Genetic Variation in Growth and Cone Traits of Pinus Koraiensis Half-Sib Families in Northeast China
Bibliographic record
Abstract
Genetic parameters were evaluated for growth and cone characteristics (tree height, diameter at breast height, volume, cone number, thousand seeds weight and single cone seeds weight) on 86 half-sib families of Pinus koraiensis aged 31 years. Analyses of variance revealed significant differences (p < 0.001) in all growth and cone traits among families while no significant differences were detected among blocks and the interaction between blocks and families. The average family values for growth traits were 17.22 m, 8.67 cm and 0.43 m3 for tree height, diameter at breast height and volume, respectively. The average cone number, thousand seeds weight and single cone seeds weight were 17.57, 748.91 g and 77.25 g, respectively. Genotypic additive variance and phenotypic variances ranged from 0.00009 to 3.820 and from 0.0005 to 23.066, while genotypic and phenotypic coefficients of variation ranged from 2.693% to 37.196% and 4.963% to 60.595%, respectively. Heritability at the individual and family level ranged from 0.152 to 0.215 and 0.611 to 0.862, respectively. Growth traits were significantly positively correlated with each other, but cone traits showed a weak correlation with growth traits. Based on 10% selection rate, nine families each were selected as elite materials in terms of high performance in volume and cone numbers, with 22.16% and 43.82% genetic gain in volume and cone number, respectively. These results provide beneficial information to select excellent families and establish orchards of P. koraiensis from improved seeds.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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".