Visualizing indirect correlations when predicting fatty acid composition from near infrared spectroscopy measurements
Publication details
Pages : 39–44
Year : 2019
Publication type : Academic chapter/article/Conference paper
Part of : Proceedings of the 18th International Conference on Near Infrared Spectroscopy 2017 Denmark ( IM Publications , 2019 )
Year : 2019
Links
:
ARKIV
:
hdl.handle.net/11250/2646553
DOI
:
doi.org/10.1255/nir2017.039
If you have questions about the publication, you may contact Nofima’s Chief Librarian.
Kjetil Aune
Chief Librarian
kjetil.aune@nofima.no
Summary
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.
