TECHNOLOGY OF BARLEY BREEDING FOR RESISTANCE TO SMUT FUNGI
Bibliographic record
Abstract
The technology of creating varieties of barley resistant to the smut diseases has been developed. Their cultivation will help to reduce crop losses, increase the profitability of seed production, improve the quality of seeds, and reduce the environmental risk from the use of chemical plant protection products. This technology was first implemented in the Kemerovo Region in 1988-1999. The wide distribution of species Ustilago nuda (Jens.) Kell. et Sw. (65 %) and U. nigra Tapke (35 %) was revealed. The covered smut ( Ustilago hordei (Pers.) Kell. Et Sw.) was registered in individual collection varieties. The first and tenth races of a loose smut and the sixth race of a black loose smut were identified. The sources of individual and group immunity to the smut fungi from the world gene pool of barley are distinguished: Moskovsky 3/125, Suzdalets, Ramos (Moscow Region); Kazer (Rostov Region); line 3 KM-1192 (Belarus); Kumir Odessky (Ukraine); Guardian (Canada). The donor properties of resistance to a loose smut in the Bagan variety, line 53 HVS 91/76, line 1899 were studied. They are recommended for use in breeding programs. With their participation a new hybrid fund was created. Variability and inheritance of quantitative traits of productivity of hybrids was studied. To select the recombinants immune to the loose smut in combination with high productivity, the most promising combinations of hybrids have been identified: Bagan × Viner; Bagan × KM-16; l. 53 HVS 91/76 × KM-7; KM-7 × l. 1899; l. 1899 × KM-7. Among them, prospective breeding lines have been selected. The results of the implementation of technology elements in the selection of barley for resistance to smut fungi is the creation of immune highly productive varieties of a new generation: Simon and Luka (Kemerovo Region). They are included in the State register of breeding achievements since 2004.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".