Inheritance of economically valuable characters and heterosis in F1 soybean hybrids
Bibliographic record
Abstract
The work presents the findings of investigations on the inheritance of the main economically valuable characters inherited by F1 soybean hybrids; the indicators used in the course of the analysis: indicators of the degree of phenotypic dominance and heterosis. The assessment of 7 soybean hybrid combinations was carried out in respect of productivity presented by 4 quantitative characters: total number of beans, seeds, weight of seeds per plant and weight of 1000 seeds. The research was carried out at the All-Russian Research Institute of Soybean Laboratory of Soybean Breeding and Genetics in years 2018-2019. In the course of the study of the complex of economically valuable characters, highly productive varieties and samples of soybean of domestic and foreign selection were used as parental forms. Crossbreeding combinations were created by using various principles of selection of the initial parental forms. As a result of the research carried out, the nature of inheritance of the main characters of productivity in intraspecific F1 soybean hybrids was found. The level of manifestation and magnitude of heterosis varied greatly, depending on the combination of crossing and the studied character, variation: from the superdominance of high value to depression. At the same time, there was a tendency for a positive interrelation between the values of heterosis and dominance: the higher the degree of phenotypic dominance, the higher the heterosis. The highest heterosis effect (24,1...55,2%) was recorded for the main elements of the yield structure (number of beans, seeds, weight of seeds per one plant) in combinations – ♀ Hei 13-3345-5 (China) x Kyoto (Canada) , ♀ (L4942 х F1 d.623/86) terminal raceme x ♂ Heihe 4 selection (China), created on the basis of the principle of ecological and geographical remoteness of the initial parental forms. These hybrid combinations are of the greatest practical interest in breeding research for high productivity in the climates of the Amur Region.
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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 | 0.000 |
| 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".