Genetic Diversity of the Male and Species in Torreya Grandis Based on SRAP Analysis
Bibliographic record
Abstract
Torreya grandis Fort. ex Lindl, a dioecious species, has a multitude of natural variation and great potential for selection and breeding. Naturally there exist some superior individuals which could be comparable to T. grandis “Merrillii”, an excellent cultivar vegetatively propagated from a superior natural variant from T. grandis. Development of T. grandis “Merrillii” industry, in addition to some historical reasons, has some effects on genetic diversity of the species. This paper analyzes SRAP marker-based genetic diversity of male populations from the same sampling sites as the female populations and genetic diversity at the species level in T. grandis with the maker data from both female and male populations. The result showed that male T. grandis populations had an abundant genetic diversity with a percentage of polymorphic loci (PPL%) of 63.67%, a number of alleles (Na) of 1.6367, an effective number of alleles (Ne) of 1.3813, a Nei’s gene diversity (H) of 0.2218, and a Shannon Information index (I) of 0.3311 and 81.48% of genetic variation existed among individuals within a population. Male T. grandis populations were not better than female populations in terms of genetic parameters. Both male and female acted on the rich genetic diversity of T. grandis at the species level. It is suggested that importance be attached to the conservation of genetic diversity in T. grandis, especially that of the male population, and selection of superior individuals could be conducted based on their good performance.
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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 | 0.001 |
| 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".