The addition of adjuvants on glyphosate enhances the control of aquatic plant Myriophyllum aquaticum (Vell.)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Knowledge about the action of glyphosate alone and associated with adjuvants in the effectiveness to control aquatic plants is important in the decision-making on its use. Objective: This study aimed to evaluate the effectiveness of glyphosate and five adjuvants in the control of Myriophyllum aquaticum. Methods: Glyphosate (Rodeo®) at doses of 1.5, 3.5, 5.5, and 7.5 L ha-1 was sprayed alone and associated with Aterbane® BR, Veget’oil®, Dash® HC, Assist®, and Agral® (0.5% v v-1), in addition to the control, with a spray solution volume of 200 L ha-1. The effectiveness of control was evaluated using the scores of a visual scale at 3, 7, 15, 21, 30, 45, and 60 days after application (DAA), regrowth, and dry matter accumulation at 60 DAA. Results: The best effectiveness of control of the glyphosate alone was 85% at the dose of 7.5 L ha-1, increasing to 100% when associated with Aterbane® and Veget’oil®. The control reached 100% for all glyphosate doses associated with Dash®. Moreover, glyphosate at the dose of 7.5 L ha-1 associated with Assist® provided a 98% control, while glyphosate doses of 3.5, 5.5, and 7.5 L ha-1 associated with Agral® provided a 100% control. Glyphosate at doses of 5.5 and 7.5 L ha-1 associated with Dash® and Agral® was more effective in reducing the regrowth and dry biomass (100%). Thus, glyphosate + Dash® and Agral® promoted the highest control (above 95%), the lowest regrowth, and the highest reduction in the dry biomass of M. aquaticum. Conclusions: The addition of Aterbane® BR, Dash®, and Agral® to glyphosate improved the effectiveness of control of M. aquaticum and contributed to reducing the applied herbicide dose.
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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 | 0.000 |
| 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 it