Impact of different drying processes on the lipid deterioration and color characteristics of <scp><i>Penaeus vannamei</i></scp>
Bibliographic record
Abstract
BACKGROUND: Fresh shrimp (Penaeus vannamei) deteriorates easily and the drying process is an important processing method for prolonging the shelf life of shrimp. The traditional drying method is hot-air-drying (HD), which can cause some problems such as nutrient loss, discoloration and lipid oxidation. In recent years, freeze-drying (FD) has been popular for removing moisture from food at lower temperatures, maintaining the structure of raw materials, and improving storage stability of products. In the present study, the effects of HD and FD on lipid and color of P. vannamei and the mechanisms involved were investigated. RESULTS: FD caused less lipid oxidation compared to HD; consequently, FD-processed shrimps had lower levels of primary and secondary oxidation products, as well as acid value, and higher contents of triacylglycerol, phosphatidylcholine, phosphatidylethanolamine, eicosapentaenoic acid and docosahexaenoic acid compared to HD-processed samples. Lipase and lipoxygenase played a role in the oxidation and hydrolysis of lipids during drying process. FD-processed shrimps had lower yellowness value and chromatic aberrations but a higher whiteness value compared to HD-processed samples. Correlation analysis showed that lipid oxidation, astaxanthin degradation and the Maillard reaction contributed to the changes of color. Principal component analysis indicated that FD caused less deterioration in quality compared to HD. CONCLUSION: In the present study, FD is recommended for preserving shrimp color and lipid nutrition in terms of lipid oxidation control. © 2020 Society of Chemical Industry.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".