Effects of Different Fertilizer Application Level on Growth and Physiology of Hibiscus cannabinus L. (Kenaf) Planted on BRIS Soil
Bibliographic record
Abstract
Hibiscus cannabinus L. or Kenaf is one of the most potential annual crop planted throughout the world. Being fastgrowing and multipurpose, it has been utilized as a substitute of jute and, more recently, as raw product for the productionof pulp and paper. With strong and long fiber yield, mass production of Kenaf throughout Malaysia is critical. Theutilization of less fertile soils such as BRIS soils is important to increase the Kenaf production throughout Malaysia. Thus,the objective of this study was to determine the effects of different level fertilizer application on growth and physiology ofKenaf planted on BRIS soils. V36 variety was used and planted in three different plots by treatments with fertilizersnamely high (1960 kg/ plot), medium (1260 kg/ plot) and low (700 kg/ plot) respectively. Each plot comprises 106,000trees where trees were planted on 20 lines. There were contrasting results on the effects of fertilizer on growth andphysiology of Kenaf in the dry (41 days) and wet season (64 days). Significant effects were only observed for diameter,height, leaf number and area during the wet season. Similar results were also found for biomass. The increasing trendswith increasing the rates of fertilizer were observed in the wet season for growth and biomass parameters. The correlationanalyses between total aboveground biomass with diameter and height were more pronounced in the wet season. AGR,RGR and EG calculated from the differences between the dry and wet season readings for aboveground biomass showedthat the higher rate of fertilizer recorded the higher values of AGR and RGR. However, no trend was observed for EG.
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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) | 0.001 | 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 | 0.001 |
| 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".