Mathematical modeling of enzymatic hydrolysis of soybean meal protein concentrate

• Published in: Chemical engineering communications Vol. 209; no. 3; pp. 338 - 350
• Main Authors: De Pretto, Cristine, de Miranda, Liceres Correa, de Siqueira, Paula Fernandes, Ribeiro, Marcelo Perencin de Arruda, Tardioli, Paulo Waldir, Giordano, Roberto de Campos, Giordano, Raquel de Lima Camargo, Costa, Caliane Bastos Borba
• Format: Journal Article
• Language: English
• Published: Philadelphia Taylor & Francis 04.03.2022; Taylor & Francis Ltd
• Subjects: Artificial neural networks; enzymatic hydrolysis; Hydrolysis; kinetics; mathematical modeling; neural network; Peptides; Proteins; Soy protein concentrate; Soybeans
• ISSN: 0098-6445; 1563-5201
• DOI: 10.1080/00986445.2020.1867849

This study aimed to model the enzymatic hydrolysis of proteins present in soybean protein concentrate meal using two steps. In the first step, the concentration of hydrolyzed peptide bonds was described as a function of time, using two kinetic models. In the second step, the way the enzyme breaks the protein down into smaller parts was investigated and modeled using an artificial neural network. Enzymatic reaction assays used for modeling were performed at pH 8, 9, and 10. It was observed that although the pH influenced the behavior of the reaction rate and the time profile of the degree of hydrolysis (DH), the peptide profile was only a function of DH, and not explicitly a function of pH. These two steps provide a combined model that enables a more detailed understanding of the reaction, showing how it advances, and how product profile varies as the reaction progresses.