Virulence characterization of the wheat stripe rust pathogen, <i>Puccinia striiformis</i> f. sp. <i>tritici</i> , in Turkey from 2018 to 2020
Bibliographic record
Abstract
Stripe (yellow) rust caused by Puccinia striiformis f. sp. tritici (Pst) is the most devastating disease of wheat in Turkey. Virulence characterization of the Pst population is critical to prevent large-scale epidemics, by developing wheat cultivars with durable resistance against the disease. In this study, 38 Pst races, including 25 races that were not previously reported, were identified from 140 isolates obtained from most regions of Turkey from 2018 to 2020 using a differential set containing 18 single Yr gene wheat lines (NILs) of ‘Avocet’. Virulence to Yr15 was not observed among any of the isolates. Virulence to the remaining 17-Yr genes was detected at various frequencies. The frequencies of virulence to Yr6, Yr9, Yr7, Yr8, Yr43, YrExp2, Yr44, YrTr1, and Yr27 were high (57.1 to 100.0%), to Yr1, Yr17, Yr32, and YrTye were moderate (24.3 to 42.9%), and to YrSP, Yr24, and Yr10 were low (9.3 to 17.1%). Only one race was virulent to Yr5 (0.7%). Many of the races identified were common among regions, indicating that Pst races migrate throughout Turkey. However, the Black Sea (BS) and the Mediterranean (ME) regions were differentiated from other regions by unique races absent in other regions, and the Yr5-virulent race, respectively. To sum up, the virulences of the races identified and their distributions among regions provided an understanding of pathogen migration and may contribute to the development of resistant wheat cultivars against stripe rust.
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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) | 0.000 | 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 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".