This study aimed to discriminate between the geographical origins of Asian red pepper powders distributed in Korea using Fourier-transform infrared (FT-IR) spectroscopy coupled with multivariate statistical analyses. Second-derivative spectral data were obtained from a total of 105 red pepper powder samples, 86 of which were used for statistical analysis, and the remaining 19 were used for blind testing. A one-way analysis of variance (ANOVA) test confirmed that eight peak variables exhibited significant origin-dependent differences, and the canonical discriminant functions derived from these variables were used to correctly classify all the red pepper powder samples based on their origins. The applicability of the canonical discriminant functions was examined by performing a blind test wherein the origins of 19 new red pepper powder samples were correctly classified. For simplicity, the four most significant variables were selected as discriminant indicator variables, and the applicable range for each indicator variable was set for each geographical origin. By applying the indicator variable ranges, the origins of the red pepper powders of all the statistical and blind samples were correctly identified. The study findings indicate the feasibility of using FT-IR spectroscopy in combination with multivariate analysis for identifying the geographical origins of red pepper powders.

This study focuses on discriminating the seed content in red pepper powders using 1 H NMR and second-derivative FT-IR Spectroscopy with canonical discriminant and multiple linear regression analyses. We used 165 test samples prepared by varying the seed content for spectroscopic analyses. The canonical discriminant functions derived from 21 peak variables were used to properly discriminate the red pepper powder samples based on their seed content with a 97.6% hit ratio. Additionally, we observed an average error of 7.0% while discriminating 42 blind samples. Multiple linear regression analysis was performed to directly determine the seed content of new samples without running a statistical program. The best regression model constructed with only two variables showed an average error of 6.2% when applied to the blind samples. These results verify the feasibility of using 1 H NMR and FT-IR Spectroscopy with statistical analyses to determine the seed content in red pepper powders.