Characterization of Maca (Lepidium meyenii/Lepidium peruvianum) Using a Mass Spectral Fingerprinting, Metabolomic Analysis, and Genetic Sequencing Approach

Ping Geng; Jianghao Sun; Pei Chen; Eric Brand; James Frame; Henry Meissner; Jeremy Stewart; Stefan Gafner; Stephanie Clark; Jesse Miller; James Harnly

doi:10.1055/a-1161-0372

Planta Medica, Table of Contents

Planta Med 2020; 86(10): 674-685
DOI: 10.1055/a-1161-0372

Natural Product Chemistry and Analytical Studies

Original Papers

Georg Thieme Verlag KG Stuttgart · New York

Characterization of Maca (Lepidium meyenii/Lepidium peruvianum) Using a Mass Spectral Fingerprinting, Metabolomic Analysis, and Genetic Sequencing Approach

Ping Geng

¹Methods and Application of Food Composition Lab, Beltsville Human Nutrition Research Center, Agriculture Research Service, US Department of Agriculture, Beltsville, MD, USA

,

Jianghao Sun

¹Methods and Application of Food Composition Lab, Beltsville Human Nutrition Research Center, Agriculture Research Service, US Department of Agriculture, Beltsville, MD, USA

,

Pei Chen

¹Methods and Application of Food Composition Lab, Beltsville Human Nutrition Research Center, Agriculture Research Service, US Department of Agriculture, Beltsville, MD, USA

,

Eric Brand

²School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong SAR

,

James Frame

³Natural Health International, San Francisco, CA, USA

,

Henry Meissner

⁴Faculty of Health Studies, Charles Sturt University & Therapeutic Research, TTD International Pty Ltd, Elanora, QLD, Australia

,

Jeremy Stewart

⁵Gaia Herbs, Brevard, NC, USA

,

Stefan Gafner

⁶American Botanical Council, Austin, TX, USA

,

Stephanie Clark

⁷NSF International Authenticity Laboratory, Petaluma, CA, USA

,

Jesse Miller

⁷NSF International Authenticity Laboratory, Petaluma, CA, USA

,

James Harnly

¹Methods and Application of Food Composition Lab, Beltsville Human Nutrition Research Center, Agriculture Research Service, US Department of Agriculture, Beltsville, MD, USA

› Author Affiliations

Abstract

Maca (Lepidium meyenii, synonym L. peruvianum) was analyzed using a systematic approach employing principal component analysis of flow injection mass spectrometry fingerprints (no chromatographic separation) to guide the selection of samples for metabolite profiling and DNA next generation sequencing. Samples consisted of 39 commercial maca supplements from 11 manufacturers, 31 unprocessed maca tubers grown in Peru and China, and a historic non-tuber maca sample from Peru. Principal component analysis of flow injection mass spectrometry fingerprints initially placed all the maca samples in three classes with similar chemical composition: commercial maca samples, tubers grown in Peru, and tubers grown in China. Metabolite profiling identified 67 compounds in the negative mode and 51 compounds in the positive mode. Compounds identified by metabolite profiling (macamides, glucosinolates, amino acids, fatty acids, polyunsaturated fatty acids, saccharides, imidazoles) were then used to identify ions in the flow injection mass spectrometry fingerprints. The tuber fingerprints were analyzed by factorial multivariate analysis of variance revealing that black, red, and yellow maca from Peru and black and yellow maca from China were compositionally different with respect to color and country. Critical ions were identified that allowed for the differentiation of maca between colors from the same country or between two countries with the same color. Genetically, all samples were confirmed to be L. meyenii based on next generation sequencing at three gene regions (ITS2, psbA, and trnL) and comparison to recorded sequences of vouchered standards.

Key words

maca - Lepidium meyenii - Brassicaceae - flow injection mass spectrometry - metabolite profiling - imidazoles - macamides - glucosinolates - PCA

Full Text

References

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