Determination of fatty acid profile in cow's milk using mid-infrared spectrometry : interest of applying a variable selection by genetic algorithms before a PLS regression - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Chemometrics and Intelligent Laboratory Systems Année : 2011

Determination of fatty acid profile in cow's milk using mid-infrared spectrometry : interest of applying a variable selection by genetic algorithms before a PLS regression

Résumé

The new challenges of the dairy industry require an accurate estimation of fine milk composition. The mid-infrared (MIR) spectrometry method appears to be a good, fast and cheap method for assessing milk fatty acid profile. Although partial least squares (PLS) regression is a very useful and powerful method to determine fine milk composition from the spectra, the estimations are not always very accurate and stable over time. Therefore a genetic algorithm (GA) combined with a PLS regression was used to produce models with a reduced number of wavelengths and a better accuracy. The results are a little sensitive to the choice of parameters in the algorithm. The number of wavelengths to consider is reduced substantially by 4 and accuracy is increased on average by 15%.

Dates et versions

hal-02644842 , version 1 (28-05-2020)

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Citer

M. Ferrand, B. Huquet, Sarah Barbey, Francis F. Barillet, F. Faucon, et al.. Determination of fatty acid profile in cow's milk using mid-infrared spectrometry : interest of applying a variable selection by genetic algorithms before a PLS regression. Chemometrics and Intelligent Laboratory Systems, 2011, 106 (2), pp.183-189. ⟨10.1016/j.chemolab.2010.05.004⟩. ⟨hal-02644842⟩
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