QUANTITATIVE STRUCTURE-RETENTION RELATIONSHIPS ANALYSIS OF RETENTION INDEX OF ESSENTIAL OILS

被引：24

作者：

Noorizadeh, Hadi ^{[1
]}

Farmany, Abbas ^{[1
]}

Noorizadeh, Mehrab ^{[1
]}

机构：

[1] Islamic Azad Univ, Fac Sci, Dept Chem, Ilam Branch, Ilam, Iran

来源：

QUIMICA NOVA | 2011年 / 34卷 / 02期

关键词：

essential oils; genetic algorithm-kernel partial least squares; Levenberg-Marquardt artificial neural network; CHROMATOGRAPHY-MASS SPECTROMETRY; ARTIFICIAL NEURAL-NETWORK; PARTIAL LEAST-SQUARES; GAS-CHROMATOGRAPHY; MULTIVARIATE REGRESSION; GENETIC ALGORITHM; DERIVATIVES; PREDICTION; SELECTION; PLS;

D O I：

10.1590/S0100-40422011000200014

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Genetic algorithm and multiple linear regression (GA-MLR), partial least square (GA-PLS), kernel PLS (GA-KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlation between retention index (RI) and descriptors for 116 diverse compounds in essential oils of six Stachys species. The correlation coefficient LGO-CV (Q(2)) between experimental and predicted RI for test set by GA-MLR, GA-PLS, GA-KPLS and L-M ANN was 0.886, 0.912, 0.937 and 0.964, respectively. This is the first research on the QSRR of the essential oil compounds against the RI using the GA-KPLS and L-M ANN.

引用

页码：242 / 249

页数：8

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