Development of an international standard set of barley differential genotypes for <i>Pyrenophora teres</i> f. <i>teres</i>
Bibliographic record
Abstract
International comparison of virulence profiles of Pyrenophora teres f . teres (Ptt), the cause of barley net blotch, is seriously restricted by inconsistencies in differential testers used among researchers. This paper reports an attempt to develop an appropriate set of differentials to standardize characterization of Ptt populations globally. Fourteen barley genotypes (Canadian Lake Shore (CLS), Harbin, c‐8755, c‐20019, Manchurian, Tifang, CI 9825, CI 5791, CI 9819, Beecher, CI 9214, Skiff, Prior and Corvette) were selected from among genotypes previously used as Ptt differentials. Three cultivars (Pirkka, Haruna Nijo and Harrington) were included to identify a universally susceptible control. Genotypes were inoculated with approximately 1000 Ptt isolates from Russia, Europe, Australia and Canada. The mean reaction frequency of genotypes ranged from highly resistant (CI 9819, CI 5791, c‐8755 and CI 9825) to highly susceptible (Harrington, Haruna Nijo and Pirkka). The best differential abilities were demonstrated by Harbin, CLS, c‐20019, Manchurian and Prior. Application of cluster analyses identified genotypes with similar reaction patterns, which supported a reduction of genotypes in the set. When combined with an algorithm comparing the ability of individual genotypes to discriminate among Ptt isolates, a further reduction of genotypes was justified. A new, concise set of barley genotypes for differentiating virulences in Ptt was formulated. It is proposed that these genotypes be adopted as the standard, international differential set to characterize and identify the virulence properties of Ptt populations across environments. The new Ptt differential set consists of the genotypes c‐8755, c‐20019, CI 5791, CI 9825, CLS, Harbin, Prior, Skiff and Harrington.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".