Reaction of barley seedlings with different stem rust resistance genes to<i>Puccinia graminis</i>f. sp.<i>tritici</i>and<i>Puccinia graminis</i>f. sp.<i>secalis</i>
Bibliographic record
Abstract
Seedling tests are desirable for disease resistance screening in breeding programs because a large number of lines can be evaluated in a short period of time and with modest space requirements. This study was undertaken to identify pathotypes of the wheat stem rust pathogen (Puccinia graminis f. sp. tritici) and cultures of the rye stem rust pathogen (Puccinia graminis f. sp. secalis) that might be useful for detecting resistance genes in barley (Hordeum vulgare) at the seedling stage. Barley accessions with different resistance genes (Rpg1, Rpg2, Rpg3, rpg4, and rpgBH) were assessed for their infection types (ITs) to 13 pathotypes of P. graminis f. sp. tritici and two cultures of P. graminis f. sp. secalis at two temperature regimes (18–21 °C and 24–25 °C). The P. graminis f. sp. tritici pathotypes HKHJ and QCCJ were effective for specifically detecting Rpg1 and rpg4, respectively, and will facilitate resistance breeding efforts. No cultures were found to be effective for specifically detecting the resistance of Hietpas-5, PI 382313, or Black Hulless at the seedling stage. Some pathotypes or cultures did, however, produce low ITs on these sources and will therefore be useful for genetic studies involving crosses with susceptible barleys
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| 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".