Effects of Nitrogen, Phosphorus and Potassium Levels on Kenaf (Hibiscus cannabinus L.) Growth and Photosynthesis under Nutrient Solution
Bibliographic record
Abstract
To date, little is known about the effect of levels of nitrogen, phosphorus and potassium on kenaf grown innutrient solution culture. The objective of the present study was to examine the effects of different nitrogen,phosphorus and potassium levels on kenaf growth such as diameter, plant height, leaf number, root dry weight,stem dry weight and leaf dry weight and physiology like chlorophyll content, photosynthesis and stomatalconductance. Treatment consisted of 5 different levels of nitrogen viz. 0, 50, 100, 200 and 400 mg/L and 5different levels of phosphorus and potassium viz. 0, 25, 50, 100 and 200 mg/L replicated thrice in a completelyrandomized design in a shade house. Growth (diameter, plant height and leaf number), chlorophyll content andphotosynthesis were measured once weekly and plant components biomass was measured, 28 DAT. Differentlevels of nitrogen, phosphorus and potassium had significant effects on all the parameters studied. The highestvalues for diameter, plant height, leaf number, root dry weight, stem dry weight, leaf dry weight, photosynthesisand stomatal conductance were obtained from 200N, 100P and 100K whereas values decreased with furtherincrease in levels of nutrient concentration. All the growth rates, chlorophyll content and photosynthesis declinedwith lower level of nitrogen, phosphorus and potassium. Among the plant components, leaf dry weight had thegreatest decrease while root/shoot ratio increased under N deficiency. The results of this study provide newknowledge to produce kenaf with better nutrient management in the field.
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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".