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Volume 9
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10.3390/foods9080989
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Article

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

by
Tae Jin Kim
1,†,
Jeong Gon Park
1,†,
Hyun Young Kim
2,
Sun-Hwa Ha
3,
Bumkyu Lee
4,
Sang Un Park
5,
Woo Duck Seo
2,* and
Jae Kwang Kim
1,*
1
Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon 22012, Korea
2
Division of Crop Foundation, National Institute of Crop Science, Rural Development Administration, Wanju, Jeonbuk 55365, Korea
3
Department of Genetic Engineering and Graduate School of Biotechnology, Kyung Hee University, Yongin 17104, Korea
4
Department of Environment Science & Biotechnology, Jeonju University, Jeonju 55069, Korea
5
Department of Crop Science, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Foods 2020, 9(8), 989; https://doi.org/10.3390/foods9080989
Received: 26 June 2020 / Revised: 16 July 2020 / Accepted: 21 July 2020 / Published: 24 July 2020
(This article belongs to the Special Issue Target and Non-Target Approaches for Food Authenticity and Traceability)
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Abstract

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. View Full-Text
Keywords: perilla; sesame; geographic origin; metabolomics; multivariate analysis; metabolite profiling perilla; sesame; geographic origin; metabolomics; multivariate analysis; metabolite profiling
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

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MDPI and ACS Style

Kim, T.J.; Park, J.G.; Kim, H.Y.; Ha, S.-H.; Lee, B.; Park, S.U.; Seo, W.D.; Kim, J.K. Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (Perilla frutescens) and Sesame (Sesamum indicum) Seeds. Foods 2020, 9, 989. https://doi.org/10.3390/foods9080989

AMA Style

Kim TJ, Park JG, Kim HY, Ha S-H, Lee B, Park SU, Seo WD, Kim JK. Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (Perilla frutescens) and Sesame (Sesamum indicum) Seeds. Foods. 2020; 9(8):989. https://doi.org/10.3390/foods9080989

Chicago/Turabian Style

Kim, Tae J., Jeong G. Park, Hyun Y. Kim, Sun-Hwa Ha, Bumkyu Lee, Sang U. Park, Woo D. Seo, and Jae K. Kim. 2020. "Metabolite Profiling and Chemometric Study for the Discrimination Analyses of Geographic Origin of Perilla (Perilla frutescens) and Sesame (Sesamum indicum) Seeds" Foods 9, no. 8: 989. https://doi.org/10.3390/foods9080989

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