Multivariate standardization techniques on ion-selective sensor arrays

Abstract

Multivariate standardization techniques [slope/bias (S/B) correction, single wavelength standardization (SWS) and piecewise direct standardization (PDS)] were used to attempt to correct changes over time in multivariate calibration models for potassium and calcium. These models were constructed with ion-selective electrode (ISE) arrays. Multivariate PDS local models which included the correlation between the sensors of the array were better than the other simple techniques. We considered the relationship between the variables (sensors) and, in the PDS treatment, we have indicated their arrangement which is taken from the loadings plot. We used the Kennard–Stone algorithm to select the standardization samples from the original responses of the samples and the partial least squares (PLS) scores of each model. These scores include information about the concentrations. The models and standardizations were validated by predictions on real samples such as natural waters. The best standardization conditions provided unbiased predictions with no loss of precision.