MULTIVARIATE STATISTICAL PROCESS-CONTROL APPLIED TO SULFATE DETERMINATION BY SEQUENTIAL INJECTION-ANALYSIS

A methodology was developed for determining sulfates in water at level s up to 500 mg l(-1) using a sequential injection analysis system. The multivariate calibration model avoids the need for the separation of interferents and sample pre-treatment. The trueness of the multivariat e calibration model was assessed by comparing the predictions of the m odel with reference concentrations determined by a reference method us ing the joint interval test for the slope and intercept of the regress ion line with errors on both axes, The accuracy, evaluated by the root mean square error of prediction, reached 6.9%, Multivariate statistic al process control techniques were used to check the system's stabilit y before developing the model and the validity of the model when it is used to predict the concentrations of unknown samples.