| Abstract:Objective: in order to realize rapid digital identification of Commelinae Herba (CH) and Commelina Diffusa (CD) based on UPLC-QTOF-MS analysis and "digital identity". Methods: Firstly, UPLC-QTOF-MS was utilized to analyze Commelinae Herba (CH) and Commelina Diffusa (CD). Then the shared ion information was extracted from different batches of CH and CD respectively after data quantification by Progenesis QI. Further, on the basic of the shared ions information of Commelinae Herba and Commelina Diffusa, their data matrice of specific ions were obtained by eliminating similar ions and screening, and the TopN ion information was output as "digital identity" of Commelinae Herba and Commelina Diffusa respectively according to ion intensity. Finally, the "digital identity" of Commelinae Herba and Commelina Diffusa was used as a benchmark for sample matching identification and feedback of the Matching Credibility (MC). Results: the results showed that based on "digital identity" of CH and CD, the rapid digital identification of CH and CD can be realized efficiently and accurately at the individual level with the MC≥68.00%, even if 5% of CD in the mixed samples can still be identified efficiently and accurately. Conclusion: Based on UPLC-QTOF-MS and "digital identity", the digital identification of CH and CD can be realized at the individual level efficiently and accurately, which is beneficial to the rapid quality control of Commelinae Herba. In addition, this study provided new idea and reference for the digitalization of traditional Chinese medicine and the construction of digital quality control. |
