Literature DB >> 26857797

Characteristic fingerprinting based on macamides for discrimination of maca (Lepidium meyenii) by LC/MS/MS and multivariate statistical analysis.

Yu Pan1,2, Ji Zhang1,2, Hong Li1,2, Yuan-Zhong Wang1,2, Wan-Yi Li1,2.   

Abstract

BACKGROUND: Macamides with a benzylalkylamide nucleus are characteristic and major bioactive compounds in the functional food maca (Lepidium meyenii Walp). The aim of this study was to explore variations in macamide content among maca from China and Peru. Twenty-seven batches of maca hypocotyls with different phenotypes, sampled from different geographical origins, were extracted and profiled by liquid chromatography with ultraviolet detection/tandem mass spectrometry (LC-UV/MS/MS).
RESULTS: Twelve macamides were identified by MS operated in multiple scanning modes. Similarity analysis showed that maca samples differed significantly in their macamide fingerprinting. Partial least squares discriminant analysis (PLS-DA) was used to differentiate samples according to their geographical origin and to identify the most relevant variables in the classification model. The prediction accuracy for raw maca was 91% and five macamides were selected and considered as chemical markers for sample classification.
CONCLUSION: When combined with a PLS-DA model, characteristic fingerprinting based on macamides could be recommended for labelling for the authentication of maca from different geographical origins. The results provided potential evidence for the relationships between environmental or other factors and distribution of macamides.
© 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Entities:  

Keywords:  Lepidium meyenii; characteristic fingerprinting; geographical origin; macamides

Mesh:

Substances:

Year:  2016        PMID: 26857797     DOI: 10.1002/jsfa.7660

Source DB:  PubMed          Journal:  J Sci Food Agric        ISSN: 0022-5142            Impact factor:   3.638


  5 in total

1.  Phenolic variation among Chamaecrista nictitans subspecies and varieties revealed through UPLC-ESI(-)-MS/MS chemical fingerprinting.

Authors:  Luis Quirós-Guerrero; Federico Albertazzi; Emanuel Araya-Valverde; Rosaura M Romero; Heidy Villalobos; Luis Poveda; Max Chavarría; Giselle Tamayo-Castillo
Journal:  Metabolomics       Date:  2019-01-19       Impact factor: 4.290

2.  Lepidium meyenii Walp (red maca) Supplementation Prevents Acrylamide-Induced Oxidative Stress and Liver Toxicity in Rats: Phytochemical Composition by UHPLC-ESI-MS/MS.

Authors:  Roberto O Ybañez-Julca; Javier Palacios; Daniel Asunción-Alvarez; Ivan Quispe-Díaz; Chukwuemeka R Nwokocha; Ricardo Diego Duarte Galhardo de Albuquerque
Journal:  Plant Foods Hum Nutr       Date:  2022-08-06       Impact factor: 4.124

3.  Chemical profiling analysis of Maca using UHPLC-ESI-Orbitrap MS coupled with UHPLC-ESI-QqQ MS and the neuroprotective study on its active ingredients.

Authors:  Yanyan Zhou; Peng Li; Adelheid Brantner; Hongjie Wang; Xinbin Shu; Jian Yang; Nan Si; Lingyu Han; Haiyu Zhao; Baolin Bian
Journal:  Sci Rep       Date:  2017-03-17       Impact factor: 4.379

4.  Optimization of Ultrasound-Assisted Extraction, HPLC and UHPLC-ESI-Q-TOF-MS/MS Analysis of Main Macamides and Macaenes from Maca (Cultivars of Lepidium meyenii Walp).

Authors:  Shu-Xiao Chen; Ke-Ke Li; Duoji Pubu; Si-Ping Jiang; Bin Chen; Li-Rong Chen; Zhen Yang; Chao Ma; Xiao-Jie Gong
Journal:  Molecules       Date:  2017-12-10       Impact factor: 4.411

5.  Differentiation of Lepidium meyenii (Maca) from Different Origins by Electrospray Ionization Mass Spectrometry with Principal Component Analysis.

Authors:  Sihou Yang; Xiaochun Sun; Yumei Gao; Rui Chen
Journal:  ACS Omega       Date:  2019-09-27
  5 in total

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