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

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          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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          Most cited references30

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          Metabolomics--the link between genotypes and phenotypes.

          Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms 'transcriptome' and proteome', the set of metabolites synthesized by a biological system constitute its 'metabolome'. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.
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            Fourier transform infrared spectroscopic analysis of protein secondary structures.

            Infrared spectroscopy is one of the oldest and well established experimental techniques for the analysis of secondary structure of polypeptides and proteins. It is convenient, non-destructive, requires less sample preparation, and can be used under a wide variety of conditions. This review introduces the recent developments in Fourier transform infrared (FTIR) spectroscopy technique and its applications to protein structural studies. The experimental skills, data analysis, and correlations between the FTIR spectroscopic bands and protein secondary structure components are discussed. The applications of FTIR to the secondary structure analysis, conformational changes, structural dynamics and stability studies of proteins are also discussed.
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              Cardiovascular and renal benefits of dry bean and soybean intake.

              Dry beans and soybeans are nutrient-dense, fiber-rich, and are high-quality sources of protein. Protective and therapeutic effects of both dry bean and soybean intake have been documented. Studies show that dry bean intake has the potential to decrease serum cholesterol concentrations, improve many aspects of the diabetic state, and provide metabolic benefits that aid in weight control. Soybeans are a unique source of the isoflavones genistein and diadzein, which have numerous biological functions. Soybeans and soyfoods potentially have multifaceted health-promoting effects, including cholesterol reduction, improved vascular health, preserved bone mineral density, and reduction of menopausal symptoms. Soy appears to have salutary effects on renal function, although these effects are not well understood. Whereas populations consuming high intakes of soy have lower prevalences of certain cancers, definitive experimental data are insufficient to clarify a protective role of soy. The availability of legume products and resources is increasing, incorporating dry beans and soyfoods into the diet can be practical and enjoyable. With the shift toward a more plant-based diet, dry beans and soy will be potent tools in the treatment and prevention of chronic disease.
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                Author and article information

                Contributors
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: VisualizationRole: Writing – original draft
                Role: Investigation
                Role: Investigation
                Role: Resources
                Role: Validation
                Role: Validation
                Role: Validation
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                24 April 2018
                2018
                : 13
                : 4
                : e0196315
                Affiliations
                [1 ] College of Pharmacy, Chung-Ang University, Seoul, Republic of Korea
                [2 ] National Agricultural Products Quality Management Service, Gimcheon, Republic of Korea
                [3 ] School of Systems Biomedical Science, Soongsil University, Seoul, Republic of Korea
                [4 ] Department of Bio and Fermentation Convergence Technology, Kookmin University, Seoul, Republic of Korea
                [5 ] Department of Food Science and Engineering, Ewha Womans University, Seoul, Republic of Korea
                College of Agricultural Sciences, UNITED STATES
                Author notes

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

                Author information
                http://orcid.org/0000-0002-4523-0534
                Article
                PONE-D-17-45085
                10.1371/journal.pone.0196315
                5916519
                29689113
                584b1a03-2238-4e86-b7a9-8bcfa019eb81
                © 2018 Lee et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 December 2017
                : 10 April 2018
                Page count
                Figures: 6, Tables: 5, Pages: 16
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003668, Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries;
                Award ID: 316081-04
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100003725, National Research Foundation of Korea;
                Award ID: NRF-2015R1A5A1008958
                Award Recipient :
                This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries(IPET) through Advanced Production Technology Development Program funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA) (316081-04 awarded to HKC). This work was also funded by the National Research Foundation of Korea (NRF-2015R1A5A1008958 awarded to HKC). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Agriculture
                Crop Science
                Crops
                Soybean
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Forecasting
                Physical Sciences
                Mathematics
                Statistics (Mathematics)
                Statistical Methods
                Forecasting
                Research and Analysis Methods
                Spectrum Analysis Techniques
                Absorption Spectroscopy
                Physical Sciences
                Chemistry
                Chemical Compounds
                Organic Compounds
                Amides
                Physical Sciences
                Chemistry
                Organic Chemistry
                Organic Compounds
                Amides
                Biology and Life Sciences
                Biochemistry
                Lipids
                Earth Sciences
                Atmospheric Science
                Atmospheric Chemistry
                Greenhouse Gases
                Carbon Dioxide
                Physical Sciences
                Chemistry
                Environmental Chemistry
                Atmospheric Chemistry
                Greenhouse Gases
                Carbon Dioxide
                Ecology and Environmental Sciences
                Environmental Chemistry
                Atmospheric Chemistry
                Greenhouse Gases
                Carbon Dioxide
                Physical Sciences
                Chemistry
                Chemical Compounds
                Carbon Dioxide
                Physical Sciences
                Mathematics
                Discrete Mathematics
                Combinatorics
                Permutation
                Physical Sciences
                Physics
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