Phoma leaf spot of wasabi ( <i>Wasabia japonica</i> ) caused by <i>Leptosphaeria biglobosa</i>
Bibliographic record
Abstract
A leaf spot disease on wasabi plants grown in commercial greenhouses in the Fraser Valley of British Columbia was characterized. Mycelial growth and pycnidial formation were observed within lesions when leaves were incubated under conditions of high humidity. Isolation from diseased tissues consistently yielded colonies of a Phoma species. Sequence analysis of the rDNA internal transcribed spacer ( ITS 1‐5.8S‐ ITS 2) region of eight isolates showed 100% nucleotide sequence identity with Phoma wasabiae and Leptosphaeria biglobosa subspecies ‘occiaustralensis’ and 99.2% identity with L. biglobosa ‘canadensis’. Pathogenicity studies on wasabi leaves showed that wounding greatly facilitated infection and enhanced lesion development for most isolates but was not required for all isolates. Chlorotic areas appeared around the inoculation sites within 4 days, followed by necrosis. Isolates displayed a range of virulence, from weakly to highly virulent, on wasabi leaves. Similar results were observed on leaves of canola cultivar Westar, i.e. wounding significantly increased lesion size and isolates displayed a range of virulence. An isolate of Leptosphaeria maculans ‘brassicae’ from canola was highly virulent on wasabi and canola leaves, causing lesions similar to those of L. biglobosa ‘occiaustralensis’ while an isolate of L. biglobosa ‘canadensis’ from canola was weakly virulent on both hosts and required wounds to infect. These results demonstrate that isolates of L. biglobosa ‘occiaustralensis’ from wasabi are as virulent as L. biglobosa ‘canadensis’ on wasabi and canola leaves but in some cases were comparable in virulence to L. maculans ‘brassicae’.
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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) | 0.001 | 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".