Physicochemical Data Mining of Msalais, a Traditional Local Wine in Southern Xinjiang of China

Abstract

Twelve physicochemical parameters of 15 traditional wine samples of Msalai were completely analyzed with data mining methods to understand the interaction between physicochemical attributes and the homogeneity among the Msalais samples. Although the physicochemical differences were significant among the Msalais samples, there was also significant correlation between chromaticity and turbidity, between total soluble solids and dry extract, between total phenol and chromaticity, volatile acid content, dry extract, as well as iron content. With multivariable dimension scale analysis, 12 physicochemical parameters were clustered according to their contribution to color (iron, color), flavor (volatile acids, alcohol content, total acid, phenol, total sugar), and body (dry extract, turbidity, total soluble solids, density) of Msalais. Homogeneity was observed in the physicochemical parameters of the samples from one modern factory; however, there was strong heterogeneous in the physicochemical parameters of the samples from different traditional workhouses. Data mining with the help of a variety of analytical methods provides a good foundation for the quality control of Msalais, especially for its grade estimation.