Effect of Biofertilizer on Growth, Yield and Bioactive Component of Plumbago zeylanica (Lead Wort)
Bibliographic record
Abstract
A comparative study on effect of chemical fertilizer and biofertiliser on Plumbago zeylanica for growth, yield and bioactive component was conducted at Bardoli (district-Surat), India between 2012 and 2013 using Random Block Design method and monthly observation of growth parameters. Application of biofertiliser Azotobacter, Azospirillum, Phosphate solubilizing Bacteria and mixture of Aza + Azo + PSB increased plant height, number of branches, number of leaves, length of root, fresh weight, dry weight and bioactive component (plumbagin). Highest effect on height (91.33±10.13) of plant was obtained with PSB applied biofertiliser whereas the number of branches (14.67±0.47) and number of leaves (25.60±13.17) was obtained with Azospirillum biofertilizer application. The length PSB (33.33±1.32), fresh weight (26.44±1.32) and dry weight of roots (24.66±1.13) was realized with application of mixture of Aza + Azo + PSB. The bioactive component (plumbagin) was high with application of Azospirillum (0.026%w/w) using HPLC. The results of this study suggest that biofertiliser have the potential to increase the growth, yield and bioactive component of Plumbago zeylanica.
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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 | 0.001 |
| 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".