Visualizing indirect correlations when predicting fatty acid composition from near infrared spectroscopy measurements
Publikasjonsdetaljer
Sider : 39–44
År : 2019
Publikasjonstype : Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
En del av : Proceedings of the 18th International Conference on Near Infrared Spectroscopy 2017 Denmark ( IM Publications , 2019 )
År : 2019
Lenker
:
ARKIV
:
hdl.handle.net/11250/2646553
DOI
:
doi.org/10.1255/nir2017.039
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Kjetil Aune
Bibliotekleder
kjetil.aune@nofima.no
Sammendrag
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.
