Biologically-Effective-Dose of Tolpyralate and Tolpyralate plus Atrazine for Control of Multiple-Herbicide-Resistant Waterhemp [<i>Amaranthus tuberculatus</i> (Moq.) J. D. Sauer] in Corn
Bibliographic record
Abstract
The biologically-effective-dose of tolpyralate, a new 4-hydroxyphenyl-pyruvate dioxygenase (HPPD)-inhibitor, applied alone or tank-mixed with atrazine, for the control of multiple-herbicide-resistant (MHR) waterhemp [Amaranthus tuberculatus (Moq.) J. D. Sauer] has not been studied in corn. Seven field experiments were conducted during a three-year period (2018, 2019, 2020) in Ontario, Canada with MHR waterhemp to determine: 1) the dose-response of MHR waterhemp to tolpyralate and tolpyralate plus atrazine, and 2) the relative efficacy of tolpyralate and tolpyralate plus atrazine to post-emergence corn herbicides, dicamba/atrazine (500/1000 g·ha−1) and mesotrione + atrazine (100 + 280 g·ha−1). Tolpyralate + atrazine (120 + 4000 g·ha−1) caused 13% corn injury at one site two weeks after application (WAA), which was observed as transient foliar chlorosis and bleaching of new leaves. At 12 WAA, the predicted dose of tolpyralate for 50% control of MHR waterhemp at Cottam and on Walpole Island was 8 and 2 g·ha−1, respectively; the predicted dose of tolpyralate + atrazine for 50% control of MHR waterhemp at Cottam and on Walpole Island was 5 + 160 and 1 + 21 g·ha−1, respectively. The difference in predicted dose at the two sites is likely due to differences in MHR density and resistance profile. Applied at the registered rate, tolpyralate (30 g·ha−1) and tolpyralate + atrazine (30 + 1000 g·ha−1) controlled MHR waterhemp similar to dicamba/atrazine and mesotrione + atrazine across sites. This study demonstrates that tolpyralate + atrazine, applied POST, provides season-long control of MHR waterhemp in corn.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".