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Record W3013881542 · doi:10.22175/rmc2018.061

Evaluation of the Incorporation of β-Glucans in Whole Muscle Chicken Breast

2018· article· en· W3013881542 on OpenAlexaff
S. M. Vasquez Mejia, Alícia de Francisco, R. Sandrina, T. da Silva, B. M. Bohrer

Bibliographic record

VenueMeat and Muscle Biology · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsChicken breastDifferential scanning calorimetryFood scienceGlucanChemistryRefrigerationSodiumChromatographyBiochemistry

Abstract

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ObjectivesThe use of soluble fiber (β-glucans) incorporated into whole muscle meat products is still unexplored and needs clarification on a number of factors including 1) if incorporation can be achieved, 2) possible levels of incorporation, 3) stability and bioavailability under conditions of storage and cooking, and 4) influence on the quality characteristics of the meat. Therefore, this study evaluated the incorporation of soluble fiber (β-glucans) in whole muscle chicken meat and identified changes in physical-chemical, textural, and microbiological properties during 9 d of storage under refrigeration at 4°C.Materials and MethodsBarley β-glucan solutions were incorporated by injection into whole muscle chicken breast 48 h after slaughter. Three chicken breast samples were injected with a handheld injector with target pump uptake of 20% for each treatment. Treatments were injected at 4°C and included 1) a salt solution (2% NaCl and 0.2% sodium tripolyphosphate (STPP); Treatment A), 2) a β-glucan solution (1.5% of β-glucan; Treatment B), and 3) a combination of salt and β-glucan solution (2% NaCl, 0.2% STPP, and 1.5% of β-glucan; Treatment C). Three independent replications were produced for each treatment. The treatments were injected at 4°C into the chicken breast samples. The samples were stored under refrigeration and evaluated at d 1, 6, and 9 for pH, cooking loss, instrumental color, shear force, microbiology, and thermal behavior by differential scanning calorimetry (DSC). One-way ANOVA analysis and means separation using a Duncan test comparison adjustment were performed using Statistica version 7.0. Statistical significance was assumed at P < 0.05.ResultsAbsorption of treatments was 8.15 ± 1.38% (m/m) without a significant difference among treatments, indicating a low absorption capacity of the samples. The maximum amount of β-glucan concentration remaining in the chicken breast after injection was 0.59 ± 0.1%. Cooking loss was less (P < 0.05) in Treatment C on d 6 and 9 compared with Treatment A and Treatment B. Shear force values were between 18 and 25 Newton (N) during storage. Shear force values were less (P < 0.05) in Treatment C samples (d 1 and 6) and Treatment A samples (d 9) when compared with other treatments on given days. No differences (P > 0.05) among treatments were observed in microbiology analyses. Coliforms decreased and psychrotrophic bacteria increased in all treatment groups during the storage period. After cooking, the maximum amount of β-glucan concentration that remained in the chicken breast was less than 0.1%, indicating that soluble fiber concentration is greatly impacted by cooking of whole muscle products injected with both β-glucans alone and in combination with a salt solution.ConclusionThe application of β-glucans in whole muscle chicken breast did not present advantages in cooking loss with respect to samples injected with salt alone. Under the conditions evaluated, incorporation of β-glucans into whole muscle chicken did not present detrimental effects to product quality or safety. However, after cooking, the fiber concentration in the final product was reduced to levels where it would not be sufficient for health benefits or for the product to be declared as a source of dietary fiber. Therefore, challenges to increase the concentration of dietary fiber in whole muscle meat products continues.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.926
Threshold uncertainty score0.392

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 head0.058
GPT teacher head0.278
Teacher spread0.220 · 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 designObservational
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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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