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Record W2169211258 · doi:10.1111/jtxs.12016

Impact of Structure Modification on Texture of a Soymilk and Cow's Milk Gel Assessed Using the <scp>N</scp>apping Procedure

2013· article· en· W2169211258 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Texture Studies · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSensory Analysis and Statistical Methods
Canadian institutionsVineland Research and Innovation CentreUniversity of Guelph
Fundersnot available
KeywordsFood scienceCaseinSoy proteinHomogenization (climate)Skimmed milkChemistryTexture (cosmology)Protein isolateWhey proteinMilk proteinSensory systemBiologyComputer science

Abstract

fetched live from OpenAlex

Abstract It was hypothesized that with careful control of the structure of a mixed protein matrix, it is possible to obtain different textures without changing ingredients or their concentrations. A model system containing soymilk, cow's milk and cream was used. To modify the texture of the final matrix, the mode of protein gelation and the order of homogenization of the cream (with soymilk or skim milk alone or with both mixed together) were investigated. Using a partial N apping and ultra‐flash profiling procedure, it was demonstrated that as long as milk was homogenized with cream, the mixed protein gels had higher thickness and mouthcoating compared with gels made from unhomogenized samples or samples made by homogenizing the cream with soymilk. It was found that aggregation of milk proteins before soy proteins resulted in more prominent fat‐related attributes such as slipperiness and fattiness compared with simultaneous aggregation of casein and soy proteins. Practical Applications Recently, there has been a growing interest in mixed protein gels; however, little information exists about their sensory properties. Such gels have the potential to be a novel category of healthy high‐protein products exhibiting consumer‐acceptable sensory properties. However, more work is needed to improve understanding of how to generate such products and to understand the processes that impact their sensory properties. The aim of the present study was to examine the sensory texture changes induced when the organization of components is modified within a mixed soymilk–dairy milk gel without changing ingredients or their concentrations. The present study also contributes to the understanding of texture perception as it demonstrates a clear link between texture perception and structure modification in a protein gel. Mixed protein systems present an attractive opportunity for the study of texture–structure relationships as they allow the development of a range of structures without modifying the system's composition.

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.956
Threshold uncertainty score0.201

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.084
GPT teacher head0.367
Teacher spread0.283 · 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