•A new polymeric monolith was prepared by glycidyl methacrylate(GMA), tripropylene glycol diacrylate (TPGDA), and ethylene dimethacrylate (EDMA).•The column was used as the stationary phase of high performance liquid chromatography (HPLC).•Separate the mixture of small molecules compounds.•The column efficiency for anthracene was high to 18,867 theoretical plates per meter.Various novel porous organic-based monoliths with the mode of hydrophobicity were synthesized by in situ free-radical crosslinking copolymerization and optimized for the separations of small molecules and high-performance reversed-phase chromatography (RP-chromatography). These monoliths contained co-polymers based on glycidyl methacrylate (GMA)/ethylene glycol dimethacrylate (EDMA)/tripropylene glycol diacrylate (TPGDA) or EDMA/TPGDA. A mixture of cetanol, methanol and poly (ethylene glycol) (PEG) was used as the porogen, with the ratio of these solvents being varied along with the polymerization temperature to generate a library of monoliths. The conditions were optimized and the resulting poly (GMA-co-TPGDA-co-EDMA) monolith was investigated by infrared spectrometer (IR), field emission scanning electron microscope (FESEM), and mercury intrusion porosimetry (MIP), respectively. The column performance was assessed by the separation of a series of neutral solutes of benzene derivatives. The result demonstrated that the prepared monolith exhibited an RP-chromatographic behavior and relatively homogeneous structure, good permeability and separation performance. Moreover, the relative standard deviations (RSDs) of the retention factor values for benzene derivatives were less than 1.5% (n = 7, column-to-column). The approach used in this study was extended to the separation of anilines.

The objective of this study was to select the elements associated with the geographical origin of rice and evaluate the traceability efficiency of these elements by a chemometrics method. The contents of 15 elements (Mg, K, Ca, Na, Be, Mn, Ni, Cu, Cd, Fe, Al, Cr, Zn, Sb, and Pb) in rice samples and the contents of their exchangeable, available form, and “total” form in soil samples from four provinces of China were analyzed by inductively coupled plasma mass spectrometry and flame atomic absorption spectrometry. The results of variance analysis and correlation analysis demonstrated that there is a significant difference in the contents for 9 of 15 elements (Mg, K, Ca, Na, Be, Mn, Ni, Cu, and Cd) in the rice samples from 4 provinces, and the 9 elements in rice samples are closely connected with the mineral elements in soil. R-type hierarchical cluster analysis of 15 elements in rice indicated that Mg, Cu, K, Ni, Be, Mn, and Ca clustered together with similar behavior in rice and soil. The predictions of the geographic origin made by linear discriminant analysis (LDA) based on 9 elements gave an overall correct classification rate of 100.0% and a cross-validation rate of 93.8%, which was superior to the result for the total 15 elements. The correct rate of Q-type hierarchical cluster analysis (Q-type CA) based on 9 elements was higher than that based on 15 elements. The result of Q-type CA and LDA demonstrated that the 9 elements are good indicators to discriminate the geographical origin of rice.

The objective of this study was to select the elements associated with the geographical origin of rice and evaluate the traceability efficiency of these elements by a chemometrics method. The contents of 15 elements (Mg, K, Ca, Na, Be, Mn, Ni, Cu, Cd, Fe, Al, Cr, Zn, Sb, and Pb) in rice samples and the contents of their exchangeable, available form, and “total” form in soil samples from four provinces of China were analyzed by inductively coupled plasma mass spectrometry and flame atomic absorption spectrometry. The results of variance analysis and correlation analysis demonstrated that there is a significant difference in the contents for 9 of 15 elements (Mg, K, Ca, Na, Be, Mn, Ni, Cu, and Cd) in the rice samples from 4 provinces, and the 9 elements in rice samples are closely connected with the mineral elements in soil. R-type hierarchical cluster analysis of 15 elements in rice indicated that Mg, Cu, K, Ni, Be, Mn, and Ca clustered together with similar behavior in rice and soil. The predictions of the geographic origin made by linear discriminant analysis (LDA) based on 9 elements gave an overall correct classification rate of 100.0% and a cross-validation rate of 93.8%, which was superior to the result for the total 15 elements. The correct rate of Q-type hierarchical cluster analysis (Q-type CA) based on 9 elements was higher than that based on 15 elements. The result of Q-type CA and LDA demonstrated that the 9 elements are good indicators to discriminate the geographical origin of rice.