Marker-assisted selection in <i>C. oleifera</i> hybrid population
Bibliographic record
Abstract
Abstract Marker-assisted selection (MAS) is implemented to improve Camellia oleifera yield and fruit attributes for meeting China’s increased demand for new varieties development. We conducted three-generational (G 0 , G 1 , and G 2 ) hybridization (diallel mating) and selection experiment and used Sequence-Related Amplified Polymorphism (SRAP). SRAP markers to investigate their utility in a MAS framework. The utilized SRAP markers were instrumental in hybrid authenticity and the identification of matroclinal or patroclinal inheritance presence, thus guiding mating pair selection and direction (their role as male or females). Across the studied 3 generations, estimates of genetic diversity parameters showed steady increase with percentage increase of ((G 0 to G 1 and G 1 to G 2 ) 9.25 and 9.05: observed number of alleles; 3.12 and 7.80: means effective number of alleles; 12.35 and 22.34: Nei‘s gene diversity; and 14.21 and 21.77: Shannon‘s index), indicating lack of diversity reduction associated with selection. Estimates of genetic distance and their correlation with heterosis were useful in guiding selection of mating pairs for achieving the desired yield and fruit attributes (fruit diameter, height, weight, and index, peel thickness, number of seeds per fruit, seed weight per fruit, and seed rate). Most yield and fruit attributes exhibited high broad-sense heritability with increasing trend over generation intervals, indicating the increased potential of hybrid breeding for this species.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".