Application of principal component analysis and discriminant analysis using latent structure regression to the identification of highly volatile organic compounds in gas mixtures based on piezoelectric quartz microweighing parameters

The applicability of the new parameters of piezoelectric quartz microweighing and principal component and discriminant analysis with the use of latent structure regression to the treatment of the output data of an array of piezoelectric sensors in the identification of individual highly volatile compounds in model three-component gas mixtures is discussed. The parameters proposed and the methods of chemometrics were used in the treatment of the multidimensional data of an electronic nose for detecting individual aromaforming compounds and evaluating changes in the aroma of food systems with functional additives.