Osmotic Dehydration of Tomato in Sucrose Solutions: Fick's Law Classical Modeling
Bibliographic record
Abstract
Osmotic dehydration of tomato was modeled by the classical Fick's law including shrinkage, convective resistance at the interface and the presence of water bulk flow. Tomato slices having 8 mm thickness were osmotically dehydrated in sucrose solutions at 50, 60, and 70 degrees Brix and at 35, 45, and 55 degrees C. Other experiments were done in a 70 degrees Brix sucrose solution at 35 degrees C with tomato slices of 4, 6, and 8 mm thickness and at different motion levels (velocities 0, 0.053, and 0.107 m/s). Tomato weight, water content, and degrees Brix of the products were measured as a function of processing time (20, 40, 80, 160, and 320 min). Results showed that temperature, concentration, thickness, and solution movement significantly influenced water loss and sucrose gain during the osmotic dehydration of tomato. The model predicted the modifications of soluble solid content and water content as a function of time in close agreement with the experimental data. Experimental Sherwood number correlations for sucrose and water were determined as Sh(s) = 1.3 Re(0.5)Sc(s) (0.15) and Sh(w) = 0.11 Re(0.5)Sc(w) (0.5), respectively. The effective diffusion coefficients of water (4.97 10(-11)- 2.10 10(-10) m(2)/s) and sucrose (3.18 10(-11)- 1.69 10(-10) m(2)/s) depended only on temperature through an Arrhenius-type relationship.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".