A D-optimal RSM-guided computational strategy for lipase immobilization on rice straw toward enhanced biocatalytic efficiency

The global enzyme market is projected to reach approximately USD 16.8 billion by 2032. The demand for lipase in free and immobilized forms increases due to its wide range of applications in different industrial sectors. Therefore, in this study, we immobilize porcine pancreatic lipase (PPL) on rice straw (RS), a lignocellulosic residue derived from agricultural waste. The PPL-immobilized RS was characterized using FTIR, SEM, and EDX. The FTIR spectra show the amide group, confirming successful immobilization. Surface characterization using SEM illustrates morphological changes after PPL immobilization. EDX reveals an increase in carbon percentage on PPL-immobilized RS, confirming the presence of proteinaceous residues, indicating successful immobilization. After immobilization, the catalytic efficiency of the immobilized PPL optimized using a D-optimal response surface methodology (RSM) using variables (pH, temperature, and ionic strength). The RSM-based model predicted optimal conditions (70 mM ionic strength, pH 7.8, 36 °C) with a projected activity of 2.61 U/mg. Experimental validation yielded 2.6 ± 0.02 U/mg, indicating excellent model accuracy and robustness. The statistical evaluation revealed strong model performance, with <i>R</i>² = 0.989, <i>Q</i>² = 0.958, model validity = 0.746, and reproducibility = 0.990, confirming its high predictive accuracy, reliability, and overall robustness.