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Record W2611673881 · doi:10.1111/1750-3841.13726

Contribution of High‐Pressure‐Induced Protein Modifications to the Microenvironment and Functional Properties of Rabbit Meat Sausages

2017· article· en· W2611673881 on OpenAlexaff
Siwen Xue, Xiaobo Yu, Huijuan Yang, Xinglian Xu, Hanjun Ma, Guanghong Zhou

Bibliographic record

VenueJournal of Food Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMinistry of Education and Child Care
FundersNational Natural Science Foundation of China
KeywordsFood scienceChemistryRheologyTexture (cosmology)High pressureRaman spectroscopyCooked meatMaterials science

Abstract

fetched live from OpenAlex

Rabbit meat batters were subjected to high pressure (HP, 100 to 300 MPa for 3, 9, or 15 min) to elucidate their effects on proteins structures, the microenvironment, and the resulting functionalities of the subsequently heated products. To determine these effects, we investigated structural and microenvironmental changes using Raman spectroscopy and also expressible moisture content, textural characteristics, and dynamic rheological properties of batters during heating (20 to 80 °C). Untreated samples served as controls. Analysis of specific Raman spectral regions demonstrated that applications of HP to rabbit meat batters tended to induce the transformation of the all-gauche S-S conformation to gauche-gauche-trans in the batter system. HP treatment higher than 100 MPa for 9 min promoted secondary structural rearrangements, and molecular polarity enhancement in the proteins prior to cooking. Also, increases of O-H stretching intensities of rabbit meat sausages were obtained by HP treatment, denoting the strengthening of water-holding capacity. These HP-induced alterations resulted in improved texture and, perhaps, improved juiciness of rabbit meat sausages (P < 0.05), however they had relatively poorer rheological properties than the controls. Nevertheless, HP treatment, especially 200 MPa for 9 or 15 min, was an effective technique for improving the functionalities of gel-type products through modification of meat proteins.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.361

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 studies0.0000.000
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 head0.083
GPT teacher head0.250
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 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

Citations10
Published2017
Admission routes1
Has abstractyes

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