Genetic Similarity among Isolates of <i>Pyrenophora tritici‐repentis</i>, Causal Agent of Tan Spot of Wheat
Bibliographic record
Abstract
Abstract Tan spot, a foliar disease of wheat, is caused by the fungus Pyrenophora tritici‐repentis. On susceptible wheat cultivars, P. tritici‐repentis induces two distinct symptoms: tan necrosis and extensive chlorosis. Presently isolates of P. tritici‐repentis are classified into 11 races based on their virulence on a set of wheat differential genotypes. In nature, this pathogen reproduces both sexually and asexually, but the extent of genetic variability in the P. tritici‐repentis population of western Canada is unknown. This study was conducted to assess the genetic variability among different isolates of P. tritici‐repentis and to determine if similarities among isolates are correlated with race classification or geographic origin of the isolates. Thirty‐three isolates of P. tritici‐repentis and one isolate each of P. teres f. sp. teres, P. teres f. sp. maculata, P. graminea, Helminthosporium sativum and an uncharacterized isolate were studied with 30 random amplified polymorphic DNA (RAPD) primers. Cluster analysis showed that all isolates had unique banding patterns and that clustering of isolates was independent of their race designation or geographic origin. Analysis of molecular variation (amova) showed that 96.8% of variability occurred among isolates and among race variability accounted for only 3.2% of the total variability.
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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 | 0.001 | 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".