Deriving mutual modes from HPLC fingerprints of traditional Chinese medicine with non-negative matrix factorization

Mutual modes derived from Chromatographic fingerprints of high-quality traditional Chinese medicine (TCM) can provide standards for quality assessment. This paper demonstrates a new method to apply non-negative matrix factorization (NMF) in deriving mutual mode from high performance liquid chromatography (HPLC) fingerprints of TCM. The HPLC fingerprints of the same species of TCM are taken as data set in NMF analysis, from which feature bases containing global features of the original data can be extracted. Reconstruction is performed to utilizing the first feature base and the mutual mode of HPLC fingerprints is obtained by projecting to basis matrix. Satisfactory results have been achieved in the experiment of species identification for Exocarpium Citrus Grandis, which has two primary species, that is, Citius Grandis `Tomentosa´ (CGT) and Citius Grandis (L.) Osbeck (CGO). Forty-seven representative batches of CGT collected from GAP in Huazhou (Guangdong Province, China), were served as the original data for mutual mode of CGT. Furthermore, six batches of CGT and six batches of CGO from different places were utilized to test the effectiveness of the mutual mode of CGT. The mutual mode of CGT derived by the proposed NMF-based method can cover the basic information on the whole, since the main representative peaks were contained. Compared with the existing approaches, the similarity results to the proposed mutual mode are more clearly distinguished among different species to some extent. The research indicates that the NMF-based method has a better capability of maintaining and summarizing the data information of original Chromatographic fingerprints and can provide an effective approach to establish the mutual model of HPLC fingerprints of TCM.