Efficient drying of laser-treated raspberry in a pulse-spouted microwave freeze dryer
Bibliographic record
Abstract
Pulse-spouted microwave freeze drying (PSMFD) has been shown to be more energy efficient than the conventional vacuum freeze dryer. PSMFD yields higher drying rate and better energy efficiency due to volumetric heating. Because of the mass transfer resistance due to the berry’s epidermal barrier during drying, the raspberry skin was subjected to laser pretreatment so as to perforate the surface with pre-selected number of fine holes generated by a CO2 laser. The perforations allow vapor generated within the bulk of the berry to escape with no resistance of the waxy skin. In addition to studying the effect of perforation parameters on drying time; therefore, quality indicators of the dried product (shrinkage ratio, hardness, rehydration capacity, color, flavor, and anthocyanin content) were also explored. The micropore parameters in experiments were set as follows: P-0 (no perforations), P-3 (12 perforations), P-6 (24 perforations), and P-9 (36 perforations). As expected, greater the number of perforations per berry shorter is the drying time, by up to 23.08%. Moreover, the shortened drying time has a positive effect on product quality as well. The shrinkage rate could be reduced by about 3.95% and the retention rate of anthocyanin could be increased by 20.02%.
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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 | 0.000 | 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) | 0.000 | 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".