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Record W4384203779 · doi:10.1002/cche.10699

The entrainment and evolution of gas bubbles in bread dough—A review

2023· article· en· W4384203779 on OpenAlexafffund
Xinyang Sun, Martin G. Scanlon, Michael T. Nickerson, Filiz Köksel

Bibliographic record

VenueCereal Chemistry · 2023
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsUniversity of SaskatchewanUniversity of Manitoba
FundersInstitute of Nutrition, Metabolism and DiabetesNatural Sciences and Engineering Research Council of CanadaJiangsu Agricultural Science and Technology Innovation FundNatural Science Foundation of Jiangsu ProvinceGovernment of Jiangsu ProvinceCanadian Institutes of Health ResearchChina Scholarship CouncilWestern Grains Research Foundation
KeywordsLeavening agentBubbleCoalescence (physics)ChemistryFood scienceEntrainment (biomusicology)Bread makingMechanicsFermentationPhysics

Abstract

fetched live from OpenAlex

Abstract Background and Objective For control of bread quality to achieve high loaf volume and uniform crumb structure, gas bubble dynamics in dough needs to be better understood throughout different breadmaking processes. The objective of this review was to establish a solid theoretical basis on how flour type, water and salt content, and mixing conditions affected the incorporation, evolution, and stabilization of gas bubbles in a dough. Findings Bubble dynamics including entrainment, disentrainment, break‐up, disproportionation, growth, and coalescence were outlined and their effects on the gas phase of the dough were assessed. The application, advantages, and disadvantages of microscopy, magnetic resonance imaging (MRI) and X‐ray microtomography techniques for qualitatively or quantitatively characterizing the void fraction and bubble size distribution (BSD) in the dough at various stages of the breadmaking process have been discussed. Conclusions Since the BSD evolution in bread dough is associated with the quality of the resultant products, to devise strategies for improving the product quality, dough formulation, and mixing conditions need to be considered. Significance and Novelty Due to the obvious challenges of monitoring the fast evolution of BSD in yeasted dough, future research needs to focus on the effects of yeast activity on dough's BSD.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.235
Threshold uncertainty score0.157

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 head0.013
GPT teacher head0.248
Teacher spread0.234 · 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

Citations24
Published2023
Admission routes2
Has abstractyes

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