Optimization of Ricotta Cheese Yield Using Response Surface Methodology

Mozzarella whey, due to its rich nutritional composition, offers considerable potential for value‐added dairy products. Ricotta cheese, a heat‐ and acid‐coagulated product, is traditionally derived from whey. This study is aimed at utilizing response surface methodology (RSM) to optimize the yield of ricotta cheese from mozzarella whey, focusing on key processing variables (heating temp, pH, curdling temp, citric acid, and CaCl 2 concentrations). The individual and interactive effects of these variables on Ricotta yield were evaluated using Box–Behnken and central composite designs. The optimal conditions were identified as 95°C heating temp, pH 6.0, 70°C curdling temp, and 0.1% citric acid concentration. These conditions resulted in a Ricotta yield of 10.88%, which is a significant improvement over previously reported yields of 5%–6%. The initial model exhibited a coefficient of determination ( R 2 ) of 0.7143. However, subsequent validation experiments under optimal conditions showed a strong correlation ( R 2 = 0.9704), with relative error percentages (< 10%) between the predicted and actual yields, confirming the model’s reliability for the optimized region. Notably, CaCl 2 did not significantly enhance the yield via ionic bridge formation; its contribution was primarily limited to increasing the total solid content. The inherent high lactose content of the whey hindered further yield enhancement, suggesting the remaining permeate as a viable source for lactose recovery. These findings demonstrate the efficacy of RSM in enhancing ricotta cheese production efficiency and provide practical insights for industrial applications.