Eigenstructure tracking analysis for assessment of peak purity in high-performance liquid chromatography with diode array detection

The application of eigenstructure tracking analysis (ETA) for the detection of an impurity under a chromatographic peak is discussed. A window of size three seems to be the most adequate for this problem. Some guidelines for interpretation of the ETA plots are given. A new normalization of spectra is proposed to remove heteroscedastic noise. The effect of this new normalization is compared with other data pretreatments. The results obtained are compared with the performance of methods such as fixed size window evolving factor analysis (FSW EFA), the methods based on the Gram-Schmidt orthogonalization and SIMPLISMA.