Phenotypic association of adult-plant resistance to leaf and stripe rusts in wheat
Bibliographic record
Abstract
Association of resistance to multiple diseases is of interest to plant breeders as it simplifies the breeding process. Phenotypic association of adult-plant resistance to leaf and stripe rusts, caused by Puccinia triticina and Puccinia striiformis f. sp. tritici, respectively, was studied in F5 wheat lines derived from a diallel cross involving one susceptible and five resistant genotypes. Resistance in the parental genotypes was formerly identified as being conditioned by the Lr34/Yr18 linkage on chromosome arm 7DS, in addition to at least two to three genes with additive effects. Adult-plant resistance to leaf rust was found to be closely associated with resistance to stripe rust in the wheat genotypes examined in this study. Results indicated that genes other than Lr34/Yr18 were also either linked or pleiotropic for resistance to both diseases. This linkage or pleiotropic effect, however, did not seem to occur in every instance. Resistance genes other than Lr34/Yr18 were estimated to have contributed to 40% and 43% reductions in severity of leaf and stripe rusts, respectively, while lines with a phenotype of leaf-tip necrosishad, on average, 30.5% and 20.8% less severity for leaf and stripe rusts, respectively.
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) | 0.000 | 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) | 0.001 | 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".