Physicochemical recognition and Chemometric characterization

In this book, seven brands of whiskey were studied based on their physicochemical and antioxidant profile data using multivariate statistics. The study aimed to estimate whether the collected data, using pattern analysis (PA), and multivariate statistical techniques such as multivariate analysis of variance (MANOVA), linear discriminant analysis (LDA), and factor analysis (FA), could aid in the differentiation of whiskey according to its brand. The MANOVA results showed that physicochemical parameters (pH, total, fixed, and volatile acidity, color) and antioxidant profile data (antioxidant activity, total phenolic content) varied significantly (p<0.05) according to whiskey brand. LDA showed that whiskey samples were classified correctly according to the brand by 90.5% based on the cross-validation method, while PA showed no missing values in the original variable set subjected to the above chemometric techniques. Similarly, FA showed that pH and color parameters (red color tone and color intensity) were the parameters that were associated most with the whiskey brand.

Autorentext
Prof. Dr. Ioannis K. Karabagias is an Assistant Professor in the Food Science & Technology Department of the School of Agricultural Sciences of the University of Patras. His research studies fall within the fields of Food Science and Food Chemistry. In 2020, he was introduced to the 2% Top World's Scientists list released by Stanford University.