College of Life Sciences, Yangtze University, Jingzhou 434025, China.
College of Chemistry and Environmental Engineering, Yangtze University, Jingzhou 434023, China.
J Chromatogr A. 2018 Oct 26;1573:18-27. doi: 10.1016/j.chroma.2018.09.019. Epub 2018 Sep 12.
The quantification of preservatives in cosmetics has attracted great attentions for their controversial and widespread use. HPLC is a prevailing method for preservatives determination among various analytical methods. However, it takes long time to fully separate these compounds because of the complexity of cosmetic matrices. In this study, a fast and green HPLC-DAD strategy assisted with second-order multivariate calibration methods based on alternating trilinear decomposition (ATLD) and multivariate curve resolution-alternating least squares (MCR-ALS) was developed for the simultaneous determination of eight selected preservatives in complex facial mask samples. This appealing strategy proved to be a useful tool for eliminating unknown interferences in complex matrices without complete separation, which benefited from the "second-order advantages" and thus made the determination of the eight analytes in facial mask samples shorten to 8.2 min under a fast elution program. In particular, for the first time, we focused on the applicability of ATLD method for modeling of HPLC-DAD data with severe signal overlapping and slight time shifts. The spiked recovery values were in the range of 71.4-124.6%, and the RMSEP and REP values ranged from 0.07 to 2.4 μg mL and 1.3-14.5%, respectively, indicating that the ATLD method could provide satisfactory prediction. The resolved spectral profiles and concentration values were compared with those obtained by the MCR-ALS method, an excellent tool for modeling of data deviating from trilinearity. Both qualitative and quantitative results from the two methods were consistent with each other, which evidenced the competence of ATLD method in handling HPLC-DAD data with severe signal overlapping and slight time shifts.
防腐剂在化妆品中的定量分析因其广泛使用而备受关注。高效液相色谱法（HPLC）是各种分析方法中用于防腐剂测定的流行方法。然而，由于化妆品基质的复杂性，这些化合物的完全分离需要很长时间。在这项研究中，开发了一种快速、绿色的 HPLC-DAD 策略，辅助基于交替三线性分解（ATLD）和多变量曲线分辨率交替最小二乘法（MCR-ALS）的二阶多元校准方法，用于同时测定复杂面膜样品中的八种选定防腐剂。这种吸引人的策略被证明是一种有用的工具，可以在不完全分离的情况下消除复杂基质中的未知干扰，这得益于“二阶优势”，从而使面膜样品中八种分析物的测定在快速洗脱程序下缩短至 8.2 分钟。特别是，我们首次关注了 ATLD 方法在严重信号重叠和轻微时间偏移的 HPLC-DAD 数据建模中的适用性。加标回收率在 71.4%-124.6%范围内，RMSEP 和 REP 值范围分别为 0.07-2.4μg·mL 和 1.3-14.5%，表明 ATLD 方法能够提供令人满意的预测。解析的光谱轮廓和浓度值与 MCR-ALS 方法获得的值进行了比较，MCR-ALS 方法是一种处理严重信号重叠和轻微时间偏移的 HPLC-DAD 数据的出色工具。两种方法的定性和定量结果相互一致，证明了 ATLD 方法在处理严重信号重叠和轻微时间偏移的 HPLC-DAD 数据方面的能力。
