Classification of aniseed drinks by means of cluster, linear discriminant analysis and soft independent modelling of class analogy based on their Zn, B, Fe, Mg, Ca, Na and Si content

Abstract

Zinc, boron, iron, magnesium, calcium, sodium and silicon were determined in aniseed drinks by inductively coupled plasma-atomic emission spectrometry (ICP-AES). These elements were considered as chemical descriptors to characterise Spanish-certified aniseed drinks brands of origin. Different pattern recognition (PR) procedures were applied for these purposes. This chemometric study have included methods like principal component analysis (PCA), non-supervised PR techniques such as cluster analysis (CA), supervised PR methods of hard modelling like linear discriminant analysis (LDA) and soft independent modelling of class analogy (SIMCA).