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Article

Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles

by
So-Yeon Kim
1,
So Young Kim
1,
Sang Mi Lee
1,
Do Yup Lee
2,
Byeung Kon Shin
3,
Dong Jin Kang
3,
Hyung-Kyoon Choi
4,* and
Young-Suk Kim
1,*
1
Department of Food Science and Engineering, Ewha Womans University, Seoul 03760, Korea
2
Department of Agricultural Biotechnology, Research Institute for Agricultural and Life Sciences, Seoul National University, Seoul 08779, Korea
3
National Agricultural Products Quality Management Service, Gimcheon 39660, Korea
4
College of Pharmacy, Chung-Ang University, Seoul 06974, Korea
*
Authors to whom correspondence should be addressed.
Molecules 2020, 25(3), 763; https://doi.org/10.3390/molecules25030763
Submission received: 2 January 2020 / Revised: 31 January 2020 / Accepted: 6 February 2020 / Published: 10 February 2020
(This article belongs to the Special Issue Progress in Volatile Organic Compounds Research)
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Abstract

Soybean (Glycine max) is a major crop cultivated in various regions and consumed globally. The formation of volatile compounds in soybeans is influenced by the cultivar as well as environmental factors, such as the climate and soil in the cultivation areas. This study used gas chromatography-mass spectrometry (GC-MS) combined by headspace solid-phase microextraction (HS-SPME) to analyze the volatile compounds of soybeans cultivated in Korea, China, and North America. The multivariate data analysis of partial least square-discriminant analysis (PLS-DA), and hierarchical clustering analysis (HCA) were then applied to GC-MS data sets. The soybeans could be clearly discriminated according to their geographical origins on the PLS-DA score plot. In particular, 25 volatile compounds, including terpenes (limonene, myrcene), esters (ethyl hexanoate, butyl butanoate, butyl prop-2-enoate, butyl acetate, butyl propanoate), aldehydes (nonanal, heptanal, (E)-hex-2-enal, (E)-hept-2-enal, acetaldehyde) were main contributors to the discrimination of soybeans cultivated in China from those cultivated in other regions in the PLS-DA score plot. On the other hand, 15 volatile compounds, such as 2-ethylhexan-1-ol, 2,5-dimethylhexan-2-ol, octanal, and heptanal, were related to Korean soybeans located on the negative PLS 2 axis, whereas 12 volatile compounds, such as oct-1-en-3-ol, heptan-4-ol, butyl butanoate, and butyl acetate, were responsible for North American soybeans. However, the multivariate statistical analysis (PLS-DA) was not able to clearly distinguish soybeans cultivated in Korea, except for those from the Gyeonggi and Kyeongsangbuk provinces.
Keywords: gas chromatography-mass spectrometry; solid-phase microextraction; soybean; origin discrimination; volatile compounds gas chromatography-mass spectrometry; solid-phase microextraction; soybean; origin discrimination; volatile compounds
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MDPI and ACS Style

Kim, S.-Y.; Kim, S.Y.; Lee, S.M.; Lee, D.Y.; Shin, B.K.; Kang, D.J.; Choi, H.-K.; Kim, Y.-S. Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles. Molecules 2020, 25, 763. https://doi.org/10.3390/molecules25030763

AMA Style

Kim S-Y, Kim SY, Lee SM, Lee DY, Shin BK, Kang DJ, Choi H-K, Kim Y-S. Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles. Molecules. 2020; 25(3):763. https://doi.org/10.3390/molecules25030763

Chicago/Turabian Style

Kim, So-Yeon, So Young Kim, Sang Mi Lee, Do Yup Lee, Byeung Kon Shin, Dong Jin Kang, Hyung-Kyoon Choi, and Young-Suk Kim. 2020. "Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles" Molecules 25, no. 3: 763. https://doi.org/10.3390/molecules25030763

APA Style

Kim, S.-Y., Kim, S. Y., Lee, S. M., Lee, D. Y., Shin, B. K., Kang, D. J., Choi, H.-K., & Kim, Y.-S. (2020). Discrimination of Cultivated Regions of Soybeans (Glycine max) Based on Multivariate Data Analysis of Volatile Metabolite Profiles. Molecules, 25(3), 763. https://doi.org/10.3390/molecules25030763

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