Optimization of Microwave-Osmotic Pretreatment of Apples with Subsequent Air-Drying for Preparing High-Quality Dried Product
Bibliographic record
Abstract
Prepared apple ( Red Gala ) cylinders were subjected to microwave-osmotic dehydration treatment under continuous flow medium spray (MWODS) conditions and then air-dried to a final 20% moisture content. The dried samples were evaluated for color and textural properties, and rehydration capacity. The MWODS pretreatments were based on a central composite rotatable design and a response surface methodology using five levels of sucrose concentration, temperature, and contact time at a constant flow rate of 2800 mL/min. The air-drying was carried out at 60 ° C, 15 ± 1 % relative humidity, and 0.64 ± 0.02 m/s air velocity. The results were compared to untreated air-dried (AD) (worst-case scenario) and freeze-dried (FD) (best-case scenario) apples without the MWODS treatment. Color properties were affected regardless of the type of treatment. Conventional AD apples were darker in color, whereas MWODS-treated samples were lighter with higher L ∗ and b ∗ values, higher Hue and Chroma values but lower a ∗ value and Δ E . Further the color parameters of MWODS-treated samples were closer or equal to the FD apples. The texture properties were also affected by the osmotic variables with MWODS treatment resulting in softer and chewier products. The AD samples were hard, and FD apples were brittle.
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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) | 0.001 | 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 | 0.001 |
| 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".