Use of genetic algorithm on mid-infrared spectrometric data: application to estimate the fatty acids profile of goat milk - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Electrophoresis Année : 2011

Use of genetic algorithm on mid-infrared spectrometric data: application to estimate the fatty acids profile of goat milk

Résumé

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.
Fichier non déposé

Dates et versions

hal-02642047 , version 1 (28-05-2020)

Identifiants

Citer

Marion Ferrand, Bérénice Huquet, Frédéric F. Bouvier, Hugues Caillat, Francis F. Barillet, et al.. Use of genetic algorithm on mid-infrared spectrometric data: application to estimate the fatty acids profile of goat milk. Electrophoresis, 2011, 4 (2), pp.245-254. ⟨10.1285/i20705948v4n2p245⟩. ⟨hal-02642047⟩
8 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More