Li Sha Sha, Lu Shao Hua, Zhai Hong Lin, Yin Bo, Mi Jia Ying
College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, 730000 People's Republic of China.
J Food Sci Technol. 2021 Jun;58(6):2170-2177. doi: 10.1007/s13197-020-04727-5. Epub 2020 Aug 18.
The determination of curcuminoids in mixtures is more difficult due to their similar chemical structures as well as serious interferences, thus the complex pretreatments of samples and the optimization of experimental conditions are often required. Here, owing to the mathematical separation of chemical signals by Tchebichef image moments, a simple and effective approach to the simultaneous quantitative analysis was proposed, and applied to the determination of the three curcuminoids in turmeric and curry based on their raw fluorescence 3D spectra. For the established linear models, the leave-one-out correlation coefficients ( ) were more than 0.9816 within the linear ranges, and the predictive correlation coefficients ( ) for the external independent samples were more than 0.9897. The intra- and inter-day precision (less than 6.82%, ), average spiked recovery (89.9% ~ 100.8%), LOD (less than 0.07 μg/mL) and LOQ (less than 0.23 μg/mL) suggest that the proposed approach is accurate and reliable. Compared with -PLS and MCR-ALS methods, our method can obtain more satisfactory results. This study provides a convenient pathway for the rapid analysis of multi-target components with similar chemical structures in mixture of different substrates.
由于姜黄素类化合物化学结构相似且存在严重干扰，混合物中姜黄素类化合物的测定更为困难，因此通常需要对样品进行复杂的预处理并优化实验条件。在此，基于Tchebichef图像矩对化学信号进行数学分离，提出了一种简单有效的同时定量分析方法，并基于姜黄和咖喱中三种姜黄素类化合物的原始荧光三维光谱对其进行测定。对于所建立的线性模型，在各线性范围内，留一法相关系数（ ）均大于0.9816，外部独立样品的预测相关系数（ ）均大于0.9897。日内和日间精密度（小于6.82%， ）、平均加标回收率（89.9% ~ 100.8%）、检出限（小于0.07 μg/mL）和定量限（小于0.23 μg/mL）表明该方法准确可靠。与 -PLS和MCR-ALS方法相比，我们的方法能获得更令人满意的结果。本研究为快速分析不同基质混合物中化学结构相似的多目标成分提供了一条便捷途径。
