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

Carl Emil Eskildsen | Zendy; Tormod Næs | Zendy; Jens Petter Wold | Zendy; Nils Kristian Afseth | Zendy; Søren Balling Engelsen | Zendy

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

Author(s) -

Carl Emil Eskildsen,

Tormod Næs,

Jens Petter Wold,

Nils Kristian Afseth,

Søren Balling Engelsen

Publication year - 2019

Publication title -

im publications open llp ebooks

Language(s) - English

Resource type - Book series

DOI - 10.1255/nir2017.039

Subject(s) - covariance , fatty acid , robustness (evolution) , infrared spectroscopy , spectroscopy , infrared , chemistry , analytical chemistry (journal) , mathematics , statistics , chromatography , physics , biochemistry , optics , organic chemistry , quantum mechanics , gene

Author 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.

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