The application of pseudotargeted metabolomics method for fruit juices discrimination

To optimize and evaluate the pseudotargeted metabolomics for juice discrimination and authentication, five widely consumed fruit (apple, orange, pear, purple grape and mandarin) juices were selected. SWATH-MS data was acquired by various windows being calculated based on total ion current, and then 2310 and 2292 MRM transitions were generated. Most of them (1522 and 1872) were detected in positive and negative modes. Distinctive separation among these juices could be observed from principal component analysis and hierarchical clustering analysis. After analysis of variance, fold change analysis and orthogonal projection to latent structures discriminant analysis, 57 potential markers were defined. Subsequently, 33 markers were putatively annotated, which could be used for juice discrimination and authentication. And 7 markers including l-phenylalanine, ascorbic acid, adenosine, epicatechin, glutathione, chlorogenic acid and nobiletin, were confirmed by standards. It is clearly indicated that pseudotargeted metabolomics could make great contribution to food industry as a new emerging technique.