Chitosan as an Edible Invisible Film for Quality Preservation of Herring and Atlantic Cod
Bibliographic record
Abstract
The effect of chitosan with different molecular weights as coatings for shelf-life extension of fresh fillets of Atlantic cod (Gadus morhua) and herring (Clupea harengus) was evaluated over a 12-day storage at refrigerated temperature (4 +/- 1 degrees C). Three chitosan preparations from snow crab (Chinoecetes opilio) processing wastes, differing in viscosities and molecular weights, were prepared; their apparent viscosities (360, 57, and 14 cP) depended on the deacetylation time (4, 10, and 20 h, respectively) of the chitin precursor. Upon coating with chitosans, a significant (p < or = 0.05) reduction in relative moisture losses of 37, 29, 29, 40, and 32% was observed for cod samples coated with 360 cP chitosan after 4, 6, 8, 10, and 12 days of storage, respectively. Chitosan coating significantly (p < or = 0.05) reduced lipid oxidation as displayed in peroxide value, conjugated dienes, 2-thiobarbituric acid reactive substances and headspace volatiles, chemical spoilage as reflected in total volatile basic nitrogen, trimethylamine, and hypoxanthine, and growth of microorganisms as reflected in total plate count in both fish model systems compared to uncoated samples. The preservative efficacy and the viscosity of chitosan were inter-related; the efficacy of chitosans with viscosities of 57 and 360 cP was superior to that of chitosan with a 14 cP viscosity. Thus, chitosan as edible coating would enhance the quality of seafoods during storage.
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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) | 0.000 | 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".