Discrimination and prediction of the origin of Chinese and Korean soybeans using Fourier transform infrared spectrometry (FT-IR) with multivariate statistical analysis
- 주제(기타) Multidisciplinary Sciences
- 설명문(일반) [Lee, Byeong-Ju; Zhou, Yaoyao; Lee, Jae Soung; Choi, Hyung-Kyoon] Chung Ang Univ, Coll Pharm, Seoul, South Korea; [Shine, Byeung Kon] Natl Agr Prod Qual Management Serv, Gimcheon, South Korea; [Seo, Jeong-Ah] Soongsil Univ, Sch Syst Biomed Sci, Seoul, South Korea; [Lee, Doyup] Kookmin Univ, Dept Bio & Fermentat Convergence Technol, Seoul, South Korea; [Kim, Young-Suk] Ewha Womans Univ, Dept Food Sci & Engn, Seoul, South Korea
- 등재 SCIE, SCOPUS
- 발행기관 PUBLIC LIBRARY SCIENCE
- 발행년도 2018
- URI http://www.dcollection.net/handler/ewha/000000151496
- 본문언어 영어
- Published As http://dx.doi.org/10.1371/journal.pone.0196315
초록/요약
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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