Linear and non-linear relationships mapping the Henry’s law parameters of organic pesticides

MOHAMMAD GOODARZI; ERLINDA V. ORTIZ; LEANDRO DOS S. COELHO; PABLO R. DUCHOWICZ

ATMOSPHERIC ENVIRONMENT

PERGAMON-ELSEVIER SCIENCE LTD

Año: 2010 vol. 44 p. 3179 - 3186

1352-2310

This work aims to predict the air to water partitioning for 96 organic pesticides by means of theQuantitative StructureeProperty Relationships Theory. After performing structural feature selection with Genetics Algorithms and Replacement Method linear approaches, it is found that among the most important molecular features appears the Moriguchi octanolewater partition coefficient, and higher lipophilicities would lead to compounds having higher Henry’s law constants. We also compare the statistical performance achieved by four fully-connected Feed-Forward Multilayer Perceptrons Artificial Neural Networks. The statistical results found reveal that the best performing model uses the LevenbergeMarquardt with Bayesian regularization (BR) weighting function for achieving the most accurate predictions.