Identification and Characterization of Verticillium longisporum Lineage A1/D1 from Brassica Crops in Manitoba, Canada
Bibliographic record
Abstract
Verticillium stripe in canola (Brassica napus L.) caused by Verticillium longisporum was first reported in Manitoba in 2014. In this study, Brassica crops including canola, mustard (Brassica juncea) and radish (Raphanus sativus) with visible symptoms of Verticillium stripe were collected from Portage La Prairie, Manitoba, and the pathogens were isolated. Isolates from canola and radish were identified to V. longisporum, which produced longer conidia (7.92–12.00 µm) than Verticillium dahliae (4.32–7.04 µm). An isolate derived from mustard was characterized as V. dahliae. Molecular diagnostics with 18S rDNA, 5.8S rDNA and mating-type marker primers were used to confirm the identification of Verticillium isolates. PCR-RFLP of the mitochondrial small subunit rDNA and the cytochrome b gene were also employed to distinguish V. longisporum isolates from V. dahliae. The multi-gene characterization approach allowed for lineage determination, and V. longisporum isolates from canola and radish were in the A1/D1 group. Isolates of Verticillium longisporum from canola inoculated onto the canola cultivar ‘Westar’ caused symptoms of stem striping, stunting and short plants. Re-isolated fungal strains from infected stems were again inoculated onto canola plants, in order to confirm that V. longisporum was the causal agent of Verticillium stripe disease in the pathogenicity test.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 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 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".