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

Meat Science
Daniel T BerheS B Engelsen

Abstract

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.

References

May 1, 1965·Journal of the American Oil Chemists' Society·D CHAPMAN
May 9, 2007·Lipids·J Renwick BeattieBruce W Moss
Aug 29, 2007·Analytica Chimica Acta·Nils Kristian AfsethVegard Herman Segtnan

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Citations

Feb 18, 2016·Meat Science·Xiaoye LiuDaniel Mörlein
Jan 25, 2017·Critical Reviews in Food Science and Nutrition·Feifei Tao, Michael Ngadi
Dec 24, 2015·Journal of Clinical Medicine·Michael E R DuganJennifer L Aalhus
Jul 28, 2020·International Journal of Molecular Sciences·Abdul Rohman, Anjar Windarsih
Oct 10, 2020·Critical Reviews in Food Science and Nutrition·Wenyang ZhangDa-Wen Sun

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