Feasibility for chemometric energy dispersive X-ray fluorescence and scattering (EDXRFS) spectroscopy method for rapid soil quality assessment

被引:28
作者
Kaniu, M. I. [1 ]
Angeyo, K. H. [2 ]
Mangala, M. J. [1 ]
Mwala, A. K. [3 ]
Bartilol, S. K. [1 ]
机构
[1] Univ Nairobi, Inst Nucl Sci & Technol, Nairobi, Kenya
[2] Univ Nairobi, Dept Phys, Appl Nucl & Radiat Phys Grp, Nairobi, Kenya
[3] Univ Nairobi, Dept Land Resource Management & Agr Technol, Nairobi, Kenya
关键词
CHEMICAL-COMPOUNDS; SPECTROMETRY; IDENTIFICATION; CLASSIFICATION;
D O I
10.1002/xrs.1363
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
Soil quality assessment (SQA) is important for modulating agricultural productivity and thus requires simple and rapid analysis of soil (macro & micro) nutrients (here called soil quality indicators - SQIs). We report proof of concept of a chemometrics-assisted energy dispersive X-ray fluorescence and scattering (EDXRFS) spectroscopy technique for direct rapid analysis of SQIs. The EDXRFS method exploits, in addition to fluorescence, the X-ray scatter peaks obtained non-invasively from soils to develop a calibration strategy for quantitative analysis of SQIs in model clay soils doped with micronutrients (Fe, Cu, and Zn) and macronutrients (NO3-, SO42-, and H2PO4-). The soil samples and certified reference materials IAEA Soil-7 and IAEA Soil-1 (used to build spectral library for soil classification) were irradiated at various live times (to simulate different signal-to-noise ratios of analyte signals and analysis speed) in a teflon holder and were analyzed using a Cd-109-excited XRF spectrometer. Principal components analysis was used for spectral data compression and pattern recognition (including for those SQI spectral signatures without any visibly discernible characteristic X-ray lines), whereas partial least squares regression and artificial neural networks were used to build a calibration and quantitative analysis strategy. The method furnishes soil micronutrient and macronutrient information simultaneously and rapidly (t = 200 s). To the best of the authors' knowledge, this is the first time that an XRF method has demonstrated spectroanalytical potential for quantitative macronutrients analysis in soils applicable to routine SQA. Coupling EDXRFS with multivariate chemometrics enables rapid and reliable assessment of chemical SQIs. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:432 / 440
页数:9
相关论文
共 36 条
[1]   Classification of some species, genera and families of plants by x-ray spectrometry [J].
Alexandre, Thais Levatti ;
Bueno, Maria Izabel M. S. .
X-RAY SPECTROMETRY, 2006, 35 (04) :257-260
[2]   Application of multivariate statistical methods to classify archaeological pottery from Tel-Alramad site, Syria, based on x-ray fluorescence analysis [J].
Bakraji, EH .
X-RAY SPECTROMETRY, 2006, 35 (03) :190-194
[3]   A gas proportional-scintillation counter for x-ray spectrometry in the 0.1-3 keV range [J].
Borges, FIGM ;
dos Santos, JMF ;
Dias, THVT ;
Santos, FP ;
Conde, CAN .
X-RAY SPECTROMETRY, 2004, 33 (02) :124-127
[4]  
Brereton R.G., 2003, DATA ANAL LAB CHEM P
[5]   Global soil characterization with VNIR diffuse reflectance spectroscopy [J].
Brown, David J. ;
Shepherd, Keith D. ;
Walsh, Markus G. ;
Mays, M. Dewayne ;
Reinsch, Thomas G. .
GEODERMA, 2006, 132 (3-4) :273-290
[6]  
Chonkar P. K., 2004, J INDIAN SOC SOIL SC, V52, P357
[7]   Combining XRF analysis and chemometric tools for a preliminary classification of argentine soils [J].
Custo, G ;
Boeykens, S ;
Cicerone, D ;
Vázquez, C .
X-RAY SPECTROMETRY, 2002, 31 (02) :132-135
[8]  
Demuth H., 2009, NEURAL NETWORK TOOLB
[9]   Honey characterization by total reflection x-ray fluorescence:: evaluation of environmental quality and risk for the human health [J].
Enrich, C. ;
Boeykens, S. ;
Caracciolo, N. ;
Custo, G. ;
Vazquez, C. .
X-RAY SPECTROMETRY, 2007, 36 (04) :215-220
[10]  
Facchin I, 1999, X-RAY SPECTROM, V28, P173, DOI 10.1002/(SICI)1097-4539(199905/06)28:3<173::AID-XRS333>3.0.CO