Synergy of Tank Mix Application of Herbicides on Canada Thistle (Cirsium arvense) under Non-cropped Situations
Bibliographic record
Abstract
Field studies were carried out under non-cropped situations using tank mix applications of some herbicides against Canada thistle (Cirsium arvense) during 2007–08 and 2008–09. Tank mix applications of carfentrazone 20 g/ha with glyphosate 1.0% (0.75% repeat year) plus 0.25% non-ionic surfactant (NIS) provided 95 (95) and 87% (82) control of Canada thistle compared to 95 (97) and 83% (82) control by glyphosate alone at 2.0+0.25% NIS, 8 and 13 weeks after treatment (WAT), respectively. Carfentrazone alone was not effective. In another experiment, tank mix applications of carfentrazone 20 g/ha+glyphosate 0.75+0.25% NIS+2,4-D amine 500 g/ha provided 98, 99, 96 and 89% control of Canada thistle compared to 85, 95, 92 and 79% control by tank mixing of 2,4-D 500 g/ha+glyphosate 1.0+0.25% NIS and 89, 92, 88 and 78% control by glyphosate alone 2.0+0.25% NIS, respectively, at 21, 42, 56 and 75 DAT. The mortality of Canada thistle was similar when glyphosate 1.0 or 1.5% was tank mixed with 20 or 40 g/ha of carfentrazone. Effect of 2, 4-D amine was significantly lower when used alone or tank mixed with carfentrazone compared to their mixture with glyphosate. The effect of herbicides was significantly higher in the second year compared to first year of spraying. Tribenuron alone at 25 g/ha+0.25% NIS or its tank mixture at 20 g/ha with 2,4-D ester 250 g/ha, metsulfuron 4 g/ha or carfentrazone 20 g/ha was not effective against Canada thistle. Similarly, tank mix applications of metsulfuron 2 or 4 g/ha with 2,4-D 250 or 500 g/ha failed to satisfactorily control Canada thistle. Glyphosate 1.0% alone or with metsulfuron 4 g/ha provided similar control of Canada thistle, but effect was significantly lower than alone application of glyphosate at 2.0+0.25% NIS.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".