Abstract
The analysis of pesticide residues in food has become, very important in recent years because of the damage they may cause in human health. The analysis of residues requires, different equipment and software for the study, characterization, identification and quantification of these chemicals. However not always the desired parameters according to the method implemented are obtained, so the estimation of these is an optimal solution, considering the short runtime. Parameter estimation, is a tool used heavily in different fields and applications, in order to obtain, an unknown value from variables related. Estimating pesticide retention times Carbamates, by a trained neural network by the method of particle swarm, is presented in this work. The data for network training were acquired through a study of levels of pesticide residues present in samples of kidney tomato (Lycopersicon esculentum).
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