Foods (Jul 2020)

Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (<i>Perilla frutescens</i>) and Sesame (<i>Sesamum indicum</i>) Seeds

  • Tae Jin Kim,
  • Jeong Gon Park,
  • Hyun Young Kim,
  • Sun-Hwa Ha,
  • Bumkyu Lee,
  • Sang Un Park,
  • Woo Duck Seo,
  • Jae Kwang Kim

DOI
https://doi.org/10.3390/foods9080989
Journal volume & issue
Vol. 9, no. 8
p. 989

Abstract

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Perilla and sesame are traditional sources of edible oils in Asian and African countries. In addition, perilla and sesame seeds are rich sources of health-promoting compounds, such as fatty acids, tocopherols, phytosterols and policosanols. Thus, developing a method to determine the geographic origin of these seeds is important for ensuring authenticity, safety and traceability and to prevent cheating. We aimed to develop a discriminatory predictive model for determining the geographic origin of perilla and sesame seeds using comprehensive metabolite profiling coupled with chemometrics. The orthogonal partial least squares-discriminant analysis models were well established with good validation values (Q2 = 0.761 to 0.799). Perilla and sesame seed samples used in this study showed a clear separation between Korea and China as geographic origins in our predictive models. We found that glycolic acid could be a potential biomarker for perilla seeds and proline and glycine for sesame seeds. Our findings provide a comprehensive quality assessment of perilla and sesame seeds. We believe that our models can be used for regional authentication of perilla and sesame seeds cultivated in diverse geographic regions.

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