Application of Central Composite Design for the Optimization of Reverse-Phase HPLC/DAD Separation of the cis- and trans- Isomers of Long-Chain Unsaturated Fatty Acids

Abstract

The study deals with the optimization of reverse-phase HPLC separation of cis-/trans- isomers of long-chain unsaturated fatty acids by the assessment of the central composite design (CCD) of response surface methodology (RSM). The optimized conditions were also applied for the analysis of fatty acids in functional cold-pressed oils. The data obtained from experimental applications of CCD was used to model the parameters that significantly affect separations. The independent variables chosen were flow rate (X 1 ), column temperature (X 2 ), and acetonitrile content in mobile phase (X 3 ). A second-order polynomial model was used to estimate the impact of variables on separation efficiencies of the C30 and C18 stationary phases. The proposed CCD models were also validated with the ANOVA. The predicted values were in good agreement with experimental data, advising expert application of CCD as an option to obtain maximum information for the modeling of reverse-phase HPLC separation with little number of experiments. The optimal values of method parameters for the efficient C18 and C30 column separations as part of the k′ response value were found to be flow rate of 1.10 and 0.42 mL min−1, temperature of 3.6 and 9.4 °C, and acetonitrile content in mobile phase of 100 and 77.4%, respectively. ANOVA test results also illustrate that the CCD models can be successfully used to predict the optimum method parameters. To maximize both sensitivity and precision of the methods, the validation procedure was also performed and the higher correlation coefficients (r = 0.9149–0.9993) were determined for all fatty acid methyl esters. Thus, the proposed experimental designs were shown to offer considerable advantages over traditional method optimization approaches.