Response Surface Methodology-Based Optimization of Natural Pigment Production from Penicillium purpurogenum

Fungal pigments are increasingly recognized as environmentally sustainable alternatives to synthetic dyes. However, their commercial utilization requires effective optimization. This study aimed to optimize pigment production by Penicillium purpurogenum using Response Surface Methodology (RSM) with a Central Composite Design (CCD). Initial screening using a one-factor-at-a-time (OFAT) approach identified pH, incubation temperature, and incubation time as critical factors affecting pigment yields. Dextrose and yeast extract were selected as the optimal carbon and nitrogen sources. A three-factor CCD comprising 20 experimental trials was conducted to evaluate the individual, quadratic, and interactive effects of these variables on the pigment production. The experimental data were well represented by a quadratic polynomial model, which was statistically significant (F = 13.49, p = 0.0002) and exhibited a high adjusted coefficient of determination (adjusted R² = 0.8554). The analysis of variance revealed that pH exerted a significant linear effect on pigment production (p = 0.0308), whereas the quadratic terms pH² (p < 0.0001) and temperature² (p = 0.0010) were highly significant, indicating pronounced curvature effects. Response surface analysis demonstrated that the interaction between pH and temperature had the most substantial impact on pigment yield, whereas the interaction between temperature and incubation time had minimal effect. Numerical optimization indicated that maximum pigment production could be achieved under conditions of near-neutral pH, moderate incubation temperature, and intermediate incubation time, which was experimentally validated with results closely aligned with the predictions.