Multi-Year Pseudo-Persistence, Mobility, and Degradation of Glyphosate and Its Degradation Product (AMPA) in a Gleysol in Quebec (Canada)
Bibliographic record
Abstract
This study evaluates the pseudo-persistence of glyphosate over three growing seasons in agricultural soils (gleysol) in Québec, Canada. The experiment was carried out in long established plots following a corn–soybean–wheat rotation cycle with various combinations of N-fertilization (mineral N-fertilization, organic N-fertilization, without fertilization) and tillage techniques (conventional tillage and no-till). The periods between glyphosate applications were 250, 326, and 398 days. Soil sampling was carried out at 0–20 cm and 20–40 cm just before each new application of herbicide. Glyphosate was not detected in any sample. Its main degradation product, aminomethylphosphonic acid (AMPA), was found and quantified in approximately 50% of the samples. The detection frequency of AMPA was higher for conventional tillage compared to no-till. Levels ranged between 0.09 and 0.46 μg.g−1. The molar balance per hectare over the first 40 cm showed that the amount of glyphosate present in the form of AMPA in the soils sometimes exceeds the amount of glyphosate applied during the previous season (10.54 or 5.27 mol glyphosate.ha−1). The cumulative effect of glyphosate applications on AMPA levels over the 3 years, however, has not been demonstrated. The effect of conventional tillage on the persistence of AMPA is significant in 2 out of 3 years. The persistence of AMPA was higher for combinations of conventional tillage/mineral N-fertilization and conventional tillage/without fertilization practices. We suggest that conventional tillage can modify parameters related to soil structure or to the structural or functional composition of the bacterial community, which could impact the degradation and leaching of glyphosate and AMPA.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".