Quantitative Determination of Sucrose Adulterated in Red Ginseng by Terahertz Time-Domain Spectroscopy (THz-TDS) with Monte Carlo Uninformative Variable Elimination (MCUVE) and Support Vector Regression (SVR)

Abstract

This paper introduces a method to detect the content of sucrose, an adulterant of red ginseng, based on terahertz spectroscopy. Experiments were carried out on red ginseng with 6 levels of adulterated concentrations using terahertz time-domain spectroscopy (THz-TDS). We separately extracted the information of the terahertz spectral curve by principal component analysis (PCA) and Monte Carlo uninformative variable elimination (MCUVE) and then separately performed quantitative analysis by partial least squares regression (PLSR) and support vector regression (SVR). Because the nonlinear line factor in the terahertz spectral curve of red ginseng samples is considered, the MCUVE-SVR has high correlation coefficient (>0.99) and ratio prediction to deviation (>7.4), low root means square error of deviation (<1.2%), and Bias (<0.05%). The results prove that MCUVE-SVR can be regarded as an ideal quantitative analysis method in the detection of sucrose incorporation in red ginseng by terahertz spectroscopy.

Discrimination of wheat unsound grains based on deep learning and terahertz spectral image technology

“…Terahertz is with the characteristics of strong penetration, etc., it has the advantages of multi-component analysis and nondestructive detection, which can effectively compensate for the lack of traditional detection methods. Pan [1]used PCA, MCUVE, PLSR and SVR algorithms to detect six different adulterated concentrations of red ginseng. The results showed that the combination of MCUVE-SVR method is a new method to detect sucrose adulteration in red ginseng.…”