Integrating parental breeding value, genetic gain, and gamete contribution for elite family selection in Platycladus orientalis
Bibliographic record
Abstract
Abstract Platycladus orientalis (L.) Franco seed orchards play an important role in sustainable forestry in China but balancing genetic gain and genetic diversity remains a significant challenge. Two key factors influence the success of seed orchards: parental breeding value and gamete contribution, as they determine both the genetic gain and diversity of the seed crops produced. This study aimed to optimize breeding strategies by analyzing parental breeding value, gamete contribution, and genetic gain across two growth periods (89 families in 2008 and 52 families in 2021). We evaluated height, diameter at breast height, and stem volume of progeny in a primary seed orchard, uncovering significant genetic variation among families. Interestingly, no correlation was found between growth traits and gamete contribution, indicating their independence. Using comprehensive scoring and PCA-biplot analysis, we consistently identified several elite families with superior growth performance in both years. We propose an optimal breeding strategy that combines 30% selective harvesting and 50% selective thinning to effectively balance genetic gain and genetic diversity, addressing a critical goal in tree improvement programs. The selected families and optimized strategy provide a scalable framework not only for P. orientalis but also for other conifer species globally, enhancing both productivity and genetic diversity in afforestation efforts.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".