Ecology and diversity of culturable fungal species associated with soybean seedling diseases in the Midwestern United States
Bibliographic record
Abstract
AIMS: To isolate and characterize fungi associated with diseased soybean seedlings in Midwestern soybean production fields and to determine the influence of environmental and edaphic factors on their incidence. METHODS AND RESULTS: Seedlings were collected from fields with seedling disease history in 2012 and 2013 for fungal isolation. Environmental and edaphic data associated with each field was collected. 3036 fungal isolates were obtained and assigned to 76 species. The most abundant genera recovered were Fusarium (73%) and Trichoderma (11.2%). Other genera included Mortierella, Clonostachys, Rhizoctonia, Alternaria, Mucor, Phoma, Macrophomina and Phomopsis. Most recovered species are known soybean pathogens. However, non-pathogenic organisms were also isolated. Crop history, soil density, water source, precipitation and temperature were the main factors influencing the abundance of fungal species. CONCLUSION: Key fungal species associated with soybean seedling diseases occurring in several US production regions were characterized. This work also identified major environment and edaphic factors affecting the abundance and occurrence of these species. SIGNIFICANCE AND IMPACT OF THE STUDY: The identification and characterization of the main pathogens associated with seedling diseases across major soybean-producing areas could help manage those pathogens, and devise more effective and sustainable practices to reduce the damage they cause.
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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) | 0.000 | 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 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".