Effect of Heat Pretreatment on Freeze Drying of Tilapia Meat
Bibliographic record
Abstract
In order to improve the drying rate and rehydration of tilapia meat, the freeze-drying characteristics and quality changes of blanched or steamed fish meat were analyzed. The effect of heat pretreatment on the quality of freeze-dried fish meat was elucidated by considering the denaturation degree of myofibrillar protein, water distribution and microstructural changes in fish meat during the drying process. The results showed that heat pretreatment could effectively improve the drying rate of tilapia meat, shortening the drying time by nine hours compared with the control group; blanching was more effective than steaming. The rehydration temperature range for tilapia meat was expanded by heat pretreatment, and good rehydration was observed at 50–80 ℃. The rehydration temperature for the control samples was 80 ℃, and the rehydration rate of the 10 min heat treatment group was more than 60%, indicating that the dried product can be rapidly rehydrated. The hardness of the rehydrated fish meat was similar to that of cooked fresh fish meat, and it had good mouthfeel. Heat pretreatment caused significant denaturation of myofibrillar protein and consequently changes in water distribution and a conspicuous increase in the peak area of transverse relaxation time T23, indicating that the increase in free water content after heat treatment is an important reason for the increase in freeze-drying rate. The experimental results can provide technical support for the development of ready-to-eat dried fish products that are suitable for rehydration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".