Academic chapter/article/Conference paper

Visualizing indirect correlations when predicting fatty acid composition from near infrared spectroscopy measurements

Eskildsen, Carl Emil Aae; Næs, Tormod; Wold, Jens Petter; Afseth, Nils Kristian; Engelsen, Søren Balling

Publication details

Pages: 39–44

Year: 2019

Open Access: green

Links:
ARKIV
DOI

Part of: Proceedings of the 18th International Conference on Near Infrared Spectroscopy 2017 Denmark (IM Publications, 2019)

In recent years, vibrational spectroscopy has been used to predict detailed sample composition like protein and fatty acid profiles. This study shows that
fatty acid predictions from near infrared measurements in food stuffs rely on covariance structures amongst the fatty acids. These covariance structures, in
turn, vary with factors like breed, age, feed, season etc. and therefore they are not likely to remain constant. Consequently, the robustness and validity of
the developed calibration models will be compromised.