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Determination of fatty acids and lipid classes in salmon oil by near infrared spectroscopy
Mari Merce Cascant, Cassandra Breil, Anne-Sylvie Fabiano-Tixier, Farid Chemat, Salvador Garrigues, Miguel de La Guardia

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

Science & Mathematics Published 2018 Verification Pending

Overview & Synopsis

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.

Indexed from repository: HAL Open Science (hal.science)
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Document Information

Document Title Determination of fatty acids and lipid classes in salmon oil by near infrared spectroscopy
Author / Organization Mari Merce Cascant, Cassandra Breil, Anne-Sylvie Fabiano-Tixier, Farid Chemat, Salvador Garrigues, Miguel de La Guardia
Subject & Discipline Multidisciplinary Academic Open Research
Categories Science & Mathematics
Publication Year 2018
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website HAL Open Science (hal.science)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-88119
Original Source Link Visit Source Page on hal.science »