Economics of Production and Marketing of Potato (<i>Solanum tuberosum</i>) in Rasuwa District, Nepal
Bibliographic record
Abstract
Potato (Solanum tuberosum) is one of the important cash crops of Nepal which contributes a lot to the rural livelihood of Nepal.It accounts for 5.52 % to AGDP of Nepal.To study the economics of production and marketing attributes of potato farming, a study was conducted in Uttargaya rural municipality of Rasuwa district.Questionnaire-based household surveys along with field observations were conducted, taking in consideration a total of 60 potato farmers selected by simple random sampling method.Additionally, 10 traders were also selected to study about the marketing.Among the different varieties used by farmers, Cardinal was the most preferred (46.7%).The average cost of production was found to be NRs 209,238/ha with BCR of 2.02.The average productivity of potato in the study area was found to be 16.15mt/ha.The average gross margin per ha, market margin and producer's share were found to be NRs 206,604, 28/kg and 53.33% respectively.Similarly, four types of marketing channels were particularly identified.Five-point scaling technique was used for ranking the production and marketing problems.It identified that high cost and lack of quality inputs (I=0.87),scarcity of irrigation water (I=0.72),disease/insect/pest (I=0.78) were the major production problems whereas wholesaler's dominancy over the market (I=0.87),low market price (I=0.77)were the marketing constraints.Moreover, middlemen's dominancy influenced the farm gate price.Technical, infrastructure, government support through subsidies if provided will surely enhance the production and profitability of potato enterprise with the advantage of climatic condition of the district.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".