The Relatioship between Plant Density and Microclimate and Nutmeg (Myristica fragrans Houtt) Production in Nutmeg and Coconut Mixed-Planting System in Wakatobi District in Indonesia
Bibliographic record
Abstract
In Wakatobi district nutmeg trees are generally cultivated in mixed planting with coconut. The research employed observation method where sample plants were determined purposively based on intersection of nutmeg and coconut tree crowns; 42 plots of pairs of nearest neighboring plants. In each plot of pair of plants, plant density of nutmeg and coconut was calculated (individually and in total), then microclimate components (solar radiation, temperature and relative humidity) and nutmeg plant characteristics (vegetative and prodution components) were measured. Research results showed that plant density of nutmeg (218 plants ha-1) had exceeded its optimum number of population, plant density of coconut 144 plants ha-1 with relative density ratio of 58:42% or nutmeg was more dominant than coconut. Transmitted radiation and temperature below the crown was decreasing, and in contrast, intercepted radiation and relative humidity increased in line with the increased plant density of nutmeg. This condition led to the decrease in sum of fruits, weight of mace, and weight of kernel of individual nutmeg tree. Coconut plant density had non-significant correlation and non-significantly contributed to microclimate and production components of nutmeg. This indicated that the tendency for decreased production of nutmeg is less affected by coconut trees, but more because of shading effect of nutmeg trees due to close distance among them. In other word, there occured intraspecific competition (nutmeg and nutmeg), and not interspecific (nutmeg and coconut). Therefore, coconut can be cultivated in mixed planting with nutmeg through appropriate plant spacing.
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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".