Glyphosate and aminomethylphosphonic acid contents in field crops soils under various weed management practices
Bibliographic record
Abstract
Abstract To avoid yield loss in field crops associated with glyphosate‐resistant weed and changes in their population dynamics, repeated applications of glyphosate‐based herbicides (GBH) and combination with other herbicides are weed management practices (WMP) increasingly used worldwide, and particularly so in southern Quebec (Canada). These practices affect soil biological activity as well as soil functions but could also influence glyphosate and its main degradation product, the aminomethylphosphonic acid (AMPA), persistence. This study was conducted in corn ( Zea mays L.) and soybean [ Glycine max (L.) Merr.] field crops to evaluate the effects of single vs. repeated GBH applications, with or without the addition of other herbicides, on glyphosate and AMPA persistence in soils throughout a growing season. In corn plots, the highest glyphosate content (0.11 mg kg –1 ) was observed following two GBH applications combined with other herbicides (i.a. S‐metolachlor and mesotrione). In soybean plots, the highest glyphosate content (0.18 mg kg –1 ) was also measured following two GBH applications combined with other herbicides (i.a. imazethapyr and chlorimuron). AMPA contents in corn plots soils were similar whatever WMP employed, whereas differences were observed in soybean plots according to the WMP. Soybean plots thus seemed more responsive to variation in weed management practices than corn plots. This study highlights the persistence of glyphosate and AMPA in agricultural soils at least 8 wk after the last GBH application.
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 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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".