Mass transfer during osmotic dehydrationand its effect on anthocyanin retention of microwave vacuum‐dried blackberries
Bibliographic record
Abstract
Abstract BACKGROUND The combination of sugar osmotic dehydration and microwave vacuum drying is an effective method for the dehydration of blackberries, the retention of their antioxidant properties, and the extension of their shelf life. Mass transfer during the osmotic dehydration of blackberries in sugar solution was investigated together with its influence on microwave vacuum drying characteristics, and the retention rate of anthocyanins in dried frozen blackberries. RESULTS The concentrations of the osmotic solutions that were tested contained 40%, 50%, and 60% sugar, and the osmotic solution temperatures were 30 °C, 40 °C, and 50 °C. The solution‐to‐blackberry mass ratio was 10:1 (w/w) and the process duration varied from 0 to 5 h. A two‐parameter mathematical model was used to describe mass transfer in the osmotic dehydration of blackberry samples and estimate moisture loss and solid gain in the final equilibrium. The results showed that the dehydration rate and solid gain rate of the blackberries increased with an increase in osmotic concentration, osmotic time, and the temperature of the solution under certain experimental conditions. The effective diffusivity of moisture and solute were estimated using the analytical solution of Fick's second law of diffusion. The moisture and effective diffusivities of sugar in the above osmotic dehydration conditions were in the range of 1.77 × 10 −9 –2.10 × 10 −9 and 1.36 × 10 −9 –1.60 × 10 −9 m 2 .s −1 , respectively. CONCLUSION The pretreatment of sugar osmosis greatly reduced the microwave vacuum drying time in the latter part of the dehydration period and increased anthocyanin retention. © 2019 Society of Chemical Industry
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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) | 0.001 | 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".