Inheritance of quantitative traits and the effect of heterosis in first-generation soybean hybrids
Bibliographic record
Abstract
The results of a selection and genetic analysis of the inheritance of essential economically beneficial traits by first-generation soybean hybrids according to the degree of phenotypic dominance and heterosis are presented. The authors considered an assessment of 18 hybrid soybean combinations based on four quantitative characteristics that make up productivity: the number of beans, the number of seeds, the weight of seeds per plant, and the weight of 1000 seeds. The research was conducted in the selection and primary seed production laboratory of the Federal State Budgetary Institution Federal Scientific Center All-Russian Research Institute of Soybeans in 2021–2022. Soybean samples for hybridization were selected using an ecological-geographical principle. The authors used the highly productive soybean varieties bred by the Federal Scientific Center All-Russian Research Institute of Soybeans as maternal forms: Sentyabrinka, Kukhanna; as paternal forms, varieties and samples from the American, European, and Asian ecological-geographical zones. The authors carried out the Artificial intraspecific hybridization in 2021 according to the method of K.K. Baby and T.P. Ryazantseva. As a result of the research, the nature of inheritance of the leading economically beneficial traits in intraspecific F 1 soybean hybrids was determined. The degree of manifestation and magnitude of heterosis varied greatly depending on the combination of crossing and the trait being studied - from overdominance to depression. It has been established that the effect of heterosis and overdominance in all four indicators: the number of beans, the number of seeds, the weight of seeds per plant, and the weight of 1000 seeds (h p = 1.14–23.96; G = 2.85–23.26%) – recorded in two promising combinations with the paternal form from the American ecological-geographical zone: ♀ Sentyabrinka x ♂ Saska (Canada) and ♀ Kuhanna x ♂ Saska (Canada). A high degree of phenotypic dominance (h p = 1.65–18.54) and heterosis (G = 5.04–44.53%) in terms of the number of beans, the number of seeds, and the weight of seeds per plant were noted in combination with paternal forms from the American (♀ September x ♂ Kyoto (Canada)), European (♀ September x ♂ Cordoba (Austria)) and Asian (♀ September x ♂ Heihe 12 (PRC)) ecological-geographical zones. These hybrid combinations are of great interest in breeding research for high productivity in the Amur region.
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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) | 0.000 | 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".