The determination of the fatty acid content of sea buckthorn seed oil using near infrared spectroscopy and variable selection methods for multivariate calibration

Abstract

This study proposes an analytical method for the simultaneous near infrared (NIR) spectrometric determination of palmitic, oleic, linoleic and linolenic acids in sea buckthorn seed oil. For this purpose, four different combinations of multivariate calibration methods and variable selections were evaluated: partial least squares (PLS) with full spectrum; PLS with uninformative variables elimination (UVE); PLS with competitive adaptive reweighted sampling (CARS); and multiple linear regression (MLR) with uninformative variable elimination combined with successive projections algorithm (UVE-SPA). An independent set of samples was employed to evaluate the performance of the resulting models. The UVE-SPA-MLR model developed with a few spectral variables provided the best results for each parameter. The values of relative errors of prediction (REP) from the UVE-SPA-MLR model for palmitic, oleic, linoleic and linolenic acids are 1.77%, 1.20%, 1.02% and 1.40%, respectively. These results indicate that this method is a feasible and fast method for the determination of the fatty acid content of sea buckthorn seed oil.