Optimization of α-Glucosidase Inhibitors Recovery from Rainbow Trout Hydrolysate Using GA-BP Neural Network
- 1 College of Agricultural Engineering and Food Science, Shandong University of Technology, Zibo, 255100, Shandong Province, China
- 2 Test Center, Zichuan District Inspection and Test Center, Zibo, 255100, Shandong Province, China
Abstract
To enhance the value of by-products from rainbow trout processing, the inhibition rate of α-glucosidase (AGIR) is used as indicators. Optimization of rainbow trout hydrolysate extraction by comparing Response Surface Methodology (RSM) and BP Neural Network (BPNN) models. The RSM results: the AGIR is 55.02%. BPNN models predicted the optimal extraction conditions: 51℃ for temperature,1:2.3 for solid-liquid ratio, 4.15 h for time and 0.2334% for enzyme dosage. The reactions obtained under optimized conditions are as follows: the α-glucosidase inhibitory rate increased to 58.14%. This proves that the BPNN model can simultaneously improve the hydrolysis degree and α-glucosidase inhibition rate of the rainbow trout hydrolysate.
DOI: https://doi.org/10.3844/ajbbsp.2025.401.411
Copyright: © 2025 Yingke Chu, Yanling Dong, Qingfeng Rong, Kun Yang and Lanlan Zhu. This is an open access article distributed under the terms of the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Rainbow Trout
- Enzymatic Hydrolysis Reaction
- BP Neural Network