Interaction between tolpyralate and atrazine for the control of annual weed species in corn
Bibliographic record
Abstract
Abstract Many studies have documented the interaction between 4-hydroxyphenylpyruvate dioxygenase (HPPD)-inhibiting and photosystem II (PSII)-inhibiting herbicides. Most have focused on the interaction between mesotrione and atrazine, with only a few studies characterizing the nature of the interaction between tolpyralate and atrazine. Therefore, five field experiments were conducted in Ontario, Canada, over a 3-yr period (2019 to 2021) to characterize the interaction between three rates of tolpyralate (15, 30, and 45 g ai ha−1) and three rates of atrazine (140, 280, and 560 g ai ha−1) for the control of seven annual weed species in corn (Zea mays L.). Tolpyralate at 30 or 45 g ha−1 applied with atrazine at 280 or 560 g ha−1 controlled velvetleaf (Abutilon theophrasti Medik.), redroot pigweed (Amaranthus retroflexus L.), common ragweed (Ambrosia artemisiifolia L.), common lambsquarters (Chenopodium album L.), and wild mustard (Sinapis arvensis L.) >90% at 8 wk after application (WAA). Tolpyralate and atrazine were synergistic at each rate combination for the control of A. theophrasti at 8 WAA. In contrast, A. retroflexus and S. arvensis control at 8 WAA was additive with each rate combination. At 8 WAA, C. album control was generally additive, but one rate combination was synergistic. Ambrosia artemisiifolia control at 8 WAA was synergistic with five rate combinations and additive with the other four. Barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] control at 8 WAA was additive with seven of the rate combinations and synergistic with two. Setaria spp. control at 8 WAA was synergistic with one more rate combination compared with E. crus-galli, but the two weed species shared the same synergistic rate combinations. This study concludes that extrapolation or broad classifications of the interaction between tolpyralate and atrazine would be inappropriate, as the interaction can vary due to herbicide rate, weed species, and the response parameter analyzed.
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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 | 0.000 |
| 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".