Prediction of total fatty acid parameters and individual fatty acids in pork backfat using Raman spectroscopy and chemometrics: Understanding the cage of covariance between highly correlated fat parameters.

Autor: Berhe DT; Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark., Eskildsen CE; Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark., Lametsch R; Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark., Hviid MS; Danish Meat Research Institute, Teknologisk Institut, Gregersensvej 9, DK-2630 Taastrup, Denmark., van den Berg F; Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark., Engelsen SB; Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark. Electronic address: se@food.ku.dk.
Jazyk: angličtina
Zdroj: Meat science [Meat Sci] 2016 Jan; Vol. 111, pp. 18-26. Date of Electronic Publication: 2015 Aug 20.
DOI: 10.1016/j.meatsci.2015.08.009
Abstrakt: This study investigates how Partial Least Squares regression models for predicting individual fatty acids (FAs) and total FA parameters depend on Raman spectral variation associated with the iodine value in pork backfat. The backfat was sampled from pigs, which were fed with different dietary fat sources and levels. Good correlations between the Raman spectra and the total FA composition parameters and most individual FAs were obtained (R(CV)(2)=0.78-0.90). However, the predictions of the individual FAs are indirect and to a high degree depend on co-variance with the total FA parameters. A new procedure was demonstrated for identifying and characterizing such indirect or non-targeted calibrations. This information is very useful when Raman spectroscopy or other vibrational spectroscopic techniques are used to predict non-targeted quality parameters such as individual FAs as they may lead to inaccurate predictions of future sample if the underlying covariance structure is changed e.g. by new dietary regimes or genotypes.
(Copyright © 2015. Published by Elsevier Ltd.)
Databáze: MEDLINE
Externí odkaz: