Virulence and diversity of<i>Puccinia striiformis</i>f. sp.<i>tritici</i>in Ethiopia
Bibliographic record
Abstract
Stripe rust of wheat (Triticum spp.), caused by Puccinia striiformis f. sp. tritici, is an important disease in Ethiopia. To investigate the population structure of the pathogen, 107 single-pustule isolates were collected from four regions (northern, central, southern, and southeastern Ethiopia) and tested on 24 differential genotypes with known resistance genes. The isolates were classified into 39 pathotypes. All isolates were virulent on Yr7 and avirulent on Yr1, Yr5, Yr15, and YrSp. Virulence complexity of the isolates ranged from 7 to 16, with a mean of 11.72. No common pathotype was shared by these regional collections. Distribution of pathotypes within the regions was quite even, whereas the richness of populations varied considerably between 1.78 (the central region) and 2.96 (the southeastern region). The genotypic, gene, and genetic diversities within populations were characterized using the Simpson, Nei, and Kosman indices. Significant differences among the regional populations were detected for both gene and genetic diversity within populations, whereas the genotypic diversity was rather stable. The lowest and highest diversities of wheat stripe rust occurred in the southern and northern regions, respectively. Genetic variation in the population structure of the pathogen observed in different geographical areas might indicate that unique wheat cultivars should be developed and released for production on a regional basis.
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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 | 0.001 | 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".