A General QSAR Model for Predicting the Acute Toxicity of Pesticides to Oncorhynchus mykiss |
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| Authors: | J. Devillers J. Flatin |
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| Affiliation: | 1. CTIS , 3 Chemin de la Gravière, 69140, Rillieux La Pape, France;2. CTIS , 3 Chemin de la Gravière, 69140, Rillieux La Pape, France;3. Faculté Catholique de Lyon, Laboratoire de Biologie Générate et Histologie , 25 rue du Plat, 69288, Lyon CEDEX 02, France |
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| Abstract: | Abstract A Quantitative Structure-Activity Relationship (QSAR) model was derived for estimating the acute toxicity of pesticides against Oncorhynchus mykiss under varying experimental conditions. Chemicals were described by means of autocorrelation descriptors encoding lipophilicity (H0 to H5) and the H-bonding acceptor ability (HBA0) and H-bonding donor ability (HBD0) 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 accounting for the weight of the fish, time of exposure, temperature, pH, and hardness. |
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| Keywords: | QSAR Oncorhynchus mykiss acute toxicity pesticides neural network autocorrelation method |
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