Heartwood-Sapwood-Bark profiles and association studies in Pterocarpus marsupium Roxb., a vulnerable antidiabetic forestry species of sub- tropical forest
Bibliographic record
Abstract
ABSTRACT Pterocarpus marsupium Roxb. is a multipurpose forestry species of the sub-tropical region of the Indian subcontinent and its heartwood is known for excellent antidiabetic properties. However, due to unsustainable extraction, its populations are dwindling in natural ranges. In the present investigation, we studied the variations of heartwood and related characters in populations sampled from central India. For this, we sampled populations from different sites falling in mixed and sal forest of the central Indian state of Madhya Pradesh. Adaptive cluster sampling was followed for selection of study sites. Wood core samples were extracted at breast height using a Haglof three-thread increment borer. For each core, we measured bark thickness, sapwood thickness, heartwood diameter (cm), bark (%), sapwood (%), heartwood (%), sapwood area, heartwood area, sapwood area to heartwood area ratio and cross-sectional area. The analysis revealed that bark thickness ranged from 1.0 – 3.6 cm with an average of 2.21 cm; sapwood thickness from 2.0 – 12.0 cm with an average of 6.16 cm; heartwood diameter from 7.29 – 102.19 cm with an average of 36.77 cm. Bark, sapwood and heartwood percentages at breast height ranged from 1.37-31.9%, 1.96-45.97%, 39.23-96.68% with a mean value of 6.34%, 17.80% and 75.86%, respectively. Sapwood area, heartwood area and cross section area at breast height was also estimated and these parameters ranged from 39.76–1043 cm², 41.68–8197.6 cm² and 161.2–9476.5 cm², respectively. Despite its vulnerable status, P. marsupium populations recorded high variations for heartwood and related parameters. Correlation and path coefficient analysis revealed that bark (%), sapwood (%) and cross-sectional area are the most significant characters having a bearing on the heartwood percentage and could be utilised for selection, improvement and exploitation of heartwood.
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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 | 0.001 | 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".