Screening of the world winter bread wheat collection for leafstem disease resistance in the Lower Volga region
Bibliographic record
Abstract
The current paper has presented the study results of collection winter bread wheat samples. The purpose of the study was to screen the world collection of winter bread wheat for disease resistance in the Nizhnevolzhsky region. The study was carried out on the basis of the FSBSI “Federal Agricultural Research Center of the South-East” (Saratov). In 2017–2021 there was conducted an estimation of the resistance of 152 winter bread wheat samples to the main pathogens. The samples were sown at the optimal time with the SSFC-8 seeder on plots of 3 m2 in a single repetition. The seeding rate was 450 germinating seeds per m2 . There have been studied the world collection varietal samples of winter bread wheat VIR (from breeding centers of the USA, Canada, Ukraine, Slovakia, Latvia, Hungary, etc.), as well as the samples of domestic breeding (FANC of the South-East, NTsZ named after P.P. Lukyanenko, Severokavkazsky FNATS, etc.). There have been identified the most harmful leaf-stem diseases, such as brown rust (Puccinia triticina Erikss.) and stem rust (Puccinia graminis f. sp. Tritici), septoria (Septoria tritici Rob. et Desm.) and yellow leaf blotch (Pyrenophora tritici-repentis (Died) Drechsler). There has been characterized the resistance of the winter bread wheat collection to the complex of leaf-stem diseases. There have been identified two samples with group resistance to brown and stem rusts, septoria and pyrenophorosis; one sample resistant to leaf rust and stem rust; three samples resistant to stem rust and septoria; one sample resistant to leaf and stem rust and septoria; six samples resistant to septoria and pyrenophorosis.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".