Genetic Diversity, Mycotoxin Profiles, and Population Structure of <i>Fusarium</i> spp<i>.</i> Associated with Fusarium Head Blight in Georgia, United States
Bibliographic record
Abstract
Fusarium head blight (FHB) has become a limiting factor in soft red winter wheat production in the southeast United States. Recent epidemics have occurred in Georgia, but genetic information on the Fusarium species responsible for FHB is unknown. This study aimed to assess pathogen population structure and genetic diversity, trichothecene profiles, and representative pathogenicity of 196 Fusarium isolates collected from 44 wheat (n = 85) and 53 corn (n = 111) fields in Georgia. Phylogenetic analysis using the translation elongation factor 1-alpha (635 bp) and RNA polymerase second largest subunit (930 bp) sequence data resolved isolates into 185 haplotypes, which represented 12 Fusarium species grouped under five species complexes. F. graminearum with 15-acetyl-deoxynivalenol (15ADON) chemotype (75.6%) and F. incarnatum (57.7%) predominated in wheat and corn, respectively, with a surprisingly higher frequency of nivalenol (NIV) F. graminearum (21.8%). Using nine variable numbers of tandem repeat markers, 82 multilocus genotypes out of 86 F. graminearum isolates were identified and grouped into two genetic clusters, pop1fg (n = 29) and pop2fg (n = 32), as part of the North American populations (NA1 and NA2) but with no chemotype differentiation. F. graminearum populations in Georgia are mostly clonal and might have evolved through at least two introductions from the northeast United States and Canada and local adaptation to maintain high genetic diversity. Pathogenicity of F. graminearum isolates from wheat and corn had high FHB severity (>60%) in wheat, which depicted the risk they can pose towards future FHB outbreaks. Overall, this baseline study provided important information on Fusarium species diversity including F. graminearum associated with FHB in Georgia that will be useful to formulate integrated disease management incorporating improved host resistance and fungicide spray programs.
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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 | 0.000 | 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 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".