Dissipation and effect of glyphosate during composting of organic wastes
Bibliographic record
Abstract
Abstract The addition of organic matter (OM) containing glyphosate during compost production, through the introduction of contaminated plant residues or sewage sludge, presents a risk of hindering the proper OM breakdown carried out by microorganisms and causing the accumulation of glyphosate or aminomethylphosphonic acid (AMPA). To measure the effect of glyphosate and glyphosate‐based herbicide (GBH) on OM decomposition as well as the dissipation of glyphosate to AMPA during composting, a controlled‐environment experiment was conducted using mesocosm‐scale vessels. Analytical‐grade (AG) glyphosate (150 mg kg –1 ) and GBH (VisionMAX) equivalent to the amounts applied in agricultural areas (300 mg kg –1 ) were added to a mixture of green residues, which were then composted for 112 d. Sampling after 2, 7, 28, and 112 d showed a negligible effect of glyphosate and GBH on physicochemical properties of the mixture (temperature, OM%, pH, total carbon [C], total nitrogen [N], and C/N ratio), ammonification, nitrification, and phosphate content. No differences between AG glyphosate and GBH treatments were measured. Glyphosate levels decreased significantly after 2 d to reach 53.1 and 71.1% of the initial content for the AG glyphosate and GBH treatments, respectively, and glyphosate dissipation was almost complete after 112 d of composting. Aminomethylphosphonic acid could not be detected at any time during the experiment regardless of the treatment. Our results show that conditions for OM decomposition were maintained despite the addition of glyphosate and suggest that only trace amounts of glyphosate or AMPA are likely to be present in mature compost.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".