College of Chemistry & Chemical Engineering, Lanzhou University, South Tianshui Road 222, Lanzhou 730000, Gansu, China.
College of Chemistry & Chemical Engineering, Lanzhou University, South Tianshui Road 222, Lanzhou 730000, Gansu, China.
J Chromatogr A. 2014 Jul 25;1352:55-61. doi: 10.1016/j.chroma.2014.05.051. Epub 2014 May 27.
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.
在高效液相色谱（HPLC）实验中，峰和噪声信号的重叠和偏移现象较为常见。本文基于高效液相色谱-光电二极管阵列检测联用技术（HPLC-PAD），提出了一种将小波矩法应用于双黄连口服液主要活性成分定量分析的实际应用。通过对三维（3D）HPLC-PAD 指纹图谱的灰度图像进行分区，根据目标峰计算小波矩，并建立线性模型。在测试范围内，相关系数（R）均大于 0.9980。日内和日间变异系数均小于 1.13%和 1.10%。回收率在 96.2%至 102.7%之间。总的检测限和定量限均小于 0.2μg/mL 和 0.7μg/mL。本研究表明，由于小波矩方法具有多分辨率和固有不变性，能够消解色谱测定中峰和噪声信号的重叠和偏移，从而缩短了分析时间，得到了可靠准确的结果。
