Introgression of leaf rust and stripe rust resistance from Sharon goatgrass (<i>Aegilops sharonensis</i> Eig) into bread wheat (<i>Triticum aestivum</i> L.)
Bibliographic record
Abstract
Leaf rust and stripe rust are devastating wheat diseases, causing significant yield losses in many regions of the world. The use of resistant varieties is the most efficient way to protect wheat crops from these diseases. Sharon goatgrass (Aegilops sharonensis or AES), which is a diploid wild relative of wheat, exhibits a high frequency of leaf and stripe rust resistance. We used the resistant AES accession TH548 and induced homoeologous recombination by the ph1b allele to obtain resistant wheat recombinant lines carrying AES chromosome segments in the genetic background of the spring wheat cultivar Galil. The gametocidal effect from AES was overcome by using an "anti-gametocidal" wheat mutant. These recombinant lines were found resistant to highly virulent races of the leaf and stripe rust pathogens in Israel and the United States. Molecular DArT analysis of the different recombinant lines revealed different lengths of AES segments on wheat chromosome 6B, which indicates the location of both resistance genes.
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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".