Stem rust: its history in Kenya and research to combat a global wheat threat
Bibliographic record
Abstract
Stem rust, caused by Puccinia graminis f. sp. tritici (Pgt), is a major disease of wheat. In Kenya, Pgt has caused sporadic but serious losses to farmers since large-scale wheat production began in the early twentieth Century. Breeding for stem rust resistance in Kenya has been conducted since 1910. Mutants of Pgt are common in Kenya as large pathogen populations survive on wheat crops planted throughout the year, with virulence to effective major genes developing shortly after release of resistant cultivars. Gene Sr31 was first deployed in Kenya in ‘Kenya Pa’a’ in 1982 and subsequently in ‘Duma’ in 1993, the latter grown on large acreage. Virulence to Sr31 was first detected in Uganda in 1998, in what became known as Pgt-Ug99 (race TTKSK). Virulence to Sr31 may have occurred earlier in Kenya, but Ug99 was first reported in 2001. Race TTKSK has migrated across East Africa and to Yemen and Iran, spreading to 13 countries with 13 race variants. Other Pgt races (TKTTF, TTRTF, TTTTF) with broad virulence were recently detected in Kenya, likely originating from central Asia. A ‘Sounding the Alarm’ message from Norman Borlaug in 2005 triggered extensive research on worldwide virulence in Pgt, and on finding, characterizing, and developing molecular markers for Sr genes effective to Ug99-lineage pathotypes of Pgt. While fungicides can control Pgt, the best strategy uses host resistance. The best gene stewardship practice to provide enduring resistance combines effective major and minor adult plant resistance (APR) genes prior to release of new wheat cultivars.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".