Determination of fatty acids and lipid classes in salmon oil by near infrared spectroscopy

• Published in: Food Chemistry
• Main Authors: Cascant, Mari Merce, Breil, Cassandra, Fabiano-Tixier, Anne-Sylvie, Chemat, Farid, de la Guardia, Miguel
• Other Authors: Garrigues, Salvador
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2018
• Subjects: Near infrared spectroscopy;Partial least square;Fatty acids;Lipid class;Omega-3;Omega-6; salmo salar; huile de poisson; spectroscopie proche infrarouge; classe lipidique; traitement statistique; évaluation de méthode; acide gras; oméga 3; oméga 6; Salmo salar
• Online Access: http://prodinra.inra.fr/ft/90CC4492-3609-45D6-A5C0-2FBBB7FB9363; http://prodinra.inra.fr/record/411715; https://doi.org/10.1016/j.foodchem.2017.06.158

Near-infrared (NIR) spectroscopy was evaluated as a rapid method for the determination of oleic, palmitic, linoleic and linolenic acids as well as omega-3, omega-6, and to predict polyunsaturated, monounsaturated and saturated fatty acids, together with triacylglycerides, diglycerides, free fatty acids and ergosterol in salmon oil. To do it, Partial Least Squares (PLS) regression models were applied to correlate NIR spectra with aforementioned fatty acids and lipid classes. Results obtained were validated in front of reference procedures based on high performance thin layer and gas chromatography. PLS-NIR has a good predictive capability with relative root mean square error of prediction (RRMSEP) values below or equal to 1.8% and provides rapid analysis without the use of any chemicals making it an environmentally friendly methodology.