Effect of Hot Air Oven and Microwave Oven Drying on Production of Quality Dry Flowers of Dutch Roses
Bibliographic record
Abstract
The present investigation was conducted to evaluate different oven drying methods for obtaining better quality dried flowers of four Dutch rose cultivars viz., Skyline, Lambada, Ravel’ and First Red. Flowers dried at 40°C in hot air oven with silica gel were more acceptable for colour (3.48), appearance (3.50) and texture (3.23). Flowers dried by non-embedding method took least time (52.32 hours) for drying compared to embedded method. Flowers of ‘Lambada’ dried without embedding took least time for drying (52.07 hours) in hot air oven compared to other cultivars. Quality parameters such as colour (3.48), appearance (3.51) and texture (3.29) were superior in flowers dried for 2.5 minutes in microwave oven by embedding in silica gel. Flowers of ‘Lambada’ dried for 2.5 minutes by embedding in silica gel were best for overall acceptability, while unacceptable quality was obtained in case of flowers dried without any embedding medium. With respect to mode of desiccation, embedded drying was best for quality parameters viz., colour (2.92), appearance (2.81) and texture (2.55); however, non-embedding methods were least acceptable for quality parameters. Flowers of cv. ‘Lambada’ dried by embedding in silica gel yielded best quality dried flowers as it scored maximum point for all the quality parameters studied.
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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 | 0.001 |
| 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 | 0.000 |
| 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".