Optimal Modified Atmosphere for Packaging and its Effects on Quality and Shelf-life of Pacific White Shrimp (<i>Litopenaeus vannamei</i>) under Controlled Freezing-point Storage at −0.8°C
Bibliographic record
Abstract
The optimal initial gas composition (CO 2 , O 2 and N 2 ) and its effects on quality and shelf-life of Pacific white shrimp (Litopenaeus vannamei) under controlled freezing-point storage at _ 0.8℃ was determined through microbial flora, pH, total volatile basic nitrogen (TVB-N), exudates and sensory analyses.Pacific white shrimp under gas to product ratio of 3:1 and gas composition spanning the whole area from 0 to 100% based on a simplex centroid mixture design were analyzed after 2, 4 and 6 days of storage.Mesophilic and psychrotrophic bacteria counts, pH and TVB-N contents decreased and formation of exudates increased with increasing of CO 2 levels, but odor and appearance scores decreased and mesophilic and psychrotrophic bacteria counts, pH and TVB-N contents increased in the shrimp with decreasing CO 2 and increasing N 2 concentration.Besides, low O 2 levels could favor the odor of raw shrimp.Finally, The optimum gas composition for modified atmosphere packaged Pacific white shrimp under controlled freezing-point storage at _ 0.8℃ was determined to be 75%CO 2 , 10%O 2 and 15%N 2 , and it could give the most suitable formation of exudates and lowest TVB-N and inhibit the growth of microbial flora; and at the same time maintain high odor and appearance scores in packaged Pacific white shrimp, and the shelf-life was extended to 11 _ 12 days, which would be obviously beneficial for the exploitation of quality control, shelf-life extension and development of active packaging on shrimps.
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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) | 0.000 | 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) | 0.000 | 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".