PSV-26 Phenotypic plasticity of Gliricidia sepium under different planting densities.
Bibliographic record
Abstract
Abstract Gliricidia sepium (Jacq.) Kunth ex Walp (G. sepium) is a versatile leguminous tree with significant potential for enhancing ecosystem services and supporting sustainable agriculture. Its ability to adapt to varying planting densities is crucial for maximizing biomass yield and forage quality. This study investigated the anatomical, productive, and bromatological responses of G. sepium to different planting densities, testing the hypothesis that increased density induces anatomical adaptations that enhance biomass production. A randomized block experiment evaluated three planting densities (10,000, 20,000, and 30,000 plants ha⁻¹), analyzing micromorphometric traits, biomass yield, bromatological composition, and key correlations among these variables. Leaf micromorphometric analysis revealed density-dependent changes in the abaxial epidermal surface, upper and lower collenchyma, lacunar parenchyma, and stomatal number and density. In stems, significant variations were observed in the medullary radius, cortex, and periderm, while roots exhibited structural modifications in the periderm and phloem. Higher planting densities positively influenced vegetative growth, with total edible plant length increasing linearly (P = 0.002), with no change in total forage production (P > 0.10). Among bromatological traits, hemicellulose content showed a decreasing trend as planting density increased (P = 0.09). Strong correlations between micromorphometric, biometric, productive, and bromatological variables suggested an integrated structural and functional adaptation to planting density. A density of 30,000 plants ha⁻¹ was optimal, balancing anatomical development, productivity, and quality. These findings confirm the phenotypic plasticity of G. sepium, demonstrating its ability to structurally and functionally adapt under intensive planting conditions. Such adaptations enhance its potential for high-yield forage production, supporting its domestication and sustainable use for ruminant feeding systems.
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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) | 0.001 | 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".