%0 Journal Article
%T Use of genetic algorithm on mid-infrared spectrometric data: application to estimate the fatty acids profile of goat milk
%A B¨Śr¨Śnice Huquet
%A Francis Barillet
%A Fr¨Śd¨Śric Bouvier
%A F¨Ślicie Faucon - Lahalle
%A Hugues Caillat
%A H¨Śl¨¨ne Larroque
%A Isabelle Palhiere
%A Marion Ferrand
%A MickaŁżl Brochard
%A Olivier Leray
%J -
%D 2011
%R DOI Code: 10.1285/i20705948v4n2p245
%X To know and to control the fine milk composition is an important concern in the dairy industry. The mid-infrared (MIR) spectrometry method appears to be a good, fast and cheap method for assessing milk fatty acid profile with accuracy. Although partial least squares (PLS) regression is a very useful and powerful method to determine fine milk composition from spectra, the estimations are often less accurate on new samples coming from different spectrometers. Therefore a genetic algorithm (GA) combined with a PLS was used to produce models with a reduced number of wavelengths and a better accuracy. Number of wavelengths to consider is reduced substantially by 5 or 10 according the number of steps in the genetic algorithm. The accuracy is increased on average by 9% for fatty acids of interest
%K mid-infrared (MIR) spectrometry
%K goat milk
%K fatty acid
%K genetic algorithms
%K Partial Least Squares (PLS) regression
%U http://siba-ese.unisalento.it/index.php/ejasa/article/view/11023