High-throughput foodomics strategy for screening flavor components in dairy products using multiple mass spectrometry
| Autor: | Feng Zhang, Wei Jia, Lin Shi, Han Wang, James Chang, Xuefeng Chen, Xiaogang Chu, Cheng Fan |
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| Rok vydání: | 2018 |
| Předmět: |
Mass spectrometry
01 natural sciences Gas Chromatography-Mass Spectrometry Analytical Chemistry 0404 agricultural biotechnology Discriminant function analysis Foodomics Animals Food science Throughput (business) Flavor Aroma Solid Phase Microextraction Mathematics Principal Component Analysis biology 010401 analytical chemistry food and beverages Discriminant Analysis 04 agricultural and veterinary sciences General Medicine equipment and supplies biology.organism_classification Linear discriminant analysis 040401 food science 0104 chemical sciences Flavoring Agents Milk Principal component analysis Dairy Products Food Science |
| Zdroj: | Food chemistry. 279 |
| ISSN: | 1873-7072 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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