Fusarium Root Rot Complex in Soybean: Molecular Characterization, Trichothecene Formation, and Cross-Pathogenicity
Bibliographic record
Abstract
Soybean is threatened by many pathogens that negatively affect this crop’s yield and quality, such as various Fusarium species that cause wilting and root rot diseases. Fusarium root rot (FRR) in soybean can be caused by F. graminearum and other Fusarium spp. that are associated with Fusarium head blight (FHB) in cereals. Therefore, it was important to inquire whether Fusarium pathogens from soybean can cause disease in wheat and vice versa. Here, we investigated the FRR complex in Manitoba (Canada) from symptomatic plants, using both culture- and molecular-based methods. We developed a molecular diagnostic toolkit to detect and differentiate between several Fusarium spp. involved in FHB and FRR, then we evaluated cross-pathogenicity of selected Fusarium isolates collected from soybean and wheat, and the results indicate that isolates recovered from one host can infect the other host. Trichothecene production by selected Fusarium spp. was also analyzed chemically via liquid chromatography mass spectrometry in both soybean (root) and wheat (spike) tissues. Trichothecenes were also analyzed in soybean seeds from plants with FRR to check the potentiality of trichothecene translocation from infected roots to the seeds. All of the tested Fusarium isolates were capable of producing trichothecenes in wheat spikes and soybean roots, but no trichothecenes were detected in soybean seeds. This study provided evidence, for the first time, that trichothecenes were produced by several Fusarium spp. (F. cerealis, F. culmorum, and F. sporotrichioides) during FRR development in soybean.
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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".