Heterosis and Combining Ability Estimates in Isoflavone Content Using Different Parental Soybean Accessions: Wild Soybean, a Valuable Germplasm for Soybean Breeding
Bibliographic record
Abstract
Isoflavone, a group of secondary metabolites in soybean, is beneficial to human health. Improving isoflavone content in soybean seeds has become one of the most important breeding objectives. However, the narrow genetic base of soybean cultivars hampered crop improvement. Wild soybean is an extraordinarily important gene pool for soybean breeding. In order to select an optimal germplasm for breeding programs to increase isoflavone concentration, 36 F1 soybean progenies from different parental accessions (cultivars, wild, Semi-wild and Interspecific) with various total isoflavone (TIF) concentration (High, Middle, Low) were analyzed for their isoflavone content. Results showed that male parents, except for Cultivars, showed positive GCA effects. In particular, wild soybean had higher positive GCA effects for TIF concentration. Both MP and BP heterosis value declined in the hybrid in which male parents were wild soybean, semi-wild soybean, interspecific offspring and cultivar in turn. In general, combining ability and heterosis in hybrids which had relative higher TIF concentration level parents showed better performance than those which had lower TIF concentration level parents. These results indicated characteristics of isoflavone content were mainly governed by additive type of gene action, and wild relatives could be utilized for breeding of soybean cultivars with this trait. A promising combination was found as the best potential hybrid for isoflavone content improvement.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".