Chemometrics analysis for investigation of retention behavior of hazardous compounds in effluents.
Environ Monit Assess
; 185(1): 473-83, 2013 Jan.
Article
em En
| MEDLINE
| ID: mdl-22399286
ABSTRACT
The toxic substances, pesticides, and organic contaminants in effluents can potentially be causing damage that includes increased cancer risk; liver, kidney, stomach, nervous system, and immune system problems; reproductive difficulties; cataracts; and anemia. A quantitative structure-retention relationship (QSRR) was developed using the partial least square (PLS), kernel PLS (KPLS), and Levenberg-Marquardt artificial neural network (L-M ANN) approach for chemometrics study. The data which contained retention time (RT) of the 47 hazardous compounds in effluents were obtained by reverse-phase high-performance liquid chromatography. Genetic algorithm was employed as a factor selection procedure for PLS and KPLS modeling methods. By comparing the results, GA-PLS descriptors are selected for L-M ANN. Finally, a model with a low prediction error and a good correlation coefficient was obtained by L-M ANN. The described model does not require experimental parameters and potentially provides useful prediction for RT of new compounds. This is the first research on the QSRR of hazardous compounds in effluents using the chemometrics models.
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Poluentes Químicos da Água
/
Substâncias Perigosas
/
Modelos Químicos
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article
País de afiliação:
Irã