Effect of Different Nutrient Media on Okra (<i>Abelmoschus esculentus</i> L. Moench) Production in Kailali, Nepal
Bibliographic record
Abstract
An experiment was conducted in Kailali district, Nepal, to evaluate the effect of different nutrient media on the production of okra (Abelmoschus esculentus L. Moench).The study employed a single-factorial Randomized Complete Block Design (RCBD) with eight treatments replicated three times.The treatments included farmyard manure (FYM), vermicompost, poultry manure, synthetic fertilizer (NPK), 50% NPK + 50% FYM, 50% NPK + 50% vermicompost, 50% NPK + 50% poultry manure, and a no-fertilizer control.The okra variety Arka Anamika was used, and data were collected on growth and yield parameters such as plant height, number of leaves and branches per plant, fruit count per plant, fruit length and diameter, and total yield (ton/ha).Measurements were taken from ten randomly selected plants from the central rows of each plot, and data were analyzed using R software.Results indicated that poultry manure led to the highest yield at 21.18 ton/ha and significantly improved growth characteristics such as plant height and leaf number while control being the lowest 9.95 ton/ha.Conversely, the control and synthetic fertilizer treatments showed the poorest performance.The findings suggest that poultry manure is an effective nutrient source for enhancing okra growth and yield.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".