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Record W2174521965 · doi:10.1094/cchem-01-15-0006-r

Use of Ultrasound to Investigate Glucose Oxidase and Storage Effects on the Rheological Properties of Cooked Asian Noodles

2015· article· en· W2174521965 on OpenAlexafffund
Daiva Daugelaite, Anatoliy Strybulevych, Martin G. Scanlon, J. H. Page, David W. Hatcher

Bibliographic record

VenueCereal Chemistry · 2015
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDynamic mechanical analysisChemistryRheologyFood scienceDynamic modulusGlucose oxidaseStress relaxationUltrasonic sensorChewinessTexture (cosmology)Composite materialMaterials sciencePolymerBiochemistryCreepOrganic chemistry

Abstract

fetched live from OpenAlex

This is the first use of a longitudinal ultrasonic technique to address the rheological properties of cooked noodles. Ultrasound (11 MHz) was utilized to investigate the influence of glucose oxidase (GOx) at the 1.5 U/g of flour level on the rheological properties of cooked alkaline noodles before and after 72 h of storage at 4°C. Cooked noodle dough samples were studied by simultaneously conducting stress relaxation and transmission ultrasonic measurements, yielding Peleg's K 1 and K 2 parameters (initial rate of relaxation and extent of relaxation, respectively) and ultrasonic information on noodle texture properties. Ultrasonic phase velocities and attenuation coefficients did not show significant differences between control and GOx noodles either before or after 72 h of refrigeration. However, refrigerated storage of control and GOx noodles did result in a significant increase in wave velocity and storage modulus ( M′ ) as well as a decrease in attenuation and tan δ L (ratio of longitudinal loss modulus to longitudinal storage modulus), indicating increased firmness of noodle structure with storage time. Stress relaxation results on fresh unrefrigerated noodles showed an increase in Peleg's K 1 and K 2 parameters with GOx addition but did not resolve any significant changes in these parameters after 72 h of storage. This small amount of GOx did not improve cooked noodle texture, although noodle matrix changes during storage were clearly revealed by the noninvasive ultrasonic data.

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)0.001
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 score0.003
Threshold uncertainty score0.333

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.059
GPT teacher head0.235
Teacher spread0.176 · 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
Published2015
Admission routes2
Has abstractyes

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