光谱学与光谱分析 |
|
|
|
|
|
Multivariate Calibration Combined with Mass Spectrometry for Rapid Analysis |
LI Qian-qian1,2, TIAN Kuang-da2, TANG Guo2, XIONG Yan-mei2, MIN Shun-geng2* |
1. College of Marine Science, China University of Geoscience, Beijing 100083, China 2. Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, China |
|
|
Abstract A mixture of four substances of benzaldehyde, iso-octane, butyl acetate, acetophenone were quantitatively analyzed by mass spectrometry combined with chemometrics.The mass chromatogram data of mixture were proceeded with two methods for quantitative analysis. One is feature selection-Multiple Linear Regression (MLR) and the other is full spectrum- Partial Least Squares (PLS). The results show that the RMSEP of benzaldehyde were 0.062 and 0.091 after selecting m/z spectrum and full spectrum respectively; RMSEP of isooctane were 0.048 and 0.057 after selecting spectrum and full spectrum respectively; which of butyl acetate were 0.021 and 0.020 and of acetophenone were 0.010 and 0.032. The feature selection results of the mixture were better than that of the full spectrum modeling results expect butyl acetate which got similar results by the two methods.
|
Received: 2014-11-27
Accepted: 2015-03-20
|
|
Corresponding Authors:
MIN Shun-geng
E-mail: minsg@263.net
|
|
[1] ZHUANG Xiao-li, XIANG Yu-hong, QIANG Hong, et al(庄小丽, 相玉红, 强 洪,等). Spectroscopy and Spectral Analysis(光谱学与光谱分析), 2010, 30(4): 933. [2] Pereira A F C, Pontes M J C, Neto F F G, et al. Food Research International, 2008, 41(4): 341. [3] DOU Ying, QIU Fang-ping, LIU Pei-yi, et al (窦 英, 邱芳萍, 刘培义,等). Chemical Journal of Chinese Universities(高等学校化学学报), 2004, 25(1): 53. [4] Grünhut M, Centurión M E, Fragoso W D, et al. Talanta, 2008, 75(4): 95. [5] LI Xiao-ru, LIANG Yi-zeng, LI Xiao-ning(李晓如, 梁逸曾, 李晓宁). Acta Pharmaceutica Sinica(药学学报), 2007, 42(2): 187. [6] Eide I, Neverdal G, Thorvaldsen B, et al. Environmental Science and Technology, 2001, 35(11): 2314. [7] Ledauphin J, Le Milbeau C, Barillier D, et al. Journal of Agricultural and Food Chemistry, 2010, 58(13): 7782. [8] Huang L F, Wu M J, Zhong K J, et al. Analyticachimicaacta, 2007, 588(2): 216. [9] Jalali-Heravi M, Vosough M. Journal of Chromatography A, 2004, 1024(1): 165. |
[1] |
LI Yu1, ZHANG Ke-can1, PENG Li-juan2*, ZHU Zheng-liang1, HE Liang1*. Simultaneous Detection of Glucose and Xylose in Tobacco by Using Partial Least Squares Assisted UV-Vis Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 103-110. |
[2] |
DONG Jian-jiang1, TIAN Ye1, ZHANG Jian-xing2, LUAN Zhen-dong2*, DU Zeng-feng2*. Research on the Classification Method of Benthic Fauna Based on
Hyperspectral Data and Random Forest Algorithm[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3015-3022. |
[3] |
LI Zhong-bing1, 2, JIANG Chuan-dong2, LIANG Hai-bo3, DUAN Hong-ming2, PANG Wei2. Rough and Fine Selection Strategy Binary Gray Wolf Optimization
Algorithm for Infrared Spectral Feature Selection[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3067-3074. |
[4] |
ZHU Yu-qi1, 2, ZHANG Xin2, DU Pan-pan2, LIU Shu1, ZHANG Gui-xin1, 2, GUAN Song-lei2*, ZHENG Zhong1*. Infrared Spectroscopy and X-Ray Spectroscopy Combined With
Inductively Coupled Plasma Mass Spectrometry for Quality
Control of Mongolian Medicine Yu Grain Soil[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3163-3169. |
[5] |
JIA Hao1, 3, 4, ZHANG Wei-fang1, 3, LEI Jing-wei1, 3*, LI Ying-ying1, 3, YANG Chun-jing2, 3*, XIE Cai-xia1, 3, GONG Hai-yan1, 3, DING Xin-yu1, YAO Tian-yi1. Study on Infrared Fingerprint of the Classical Famous
Prescription Yiguanjian[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3202-3210. |
[6] |
JIN Xu-guang1, 2, WANG Jin-zhuan1, 2*, LI Bei1, 2, QUE Wan-ting1, 2, WANG Liang1, 2, ZHANG Fan1, 2, ZHANG Chi1, ZHOU Jun-gui1, FU Rong-jin1. Quantification of Au in Gold Ornaments Obtained by Different Electroformed Process[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(09): 2755-2760. |
[7] |
ZHANG Xia1, WANG Wei-hao1, 2*, SUN Wei-chao1, DING Song-tao1, 2, WANG Yi-bo1, 2. Soil Zn Content Inversion by Hyperspectral Remote Sensing Data and Considering Soil Types[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2019-2026. |
[8] |
ZHANG Hao-yu1, FU Biao1*, WANG Jiao1, MA Xiao-ling2, LUO Guang-qian1, YAO Hong1. Determination of Trace Rare Earth Elements in Coal Ash by Inductively Coupled Plasma Tandem Mass Spectrometry[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2074-2081. |
[9] |
LUO Dong-jie, WANG Meng, ZHANG Xiao-shuan, XIAO Xin-qing*. Vis/NIR Based Spectral Sensing for SSC of Table Grapes[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2146-2152. |
[10] |
WANG Bin1, 2, ZHENG Shao-feng2, GAN Jiu-lin1, LIU Shu3, LI Wei-cai2, YANG Zhong-min1, SONG Wu-yuan4*. Plastic Reference Material (PRM) Combined With Partial Least Square (PLS) in Laser-Induced Breakdown Spectroscopy (LIBS) in the Field of Quantitative Elemental Analysis[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2124-2131. |
[11] |
CHENG Xiao-xiang1, WU Na2, LIU Wei2*, WANG Ke-qing2, LI Chen-yuan1, CHEN Kun-long1, LI Yan-xiang1*. Research on Quantitative Model of Corrosion Products of Iron Artefacts Based on Raman Spectroscopic Imaging[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(07): 2166-2173. |
[12] |
ZHANG Mei-zhi1, ZHANG Ning1, 2, QIAO Cong1, XU Huang-rong2, GAO Bo2, MENG Qing-yang2, YU Wei-xing2*. High-Efficient and Accurate Testing of Egg Freshness Based on
IPLS-XGBoost Algorithm and VIS-NIR Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1711-1718. |
[13] |
ZHOU Qi1, 2, WANG Jian-jun1, 2*, HUO Zhong-yang1, 2*, LIU Chang1, 2, WANG Wei-ling1, 2, DING Lin3. UAV Multi-Spectral Remote Sensing Estimation of Wheat Canopy SPAD Value in Different Growth Periods[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(06): 1912-1920. |
[14] |
LIN Jing-tao, XIN Chen-xing, LI Yan*. Spectral Characteristics of “Trapiche-Like Sapphire” From ChangLe, Shandong Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1199-1204. |
[15] |
LI Quan-lun1, CHEN Zheng-guang1*, JIAO Feng2. Prediction of Oil Content in Oil Shale by Near-Infrared Spectroscopy Based on Stacking Ensemble Learning[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(04): 1030-1036. |
|
|
|
|