Soil Microbiology in Glyphosate‐Resistant Corn Cropping Systems
Bibliographic record
Abstract
Genetically modified herbicide resistant crops are commonly grown since their introduction in the 1990s, but growing these crops could affect soil microorganisms. We evaluated the effects of glyphosate‐resistant (GR) corn ( Zea mays L.) and glyphosate application on soil microbial biomass carbon (MBC), β‐glucosidase enzyme activity (final season only), bacterial functional diversity, and bacterial community‐level physiological profiles (CLPPs) in corn monoculture in five seasons. We also determined if growing GR corn in crop rotations would alter these effects. In monoculture, the GR trait (GR corn vs. conventional corn) had no effects on MBC, β‐glucosidase activity, or functional diversity in any year. However, there were differences in CLPPs related to this trait in three seasons. Glyphosate application in monoculture increased MBC in corn rhizosphere in one season, and decreased MBC and bacterial diversity in bulk soil in another season. In crop rotations, GR corn (relative to conventional corn) decreased bacterial diversity and MBC in bulk soil in two seasons, and increased β‐glucosidase activity in corn rhizosphere and bacterial diversity in bulk soil in the final season. Growing GR corn in crop rotation compared to growing it in monoculture decreased MBC in corn rhizosphere in one season, but increased MBC and bacterial diversity in bulk soil in four seasons, and increased β‐glucosidase activity in corn rhizosphere and bulk soil in the final season. These results show that the GR technology had mostly no effects on soil microorganisms, had some inconsistent effects, and growing GR corn in crop rotation mostly mitigated any negative effects.
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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 | 0.000 | 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".