Benefit of Adding Ammonium Sulfate or Additional Glyphosate to Glyphosate in Corn and Soybean
Bibliographic record
Abstract
Nine field trials (4 in corn and 5 in soybean) were conducted over 2 years (2014 and 2015) to determine if there is greater benefit of adding ammonium sulfate (AMS) (2.5 L·haˉ1) or an equal dollar value of glyphosate (406 g·ae·haˉ1) to glyphosate applied at 450, 675 or 900 g·ae·haˉ1 for weed control in corn and soybean. Glyphosate applied at 450 g·ae·haˉ1 controlled velvetleaf 90% to 98%, common ragweed 80% - 97%, common lambsquarters 91% - 99%, Eastern black nightshade 83% - 100% and barnyardgrass 73% - 97% in corn and common ragweed 37% - 89%, common lambsquarters 39% - 98%, barnyardgrass 90% - 98% and green foxtail 91% - 98% in soybean. The addition of AMS to glyphosate applied at 450, 675 or 900 g·ae·haˉ1 provided little to no added benefit for the control of velvetleaf, common ragweed, common lambsquarters, Eastern black nightshade, barnyardgrass and green foxtail in corn and soybean. There was a greater benefit in weed control efficacy by simply adding and equal dollar value of glyphosate (406 g·ae·haˉ1) than AMS (2.5 L·haˉ1) to glyphosate. There was no difference in corn or soybean yield among the herbicide treatments evaluated. Based on these results, addition of AMS to glyphosate at rates evaluated had little benefit on weed control efficacy or yield of corn and soybean.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".