Effects of Different Fertilizer Application Level on Growth and Physiology of Hibiscus cannabinus L. (Kenaf) Planted on BRIS Soil
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it