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Record W2277421680 · doi:10.14288/1.0089304

Effectiveness of polyol blends as cryoprotectants in surimi and natural actomyosin from ling cod (ophiodon elongatus)

2009· article· en· W2277421680 on OpenAlexaff
Fathima Yasmina Sultanbawa

Bibliographic record

VenuecIRcle (University of British Columbia) · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolyolCryoprotectantChemistryFood sciencePolymer scienceFisheryOrganic chemistryBiologyPolyurethane

Abstract

fetched live from OpenAlex

Cryoprotectants with decreased sweetness are desirable for products like surimi because of consumer preference for less sweet foods. Physical, biochemical and Raman spectroscopic techniques were used to evaluate such cryoprotectants in ling cod surimi and natural actomyosin (NAM) model systems. Cryoprotectant blends with decreased sweetness were first investigated for their potential to stabilize ling cod surimi during frozen storage at -18°C for 4 months. A central composite rotatable design (CCRD) was used to formulate 25 blends containing lactitol, Litesse™, sucrose, and sorbitol, at final total concentrations of 4-12%. Although decreases in % salt extractable proteins, apparent viscosity and water binding capacity were observed, the gel strength, colour, pH and myosin heavy chain:actin ratio did not change significantly after frozen storage in surimi containing cryoprotectant blends. Differences for surimi with and without cryoprotectants were significant (P > 0.05). All 25 blends gave surimi and cooked gels comparable to the commercial blend (4% sucrose, 4%> sorbitol). For optimization of cryoprotectant blend composition, a CCRD was used to formulate 25 blends containing lactitol, Litesse™, sucrose and sorbitol at final total concentrations of 2-6%>. Highly significant regression models (P<0.001) were obtained for gel strength, firmness, fold test, total and specific ATPase activities. Sensory evaluation indicated that the commercial blend was perceived to be sweeter than the 5.5 and 6% optimal blends (P<0.05). Individual cryoprotectants at 8%, optimal blends at 4, 5.5, 6 and 8%) and the commercial blend were all effective in maintaining gel strength of NAM and surimi gels. Hydrogen, ionic and hydrophobic interactions were the main forces contributing to aggregation of NAM during frozen storage and disulfide bonds contributed as a secondary process as indicated by SDS-PAGE profiles, solubility, surface hydrophobicity, sulfhydryl (SH) group and disulfide bond content, and Raman spectroscopy. Surface hydrophobicity, reactive and total SH decreased during frozen storage in the treatments without cryoprotectants. Raman spectroscopy revealed an increase in the proportion of a-helix in the treatments without cryoprotectants and with 4% individual cryoprotectants. Ling cod proteins were protected from freeze denaturation by individual cryoprotectants at 8%, optimal blends at 4, 5.5, 6 and 8% and the commercial blend.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.006
GPT teacher head0.172
Teacher spread0.167 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2009
Admission routes1
Has abstractyes

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