Abstract
Application of Genetic Programming (GP) in Prediction of Gas Chromatographic Retention Time of some Pesticides
Highlights
Pesticides are a group of organic compounds that are used in most sectors of the agricultural production on a large scale
The present study investigates the use of Multiple linear regression (MLR) and genetic programming (GP) for developing quantitative structure–retention relationship (QSRR) model as mathematical regression equation to predict the gas chromatographic retention times of some pesticides
The present study investigates the use of MLR and GP methods for developing linear and symbolic equations as QSRR models for prediction of gas chromatographic retention time of some pesticides
Summary
Pesticides are a group of organic compounds that are used in most sectors of the agricultural production on a large scale. These compounds prevent or reduce losses by pests and can improve quality and cosmetic appeal of the product [1, 2]. Despite extensive use of these chemicals there are serious concerns about health risks arising for the general population from residues on food and drinking water [5, 6] Most of these compounds have low rates of biodegradation and tendency to bioaccumulation that could make an environmental and human health risks [7,8,9].
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
