Abstract

Mountain-cultivated ginseng (MCG), which is considered the highest quality Panax ginseng C.A. Meyer, is priced higher than cultivated ginseng (CG) due to its longer growth period in the forest. However, accurately determining their age has been a persistent challenge. In this study, we examined the concentration of ginsenoside Rg1, Re, Rb1, and Rd in MCG and CG by analyzing their terahertz spectroscopic peaks. We found that MCG exhibited significant absorption peaks at 5.11, 8.23, and 9.07 THz in the range of 2–12 THz, while CG showed remarkable peaks at 8.67 and 10.57 THz. By combining the absorption raw data with multivariate statistical analysis OPLS-DA and machine learning, we were able to effectively distinguish MCG from CG with a coefficient of determination (R2) of 97.5 % and a predictive rate (Q2) of 94.5 %. Additionally, using the Multilayer Perceptron (MLP) algorithm, we accurately classified MCG samples aged 5–20 years into three distinct groups with an accuracy of 96.0 %. In contrast, the ginsenoside content analysis using high-performance liquid chromatography only provided broad categories for species and age groups. The terahertz method proved to be a fast and time-saving technique without the need for additional preparation. This method not only enables the differentiation of MCG from CG, but also allows for age-based categorization.

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