Optimization of oil extraction from Lallemantia iberica seeds using ultrasound-assisted extraction

Cnicus benedictus Oil as a Raw Material for Biodiesel: Extraction Optimization and Biodiesel Yield

“…The operating conditions were as follows: secondary electron mode, 30 kV accelerating voltage, 10 mm working distance. All samples were gold coated by DC magnetron sputtering for 60 s prior to SEM examination in order to ensure surface conductivity [19].…”

“…Response surface methodology (RSM) using the Box-Behnken design (BBD) was employed to assess the influence of each process variable on the oil extraction yield from CB fruits. RSM, an effective statistical technique, allows for the analysis of individual con-tributions and interactions of independent variables on the response, and could accurately describe the global process based on a limited number of runs [19]. BBD, which is one of the most common rotatable models, was preferred for obtaining a polynomial model (second order) to explain the contribution of each process variable on the response (extraction yield of CB oil).…”

“…BBD, which is one of the most common rotatable models, was preferred for obtaining a polynomial model (second order) to explain the contribution of each process variable on the response (extraction yield of CB oil). The obtained data were integrated into the following second-order polynomial model according to Equation (1), where Y is the response variable, β 0 is the constant term, β i are the linear coefficients, and β ii and β ij represent the quadratic and interactive coefficients, respectively [19]:…”

“…Statistical methods such as response surface methodology (RSM) are often used to search for the optimal conditions of a process, particularly if there are several parameters and interactions which could influence the system evolution. By reducing the number of experimental trials which should be carried out to assess the interactions among influencing variables, RSM reduces the efforts and the experimental costs [18,19]. The Box-Behnken design (BBD) was chosen in this work as it implies a small number of runs, as compared to other statistical designs [19].…”

“…By reducing the number of experimental trials which should be carried out to assess the interactions among influencing variables, RSM reduces the efforts and the experimental costs [18,19]. The Box-Behnken design (BBD) was chosen in this work as it implies a small number of runs, as compared to other statistical designs [19].…”