An integrated instrumental and sensory techniques for assessing liking, softness and emotional related of gluten-free bread based on blended rice and bean flour.

Acceptability Face emojis Food texture Food-related emotions Gluten-free Just-About-Right Mixolab

Journal

Food research international (Ottawa, Ont.)
ISSN: 1873-7145
Titre abrégé: Food Res Int
Pays: Canada
ID NLM: 9210143

Informations de publication

Date de publication:
04 2022
Historique:
received: 29 07 2021
revised: 05 01 2022
accepted: 24 01 2022
entrez: 26 3 2022
pubmed: 27 3 2022
medline: 8 4 2022
Statut: ppublish

Résumé

Despite recent scientific advances and the growth of the gluten-free market, important issues such as the improvement of the sensory and nutritional quality of gluten-free bread (GFB) still need to be addressed. Therefore, the aim of the present study was to integrate instrumental and sensory techniques for assessing liking, softness, and emotions related to GFB based on rice flour (RF) and bean flour (BF). Results shows that common BF increases the ash, protein, and dietary fiber content of bread. The RF and BF blend improves dough thermomechanical properties, bread volume, instrumental texture properties and acceptability, as well as being the formulation indicated by consumers as presenting ideal softness, all of which subsequently correlated with positive food-related emotions, based on a facial emojis list. Thus, a RF and BF blend is a valuable ingredient producing nutrient-dense and acceptable GFB, which is important for consumers who choose or must adhere to a gluten-free diet. This research highlights promising predictors able to correlate dough parameters, as well as physical properties of bread with the sensory quality of GFB; this could be helpful to food scientists and producers to conduct extensive sensory and consumer research regarding both commercial and experimental GFB to establish whether those products meet consumer expectations, showing the relevance of continuing studies.

Identifiants

pubmed: 35337589
pii: S0963-9969(22)00056-4
doi: 10.1016/j.foodres.2022.110999
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

110999

Informations de copyright

Copyright © 2022 Elsevier Ltd. All rights reserved.

Auteurs

Etiene V Aguiar (EV)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil.

Fernanda G Santos (FG)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil.

Letícia Faggian (L)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil.

Marielle Batista da Silveira Araujo (MB)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil.

Vitória Alves Araújo (VA)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil.

Ana Carolina Conti (AC)

São Paulo State University (UNESP), Institute of Biosciences, Humanities and Exact Sciences (IBILCE), Campus São José do Rio Preto, Department of Food Engineering and Technology. Rua Cristóvão Colombo, 2265, CEP 15054-000 São José do Rio Preto, SP, Brazil.

Vanessa D Capriles (VD)

Federal University of São Paulo (UNIFESP), Institute of Health and Society (Campus Baixada Santista), Department of Biosciences. Rua Silva Jardim, 136, CEP 11015-020 Santos, SP, Brazil. Electronic address: vanessa.capriles@unifesp.br.

Articles similaires

1.00
Oryza Agricultural Irrigation Potassium Sodium Soil
Humans Female Prefrontal Cortex Male Spectroscopy, Near-Infrared

Fine mapping of a major QTL, qECQ8, for rice taste quality.

Shan Zhu, Guoping Tang, Zhou Yang et al.
1.00
Oryza Quantitative Trait Loci Taste Chromosome Mapping Phenotype

Classifications MeSH