Identification of health-promoting bioactive phenolics in black walnut using cloud-based metabolomics platform

  • Danh C. Vu
  • Jihyun Park
  • Khanh-Van Ho
  • Lloyd W. Sumner
  • Zhentian Lei
  • C. Michael Greenlief
  • Brian Mooney
  • Mark V. Coggeshall
  • Chung-Ho LinEmail author
Original Paper


This study aimed to identify bioactive phenolics of eleven black walnut cultivars using a cloud-based metabolomics platform. The metabolomics software platform, XCMS Online, was used to incorporate peak detection, peak grouping, spectra extraction and non-linear retention time correction/alignment. In total, 49 phenolics previously known to promote health benefits were putatively identified in the black walnut kernels. The relative abundance of these phenolics differed significantly among the studied cultivars. Antioxidant activity of the Mystry extract was highest among the six examined cultivars. In addition, the antioxidant activities were found to be positively correlated with the relative abundance of thirteen phenolics. The principal component analysis provided a visible differentiation in phenolic metabolite profiles among the examined black walnuts. The results of hierarchical cluster analysis showed three clusters of black walnuts. Mystry differed from the other cultivars due to its highest relative abundance of gallic acid and ellagitannins. This study demonstrated that metabolite profiling could be an efficient analytical tool to identify potential health-promoting compounds and investigate metabolite variations among black walnuts.


Walnut Phenolics Untargeted analysis Metabolomics Antioxidant 



The authors would like to thank the Center for Agroforestry, University of Missouri under cooperative agreement 58-6227-1-004 with the USDA-ARS and Missouri Department of Agriculture Specialty Crop Block Grant Program (SCBGP) #16SCBGPMO0003 for supporting this research. The MU Metabolomics Center has been graciously supported by several entities over the years for plant metabolomics. These specifically include support from the University of Missouri, The Samuel Roberts Noble Foundation, Bruker Daltonics GmbH, Agilent Technologies, US National Science Foundation (NSF)-JST Metabolomics for a Low Carbon Society #1139489, NSF MRI DBI #1126719, NSF RCN #1340058, and NSF MCB #1024976.

Compliance with ethical standards

Conflict of interest

The authors declare no conflict of interest.

Research involving in human and animal studies

This article does not contain any studies with human or animal subjects.

Supplementary material

11694_2019_325_MOESM1_ESM.docx (367 kb)
Supplementary file1 (DOCX 362 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Danh C. Vu
    • 1
  • Jihyun Park
    • 1
  • Khanh-Van Ho
    • 1
  • Lloyd W. Sumner
    • 2
    • 3
  • Zhentian Lei
    • 2
    • 3
  • C. Michael Greenlief
    • 3
    • 4
  • Brian Mooney
    • 3
    • 4
  • Mark V. Coggeshall
    • 5
  • Chung-Ho Lin
    • 1
    Email author
  1. 1.Center for Agroforestry, School of Natural ResourcesUniversity of MissouriColumbiaUSA
  2. 2.Metabolomics CenterUniversity of MissouriColumbiaUSA
  3. 3.Bond Life Sciences CenterUniversity of MissouriColumbiaUSA
  4. 4.Charles W. Gehrke Proteomics CenterUniversity of MissouriColumbiaUSA
  5. 5.Hardwood Tree Improvement and Regeneration CenterUnited States Department of Agriculture, Forest Service, Northern Research StationWest LafayetteUSA

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