Author Login

Correspondence to Author: Mohammad Hosein Fatemi , Hamideh Ahangar Darabi, 

Chemometrics laboratory, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran

DOI: 10.52338/joes.2024.4016

Abstract:

Ecotoxicological classification risk index for soil (ECRIS), is a new classification system specific for soil risk assessment, which gives a comparative indication of the risk linked to environmental contamination by any chemical. In this work this parameter was estimated by quantitative structure– activity relationship approaches by using interpretable molecular descriptors. Linear and nonlinear models were developed using multiple linear regressions (MLR) and artificial neural network (ANN) methods. Robustness and reliability of the constructed MLR and ANN models were evaluated by using the leave-one-out cross-validation method, which produces the statistics of Q2 MLR = 0.84, Q2 ANN = 0.93. Furthermore, the chemical applicability domains of these models were determined via leverage approach. The results of this study indicated the ability of developed QSPR models in the prediction of ECRIS of various chemicals from their calculated molecular structural descriptors.

Citation:

Fatemi Mohammad Hossein. Prediction of ecotoxicological classification risk index for soil of some organic compounds. Journal of Environmental And Sciences 2024.