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

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.

Qualitative Analysis of Traditional Italian Dishes: FTIR Approach

“…Thus, the IR spectra can be used to identify or differentiate between samples [14]. The list of applications includes evaluating and determining components [15,16], monitoring contaminants and adulterants [17,18], classification [19,20], discrimination [21,22], authentication [23,24], etc. In this context, the review of Rodriguez-Saona and Allendorf [25] is worth mentioning.…”

Soybean (Glycine max L.) isoflavones: Chemical composition and its chemometrics-assisted extraction and authentication

“…CCD, a type of RSM technique introduced by Box and Wilson (1951), was composed of three parts, including full factorial or fractional factorial design, star points, and center point (Box and Wilson, 1951). This design was successfully generated and applied for optimizing isoflavones extraction of soybean of DT2010 (Le et al, 2019), BRS 257 (Yoshiara et al, 2018 and JS 335 cultivar (Lakshmi et al, 2013). Several optimization parameters, namely, solvent concentration, extraction time, reaction temperature, solvent-material ratio, and pH, can be defined as experimental factors to achieve optimized extraction conditions.…”

“…Tempeh Maceration, LLE FFD (Yuliani et al, 2018) Soybeans (BRS 257 cultivar) Ultrasonication, centrifugation, filtration (Yoshiara et al, 2012) Soybean seeds (DT2010 cultivar) Maceration CCD (Le et al, 2019) Soybeans (BRS 257 cultivar) Agitation, centrifugation CCD (Yoshiara et al, 2018) Soybeans (JS 335 cultivar) Leaching, membrane process, and LLE-CCD (Lakshmi et al, 2013) Soy flour Agitation, fractionation BBD (Abdella et al, 2018) Black soybean variety VL Bhatt CSE, MAE, EAE BBD (Kumar et al, 2019) Chinese soybean cheese UAE BBD (Jianming et al, 2013) Soybean from the Guangdong Inspection and Quarantine Technology Center…”

“…Metabolite profiling using HPLC method combined with PLS-DA and CA for assessing the quality of food soybeans from China, Japan, and Korea has been successfully conducted (Kim et al, 2014). The studyies by Lee et al (2018) reported the employment of Fourier transform infrared (FTIR) spectroscopy in combination with PLS-DA and CA to discriminate between Chinese and Korean soybeans. In this study, the PLSR model was generated to determine the origin of soybeans using the appropriate wavenumber selection (Lee et al, 2018).…”

“…In two last decades, soy products were not only consumed as one of the functional foods but also were reported to provide several benefits on cardiovascular health, bone health, kidney function, cognitive function, mental health, skin health, reproduction function, thyroid function, and anticancer (Messina, 2016). The research interest on anticancer activities of soy isoflavones has increased in recent years due to their beneficial effects on the prostate cancer (Dong, 2011;Sivoňová et al, 2018;Sugiyama et al, 2013;Zhang et al, 2016), breast cancer (Boucher et al, 2013;Kang et al, 2010;Yuliani et al, 2016;Ziaei and Halaby, 2017), ovarian cancer (Lee et al, 2012;Zhuang et al, 2010), and colorectal cancer (Shafiee et al, 2016;Yu et al, 2016). Previous studies was reported that the biological activities of soy foods were linked to the presence of the soy isoflavones (Lissin and Cooke, 2000;Valsecchi et al, 2011).…”