Comparative population structure and trichothecene mycotoxin profiling of <i>Fusarium graminearum</i> from corn and wheat in Ontario, central Canada
Bibliographic record
Abstract
Fusarium graminearum causes fusarium head blight ( FHB ) of wheat and gibberella ear rot ( GER ) of corn in Canada and also contaminates grains with trichothecene mycotoxins. Very little is known about trichothecene diversity and population structure of the fungus from corn in Ontario, central Canada. Trichothecene genotypes of F . graminearum isolated from corn ( n = 452) and wheat ( n = 110) from 2010 to 2012 were identified. All the isolates were deoxynivalenol ( DON ) type. About 96% of corn isolates and 98% of wheat isolates were 15‐acetyl deoxynivalenol (15 ADON ) type. The fungal population structures from corn ( n = 313) and wheat ( n = 73) were compared using 10 variable number tandem repeat ( VNTR ) markers. The fungal populations and subpopulations categorized based on host, cultivar groups, years and geography showed high gene ( H = 0.818–0.928) and genotypic ( GD = 0.999–1.00) diversity. Gene flow was also high between corn and wheat population pairs ( Nm = 8.212), and subpopulation pairs within corn ( Nm = 7.13–23.614) or wheat ( Nm = 19.483) populations. Phylogenetic analysis revealed that isolates from both hosts were F. graminearum clade 7. These findings provide baseline data on 3‐acetyl deoxynivalenol (3 ADON ) and 15 ADON profiles of F . graminearum isolates from corn in Canada and are useful in evaluating mycotoxin contamination risks in corn and wheat grains. Understanding the fungal genetic structure will assist evaluation and development of resistant cultivars/germplasm for FHB on wheat and GER on corn.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".