Differentiating Puerariae Lobatae Radix and Puerariae Thomsonii Radix using HPTLC coupled with multivariate classification analyses

• Seven multivariate classification techniques were employed.
• The classification abilities from the HPTLC and UPLC were compared.
• KNN, PLS-DA, PCA-DA and SVM-DA showed the highest rate of correct classification.
• SIMCA showed the lowest rate of correct species classification.
• Models from HPTLC demonstrated comparable classification performance as UPLC.

Puerariae Lobatae Radix (PLR), the root of Pueraria lobata, is a traditional Chinese medicine for treating diabetes and cardiovascular diseases. Puerariae Thomsonii Radix (PTR), the root of Pueraria thomsonii, is a closely related species to PLR and has been used as a PLR substitute in clinical practice. The aim of this study was to compare the classification accuracy of high performance thin-layer chromatography (HPTLC) with that of ultra-performance liquid chromatography (UPLC) in differentiating PLR from PTR. The Matlab functions were used to facilitate the digitalisation and pre-processing of the HPTLC plates. Seven multivariate classification methods were evaluated for the two chromatographic methods. The results demonstrated that the HPTLC classification models were comparable to the UPLC classification models. In particular, k-nearest neighbours, partial least square-discriminant analysis, principal component analysis-discriminant analysis and support vector machine-discriminant analysis showed the highest rate of correct species classification, whilst the lowest classification rate was obtained from soft independent modelling of class analogy. In conclusion, HPTLC combined with multivariate analysis is a promising technique for the quality control and differentiation of PLR and PTR.

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