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

Authors
  • Ferrand, Marion
  • Huquet, Bérénice
  • Bouvier, Frédéric
  • Caillat, Hugues
  • Barillet, Francis
  • Faucon-Lahalle, Félicie
  • Larroque, Helene
  • Leray, Olivier
  • Palhière, Isabelle
  • Brochard, Mickael
Publication Date
Jan 01, 2011
Identifiers
DOI: 10.1285/i20705948v4n2p245
OAI: oai:HAL:hal-02642047v1
Source
HAL-Descartes
Keywords
Language
English
License
Unknown
External links

Abstract

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.

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