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Biochemical Properties of Natural Actomyosin Extracted from Normal and Pale, Soft, and Exudative Pork Loin After Frozen Storage

2005· article· en· W2062723237 on OpenAlexafffund
Haihong Wang, Mary D. Pato, P.J. Shand

Bibliographic record

VenueJournal of Food Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Saskatchewan
FundersMinistry of Agriculture - Saskatchewan
KeywordsChemistryLoinFood scienceMyosinDenaturation (fissile materials)Disulfide bondWater holding capacityLongissimus muscleLongissimusMyofibrilBiochemistryAnatomyAnimal scienceBiology

Abstract

fetched live from OpenAlex

ABSTRACT: The studies of natural actomyosin (NAM) extracted from normal and pale, soft, and exudative (PSE) pork longissimus muscle stored at ‐20°C for up to 6 mo, revealed that the surface hydrophobicity (S 0 ‐ANS) of NAM from PSE pork was significantly ( P < 0.05) higher than that from normal pork indicating greater conformational changes in proteins from PSE meat that resulted in the exposure of hydrophobic aromatic amino acid residues on the surface. Also, the S 0 ‐ANS of NAM was a function of storage time. The equations were as follows: S 0 ‐ANS = 16.9 × storage mo + 123 for normal and S 0 ‐ANS = 17.5 × storage mo + 164 for PSE. NAM from frozen normal pork had lower α‐helical content than comparable fresh pork. With extended frozen storage, viscosity of NAM from PSE meat was lower than that from normal pork. The sulfhydryl and disulfide contents were unchanged. Electrophoresis revealed an extra 95 to 100 kDa band from PSE meat NAM, possibly from α‐actinin or myosin degradation. Water‐binding capacity (WBC) of normal and PSE meat decreased with increasing storage time; however, there were only minor changes in thaw loss. The decrease of WBC of pork meat partially can be explained by the increase of S 0 ‐ANS observed for the NAM. These results suggest that proteins from PSE pork are more susceptible to denaturation and degradation in fresh meat and following frozen storage.

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 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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score0.195

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.227
Teacher spread0.201 · 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 teacher head, 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

Citations44
Published2005
Admission routes2
Has abstractyes

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