## 3 Results and Discussion
### Validation of the Origin Discrimination Table  
In previous studies that used methods of inorganic content analysis, such as inductively coupled plasma-mass spectrometry or ED-XRF, the reported efficiency was 91.0-94.0%. Moreover, various statistical techniques were applied based on the concentration of 4-8 types of inorganic compounds [19; 20; 21]. [PERSON] et al. [5] utilized FT-NIRS, a method of organic content analysis. The reported efficiency was 96.1-96.5% based on the difference in the absorbance spectra of organic compounds using the NIR. Through the gene-based analysis in this study, 595 out of 630 domestic samples were predicted as being domestic, with 94.4% sensitivity. In addition, 446 out of 466 imported samples were predicted as being foreign, with 95.7% selectivity. Finally, the efficiency of the origin discrimination table was 95.0%. Conversely, in the analysis based on 10 markers (marker 1-10), 506 of 630 domestic samples were predicted to be domestic, achieving a sensitivity of 80.3%. In addition, 411 of 466 imported samples were predicted to be foreign, demonstrating a selectivity of 88.2%. However, the overall efficiency of the origin discrimination table was 83.7%, and a significant reduction was observed when compared to the analysis with 11 markers. Thus, the analytical method developed in this study exhibited a similar level of efficiency to conventional physicochemical analyses (95.0% vs. 91.0-96.5%) (Table 5). Figure 4: Morphological comparison between Pungsannamul and Chinese varieties with an overlapping judgment value (1215). Morphological comparison between (**A**) Pungsannamul and (**B**) Chinese varieties with an overlapping judgment value (1215). To determine the practicality of the origin discrimination table proposed in this study, soybean samples from 2019 to 2022, with accurately identified origins, were collected, and their judgment values were applied to the discrimination table. The judgment values calculated using the 11 InDel markers selected for 30 domestic and 30 imported soybeans were applied to the discrimination table. As shown in Table 6, 29 out of 30 domestic soybeans were discriminated as domestic, showing a 96.7% domestic predictive rate. Furthermore, all 30 imported soybeans were discriminated as foreign, demonstrating a 100.0% foreign predictive rate. Substantially high levels of domestic and foreign predictive rates were obtained at 98.3% on average for the discrimination table using 11 gene-based markers. These results suggest that the discrimination table can effectively discriminate between domestic and imported soybean varieties despite the slightly low level of domestic soybean discrimination caused by a low sensitivity (94.4%) and domestic predictive rate (96.7%) compared to the selectivity (95.7%) and foreign predictive rate (100.0%). The conventional physicochemical analyses of organic and inorganic compounds for soybean origin discrimination are classification methods for variation in cultivation conditions using statistical techniques. As such, the predictive rate and efficiency may [22; 23; 24]. By contrast, gene-based analyses are independent of compositional changes depending on the cultivation conditions. Soybeans that have been developed to adapt to the climate and pests of each country are known to be unable to be grown successfully in other countries. In particular, the production areas of soybeans imported into Korea are limited to some areas, and these areas have different latitudes and longitudes, compared to Korea. Therefore, it is highly unlikely that imported soybeans can be grown domestically. Therefore, it has been possible to accurately determine the country of origin by utilizing the unique genetic characteristics of soybean varieties.