ESTIMATION OF SOIL PARTITION-COEFFICIENTS OF PESTICIDES FROM THEIR CHEMICAL-STRUCTURE

被引：26

作者：

LOHNINGER, H

机构：

[1] A-1060 Vienna

来源：

CHEMOSPHERE | 1994年 / 29卷 / 08期

关键词：

SOIL SORPTION COEFFICIENTS; PESTICIDES; MULTIPLE LINEAR REGRESSION; NEURAL NETWORKS; RBF-NETWORKS; FEATURE SELECTION; QSPR;

D O I：

10.1016/0045-6535(94)90309-3

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The aim of this work was to investigate the estimation of soil partition coefficients (normalized to the organic carbon content) of pesticides solely from their chemical structure. Both multiple linear regression and neural networks have been applied to build a model from topological indices and structural fragments. The model has been derived from a data set of 120 pesticides and is based on eleven structural parameters. The application of the model to a test set of 81 other pesticides showed a performance which is comparable to conventional models based on water solubility.

引用

页码：1611 / 1626

页数：16

共 28 条

[1] HIGHLY DISCRIMINATING DISTANCE-BASED TOPOLOGICAL INDEX [J].