Virulence analysis of <i>Puccinia graminis</i> f.sp. <i>tritici</i> populations in Ethiopia with special consideration of Ug99
Bibliographic record
Abstract
Wheat stem rust samples were collected in 2006 and 2007 in the Arsi, Bale, Shewa and northwest regions of Ethiopia to determine virulence diversity and race distribution in Puccinia graminis f.sp. tritici populations. Stem rust incidence was high in Arsi, Bale and east Shewa. In northwest Ethiopia, and north and west Shewa, stem rust was prevalent at low levels. A total of 152 isolates was analysed and 22 races were identified. Races TTKSR (Ug99), TTHSR and RRTTR were predominant, with frequencies of 26·6, 17·7 and 11·1%, respectively. These races were also detected in all regions. The highly virulent race designated Ug99 was present throughout the country and dominated in all regions except northwest Ethiopia. A variant of Ug99 virulent against the stem rust resistance gene Sr24 was not detected in this study. Four stem rust resistance genes ( Sr13, Sr30, Sr36 and SrTm p) were found to confer resistance to most of the races prevalent in Ethiopia. With the exception of Sr30 , which is not effective against Ug99, these genes could be used in breeding for resistance to stem rust in Ethiopia.
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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".