Pore Development and Moisture Transfer in Chicken Meat during Deep-Fat Frying
Bibliographic record
Abstract
Changes in the structure of food products play important role in the various mass transfer processes during deep-fat frying. The relationship between moisture loss and pore formation were investigated at frying oil temperatures of 170, 180, and 190°C and frying times up to 900 s. Porosity and pore structure were characterized by using mercury intrusion porosimetry and helium displacement pycnometer. Moisture transfer in the samples was modeled using Fick's law and effective moisture diffusivity was computed from experimental data. Pore formation changes significantly (P < 0.01) in time as modulated by frying oil temperature. A peak pore fraction of 0.283 (after 360 s of frying), 0.238 and 0.220 (after 900 s of frying) at frying temperatures 190, 180 and 170°C, respectively was observed. Effective moisture diffusivity of 5.4 to 6.9 × 10−9 m2 s−1 and activation energy of 20 kJ/mol was obtained for the frying oil temperatures. Changes in pore structure influenced moisture diffusivity and oil uptake. Eighty-four percent of the pores are capillary pores, hence moisture transfer increased.
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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".