Post-harvest and value chain management of large cardamom in hills and uplands
Bibliographic record
Abstract
Amomum subulatum Roxb. is cultivated largely in the eastern Himalayan region viz., Nepal, Bhutan and Indian states comprising of Sikkim, Uttaranchal and Darjeeling district of West Bengal. It is widely used in foods, beverages, perfumes and having enormous medicinal values. Some popular cultivars include Ramsey, Sawney, Golsey and Varlangey. Curing is the most crucial step in processing as capsule quality largely depends on curing conditions and methods. Optimum curing temperature is 45–55 °C and is usually done in traditional bhattis. Dried capsules are usually packed in polythene-lined jute bags for storage at 11% moisture content. The postharvest value chain consists of growers, collectors, traders, and exporters. The primary processing steps required by the present market are curing, tail cutting and grading. Curing is carried out by the farmers, and the remaining steps are done by wholesalers. India exports large cardomom to Australia, Canada, Pakistan, UK, etc. Singtam, Gangtok, Jorethang, Rongli, and Mangan etc., are the major local markets in Sikkim while Siliguri is the main trade junction from where it is distributed to Guwahati, Kolkata and Delhi. Well processed quality capsules have great demand in the market and help the growers by protecting and promoting their livelihood. This article reviews the agrotechniques of cultivation, postharvest processing, quality issues and trade patterns of large cardamom towards increasing its quality and value and thereby to protect and promote the livelihoods of several thousands of people in the value chain.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".