Abstract
The morel mushroom (Morchella sp.) is reputed as one of the most highly-prized edible fungi with mounting cultivated area as well as commercial popularity in China. To date, optimized methods specific for quality evaluation and constituent analysis of Morchella sp. are still non-available, impeding the healthy and sustainable development of this industry. Herein, an untargeted UPLC-Q-TOF-MS-based metabolomics approach was performed to characterize the metabolite profiles of morel samples from four distinct geographical origins of China, viz. Gansu, Guizhou, Liaoning, and Henan province. A total of 32 significantly different metabolites assigned to lipids (19), organic acids (9), amino acids (3), and ketones (1) were identified to distinguish the geographic-segregation samples amenable to multivariate analysis. These metabolites may serve as molecular markers indicative of specific regions. More importantly, the lipid, protein and amino acid metabolism were responsible for geographic differences as revealed by KEGG pathway enrichment analysis. Collectively, this study not only pioneered high-throughput methodology to evaluate quality of Morchella sp. and distinguish geographical origins in a sensitive, rapid and efficient manner, but also shed light on the potential link between physiochemical variation and geological origins from a metabolic perspective, which may be conducive to the advancement of edible fungi industry and establishment of food traceability system.
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