High-throughput foodomics strategy for screening flavor components in dairy products using multiple mass spectrometry

Abstract A reliable Fisher discriminant model was established which was able to analyze the aroma component in milk, dairy products, flavors and fragrance, and applied on its variety identification. Foodomics was applied on screening of flavor components in 1093 dairy products and flavor samples in this study. Stepwise discrimination was used to screen the components of the dairy products and flavor samples that had a significant effect on the classification results, and discriminant function analysis. Then nine principal components were used for established the Fisher discriminant model. The three-dimensional coordinate distance of the sample was calculated and as the gist. The result showed that samples and flavors were distributed in eight different sites. The separation and clustering effects are better. The objective of the present study was to effectively determine whether or not flavors were added to dairy products.