-1 at 2 weeks after herbicide application (WAA); 50, 115, and 214 g ai ha-1 at 4 WAA; and 69, 158, and 294 g ai ha-1 at 8 WAA, respectively. The calculated diflufenican doses that caused a 50, 80, and 95% reduction in MHR waterhemp density were 28, 70, and Non-est. g ai ha-1 and the doses that caused a 50, 80, and 95% reduction in MHR waterhemp biomass were 44, 109, and Non-est. g ai ha-1, respectively. The calculated diflufenican doses that resulted in 50, 80, and 95% of the soybean yield of the industry standard herbicide (flumioxazin/pyroxasulfone) were 3, 12, and 57 g ai ha-1, respectively. Diflufenican (180 g ai ha-1) PRE controlled MHR waterhemp 89, 92, and 85%; metribuzin (300 g ai ha-1) PRE controlled MHR waterhemp 94, 84, and 69%; and flumioxazin/pyroxasulfone (105/134 g ai ha-1) PRE controlled MHR waterhemp 100, 99, and 98% at 2, 4, and 8 WAA, respectively. Diflufenican, metribuzin, and flumioxazin/pyroxasulfone applied PRE reduced MHR waterhemp density 96, 84, and 100% and biomass 93, 67, and 99%, respectively at 8 WAA. Diflufenican, metribuzin, and flumioxazin/pyroxasulfone applied PRE caused 9, 0, and 4% visible soybean injury, respectively but the injury was transient and caused no adverse effect on seed moisture content or seed yield of soybean. This study concludes that diflufenican and metribuzin applied PRE provide comparable MHR waterhemp control; however, control was lower than flumioxazin/pyroxasulfone.
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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".