UHPLC-QTOF-MS-based untargeted metabolomics revealing the differential chemical constituents and its application on the geographical origins traceability of lily bulbs

Abstract

Lily bulbs have been historically used as an edible and medicinal homologous plant. Identifying the geographical origins of lily bulbs produced in specific origin is of great importance since the geographical origins of lily bulbs influence their quality and price greatly. In this work, an untargeted metabolomic method based on UHPLC-QTOF-MS was established for revealing the differential chemical constituents of lily bulbs among different origins and predicting the geographical origins of them by chemometric modeling. A total of 15 differential compounds were screened and identified from untargeted metabolomic data of 50 lily bulb samples by our previously developed AntDAS software. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) showed that samples from five different origins were obviously distinguished based on the differential compounds. What's more, 7 and 6 key characteristic markers were discovered by partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA), respectively. Finally, heatmap, PLS-DA and OPLS-DA models were reconstructed based on the discovered key characteristic markers, and external validation lily bulb samples were successfully discriminated, with recognition rate of 100%. This study demonstrated that the proposed strategy has great potentials for the differentiation and identification of the geographical origins of lily bulbs.