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ARS Home » Northeast Area » Beltsville, Maryland (BHNRC) » Beltsville Human Nutrition Research Center » Food Composition and Methods Development Laboratory » Research » Publications at this Location » Publication #313823

Research Project: Metabolite Profiling and Chemical Fingerprinting Methods for Characterization of Foods, Botanical Supplements, and Biological Materials

Location: Food Composition and Methods Development Laboratory

Title: Differentiation of the two major species of Echinacea (E. augustifolia and E. purpurea) using a flow injection mass spectrometric (FIMS) fingerprinting method and chemometric analysis

Author
item Lu, Yingjian - University Of Maryland
item Chen, Pei

Submitted to: Analytical Methods
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/2/2015
Publication Date: 12/10/2015
Citation: Lu, Y., Chen, P. 2015. Differentiation of the two major species of Echinacea (E. augustifolia and E. purpurea) using a flow injection mass spectrometric (FIMS) fingerprinting method and chemometric analysis. Analytical Methods. 4:246-251.

Interpretive Summary: A rapid, simple, and reliable flow-injection mass spectrometric (FIMS) method was developed to discriminate two major Echinacea species (E. purpurea and E. angustifolia) samples. Fifty-eight Echinacea samples collected from United States were analyzed using FIMS. Principle component analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used to process the FIMS data. The results showed that FIMS fingerprinting technique (1 min per sample) successfully discriminated the two Echinacea species. The FIMS method also identified cichoric acid, caftaric acid, echinacoside, and some sugars as the components contributed most significantly in differentiating the two Echinacea species as well as the aerial and root parts of E. purpurea by using FIMS spectrometric fingerprints combined with PCA and SIMCA analysis.

Technical Abstract: A rapid, simple, and reliable flow-injection mass spectrometric (FIMS) method was developed to discriminate two major Echinacea species (E. purpurea and E. angustifolia) samples. Fifty-eight Echinacea samples collected from United States were analyzed using FIMS. Principle component analysis (PCA) and soft independent modeling of class analogy (SIMCA) were used to process the FIMS data. The results showed that FIMS fingerprinting technique (1 min per sample) successfully discriminated the two Echinacea species. The FIMS method also identified cichoric acid, caftaric acid, echinacoside, and some sugars as the components contributed most significantly in differentiating the two Echinacea species as well as the aerial and root parts of E. purpurea by using FIMS spectrometric fingerprints combined with PCA and SIMCA analysis.