Wheat, Field Pea, and Canola Response to Glyphosate and AMPA Soil Residues
Bibliographic record
Abstract
The tripling of glyphosate use in the Canadian prairies during the past decade has raised concerns over the possible accumulation of glyphosate and its main metabolite AMPA in soil over time and whether there could be any detrimental effects on crop production. A controlled environment study was conducted at two locations in Alberta, Canada, to determine glyphosate and AMPA soil concentrations that would injure wheat, field pea, and canola. Treatments included glyphosate acid or AMPA applied at 0, 10, 25, 100, 250, and 500 mg kg−1soil. Shoot and root biomass determinations 8 wk after emergence (WAE) indicated that shoot and root biomass of all crops progressively declined with increasing soil concentrations of glyphosate at both locations. In contrast, AMPA reduced crop shoot and root biomass at only one of two sites. Estimated soil concentrations of glyphosate causing 20% reductions in shoot and root biomass ranged from 80 to 190, 90 to 350, and 120 to 320 mg kg−1for field pea, canola, and wheat, respectively. Soil concentrations of AMPA causing 20% crop biomass reductions ranged from 40 to 70, 20 to 30, and 80 to 120 mg kg−1for field pea, canola, and wheat, respectively. Although substantial crop injury occurred in this study, it must be noted that these rates are very high in terms of field application rates that would be required to achieve these soil concentrations. Doses causing crop injury would convert to estimated glyphosate field rates ranging from 17.6 to 77 kg ha−1. Overall results indicate that even with frequent high-dose glyphosate applications over several years, the likelihood of wheat, field pea, and canola injury from soil residues is low. Nevertheless, there may be merit in greater monitoring of glyphosate and AMPA soil residues in cropping systems with high glyphosate utilization over a long time period.
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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 | 0.000 | 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 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".