The influence of irrigation and fertilization on heartwood and sapwood contents in 18-year-old <i>Eucalyptus globulus</i> trees
Bibliographic record
Abstract
The quality of wood from 18-year-old Tasmanian bluegum (Eucalyptus globulus Labill.) trees was assessed in relation to heartwood content, accumulation of extractives, and pulp yield using two growth conditions: control (C) and growth optimized by irrigation and fertilization in the first 6 years of growth (IL). Within the tree, heartwood content decreased from the base upwards, representing, on average, 77.7% and 67.6% at the base and 7.0% and 4.8% at 29.3 m height for IL and C trees, respectively. Heartwood volume represented 65.6% and 55.6% of total tree volume for IL and C trees, respectively. Heartwood content was positively correlated with tree growth, while sapwood content remained rather constant, with a radial width of approximately 2 cm. Heartwood contained more extractives than sapwood (5.3% vs. 4.0%) and pulp yield was lower from heartwood than from sapwood (58.0% vs. 56.0%). Pulp yield was negatively correlated with content of extractives. No difference in extractives or pulp yield was found between IL and C trees. The presence of heartwood decreases the quality of raw material for pulping and should be regarded as a stem-quality variable in eucalypt forestry.
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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 | 0.000 | 0.000 |
| 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 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".