Determining sample differences in a sample series of complex liquid chromatography-diode array detector data using chemometrics

In analytical laboratories, one often has to deal with sample series that have minor differences between them. For example, different batches of the same material may cause manufacturing problems, and quality control is an important issue. Another example is decomposition studies, where changes may or may not occur in a sample. To extract the differences between such highly related samples from LC-DAD (liquid chromatography-diode array detector) data is a time-consuming and subjective task. This paper describes an algorithm that efficiently extracts such differences.