Virulence Dynamics of the Barley Leaf Rust Pathogen (<i>Puccinia hordei</i>) in the United States from 1989 to 2020
Bibliographic record
Abstract
Barley leaf rust, caused by Puccinia hordei, is an important disease of barley worldwide. The pathogen can develop new races that overcome resistance genes, emphasizing the need for monitoring its virulence. This study characterized 519 P. hordei isolates collected in the United States from the 1989 to 2000 and 2010 to 2020 survey periods on 15 Rph (Reaction to Puccinia hordei) genes. We analyzed linearized infection type data to detect virulence patterns across the United States and in five geographical regions: Pacific/West (PW), Southwest (SW), Midwest (MW), Northeast (NE), and Southeast (SE). Over 32 years, we observed high mean infection scores for Rph1.a, Rph4.d, and Rph8.h; intermediate scores for Rph2.b, Rph9.i, Rph10.o, Rph11.p, and Rph13.x; and low scores for Rph3.c, Rph5.e, Rph5.f, Rph7.g, Rph9.z, Rph14.ab, and Rph15.ad. Virulence for Rph2.b, Rph3.c, Rph5.e, Rph9.z, Rph10.o, Rph11.p, and Rph13.x significantly differed between the two survey periods. From 1989 to 2020, regional patterns of virulence were found for Rph5.e, Rph5.f, Rph7.g, and Rph14.ab, while regionalities of virulence for Rph3.c, Rph9.i, Rph9.z were only observed in the 2010 to 2020 survey period. Virulence associations were also detected in the P. hordei population. Notably, isolates that were virulent to Rph5.e and Rph6.f were more likely to be avirulent to Rph7.g and Rph13.x, and vice versa. In decreasing order of effectiveness, Rph15.ad, Rph5.e, Rph3.c, Rph9.z, Rph7.g, Rph5.f, and Rph14.ab were the most effective Rph genes in the United States from 1989 to 2020. Pyramiding Rph15.ad with other widely effective Rph and adult plant resistance genes may provide long-lasting resistance against P. hordei.
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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 | 0.000 | 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 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".