Genetic Diversity Analysis of Hybrid Rice Parental Lines and Genetic Purity Assessment of Hybrid Seeds of China
Bibliographic record
Abstract
Thirty-five pairs of SSR primers were used for genetic diversity analysis and DNA fingerprinting of 31 hybrid rice core parental lines developed in central- and southern-China using one japonica rice line and three inbred rice lines as the check varieties. The average number of alleles (Na) per SSR locus was 4.02, with a range of two to eight, the effective number of alleles (Ne) was 83.16 with a mean of 2.38, ranging from 1.19 to 4.66. The polymorphic information content (PIC) ranged from 0.16 to 0.79, with an average number of 0.52. The results of the cluster analysis indicated that the check varieties viz., one japonica rice and three inbred rice, were clustered into two groups with similarity coefficients of 0.62 and 0.71 respectively indicating their relatedness. Thirty-one hybrid rice parental lines were clustered into 6 groups according to their different types, pedigrees and regions of development with similarity coefficients of approximately 0.76. The highest genetic similarity coefficient (0.94) was observed between Y58S and C815S, and the lowest (0.63) was observed between Quan9311A and Peiai64S. The purity of one hybrid rice cultivar was tested using characteristic marker and the field test, and it was demonstrated that the purities obtained using the two methods were similar. This research will be helpful for rice breeding, new cultivar registration and seed production.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".