A practical application of wavelet moment method on the quantitative analysis of Shuanghuanglian oral liquid based on three-dimensional fingerprint spectra.

The overlapping and shifts of peaks and noise signals appear mostly in high performance liquid chromatography (HPLC) experiments. A practical application of wavelet moment method on the quantitative analysis of the main active components in Shuanghuanglian oral liquid samples was presented based on the determination of HPLC coupled with photodiode array detector (PAD). The wavelet moments were calculated from the divided regions in the grayscale images of three-dimensional (3D) HPLC-PAD fingerprint spectra according to the target peak(s), and then used to establish linear models, respectively. The correlation coefficients (R) were more than 0.9980 within the test ranges. The intra- and inter-day variations were less than 1.13% and 1.10%, respectively. The recovery ranged from 96.2% to 102.7%. The overall LODs and LOQs were less than 0.2 μg/mL and 0.7 μg/mL, respectively. Our study indicated that wavelet moment approach could defuse the overlapping and shifts of peaks and noise signals in the chromatographic determination owing to its multi-resolution and inherently invariance properties. Thus the analytical time was shortened, and the obtained results were reliable and accurate.