Evaluation of Biostimulants Added to Post Emergence Herbicides in Soybean
Bibliographic record
Abstract
There is little information on the effect of the addition of biostimulants such as AX13-04-4, Crop Booster or RR Soy Booster to post emergence herbicides in soybean under Ontario environmental conditions. A total of 69 field experiments were conducted in soybean at two locations (Ridgetown and Exeter, Ontario, Canada) to evaluate the effect of biostimulants added to various post emergence herbicides on crop injury, weed control and yield of soybean. There was minimal soybean injury (6% or less) from glyphosate, chlorimuron, imazethapyr, fomesafen or quizalofop applied alone or in combination with biostimulants. At 4 weeks after herbicide treatment (WAT), the addition of biostimulants to glyphosate, chlorimuron, imazethapyr, fomesafen or quizalofop did not affect weed control except for control of common ragweed which was increased 2% with the addition of RR Soy Booster to glyphosate + imazethapr, and the control of common lambs quarters which was increased 4% with the addition of Crop Booster to glyphosate + fomesafen. At 8 WAT, biostimulants evaluated had no effect on weed control except for Crop Booster added to glyphosate + fomesafen which increased green foxtail control 2% and Crop Booster added to glyphosate + chlorimuron, glyphosate + fomesafen and glyphosate + quizalofop which increased common lambs quarters control 1%, 3%, and 4%, respectively. The addition of biostimulants to the post emergence herbicides evaluated had no effect on soybean yield. Based on these results, the addition of biostimulants such as AX13-04-4, Crop Booster or RR Soy Booster to commonly used post emergence herbicides in Ontario has no significant effect on crop injury, weed control or yield of soybean.
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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 | 0.004 | 0.001 |
| 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 | 0.000 | 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".