Abstract
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.
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