Quality Grading Evaluation of Changii Radix Based on a Biology-Related Chemical Indicator Prediction Model

The quality of traditional Chinese medicine (TCM) is a prerequisite for clinical efficacy. However, the existing quality evaluation methods are not strongly correlated with efficacy, and they are unable to adequately reflect the quality grade of Changii Radix (CR).

In this study, a biology-related chemical indicator quality grading prediction model was developed to predict the quality grade of CR.

Firstly, the quality grade of CR was pre-classified based on immunological activity. Subsequently, one-way analysis of variance, gray correlation analysis, and Pearson correlation analysis were employed to identify the chemical indicators associated with immunological activity. Finally, separately using chemical indicators as independent variables and quality grades as dependent variables, the logistic regression model and a multi-index weighted quality comprehensive evaluation index (QCEI) were constructed to predict the quality grade of CR.

The results indicated that 27 batches of CR samples could be divided into three grades of I, II, and III. The gray correlation degrees and Pearson correlation coefficients between water-soluble extractives, polysaccharide, amino acid, and immunological activity all exceeded 0.8 and 0.4 (p < 0.05), respectively. Additionally, both the logistic regression model and QCEI could effectively predict the quality grade of CR, with the logistic regression model showing superior performance.

This study is the first to establish a chemistry-biology integrated strategy for evaluating the quality grade of CR, providing a novel insight into the assessment of TCM quality grade.