Dragon Fruit Farming in Nepal: A Comprehensive Review
Bibliographic record
Abstract
Dragon fruit is a promising horticultural crop due to its resilience to pests, diseases, and abiotic stresses, as well as its nature to thrive on marginal lands.Dragon fruit can be grown in a in a wide range of soils, from sandy loam to clay loam, particularly in the Terai and lower hills of Nepal.A temperature of about 25 °C is suitable for its growth, and about 7-10 hours of sunlight are required for active growth and development.Dragon fruit is propagated by using cuttings and seeds, but seed is less favorable.Red pitaya, American beauty, Costarican sunset and white pitaya are widely popular varieties of dragon fruit in Nepal.The fruits are produced between June and September and harvested three or four times per month.Lack of market, high production costs, and lack of proper knowledge were the major problems in dragon fruit farming.This review points out the cultivation practices and challenges of dragon fruit in the country, aiming to help future research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".