Tolerance of Glyphosate-Resistant Maize to Glyphosate Plus MCPA Amine Is Influenced by Dose and Timing
Bibliographic record
Abstract
There is little information on tolerance of glyphosate-resistant maize to glyphosate plus MCPA amine as influenced by dose and timing under Ontario environmental conditions. A total of seven field trials were conducted at various locations in Ontario, Canada, in 2011–2013 to evaluate tolerance of field maize to tank mixes of glyphosate (900 g a.e./ha) plus MCPA amine (79, 158, 315, 630, 1260, 2520, or 5040 g a.e./ha) at either the 4- or 8-leaf stage. The predicted dose of MCPA amine that caused 5, 10, and 20% injury was 339, 751, and 1914 g a.e./ha when applied to 4-leaf maize but only 64, 140, and 344 g a.e./ha when applied to 8-leaf maize, respectively. The predicted dose of MCPA amine that caused 5, 10, and 20% reduction in shoot dry weight of maize was 488, 844, and 1971 g a.e./ha when applied to 4-leaf maize and only 14, 136, and 616 g a.e./ha when applied to 8-leaf maize, respectively. The predicted dose of MCPA amine that caused 5, 10, and 20% yield reduction was 2557, 4247, and >5040 g a.e./ha when applied to 4-leaf maize and 184, 441, and 1245 g a.e./ha when applied to 8-leaf maize, respectively. Based on these results, glyphosate plus MCPA amine applied at the manufacturer’s recommended dose of 630 g a.e./ha applied to 4-leaf maize has potential to cause injury but the injury is transient with no significant reduction in yield. However, when glyphosate plus MCPA amine is applied to 8-leaf maize it has the potential to cause significant injury and yield loss in maize.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".