Multivariate Calibration Techniques Applied to the Spectrophotometric Analysis of Binary Mixture

Abstract

The UV spectrophotometric analysis of a binary mixture containing p-toluidine and o-nitroaniline by multivariate calibration methods, such as Multivariate Linear Regression (MLR), Principal Components Regression (PCR), Partial Least Squares regression (PLS), was described. R2 values and the RMSE values for both the compounds were used for the selection of best model, using 32 datasets and 13 testsets. PLS1 model best fits the requirements and was used to predict the concentration of both the compounds. The present work demonstrate that UV-Vis spectroscopy coupled with Multivariate methods can be used to in situ monitor the concentration changes, providing a novel approach to determine the competitive effects of different organic pollutants during water purification and wastewater treatment.