학술논문
USE OF GENETIC ALGORITHM ON MID-INFRARED SPECTROMETRIC DATA: APPLICATION TO ESTIMATE THE FATTY ACIDS PROFILE OF GOAT MILK.
Document Type
Article
Author
Source
Subject
*INFRARED spectroscopy
*MILK quality
*DAIRY products
*LEAST squares
*REGRESSION analysis
*FATTY acids
*
*
*
*
*
Language
ISSN
2070-5948
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. [ABSTRACT FROM AUTHOR]