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: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
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| Series: | CyTA - Journal of Food |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19476337.2025.2541888 |
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| Summary: | 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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| ISSN: | 1947-6337 1947-6345 |