Changes in the phyllosphere and rhizosphere microbial communities of soybean in the presence of pathogens
Bibliographic record
Abstract
Soybean (Glycine max L.) is host to an array of foliar- and root-infecting pathogens that can cause significant yield losses. To provide insights into the roles of microorganisms in disease development, we evaluated the bacterial and fungal communities associated with the soybean rhizosphere and phyllosphere. For this, leaf and soil samples of healthy, Phytophthora sojae-infected and Septoria glycines-infected plants were sampled at three stages during the production cycle, and then subjected to 16S and Internal Transcribed Spacer (ITS) amplicon sequencing. The results indicated that biotic stresses did not have a significant impact on species richness and evenness regardless of growth stage. However, the structure and composition of soybean microbial communities were dramatically altered by biotic stresses, particularly for the fungal phyllosphere. Additionally, we cataloged a variety of microbial genera that were altered by biotic stresses and their associations with other genera, which could serve as biological indicators for disease development. In terms of soybean development, the rhizosphere and phyllosphere had distinct microbial communities, with the fungal phyllosphere most influenced by growth stage. Overall, this study characterized the phyllosphere and rhizosphere microbial communities of soybean, and described the impact of pathogen infection and plant development in shaping these bacterial and fungal communities.
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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 | 0.001 | 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 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".