Genetic control of kraft pulp yield in<i>Eucalyptus globulus</i>
Bibliographic record
Abstract
Pulp yield is an important breeding objective for Eucalyptus globulus Labill., but evaluation of its genetic control and genetic correlations with other traits has been limited by its high assessment cost. We used near infrared spectroscopy to study genetic variation in pulp yield and other traits in a 16-year-old E. globulus trial. Pulp yield was predicted for 2165 trees from 467 open-pollinated families from 17 geographic subraces. Significant differences between subraces and between families within subraces were detected for all traits. The high pulp yield of southern Tasmanian subraces suggested that their economic worth was previously underestimated. The narrow-sense heritability of pulp yield was medium (0.40). The significant positive genetic correlation between pulp yield and diameter (0.52) was at odds with the generally neutral values reported. The average of the reported genetic correlations between pulp yield and basic density (0.50) was also at odds with our nonsignificant estimate. Pulp yield of the subraces increased with increasing latitude, producing a negative correlation with density (–0.58). The absence of genetic correlations within subraces between pulp yield and density suggests that the correlation may be an independent response of the two traits to the same or different selection gradients that vary with latitude.
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 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".