Principal components analysis as a tool for identity control using near-infrared spectroscopy

2003 ◽  
Vol 661-662 ◽  
pp. 319-323 ◽  
Author(s):  
Roman Bossart ◽  
Holger Keller ◽  
Hanspeter Kellerhals ◽  
Joachim Oelichmann
Keyword(s):  
Infrared Spectroscopy ◽  
Principal Components Analysis ◽  
Near Infrared Spectroscopy ◽  
Principal Components ◽  
Near Infrared ◽  
Identity Control ◽  
Components Analysis

scholarly journals Near Infrared Spectroscopy and Principal Components Analysis for Investigation of Soils Submitted to Different Land Uses in the Brazilian Eastern Amazon

2020 ◽  
Vol 12 (1) ◽  
pp. 51-62
Author(s):  
José Cícero Alves Silva ◽  
Diana Signor ◽  
Andréa Monteiro Santana Silva Brito ◽  
Carlos Eduardo Pellegrino Cerri ◽  
Plínio Barbosa de Camargo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Principal Components Analysis ◽  
Near Infrared Spectroscopy ◽  
Principal Components ◽  
Near Infrared ◽  
Land Uses ◽  
Components Analysis

Identification of Liquor Brands Based on near Infrared Spectroscopy

2013 ◽  
Vol 834-836 ◽  
pp. 935-938
Author(s):  
Lian Shun Zhang ◽  
Chao Guo ◽  
Bao Quan Wang
Keyword(s):  
Principal Component Analysis ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Principal Components ◽  
Near Infrared ◽  
Scatter Correction ◽  
Principal Component ◽  
Component Analysis ◽  
Correction Method ◽  
Variance Contribution

In this paper, the liquor brands were identified based on the near infrared spectroscopy method and the principal component analysis. 60 samples of 6 different brands liquor were measured by the spectrometer of USB4000. Then, in order to eliminate the noise caused by the external factors, the smoothing method and the multiplicative scatter correction method were used. After the preprocessing, we got the revised spectra of the 60 samples. The difference of the spectrum shape of different brands is not much enough to classify them. So the principal component analysis was applied for further analysis. The results showed that the first two principal components variance contribution rate had reached 99.06%, which can effectively represent the information of the spectrums after preprocessing. From the scatter plot of the two principal components, the 6 different brands of liquor were identified more accurate and easier than the spectra curves.

Components Analysis of Biochar Based on Near Infrared Spectroscopy Technology

2018 ◽  
Vol 46 (4) ◽  
pp. 609-615 ◽  
Author(s):  
Yue XIE ◽  
Fei-Yue LI ◽  
Xing-Jun FAN ◽  
Shui-Jin HU ◽  
Xin XIAO ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Components Analysis
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