YIELD OF DIFFERENT ORIGIN SOYBEAN VARIETY UNDER THE WESTERN SIBERIA CONDITIONS
Bibliographic record
Abstract
The studies were carried out in 2012–2022 in the southern forest-steppe of Western Siberia on the fields of the laboratory for the selection of leguminous crops of the Federal State Budgetary Scientific Institution of the Omsk ARC according to generally accepted methods. The purpose of research is to search for valuable sources for breeding and the creation of high-yielding soybean varieties adapted to the soil and climatic conditions of the forest-steppe of Western Siberia. Of the 243 collection samples of VIR of foreign selection, studied for the first time, 128 pieces matured. (52.8%). Valuable for breeding are varieties: Maple Ridge and Optimus (Canada); Fiskeby 4 (Sweden), Sito (Germany), Varsovie (Poland); Avanta, SibNIISKhoz 6, Bezenchukskaya uluchshennaya, Lydia (RF) and others. It is extremely risky to cultivate varieties that are not included in the State Register of Breeding Achievements for the 10th region, since they are not early enough and not stable in yield. For 2012–2023 the state register of the Russian Federation includes 7 early maturing soybean varieties bred by the Omsk ANC, of which 5 (Zolotystaya, Sibiryachka, Cheremshanka, Sibiriada, Sibiriada 20) are recommended for the 10th region. They need to be introduced into production in the forest-steppe of Western Siberia. On average, over 11 years, the yield of Omsk soybean varieties in the Competitive variety trial amounted to 2.79 t/ha, in favorable 2016 and 2017. – more than 3.5 t/ha. The Omsk Agricultural Research Center has created a new early maturing variety Sibiriada 20, which has been included in the State Register of the Russian Federation since 2023 and approved for use in the Central, Volga-Vyatka, Middle Volga, Urals, West Siberian and East Siberian regions. In 2018–2022 in the Competitive variety trial, its average seed yield was 3.11 t/ha (0.49 t/ha higher than the Sibiryachka standard), the maximum in 2018 was 4.46 t/ha.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".