Computer-Aided Optimization and Mechanistic Elucidation of the Peanut-Derived Peptides Preparation Process
Year: 2025
Type: conference-paper
Abstract: Peanuts (Arachis hypogaea L.) are one of the important oil crops in China, rich in oil and protein. However, compared to soybean protein, peanut protein has not been widely utilized in the food industry. To improve the comprehensive utilization of peanut protein resources and streamline production processes, this study employed computer-aided response surface methodology to optimize enzymatic hydrolysis parameters using peanut meal as the raw material. Alkaline protease and papain were utilized for stepwise hydrolysis to investigate the preparation of peanut peptides. Machine learning models (random forest regression) were integrated to analyze single-factor experimental data, identifying critical process variables. The optimal conditions for alkaline protease hydrolysis were determined as pH 9.0, 53°C, enzyme dosage of 2083 U/g, and 4-hour hydrolysis at 5% substrate concentration, while papain hydrolysis achieved maximum efficiency at pH 7.0, 55°C, 400 U/g enzyme dosage, and 4-hour reaction. Under these computationally optimized conditions, the peptide content and yield reached 79.88% and 88.83%, respectively, with a 32% reduction in experimental iterations compared to conventional approaches. This methodology provides an efficient strategy for valorizing peanut protein resources in functional food applications.
Authors: Ruilei Jia, Diyi Huang, Xiaoru Wang, Jie Zhou, Zengkun Sun, Tao Xia
Institutions: Qilu University of Technology, Shandong Academy of Sciences
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
SDG: Zero hunger
Open Access status: gold
Awards: G5161984613, G905605905
OpenAlex ID: W4413506172