Linear and nonlinear quantitative structure linear retention indices relationship models for essential oils
Hadi Noorizadeh · Eurasian Journal of Analytical Chemistry · 2012
Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS) and kernel PLS (GA-KPLS) techniques were used to investigate the correlation between linear retention indices (LRI) and descriptors for 101 diverse compounds in essential oils of six Stachys species which obtained by gas chromatography/electron impact mass spectrum (GC-EIMS). The correlation coefficient LGO-CV (Q 2 ) between experimental and predicted LRI for training and test sets by GA-MLR, GA-PLS and GA-KPLS was 0.936, 0.942 and 0.967 (for 80 compounds), 0.860, 0.871 and 0.919 (for 21 compounds), respectively. This indicates that GA-KPLS can be used as an alternative modeling tool for quantitative structure–retention relationship (QSRR) studies