Genetic Algorithm Based Wavelengths Selection Coupled with Partial Least Squares for Simultaneous Spectrophotometric Determination of Phosphate and Silicate in Detergent Products

Background: Phosphate and silicate are very important in a variety of compounds such as mineral resources, underground water, detergents and cleaners. Phosphate and silicate in water positively influence the metabolism of plants and animals. They have led to an environmental problem. This problem can have serious consequences because phosphate and silicate are widely utilized in water softening, surfactants and a large number of other applications. Methods: Genetic algorithm (GA) is an appropriate method for selecting wavelengths for PLS (partial least squares) calibration of mixtures which have almost identical spectra without losing prediction capacity using spectrophotometric method. In this paper, we have described a simple, sensitive and selective spectrophotometric method for the simultaneous determination of phosphate and silicate based on the formation of phospho- and silicomolybdenum blue complexes in the presence of ascorbic acid. Results: The complexes of phosphate and silicate with a reagent in the presence of ascorbic acid have been simultaneously determined by genetic algorithm- partial least squares (GA-PLS) although they showed a spectral overlap. The calibration curve was linear over a concentration range of 0.01-2.00 and 0.01-3.80 μgmL-1 for phosphate and silicate, respectively. The root mean square error (RMSE) for phosphate and silicate was 0.372 and 0.301, respectively. Conclusion: The present study indicates that the GA can be a good method for feature selection in spectral data sets. Results show that GA-PLS is an excellent calibration method for the determination of phosphate and silicate. In the end the proposed method was successfully applied for the simultaneous determination of phosphate and silicate in synthetic detergents.