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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

Abstract : 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%.
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https://hal.inrae.fr/hal-02644842
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Submitted on : Thursday, May 28, 2020 - 11:35:13 PM
Last modification on : Wednesday, January 12, 2022 - 1:57:50 PM

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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, Elsevier, 2011, 106 (2), pp.183-189. ⟨10.1016/j.chemolab.2010.05.004⟩. ⟨hal-02644842⟩

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