Structure-toxicity modeling of pesticides to honey bees

被引：25

作者：

Devillers, J

Pham-Delègue, MH

Decourtye, A

Budzinski, H

Cluzeau, S

Maurin, G

机构：

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

[2] INRA, Lab Neurobiol Comparee Invertbres, F-91440 Bures Sur Yvette, France

[3] Univ Bordeaux 1, CNRS, UMR 5472, LPTC, F-33405 Talence, France

[4] ACTA, F-75595 Paris 12, France

来源：

SAR AND QSAR IN ENVIRONMENTAL RESEARCH | 2002年 / 13卷 / 7-8期

关键词：

acute toxicity; Apis mellifera; artificial neural network; autocorrelation method; pesticides; QSAR;

D O I：

10.1080/1062936021000043391

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 on the honey bee. Chemicals were described by means of autocorrelation descriptors encoding lipophilicity (H), molar refractivity (MR) and the H-bonding acceptor ability (HBA) of the pesticides. A three-layer feedforward neural network trained by the back-propagation algorithm was used as statistical engine for deriving a powerful QSAR model. The root mean square residual (RMSR) values for the training and testing sets were 0.430 and 0.386, respectively. The practical interest of this original model was discussed.

引用

页码：641 / 648

页数：8

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