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Record W2106075660 · doi:10.3844/ajassp.2010.859.877

Fish Spoilage Mechanisms and Preservation Techniques: Review

2010· article· en· W2106075660 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAmerican Journal of Applied Sciences · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaNational Science Council
KeywordsFood spoilageShelf lifeFood scienceFood preservationPopulationFish productsFood industryFlavorBiologyFish <Actinopterygii>ChemistryFishery

Abstract

fetched live from OpenAlex

Problem statement: Spoilage of food products is due to chemical, enzymatic or microbial activities One-fourth of the world's food supply and 30% of landed fish are lost through microbial activity alone. With the ever growing world population and the need to store and transport the food from one place to another where it is needed, food preservation becomes necessary in order to increase its shelf life and maintain its nutritional value, texture and flavor. The freshness and quality of fish have always gained the attention by Food Regulatory Agencies and Food Processing Industry. Proper handling, pretreatment and preservation techniques can improve the quality fish and fish products and increase their shelf life. Methodology: Historically salting, drying, smoking, fermentation and canning were the methods to prevent fish spoilage and extend its shelf life. In response to consumer demand for texture, appearance and taste, new methods were developed including: Cooling, freezing and chemical preservation. A comprehensive review of the literature on the subject of fish spoilage and modern preservation techniques was carried out. Conclusion: Fish spoilage results from three basic mechanisms: Enzymatic autolysis, oxidation, microbial growth. Low temperature storage and chemical techniques for controlling water activity, enzymatic, oxidative and microbial spoilage are the most common in the industry today. A process involving the addition of an EDTA (1 mM)-TBHQ (0.02%) combination and ascorbic acid and storage at refrigerated temperatures (5C) in darkness can be the most positive for controlling the spoilage of fish and fish product. The suggested process would address antimicrobial activity as well as destructive oxidation of the desired lipids and fats. However, more efforts are required to understand the role of proximate composition of fish, post harvest history, environmental conditions, initial microbial load, type and nature of bacteria and their interaction in order to optimize the shelf-life of fish.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.305
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.026
GPT teacher head0.265
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it