Diversity and Virulence of<i>Streptomyces</i>spp. Causing Potato Common Scab in Prince Edward Island, Canada
Bibliographic record
Abstract
Common scab (CS) is a potato disease that significantly decreases the market value of potato tubers after the development of necrotic lesions on their surface. Streptomyces scabiei is the main causal agent of CS; however, other closely related species, including S. acidiscabies and S. turgidiscabies, have also been shown to cause the disease. In this study, we characterized the genetic and phenotypic diversity of Streptomyces spp. causing CS in Prince Edward Island, the main potato-producing province in Canada. Two hundred and ninety-six pathogenic Streptomyces spp. isolates were retrieved from diseased tubers harvested from six fields located across a longitudinal geographical gradient. Genome fingerprinting analyses using repetitive elements PCR (ERIC- and BOX-PCR) revealed 14 distinct genetic groups. Thirteen groups were taxonomically affiliated with S. scabiei, whereas the fourteenth group was affiliated with S. acidiscabies. Their geographical distribution was characterized and revealed that on average between six and eight different genetic groups were detected per field, with variable abundance. Virulence assays showed strong differences in virulence between the genetic groups, ranging from low to highly virulent. Interestingly, pathogenic Streptomyces spp. populations in each field seem to be dominated by the most virulent genetic groups. The results obtained will contribute to better understanding of the population dynamic of pathogenic Streptomyces spp. causing CS of potato and promoting the development of more efficient detection and intervention tools to manage this important potato disease.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".