The influence of particular chromosome regions of Triticum timopheevii on the formation of resistance to diseases and quantitative traits in common wheat
Bibliographic record
Abstract
Evaluation of the influence of Triticum timopheevii Zhuk. introgression fragments (2 n = 28, A t A t GG) and their combinations on resistance to leaf and stem rust, powdery mildew, and a number of quantitative traits in 15 introgressive lines of common wheat was conducted. Analysis of introgressive lines by molecular genetic and cytological methods showed the efficiency of using a complex of different types of markers for detailed characterization of hybrid forms and detection of different translocations and substitutions. Evaluation of lines according to their resistance to fungal diseases showed that lines that contain an introgressive fragment of the 5G chromosome in their genome are completely resistant to populations of leaf rust in Western Siberia and the stem rust that is typical for Omsk oblast. Lines 3862-5 and 3862-15, which contain a fragment of the long arm of the 2G chromosome in their genome, were resistant to the population of stem rust in Western Siberia. Introgressive lines were studied for a number of quantitative traits. No negative influence of alien material on the yield and other quantitative traits was observed in all studied lines, which allows one to use them in breeding as donors of resistance to fungal diseases. In addition, the positive influence of T. timopheevii 2G chromosome fragments on the number of grains in an ear was determined.
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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".