Kenyan Isolates of <i>Puccinia graminis</i> f. sp. <i>tritici</i> from 2008 to 2014: Virulence to <i>SrTmp</i> in the Ug99 Race Group and Implications for Breeding Programs
Bibliographic record
Abstract
Frequent emergence of new variants in the Puccinia graminis f. sp. tritici Ug99 race group in Kenya has made pathogen survey a priority. We analyzed 140 isolates from 78 P. graminis f. sp. tritici samples collected in Kenya between 2008 and 2014 and identified six races, including three not detected prior to 2013. Genotypic analysis of 20 isolates from 2013 and 2014 collections showed that the new races TTHST, TTKTK, and TTKTT belong to the Ug99 race group. International advanced breeding lines were evaluated against an isolate of TTKTT (Sr31, Sr24, and SrTmp virulence) at the seedling stage. From 169 advanced lines from Kenya, 23% of lines with resistance to races TTKSK and TTKST were susceptible to TTKTT and, from two North American regional nurseries, 44 and 91% of resistant lines were susceptible. Three lines with combined resistance genes were developed to facilitate pathogen monitoring and race identification. These results indicate the increasing virulence and variability in the Kenyan P. graminis f. sp. tritici population and reveal vulnerabilities of elite germplasm to new races.
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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) | 0.001 | 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".