Priority technologies for developing new highly productive varieties of spring bread wheat in the Middle Urals
Bibliographic record
Abstract
The study has been carried out at the FSBSI «Ural Federal Agrarian Research Center of the Ural Branch of the Russian Academy of Sciences» on the fields of the Krasnoufimsk Breeding Center in 2019–2021. The purpose was to develop new highly productive varieties of spring bread wheat adapted to the climatic conditions of the Middle Urals using parental forms with high breeding indices in hybridization. There has been given a characteristic of the earlymaturing variety ‘Ekstra’ and middle-early maturing ‘Nitsa’ and their parents, namely, ‘Omskaya 35’ and ‘Iren’, ‘Ekaterina’ and ‘Krasnoufimskaya 100’, according to such breeding indices as Mexican, Canadian, Poltava, attraction, productivity, potential head productivity, intensity, micro-distribution, linear head density, grain filling. There has been shown that the productivity advantage of the variety ‘Ekstra’ over the variety ‘Iren’ was 0.37 t/ha (11.1 %) and over thevariety ‘Omskaya 35’ it was 0.31 t/ha (9.1 %). The variety ‘Ekstra’ has combined the high values of six breeding indices from the middle maturing variety ‘Omskaya 35’ and exceeded both parents in the studied indices. The productivity advantage of the variety ‘Nitsa’ was 0.52 t/ha (19.2 %) over the variety ‘Ekaterina’ and over the variety ‘Krasnoufimskaya 100’ it was 0.40 t/ha (14.2 %). It has combined the high values of four indices from the variety ‘Ekaterina’, six from the variety ‘Krasnoufimskaya 100’ and significantly exceeded the parental varieties according to such indices as Poltava, Mexican, microdistribution, attraction, grain filling, intensity. There has been identified a high positive correlation between grain productivity and attraction indices (r = 0.761) and Mexican (r = 0.864), an average positive correlation between indices of intensity (r = 0.601), potential head productivity (r = 0.507), grain filling (r = 0.333). The results have showed that involving parents with high values of breeding indices into hybridization could contribute to the development of new highly productive varieties of spring wheat.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".