LAUSR

For the more complex samples, the chemical higher-order data can collect their various information, which becomes the necessary foundation of accurate analysis. In this paper, Tchebichef cubic moment (TCM) was developed to the analysis of chemical third-order data for the first time. Then the proposed TCM approach was applied to the fluorescence excitation-emission-time data for the analysis of adrenaline and noradrenaline in urinary samples (Data I) and the data fusion of EEM, NMR and LC-MS spectra for the determination of the five target components (Data II), respectively. For the Data I, the all cross-validation correlation coefficients ( ) of the obtained linear models on calibration set were more than 0.9937 and the prediction root-mean-square errors (RMSEp) of external independent test samples were less than 0.0250 μM. For the Data II, all were higher than 0.9846 and RMSEp were less than 0.2267 μM. Compared with several conventional methods, the proposed method was more convenient and accurate. This study provides another effective approach to the analysis of complex samples based on their chemical third-order data.