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.
