Using ANOVA-PCA for discriminant analysis: application to the study of mid-infrared spectra of carrageenan gels as a function of concentration and temperature.

In this work the ANOVA-PCA method is applied to a MIR spectroscopy dataset of carrageenan in order to evaluate which of the factors within its fixed effects experimental design are significant in relation to the residual error. The factors defined in the experimental design are concentration (1% and 2%), temperature (30, 40, 45, 50, and 60 degrees C), day (1 and 2) and sample (20 samples, 3 repetitions). The two factors, concentration and temperature, were considered as significant and the main features related with its physico-chemical properties were identified. It is also of interest to acquire a better understanding of the interaction between concentration and temperature and its effect on the adhesion of gels onto the surface of contact. In fact, no significant interaction was found between the two factors, but it was shown that the factor temperature behaves in a non-linear way. As classification using the ANOVA-PCA procedure has not been developed until now, a new method is proposed for the classification of new samples in respect to the levels of each significant factor.