Design of experiment and statistical analysis

This study aims to optimize several parameters which have an effect in chlorophyll extraction process. Response surface methodology (RSM) was chosen as a tool for optimization. RSM can reduce the number of experiment for evaluating the parameters and their interactions (Sinha et al. 2012b). A full three-level factorial design was used with three independent variables, namely pH, ZnCl₂ concentration and extraction temperature. The dependent variable in this study is total chlorophyll content (TCC), with detail of independent variables and their range and level are written in Table 1.

A second-order polynomial equation was employed to correlate the response (dependent variable) and factors (independent variables). The polynomial equation has a general form which written as follows (Bezerra et al. 2008; Montgomery 2013):

where Y is the response; x_i and x_j are the factors (i and j is the range from 1 to k); β₀ is the constant coefficient; β_i, β_ii, β_ij are the coefficients for the linear, quadratic and interaction effect; and ε represents the error. The accuracy of proposed model was assessed using the coefficient of determination (R²). R² has value ranged from 0 to 1, if R² close to 1 indicates that the model is more accurate (Vendaraman et al. 2017).