Characterization of Chinese eggplant isolates of the fungal pathogen Verticillium dahliae from different geographic origins
Bibliographic record
Abstract
Verticillium dahliae is a fungal pathogen that causes wilt disease in a wide range of host plants. Characterization of virulence, morphological, and molecular variations among V. dahliae isolates from different geographic origins is essential for any breeding program aimed at producing plant cultivars resistant to this disease. We characterized virulence variation among V. dahliae isolates from Chinese cultivated eggplant grown in Northeast China by pathogenicity testing on susceptible, moderately resistant, and resistant eggplant accessions in a glasshouse using a root-dipping method of infection. These isolates were also characterized for morphological features based on growth on potato dextrose agar media and for genetic variation based on ISSR markers. All 12 isolates were divided into three pathotypes based on the virulence, i.e., strong, moderate, or weak type. Three isolates were categorized as defoliating pathotypes, with strong virulence, and the rest of the isolates were categorized as non-defoliating pathotypes, with moderate to weak virulence. The eggplant isolates were classified into three morphological types or morphotypes, hypha, hypha-sclerotia, and sclerotia; no significant correlations were detected between pathotypes and morphotypes or geographic origins. ISSR fingerprinting indicated genetic diversity among isolates, ranging from 0.26 to 0.69. Specific fingerprint types were not correlated with either pathotype or morphotype. However, ISSR analyses did reveal two clusters in which the isolates in each share the same or neighboring geographic origins.
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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".