Batch Drying Kinetics of Cardamom in a Two-Dimensional Spouted Bed
Bibliographic record
Abstract
Cardamom (Elettaria cardamom L.) is considered the “Queen of the Spices” and enjoys a unique position in the international spices market. It finds application in culinary art for flavoring of foods, pharmaceutical, perfumery, cosmetics, and several other industries. Cardamom capsules contain 80% (wb) moisture content at the time of harvest, which must be brought down to 8–12% (wb) for safe storage. Drying is one of the most important unit operations in the commercial production of cardamom, because it determines the color of the end product. Conventionally, the cardamom capsules are dried in a kiln dryer, which yields a poor quality end product. The batch drying kinetics of cardamom were investigated experimentally in a two-dimensional spouted bed using both continuous and intermittent (on/off) spouting and heating schemes. The parameters investigated include inlet air temperature, bed height, slant angle, separation distance, draft tube height, and intermittency of spouting. The results indicated that the drying kinetics were comparable with fluidized beds for slow drying materials, where the drying rate is controlled by internal moisture diffusion. The drying characteristics of the cardamom in the spouted bed indicated that the inlet air temperature was the parameter that most significantly affected the drying rate as well as the quality of the product. It also showed that the intermittent drying of particles took 13 to 18 h compared to continuous drying, which ranged from 9½ to 13 h. Intermittent drying can save up to 25% of the thermal energy, in addition to yielding a better quality product in terms of color, flavor, and percentage yield of oleoresin extract.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".