Tools for easing understanding of complex data

Special Symposium - Innovations in Food Technology (LMC Congress)

Modern Analysis: Chemical & Multivariate Analysis (Food-6a)

Mr Anders Juul Lawaetz
University of Copenhagen
Faculty of Life Sciences, Dpt. of Food Science, Quality and Technology
Rolighedsvej 30,
1958 Frederiksberg C
Denmark

Prof Rasmus Bro
University of Copenhagen
Faculty og Life Sciences, Dpt. of Food Science, Quality and technology
Rolighedsvej 30,
1958 Frederiksberg C
Denmark

Keywords: Pricipal Component Analysis, Complex data, Rotation Principles

In recent years, chemometric tools such as principal component analysis (PCA) have been increasingly used, and used on increasingly complex data. However, when trying to understand very complex and highly multivariate data (e.g. from GC-MS or NMR), even PCA can sometimes be complicated to interpret. By rotation of the loading or scores of the PCA-model to a simple structure it is possible to enabling simpler, yet still complete visualization and interpretation of complex models. In this presentation, different rotation principles are shown using several different types of applications.

Presented Thursday 20, 09:35 to 09:50, in session Modern Analysis: Chemical & Multivariate Analysis (Food-6a).