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The preservable effects of ultrasound-assisted alginate oligosaccharide soaking on cooked crayfish subjected to Freeze-Thaw cycles

2022· article· en· W4311142932 on OpenAlexaff
Jiping Han, Yingjie Sun, Tao Zhang, Cheng Wang, Lingming Xiong, Yanhong Ma, Yongzhi Zhu, Ruichang Gao, Lin Wang, Ning Jiang

Bibliographic record

VenueUltrasonics Sonochemistry · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMinistry of Agriculture
FundersJiangsu Agricultural Science and Technology Innovation Fund
KeywordsChemistryZeta potentialMyofibrilOligosaccharideDenaturation (fissile materials)Particle sizeChromatographyFood scienceMaterials scienceNuclear chemistryBiochemistryNanotechnology

Abstract

fetched live from OpenAlex

To improve the quality of cooked and frozen crayfish after repeated freeze–thaw cycles, the effects of alginate oligosaccharide (1 %, w/v) with ultrasound-assisted (40 W, 3 min) soaking (AUS) on the physicochemical properties were investigated. The AUS samples improved water-holding capacity with 19.47 % higher than the untreated samples. Low-field nuclear magnetic resonance confirmed that mobile water (T22) in the samples after 5 times of freeze–thaw cycles was reduced by 13.02 % and 29.34 % with AUS and without treatment, correspondingly; and with AUS and without treatment, average size of the ice crystals was around 90.26 μm2 and 113.73 μm2, and average diameter of the ice crystals was 5.83 μm and 8.14 μm, respectively; furthermore, it enhanced the solubility and zeta potential, lowered the surface hydrophobicity, reduced the particle size, and maintained the secondary and tertiary structures of myofibrillar protein (MP) after repeated freeze-thawing. Gel electrophoresis revealed that the AUS treatment mitigated the denaturation of MPs. Scanning electron microscopy revealed that the AUS treatment preserved the structure of the tissue. These findings demonstrated that the AUS treatment could enhance the water retention and physicochemical properties of protein within aquatic meat products during temperature fluctuations..

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)0.001
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 score0.083
Threshold uncertainty score0.805

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.016
GPT teacher head0.233
Teacher spread0.217 · 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

Citations27
Published2022
Admission routes1
Has abstractyes

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