Process optimization and quality analysis of strawberry lees steamed buns

This study employed an artificial neural network and a genetic algorithm to optimize the production of steamed buns made with strawberry lees. The optimal parameters identified were: 17% strawberry lees addition, dough fermentation at 36°C for 120 min, and a 50-min proofing period. The experimental...

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Main Authors: Qianqian Tong, Linlin Yin, Hong Rong, Jingjing Yang, Mengmeng Gu, Chaojia Shi
Format: Article
Language:English
Published: Taylor & Francis Group 2025-12-01
Series:CyTA - Journal of Food
Subjects:
Online Access:https://www.tandfonline.com/doi/10.1080/19476337.2025.2541888
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author Qianqian Tong
Linlin Yin
Hong Rong
Jingjing Yang
Mengmeng Gu
Chaojia Shi
author_facet Qianqian Tong
Linlin Yin
Hong Rong
Jingjing Yang
Mengmeng Gu
Chaojia Shi
author_sort Qianqian Tong
collection DOAJ
description This study employed an artificial neural network and a genetic algorithm to optimize the production of steamed buns made with strawberry lees. The optimal parameters identified were: 17% strawberry lees addition, dough fermentation at 36°C for 120 min, and a 50-min proofing period. The experimental sensory score (84.03 ± 1.76) was close to the predicted score (83.32). Analyses indicated that strawberry lees enhanced the properties and palatability of the buns compared to traditional yeast buns, although they contained more fiber and were of lower quality than commercial varieties. The free amino acid profiles varied, with glutamic acid exhibiting the highest taste activity value. A total of 79 volatile compounds were identified, primarily esters and alcohols, with heptanoic acid and octanoic acid ethyl ester contributing to a unique aroma. These buns address the issue of lees disposal and establish a foundation for the large-scale production of nutritious steamed buns.
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institution Kabale University
issn 1947-6337
1947-6345
language English
publishDate 2025-12-01
publisher Taylor & Francis Group
record_format Article
series CyTA - Journal of Food
spelling doaj-art-cdcb35fc7f1b416a8a0eaf2eaac9d1cf2025-08-20T04:02:41ZengTaylor & Francis GroupCyTA - Journal of Food1947-63371947-63452025-12-0123110.1080/19476337.2025.2541888Process optimization and quality analysis of strawberry lees steamed bunsQianqian Tong0Linlin Yin1Hong Rong2Jingjing Yang3Mengmeng Gu4Chaojia Shi5Bioengineering School, Huainan Normal University, Huainan, Anhui, ChinaBioengineering School, Huainan Normal University, Huainan, Anhui, ChinaBioengineering School, Huainan Normal University, Huainan, Anhui, ChinaBioengineering School, Huainan Normal University, Huainan, Anhui, ChinaBioengineering School, Huainan Normal University, Huainan, Anhui, ChinaBioengineering School, Huainan Normal University, Huainan, Anhui, ChinaThis study employed an artificial neural network and a genetic algorithm to optimize the production of steamed buns made with strawberry lees. The optimal parameters identified were: 17% strawberry lees addition, dough fermentation at 36°C for 120 min, and a 50-min proofing period. The experimental sensory score (84.03 ± 1.76) was close to the predicted score (83.32). Analyses indicated that strawberry lees enhanced the properties and palatability of the buns compared to traditional yeast buns, although they contained more fiber and were of lower quality than commercial varieties. The free amino acid profiles varied, with glutamic acid exhibiting the highest taste activity value. A total of 79 volatile compounds were identified, primarily esters and alcohols, with heptanoic acid and octanoic acid ethyl ester contributing to a unique aroma. These buns address the issue of lees disposal and establish a foundation for the large-scale production of nutritious steamed buns.https://www.tandfonline.com/doi/10.1080/19476337.2025.2541888Steamed bunsartificial neural networkgenetic algorithmquality characteristicsflavor compounds
spellingShingle Qianqian Tong
Linlin Yin
Hong Rong
Jingjing Yang
Mengmeng Gu
Chaojia Shi
Process optimization and quality analysis of strawberry lees steamed buns
CyTA - Journal of Food
Steamed buns
artificial neural network
genetic algorithm
quality characteristics
flavor compounds
title Process optimization and quality analysis of strawberry lees steamed buns
title_full Process optimization and quality analysis of strawberry lees steamed buns
title_fullStr Process optimization and quality analysis of strawberry lees steamed buns
title_full_unstemmed Process optimization and quality analysis of strawberry lees steamed buns
title_short Process optimization and quality analysis of strawberry lees steamed buns
title_sort process optimization and quality analysis of strawberry lees steamed buns
topic Steamed buns
artificial neural network
genetic algorithm
quality characteristics
flavor compounds
url https://www.tandfonline.com/doi/10.1080/19476337.2025.2541888
work_keys_str_mv AT qianqiantong processoptimizationandqualityanalysisofstrawberryleessteamedbuns
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AT hongrong processoptimizationandqualityanalysisofstrawberryleessteamedbuns
AT jingjingyang processoptimizationandqualityanalysisofstrawberryleessteamedbuns
AT mengmenggu processoptimizationandqualityanalysisofstrawberryleessteamedbuns
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