Effect of low‐temperature preservation on quality changes in Pacific white shrimp, <i>Litopenaeus vannamei</i>: a review
Bibliographic record
Abstract
Shrimp has been widely accepted as an excellent resource for white meat due to its high-protein and low-fat content, especially low cholesterol. However, shrimps are highly perishable during preservation and retailing procedures due to the activities of enzymatic proteolysis, lipid oxidation, and microbial degradation. With increasing knowledge of and demands for safety, nutrition, and freshness of shrimp products, energy efficient, quality, maintained, and sustainable preservation technologies are needed. Low-temperature preservation, a practical processing method for improving the shelf life of food products, is widely used in the aquatic industry. This review focuses on the effects of low-temperature preservation on the quality changes in Litopenaeus vannamei. It considers physicochemical properties, sensory evaluation, melanosis assessment, and microbiological analysis. The perspectives of non-protein-based techniques on quality analysis of shrimps during preservation are also discussed. © 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".