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Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis

Bakery products made from naturally fermented sourdough show a diversified flavor and nutritional profile. Djulis (Chenopodium formosanum), known as red quinoa or Taiwan djulis, originally cultivated by Taiwanese indigenous people in mountain areas in eastern and southern Taiwan, has a high nutritio...

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Autores principales: Chung, Pei-Ling, Liaw, Ean-Tun, Gavahian, Mohsen, Chen, Ho-Hsien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555873/
https://www.ncbi.nlm.nih.gov/pubmed/32825461
http://dx.doi.org/10.3390/foods9091149
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author Chung, Pei-Ling
Liaw, Ean-Tun
Gavahian, Mohsen
Chen, Ho-Hsien
author_facet Chung, Pei-Ling
Liaw, Ean-Tun
Gavahian, Mohsen
Chen, Ho-Hsien
author_sort Chung, Pei-Ling
collection PubMed
description Bakery products made from naturally fermented sourdough show a diversified flavor and nutritional profile. Djulis (Chenopodium formosanum), known as red quinoa or Taiwan djulis, originally cultivated by Taiwanese indigenous people in mountain areas in eastern and southern Taiwan, has a high nutritional value and characteristic properties. In the present study, a new bakery product (djulis sourdough bread) was developed and a combination of the Taguchi method coupled with grey theory was utilized to optimize the baking parameters (product formulation). Five main factors, i.e., djulis sourdough (A), hulled djulis (B), oil type (C), a mixture of bread flour (wet gluten content of 29.0%) and a high-gluten flour (wet gluten content of 35.5%) (D), and honey (E), (each at four levels) were chosen for the Taguchi experiment design (L(16)(4)(5)). Dependent parameters were the data from texture profile analysis (brittleness, springiness, cohesiveness, gumminess, and chewiness), color analysis (L*, a*, and b*), and sensory evaluation (appearance, aroma, bitterness, sourness, chewiness, and overall acceptance) of the final product. Taguchi grey relational analysis successfully determined the optimal conditions based on combined parameters (5 factors), which highlighted the advantages of this innovative optimization technique. The result shows that the optimal formula for producing a djulis sourdough bread with the best texture, color, and sensory qualities was A3B1C1D2E2, i.e., 20% djulis sourdough, 0% addition of hulled djulis, 8% unsalted butter, 80% wheat flour + 20% high-gluten flour, and 10% honey, respectively. Such a novel application could be a reference for improving the quality of bakery products in the industry. Moreover, it seems that the new bakery product developed in this study has good potential to be commercially produced after further nutritional and economic analysis.
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spelling pubmed-75558732020-10-19 Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis Chung, Pei-Ling Liaw, Ean-Tun Gavahian, Mohsen Chen, Ho-Hsien Foods Article Bakery products made from naturally fermented sourdough show a diversified flavor and nutritional profile. Djulis (Chenopodium formosanum), known as red quinoa or Taiwan djulis, originally cultivated by Taiwanese indigenous people in mountain areas in eastern and southern Taiwan, has a high nutritional value and characteristic properties. In the present study, a new bakery product (djulis sourdough bread) was developed and a combination of the Taguchi method coupled with grey theory was utilized to optimize the baking parameters (product formulation). Five main factors, i.e., djulis sourdough (A), hulled djulis (B), oil type (C), a mixture of bread flour (wet gluten content of 29.0%) and a high-gluten flour (wet gluten content of 35.5%) (D), and honey (E), (each at four levels) were chosen for the Taguchi experiment design (L(16)(4)(5)). Dependent parameters were the data from texture profile analysis (brittleness, springiness, cohesiveness, gumminess, and chewiness), color analysis (L*, a*, and b*), and sensory evaluation (appearance, aroma, bitterness, sourness, chewiness, and overall acceptance) of the final product. Taguchi grey relational analysis successfully determined the optimal conditions based on combined parameters (5 factors), which highlighted the advantages of this innovative optimization technique. The result shows that the optimal formula for producing a djulis sourdough bread with the best texture, color, and sensory qualities was A3B1C1D2E2, i.e., 20% djulis sourdough, 0% addition of hulled djulis, 8% unsalted butter, 80% wheat flour + 20% high-gluten flour, and 10% honey, respectively. Such a novel application could be a reference for improving the quality of bakery products in the industry. Moreover, it seems that the new bakery product developed in this study has good potential to be commercially produced after further nutritional and economic analysis. MDPI 2020-08-20 /pmc/articles/PMC7555873/ /pubmed/32825461 http://dx.doi.org/10.3390/foods9091149 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Chung, Pei-Ling
Liaw, Ean-Tun
Gavahian, Mohsen
Chen, Ho-Hsien
Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title_full Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title_fullStr Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title_full_unstemmed Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title_short Development and Optimization of Djulis Sourdough Bread Using Taguchi Grey Relational Analysis
title_sort development and optimization of djulis sourdough bread using taguchi grey relational analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7555873/
https://www.ncbi.nlm.nih.gov/pubmed/32825461
http://dx.doi.org/10.3390/foods9091149
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