Discrimination of land-use types in a catchment by energy dispersive X-ray fluorescence and principal component analysis

Abstract In this work, a method was established for discriminating geographical origins of wheat flour based on energy dispersive X-ray fluorescence spectrometry (ED-XRF) and chemometrics. 68 wheat flour samples from three different origins were collected and analyzed using ED-XRF technology. Firstly, the principal component analysis method was applied to analyze the feasibility of discrimination and reduce data dimensionality. Then, Competitive Adaptive Reweighted Sampling (CARS) was used to further extract feature variables, and 12 energy variables (corresponding to mineral elements) were identified and selected to characterize the geographical attributes of wheat flour samples. Finally, a non-linear model was constructed using principal component analysis and quadratic discriminant analysis (QDA). The CARS-PCA-QDA model showed that the accuracy of five-fold cross-validation was 84.25%. The results showed that the established method was able to select important energy channel variables effectively and wheat flour could be classified based on geographical origins with chemometrics, which could provide a theoretical basis for unveiling the relationship between mineral element composition and wheat origin.

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Variation of elemental concentration in leather during post-tanning operation using energy dispersive X-ray fluorescence spectroscopy: principal component analysis approach

International Journal of Environmental & Analytical Chemistry ◽

10.1080/03067319.2020.1746292 ◽

2020 ◽

pp. 1-13

Author(s):

Kallen Mulilo Nalyanya ◽

Ronald K. Rop ◽

Arthur S. Onyuka ◽

Zephania Birech ◽

Justus J. Okonda

Keyword(s):

Principal Component Analysis ◽

Fluorescence Spectroscopy ◽

Elemental Concentration ◽

Principal Component ◽

Component Analysis ◽

Energy Dispersive ◽

Analysis Approach ◽

X Ray

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Principal component analysis-assisted energy dispersive X-ray fluorescence spectroscopy for non-invasive quality assurance characterization of complex matrix materials

X-Ray Spectrometry ◽

10.1002/xrs.2405 ◽

2012 ◽

Vol 41 (5) ◽

pp. 321-327 ◽

Cited By ~ 6

Author(s):

K. H. Angeyo ◽

S. Gari ◽

J. M. Mangala ◽

A. O. Mustapha

Keyword(s):

Principal Component Analysis ◽

Quality Assurance ◽

Fluorescence Spectroscopy ◽

Principal Component ◽

Component Analysis ◽

Energy Dispersive ◽

Complex Matrix ◽

X Ray ◽

Non Invasive

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Energy dispersive X-ray fluorescence spectrometry characterization of wall mortars with principal component analysis: Phasing and ex situ versus in situ sampling

Journal of Cultural Heritage ◽

10.1016/j.culher.2019.12.007 ◽

2020 ◽

Vol 43 ◽

pp. 90-97

Author(s):

Mary Kate Donais ◽

Mina Alrais ◽

Kaliopi Konomi ◽

David George ◽

William H. Ramundt ◽

...

Keyword(s):

Principal Component Analysis ◽

Principal Component ◽

Component Analysis ◽

Energy Dispersive ◽

Ex Situ ◽

Fluorescence Spectrometry ◽

X Ray

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An Estimation Framework for Economic Cost of Land Use Based on Artificial Neural Networks and Principal Component Analysis with R

2019 IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference (IMCEC) ◽

10.1109/imcec46724.2019.8984158 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ziyu Wan ◽

Mengmeng Gong ◽

Feng Jiang

Keyword(s):

Neural Networks ◽

Principal Component Analysis ◽

Land Use ◽

Artificial Neural Networks ◽

Principal Component ◽

Economic Cost ◽

Component Analysis ◽

Artificial Neural

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Principal Component Analysis of Multiwavelength Properties of Seyfert Galaxies

Symposium - International Astronomical Union ◽

10.1017/s0074180900176752 ◽

1994 ◽

Vol 159 ◽

pp. 502-502

Author(s):

Deborah Dultzin–Hacyan ◽

Carlos Ruano

Keyword(s):

Principal Component Analysis ◽

Statistical Analysis ◽

Principal Component ◽

Seyfert Galaxies ◽

Component Analysis ◽

X Ray ◽

Radio Data

A multidimensional statistical analysis of observed properties of Seyfert galaxies has been carried out using Principal Component Analysis (PCA) applied to X-ray, optical, near and far IR and radio data for all the Seyfert galaxies types 1 and 2 for the catalog by Lipovtsky et al. (1987).

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Multi-Variate Analysis of Trace Elements from XRF Studies for Classification According to Origin

Applied Spectroscopy ◽

10.1366/0003702924124691 ◽

1992 ◽

Vol 46 (5) ◽

pp. 843-847 ◽

Cited By ~ 11

Author(s):

C. T. Yap

Keyword(s):

Principal Component Analysis ◽

Trace Elements ◽

Geographical Origin ◽

Principal Component ◽

Energy Dispersive ◽

Fluorescence Technique ◽

X Ray ◽

Elegant Method ◽

Variate Analysis ◽

Made In

The concentrations of twelve trace elements (Mn, Fe, Co, Ni, Cu, Zn, As, Rb, Sr, Y, Zr, and Nb) in 143 pieces of Chinese porcelain made in Jingdezhen, China and elsewhere were obtained with the use of the energy-dispersive x-ray fluorescence technique. An elegant method of multi-variate analysis, known as principal component analysis, was successfully employed in fingerprinting the geographical origin of the porcelain samples.

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