Glyphosate and aminomethyphosphonic (AMPA) contents in Brazilian field crops soils
Bibliographic record
Abstract
Because of a lack of direct measurements, the presence and persistence of glyphosate and its main metabolite aminomethylphosphonic acid (AMPA) in agricultural soils of Brazil remains unknown. This paper aims at reporting glyphosate and AMPA contents in Brazilian field crop soils at the country scale from southern states to eastern Amazon. Brazilian field crop farmers are among the highest users of glyphosate-based herbicides (GBH) in the world. Soybean and corn field crop soils from 17 sites were collected at two depths (i.e. 0-20 cm and 20-40 cm) in 2016 and 2018. The study area encompasses three regions of Brazil: southern Brazil, central-west Brazil and eastern Amazon, all having in common intensive, conventional, large-scale grain farming. ßGlyphosate and AMPA contents were measured using a GC-ECD following soil extraction. Both chemicals were ubiquitously detected in soils cultivated under various agricultural practices ranging from ploughing to no-till ones. Average measured glyphosate and AMPA contents were 0.08 ± 0.09 µg/g and 0.17 ± 0.16 µg/g respectively with maximum values of 0.57 µg/g and 0.98 µg/g. Glyphosate plus AMPA contents in the top 40 cm of soils presented cumulated amounts exceeding the annual glyphosate inputs via GBH. This is interpreted as a multiannual persistence of these chemicals in Brazilian agricultural soils. Downward migration of glyphosate and AMPA is also suspected with regard to the vertical distribution of these chemicals along with deeper soil horizons. This study highlights the backlash of conservation agriculture as far as glyphosate and AMPA presence in agricultural soils are concerned. These compounds persistence in Brazilian soils appear to be longer than what is usually reported in the literature, especially so for tropical environments. The worldwide concern about the ubiquitous presence of glyphosate and AMPA in the environment needs a broader screening in Brazilian field crop soils since the majority of the available data comes from Argentina, Europe and to a lesser extent North America.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".