Rapid quality assessment of Succus Bambusae oral liquid based on near infrared spectroscopy and chemometrics

In this study, a rapid quality assessment method of SBOL was established by fourier-transform near infrared (FT-NIR) spectroscopy combined with chemometric analysis. Combined with Hotelling T 2 and DModX statistics, warning limits and control limits were set for SBOL samples quality of different manufacturers. The contents of volatile components (4-hydroxybenzaldehyde, vanillin, syringaldehyde, acetylsyringone and methyl syringate) in 100 samples of SBOL were determined by gas chromatography-Mass spectrometry (GC-MS). Partial least-squares-discriminant analysis (PLS-DA), data-driven soft independent modeling of class analogy (DD-SIMCA) and random forest (RF) algorithms were used to establish the qualitative models of SBOLs based on NIR spectroscopy, which in terms of error rate and accuracy were satisfactory. Partial least squares regression (PLSR) algorithm was used to establish a quantitative calibration model. In this case, NIR showed a good performance with the effective discrimination of SBOL from different manufacturers, but the rapid quantitative model of quality markers (Q-markers) with moderate performance. • Near-infrared spectroscopy was applied for the quality control of Succus Bambusae oral liquid (SBOL). • SBOL from different manufacturers were accurately distinguished using Chemometrics. • Partial least squares models were used for the rapid determination of active compounds in SBOL with moderate performance.