Evaluation of the predictive capability and process optimization of pectin extraction from lemon waste peels

Abstract Pectin is a natural biopolymer that has gained popularity in the pharmaceutical and biotechnology industries. This study investigated pectin extraction from lemon waste peel under various process parameters, such as temperature, pH, and extraction time. The effects of these parameters on pectin yield were investigated using Response Surface Methodology (RSM). These experiments were conducted under various parameter ranges, such as 60 °C–80 °C, pH 1–3, and extraction time of 1–3 h. The experimental data were used to develop a quadratic regression model using the RSM and a Central Composite Design (CCD).The interaction effect of pH and extraction time had a significant (p<0.0001) effect on the pectin yield compared to that of temperature. A ramp analysis was performed to determine the optimal parameter conditions for maximum pectin yield. The predicted pectin yields and experimental values are close agreement each other, confirming that the regression model accurately predicts the data within the error for the model. The calculated R 2 and adjusted R 2 values are, with slight variation, 0.99 and 0.975, respectively. The experimental and predicted pectin yields are 26.80 % and 28.86 %, respectively, under the optimum conditions of a temperature of 66.4 °C, pH of 1.01, and extraction time of 1.4 h.