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Record W3013315868 · doi:10.22175/rmc2016.019

Effects of the Addition of Frozen Mechanically Separated Pork on Functional Properties and Lipid Oxidation of Emulsion Type Pork Sausage

2017· article· en· W3013315868 on OpenAlexaff
Juhui Choe, P.J. Shand

Bibliographic record

VenueMeat and Muscle Biology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsEmulsionFood scienceLipid oxidationChemistryBiochemistry

Abstract

fetched live from OpenAlex

ObjectivesMechanically separated meats (MSM) allow the recovery of valuable protein during carcass fabrication and are used throughout the world due to their low cost. MSM are generally shipped under frozen conditions and are used in processing of various meat products. It is not unusual to have MS meats available long after production, but how does the quality change with length of frozen storage and how does that affect functionality? Therefore, the objective of the present study was to investigate functional properties of emulsion type meat product added with various levels of frozen MS pork (MSP; 5- and 8-months post production).Materials and MethodsThe MSP (22.5% fat, 14.3% protein) was obtained through commercial channels, subdivided and randomly assigned to two frozen storage (–20°C) periods (5- and 8-mo). After each frozen storage interval, the MSP meats were thawed at 1°C for 48 h, and coarsely ground. The control sausage formulation consisted of fresh boneless pork shoulder (regular pork), 26 to 28% water, 3% salt, 0.3% sodium tripolyphosphate with ∼10.5% fat and 12.5% protein content. MSP was substituted for the fresh pork (1:1). Four treatments (3.7 kg/treatment) of emulsion type sausage were produced with four addition levels of frozen MSP [0 (control), 5 (MSP-5), 10 (MSP-10), and 15% (MSP-15)]. The meats were chopped and emulsified with ingredients using a silent cutter and emulsion mill, respectively. Batters were stuffed in casings and then cooked in a water bath to a final internal temperature of 71°C. Meat batters were assessed for protein solubility, water holding capacity, viscosity and lipid oxidation (TBARS). The functional properties of cooked sausage such as texture profile analysis, shear stress and strain at failure and TBARS were also evaluated. Lipid oxidation of regular pork and MSP were also determined. The data were analyzed using the General Linear Model (GLM) procedure of the SAS statistical package. Differences in means between treatments were determined using Duncan’s multiple range tests (P < 0.05).ResultsThe MSP had higher (P < 0.05) lipid oxidation compared to regular pork. In general, with an increase in addition levels of frozen MSP, the cook loss, expressible moisture and lipid oxidation increased and viscosity and hardness were decreased (P < 0.05). However, 5 and 10% of frozen MSP addition did not influence WHC (cook loss, expressible moisture and drip loss) and protein solubility (total soluble and sarcoplasmic protein) compared to the control sausage. Extended freezing storage periods of MSP generally lead to deterioration in WHC, lipid oxidation and instrumental hardness, while viscosity and shear stress and strain at failure were not affected by freezing storage periods of MSP.ConclusionThe results suggested that substitution of 5% frozen MSP could contribute similar functional properties compared to the control formulation. In general, sausages with up to 10% addition level of frozen MSP had similar WHC and torsional shear as the control. Functionality of frozen MSP continues to decline during frozen storage, with noticeable differences in sausage properties due to a 3 mo difference in frozen storage time (8 mo vs 5).

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)0.000
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 score0.575
Threshold uncertainty score0.107

Codex and Gemma teacher scores by category

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 head0.051
GPT teacher head0.237
Teacher spread0.186 · 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".

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Citations0
Published2017
Admission routes1
Has abstractyes

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