The determination of the fatty acid content of sea buckthorn seed oil using near infrared spectroscopy and variable selection methods for multivariate calibration |
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| Affiliation: | 1. Dipartimento di Scienze Fisiche e Chimiche, Università dell’Aquila, Via Vetoio 2, 67100, Coppito, L’Aquila, Italy;2. Sorbonne Universities, UPMC, Laboratoire de Réactivité de Surface UMR CNRS 7197, Tour 43-53, 3rd floor, 4 Pl. Jussieu, 75005, Paris, France;3. Service de Bioénergétique, Biologie Structurale et Mécanismes (SB2SM) CEA, iBiTec-S, Biochimie Biophysique et Biologie Structurale (B3S), I2BC, UMR 9198, F-91191 Gif-sur-Yvette, France;1. Institute of Physics, Faculty of Mathematics and Physics, Charles University, Ke Karlovu 5, 121 16 Prague 2, Czech Republic;2. Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Flemingovo náměstí 2, 166 10 Prague 6, Czech Republic;1. Faculty of Chemistry, Jagiellonian University, Ingardena 3, 30-060 Kraków, Poland;2. Frank Laboratory of Neutron Physics, JINR, 141980 Dubna, Russia;1. Department of Neurobiology, Institute of Pharmacology, Polish Academy of Sciences, Smętna 12, 31-343 Kraków, Poland;2. Faculty of Foundry Engineering, AGH University of Science and Technology, ul. Reymonta 23, 30-059 Kraków, Poland;3. Institute of Nuclear Physics, Polish Academy of Science, 31-342 Krakow, Poland;4. Faculty of Chemistry, Jagiellonian University, ul. Ingardena 3, 30-060 Kraków, Poland;5. Department of Chemistry, Hankuk University of Foreign Studies, Yongin, Kyunggi-Do, 449-791, South Korea |
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| 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. |
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| Keywords: | Sea buckthorn seed oil Near infrared spectrometry Uninformative variables elimination Competitive adaptive reweighted sampling Successive projections algorithm |
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