Abstract
This study used soybean meal as the substrate and systematically optimized its enzymatic hydrolysis through single-factor experiments and response surface methodology. A predictive model based on a Box-Behnken design was developed to improve protein hydrolysis efficiency and increase the yield of functional products. The optimal conditions were 1.45% enzyme addition, a reaction time of 62 h, a temperature of 36.5 °C, and a moisture content of 35%. Under these conditions, the small-peptide content increased 16.33-fold. Structural analyses showed that enzymatic treatment markedly disrupted the compact surface of soybean meal, converting it into a loose, porous matrix. In addition, enzymolysis altered the protein secondary structure from ordered α-helices and folded conformations to more disordered, flexible forms, thereby improving the molecular-weight distribution. Composition analyses showed an 114.2% increase in total free amino acids, including essential amino acids. Moreover, DPPH radical-scavenging activity increased from 18.37% to 57.99%. Overall, this study optimized the enzymatic hydrolysis conditions for soybean meal and provides valuable insights for the development of high-value protein-peptide products.