Impact of Glyphosate and Glyphosate-Based Herbicides on Phyllospheric Methylobacterium
Bibliographic record
Abstract
Abstract Symbiotic Methylobacterium comprise a significant portion of the phyllosphere, and are known to benefit host plant growth, development, and confer tolerance to stress factors. The near ubiquitous use of the broad-spectrum herbicide, glyphosate, in farming operations globally has necessitated a more expansive evaluation of the impacts of the agent itself and formulations containing glyphosate on important components of the plant phyllosphere, including Methylobacterium. This study provides an investigation of the sensitivity of 18 strains of Methylobacterium to glyphosate and two commercially available glyphosate-based herbicides (GBH). Nearly all strains of Methylobacterium showed signs of sensitivity to the popular GBH formulations WeatherMax® and Transorb® in a modified Kirby Bauer experiment. However, exposure to pure forms of glyphosate did not show a significant effect on growth for any strain in both the Kirby Bauer test and in liquid broth, until polysorbate-20 (Tween20) was added as a surfactant. Artificially increasing membrane permeability through the introduction of polysorbate-20 caused a 78–84% reduction in dry cell biomass relative to controls containing glyphosate or high levels of surfactant only (0–9% and 6–37% reduction respectively). The observable high sensitivity of Methylobacterium to the tested GBH formulations, including complete bactericidal activity in liquid broth at concentrations as low as 0.05% w/v (500 µg/L), was shown by the inability to recover culture viability when transferred to fresh media. To better understand the compatibility of important phyllospheric bacteria with commercial herbicides, this study endeavours to uncover the feasibility of synthetic products with biofertilizers and explores possible mechanisms by which toxicity may be induced in Methylobacteria.
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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) | 0.001 | 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".