Production of amylases by fungi under solid-state fermentation is considered the best methodology for commercial scaling that addresses the ever-escalating needs of the worldwide enzyme market. Here response surface methodology (RSM) was used for the optimization of process variables for α-amylase enzyme production from Trichoderma virens using watermelon rinds (WMR) under solid-state fermentation (SSF). The statistical model included four variables, each detected at two levels, followed by model development with partial purification and characterization of α-amylase. The partially purified α-amylase was characterized with regard to optimum pH, temperature, kinetic constant, and substrate specificity. The results indicated that both pH and moisture content had a significant effect (P < 0.05) on α-amylase production (880 U/g) under optimized process conditions at a 3-day incubation time, moisture content of 50%, 30 °C, and pH 6.98. Statistical optimization using RSM showed R2 values of 0.9934, demonstrating the validity of the model. Five α-amylases were separated by using DEAE-Sepharose and characterized with a wide range of optimized pH values (pH 4.5-9.0), temperature optima (40-60 °C), low Km values (2.27-3.3 mg/mL), and high substrate specificity toward large substrates. In conclusion, this study presents an efficient and green approach for utilization of agro-waste for production of the valuable α-amylase enzyme using RSM under SSF. RSM was particularly beneficial for the optimization and analysis of the effective process parameters.

Molecular Biology Department Genetic Engineering and Biotechnology Division National Research Centre El Behoth St Dokki Cairo Egypt

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