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. 2018 Apr 24;13(4):e0196315.
doi: 10.1371/journal.pone.0196315. eCollection 2018.

Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis

Byeong-Ju Lee  1 , Yaoyao Zhou  1 , Jae Soung Lee  1 , Byeung Kon Shin  2 , Jeong-Ah Seo  3 , Doyup Lee  4 , Young-Suk Kim  5 , Hyung-Kyoon Choi  1
Affiliations

Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis

Byeong-Ju Lee et al. PLoS One. .

Abstract

The ability to determine the origin of soybeans is an important issue following the inclusion of this information in the labeling of agricultural food products becoming mandatory in South Korea in 2017. This study was carried out to construct a prediction model for discriminating Chinese and Korean soybeans using Fourier-transform infrared (FT-IR) spectroscopy and multivariate statistical analysis. The optimal prediction models for discriminating soybean samples were obtained by selecting appropriate scaling methods, normalization methods, variable influence on projection (VIP) cutoff values, and wave-number regions. The factors for constructing the optimal partial-least-squares regression (PLSR) prediction model were using second derivatives, vector normalization, unit variance scaling, and the 4000-400 cm-1 region (excluding water vapor and carbon dioxide). The PLSR model for discriminating Chinese and Korean soybean samples had the best predictability when a VIP cutoff value was not applied. When Chinese soybean samples were identified, a PLSR model that has the lowest root-mean-square error of the prediction value was obtained using a VIP cutoff value of 1.5. The optimal PLSR prediction model for discriminating Korean soybean samples was also obtained using a VIP cutoff value of 1.5. This is the first study that has combined FT-IR spectroscopy with normalization methods, VIP cutoff values, and selected wave-number regions for discriminating Chinese and Korean soybeans.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Map showing the origin of the Chinese and Korean soybeans used in the experiments.
(A) Map of China. The Chinese provinces were divided into three regions: northeastern, eastern, and southeastern. The northeastern region comprises four provinces: (a) Neimenggu, (b) Heilongjiang, (c) Jilin, and (d) Liaoning. The eastern region comprises four provinces: (e) Hebei, (f) Shandong, (g) Anhui, and (h) Hubei. The southeastern region comprises five provinces: (i) Zhejiang, (j) Jiangxi, (k) Fujian, (l) Guangdong, and (m) Guangxi. (B) Map of South Korea. The South Korean provinces were divided into three regions: upper, left side, and right side. The upper region comprises three provinces: (1) Gyeonggi-do, (2) Gangwon-do, and (3) Chungcheongbuk-do. The left-side region comprises three provinces: (4) Chungcheongnam-do, (5) Jeollabuk-do, (6) and Jeollanam-do. The right-side region comprises two provinces: (7) Gyeongsangbuk-do and (8) Gyeongsangnam-do.
Fig 2
Fig 2. Morphological characteristics of the eight Korean soybean samples.
(1) Gyeonggi-do Anseong, (2) Gangwon-do Yeongwol, (3) Chungcheongbuk-do Eumseong, (4) Chungcheongnam-do Cheonan, (5) Jeollabuk-do Imsil, (6) Jeollanam-do Yeonggwang, (7) Gyeongsangbuk-do Uiseong, and (8) Gyeongsangnam-do Geochang.
Fig 3
Fig 3. Morphological characteristics of the 13 Chinese soybean samples.
Fig 4
Fig 4. Representative FT-IR spectral data of soybeans from Neimenggu province.
Fig 5
Fig 5. Hierarchical cluster analysis derived from the most suitable prediction models for the discrimination of soybean samples.
(A) Chinese vs. Korean soybean samples (single linkage), (B) discrimination of Chinese soybean samples (Ward), and (C) discrimination of Korean soybean samples (Ward).
Fig 6
Fig 6. Flow chart for discrimination of unidentified soybean origin using FT-IR.
See this image and copyright information in PMC

References

    1. Mateos-Aparicio I, Redondo Cuenca A, Villanueva-Suárez MJ, Zapata-Revilla MA. Soybean, a promising health source. Nutr Hosp. 2008;23: 305–312. - PubMed
    1. Albulescu M, Popovici M. Isoflavones-biochemistry, pharmacology and therapeutic use. Rev Roum Chim. 2007;52: 537–550.
    1. Anthony MS, Clarkson TB, Hughes CL Jr, Morgan TM, Burke GL. Soybean isoflavones improve cardiovascular risk factors without affecting the reproductive system of peripubertal rhesus monkeys. J Nutr. 1996;126: 43–50. doi: 10.1093/jn/126.1.43 - DOI - PubMed
    1. Anderson JW, Smith BM, Washnock CS. Cardiovascular and renal benefits of dry bean and soybean intake. Am J Clin Nutr. 1999;70: 464s–474s. - PubMed
    1. Ravindranath MH, Muthugounder S, Presser N, Viswanathan S. Anticancer therapeutic potential of soy isoflavone, genistein. Adv Exp Med Biol. 2004;546: 121–165. - PubMed

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