An integrated strategy of marker ingredients searching and near infrared spectroscopy rapid evaluation for the quality control of Chinese eaglewood

• An integrated technique of UPLC–Q/Tof and NIRS for quality control of TCM was proposed.
• Four THPECs were firstly identified as potential markers to distinguish the authenticity of the Chinese Eaglewood.
• With siPLS algorithm, the optimal waveband variables of NIR were targeted on the four THPECs.
• The integrated technique presented a superior classification result than NIR full spectra and HPLC fingerprints.

The application of near infrared spectroscopy (NIRS) in traditional Chinese medicine (TCM) has usually been limited by its blindness to qualitative or quantitative multivariate analysis and because its chemical significance is easily ignored. Here, an integrated technology of ultra-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UPLC–Q/Tof) and NIRS was proposed to set up a systematic quality control of Chinese Eaglewood (CE). UPLC–Q/Tof combined with principle compound analysis (PCA) was used to identify the marker ingredients of CE. Four types of highly oxidized 5,6,7,8-tetrahydro-2-(2-phenylethyl) chromones (THPECs) were then identified as potential markers to distinguish the authenticity of the CE. Based on the marker ingredients, the definite wavenumber intervals and spectral pretreatment pattern of NIRS were selected to act as an alternative evaluation technology directed against CE powder samples. Calibration equations were developed from the contents of the four markers, as detected by high performance liquid chromatography (HPLC) and NIRS data, using synergy interval partial least squares (siPLS) algorithm with Leave-One-Out (LOO) cross-validation. Using siPLS regression, satisfactory calibration statistics were obtained for the prediction of the marker ingredients. The correlation coefficient (r) between the predicted and reference results for the test set was used as an evaluation parameter for the models (r > 0.9). Hierarchical cluster analysis and partial least squares-discriminant analysis (PLS-DA) were applied to further analyze the quantitative results from NIRS. From this systematic method, 50 CE samples were divided into superior, qualified, unqualified, and fake samples, displaying a more elaborate division than PLS-DA, which is only based on whole NIR spectra or HPLC. This tandem technique of UPLC–Q/Tof and NIRS assessment presented in this work can be used as a rapid evaluation approach for the quality control of complicated herbal medicines.

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