A general QSAR model for predicting the acute toxicity of pesticides to Lepomis macrochirus

被引：25

作者：

Devillers, J ^{[1
]}

机构：

[1] CTIS, F-69140 Rillieux La Pape, France

来源：

SAR AND QSAR IN ENVIRONMENTAL RESEARCH | 2001年 / 11卷 / 5-6期

关键词：

acute toxicity; artificial neural network; autocorrelation method; Lepomis macrochirus; pesticides; QSAR;

D O I：

10.1080/10629360108035361

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

A Quantitative Structure-Activity Relationship (QSAR) model was derived for estimating the acute toxicity of pesticides against Lepomis macrochirus under varying experimental conditions. Chemicals were described by means of autocorrelation descriptors encoding lipophilicity (H(0) to H(5)) and the H-bonding acceptor ability (HBA(0)) and H-bonding donor ability (HBD(0)) of the pesticides. A three-layer feedforward neural network trained by the back-propagation algorithm was used as statistical engine for deriving a powerful OSAR model accounting for the weight of the fish, time of exposure, temperature, pH, and water hardness.

引用

页码：397 / 417

页数：21

共 28 条

[1] The use of artificial neural networks to assess fish abundance and spatial occupancy in the littoral zone of a mesotrophic lake [J].