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1. Chaos entropy index combined with linear discriminant analysis for identification of hogwash oil | |||
ZHENG Wenjun,CHEN Lin,WANG Xin,FANG Xiaowei,CHEN Huanwen | |||
Chemistry 04 June 2012 | |||
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Abstract:Based on surface desorption atmospheric pressure chemical ionization mass spectrometry (DAPCI-MS), a new method for identifying mixtures without pronounced characteristic markers was proposed and applied to hogwash oil's recognition. The chaos level of MS spectrograms for 33 oil samples was calculated using the new proposed concept: chaos entropy index (CEI) and the results were subjected to stepwise linear discriminant analysis (LDA). For the first time, total peaks' chaos level was treated as a criterion for identification of mixtures, which effectively avoided high misjudgment-rate problems commonly existed in traditional physical and chemical inspections. Discrimination model built by stepwise LDA based on the 5 selected parameters (101-200 m/z, 201-300 m/z, 301-400 m/z, 401-500 m/z, 501-600 m/z) achieved 100% classification in leave-1/10-out cross-validation. The oil study presented here demonstrated that CEI combined with LDA is an effective way for the identification of hogwash oils and this new method is of great significance for analyzing other complex mixtures without characteristic markers. | |||
TO cite this article:ZHENG Wenjun,CHEN Lin,WANG Xin, et al. Chaos entropy index combined with linear discriminant analysis for identification of hogwash oil[OL].[ 4 June 2012] http://en.paper.edu.cn/en_releasepaper/content/4481056 |
2. Simultaneous separation and validation of benzoic acid compounds by capillary electrophoresis | |||
Gao Suya ,Li Ting ,Li Hua | |||
Chemistry 19 March 2010 | |||
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Abstract:A simple and inexpensive capillary electrophoresis (CE) was applied to separate six benzoic acid compounds with similar structure. The investigation was carried out by capillary zone electrophoresis (CZE) and micellar electrokinetic capillary chromatography (MECC). To avoid a time-consuming and tedious procedure, orthogonal experimental design for separation experiments was applied to find the optimal conditions in terms of the resolution and analytical time. The best conditions for separation were obtained using a 20 mM borax and 30 mM sodium dodecyl sulfate (SDS) buffer (pH9.8) containing 2 mM β-CD and 4% methanol (volume fraction). Online UV detection was performed at 250 nm. A voltage of 16 kV was applied and the temperature was controlled at 21℃. Gravity injection was performed for 5 s. The method was validated for the quantification of benzoic acid and salicylic acid in Zuguangsan powder, a traditional Chinese patent medicine. The separation and determination were satisfactory, quick and reliable. | |||
TO cite this article:Gao Suya ,Li Ting ,Li Hua . Simultaneous separation and validation of benzoic acid compounds by capillary electrophoresis[OL].[19 March 2010] http://en.paper.edu.cn/en_releasepaper/content/40889 |
3. Study on the Determination of Three Components in Potato Using Near Infrared Spectroscopy Based on Partial least squares and Generalized Regression Neural Networks Model | |||
Qin Huajun,Liu Boping ,Cao Shuwen | |||
Chemistry 16 April 2009 | |||
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Abstract:Partial least squares (PLS) and generalized regression neural networks (GRNN) prediction model for fibre, starch and protein in potato had been established with good veracity. 12 peak value data from 3 principal components straight ahead compressed from original data by PLS were taken as inputs of GRNN while 3 predictive targets as outputs. 0.1 was chosen as smoothing factor for its good approximation and prediction with the lowest error compared with 0.2, 0.3, 0.4, and 0.5. Predictive correlation coefficient of three components by the model are 0.945, 0.992, and 0.938. The results show that PLS-GRNN using in NIRS is a rapid, effective means for measuring fibre, starch and protein in potato. The results are important in quality controlling and evaluating in fruit and vegetable industry, and can also be used in quantitative analysis of other samples. | |||
TO cite this article:Qin Huajun,Liu Boping ,Cao Shuwen. Study on the Determination of Three Components in Potato Using Near Infrared Spectroscopy Based on Partial least squares and Generalized Regression Neural Networks Model[OL].[16 April 2009] http://en.paper.edu.cn/en_releasepaper/content/31456 |
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