Profiling Complex Volatile Components of Herbs by Hs-Gc-Ms and Entropy Minimization Software: An Example On Ligusticum Chuanxiong Hort

Volatile oil, as an important bioactive fraction of medicinal herbs, is comprised of a diversity of compounds. At present, gas chromatography-mass spectrometry (GC-MS) is one of the mainstream approaches to profiling these complex components. However, GC-MS faces the major bottleneck in data analysis, such as co-elution of more than one compound, and interference caused by high background noise; this usually makes an operator has to spend a lot of time and effort in optimizing experimental conditions. Taking Chuanxiong Rhizoma (the dry rhizome of Ligusticum chuanxiong Hort., abbreviated as “CR”) as an example, this study is intended to provide a feasible, quick and cost-effective solution for the compound identification based on the chemometric method of entropy minimization (EM) algorithm. Ten batches of geo-authentic CR and eight batches of non-authentic CR including Fuxiong, Shanchuanxiong (two varieties of immature CR but at different growth stages, abbreviated as “FX” and “SCX”, respectively) and Cnidii Rhizoma (the dried rhizome of Cnidium officinale Makino, “CNR”) were determined by headspace GC-MS. The co-eluted and overlapped peaks and low-concentration peaks with high background etc. were precisely reconstructed by EM algorithm, and then the reconstructed pure mass spectra of each component were compared with the ion fragment information in NIST library for qualitative identification. This EM algorithm proves to be capable of delivering results with increased accuracy and high confidence. Moreover, by the GC-MS fingerprint established in this work, it is demonstrated that the volatile chemical profiles of FX and SCX, as well as CNR, were significantly different from those of geo-authentic CR, suggesting that they should not be confused in clinical practice and pharmaceutical industry. In brief, the advanced EM algorithm is envisioned to be applied to a variety of medicinal herbs, enabling the rapid and accurate identification of volatile phytochemicals.