Genetic Diversity of Soybean Landraces with Different Seed Coat Color
Bibliographic record
Abstract
In this study, the genetic diversity of 52 soybean landraces were analyzed using 60 SSR (Simple sequence repeat) markers. The results showed that a total of 545 alleles were detected by 60 pairs of SSR primers, with a range of 2-18 alleles and an average of 9.08 alleles per SSR locus. The gene diversity of 60 SSR markers was 0.4529-0.9210, with an average of 0.7579; the polymorphism information content was 0.3562-0.9157, with an average of 0.7288. The results showed that the genetic diversity of black and green soybeans was relatively high. The results of cluster analysis showed that 52 soybean landraces could be divided into 5 groups. AMOVA analysis showed that 11.27% of the genetic variation existed among groups. The Fst between yellow and black seed coat soybean, and the Fst between yellow and light green seed coat soybean were 0.0788 and 0.0867, respectively, indicating moderate genetic differentiation. This study can provide reference information for further utilization of soybean landraces and genetic improvement of black and green soybean varieties.
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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".