RESULTS OF CREATION AND STUDY OF HYBRID SOYBEAN POPULATIONS IN THE FOREST-STEPPE OF WESTERN SIBERIA
Bibliographic record
Abstract
The aim of the study is to create hybrid material valuable for breeding soybean varieties of the Siberian ecotype, combining early maturity with high seed productivity in the forest-steppe conditions of Western Siberia. The studies were conducted in 2020–2023 in the southern forest-steppe of the Omsk Region at the Omsk Scientific Research Center using generally accepted methods. Objects of study: 47 F1-F3 populations isolated from 4 hybrid combinations created in 2020 by crossing the early maturing line of local selection L 52/14 (Mageva Dina) with later maturing paternal foreign varieties Prudence, Maxus, Kofu (Canada), Pripyat (Belarus), and these original forms. The weather conditions of the period May – September in the years of the experiments were dry (HTC in 2021 – 0.58; 2022 – 0.95; 2023 – 0.78), but relatively favorable for the development of soybean plants. The greatest transgression in seed weight per plant was established in the populations: F2 (L 52/14 Kofu) – the degree of Tc = 138.4 %, the frequency of Tch = 20.9 % and F3 (L 52/14 Maxus) – Tc = 132.3 %, Tch = 8.6 %. In F1–F3, all types of inheritance (hp) of the duration of the growing season (DVP) and seed weight per plant (SWP) were revealed. The earliest maturing population (L 52/14 Prudence) (on average over 3 years, PVP = 90 days) had a negative effect in the inheritance of the analyzed indicators. Only L 52/14 Kofu showed positive overdominance for MSR in F1 and F2. All the created hybrid populations are valuable for soybean breeding in the southern forest-steppe of Western Siberia. But the most promising is the hybrid L 52/14 Prudence – from it, F3 populations with a vegetation period of no more than 105 days with increased transgression rates for MSR were isolated. In the F3 populations of the other three hybrids, 16–35 % of plants had the maximum permissible PVP for the conditions of Western Siberia – 118–125 days. But given the high productivity potential, they are valuable source material for soybean breeding in other regions of the Russian Federation.
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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".