Development of a Chemometric Energy Dispersive X - Ray Fluorescence
and Scattering Spectroscopy Method for Rapid Soil Quality Assessment
By
Muchai Ian Kaniu
Abstract
Sustainable land use and agricultural productivity especially in precision farming depends on the
management of soil quality and thus necessitates soil quality assessment (SQA). This calls for
cheap, simple and rapid but accurate analysis of labile micro-and macro-nutrients (herein called
soil quality indicators, SQIs). Conventional analytical methods of SQA are tedious, destructive
and expensive. This study presents the results of the systematic experimental study on the
applicability of chemometric-assisted Energy Dispersive X-ray Fluorescence (EDXRF)
spectroscopy for rapid, direct and non-destructive characterization of soils for SQA. While
EDXRF is a standard analytical technique for elemental analysis, chemometrics is a relatively
new discipline for extracting latent relationships that are concerned with physical and chemical
phenomenon from complex multivariate data. Thus the combination of EDXRF and
chemometrics affords direct transformation of X-ray spectral data to analyte concentrations and
other material properties that are implicit to complex sample matrices such as soil and
exploratory analysis, which opens up for the investigation of factors affecting soil quality.
The capabilities of the EDXRF technique have been extended beyond the classical analysis
based on fluorescence peaks by further exploiting the scatter radiation profiles obtained noninvasively from soil samples to (i) correct for matrix effects observed in the spectrum
deconvolution of both micro- and macro-nutrient fluorescence (and scatter) radiation intensity
respectively to the concentration of selected SQIs, and (ii) to develop multivariate calibration
strategies for quantitative analysis of the macronutrients viz. Principal Component Analysis
(PCA), Partial Least Squares (PLS) regression and Artificial Neural Networks (ANNs). PCA
has been used for spectral data compression, modeling and pattern recognition for selected soils
used in this study, while PLS and ANNs have been used to design and test calibration strategies,
and quantitative analysis of selected SQIs (Fe, Cu, Zn, NO3-, SO42-, H2PO42-.) based on kaolin
as
a model soil with simulated composition of Fe, Cu, Zn, NO3 -, SO42-, H2PO42-. Certified
reference
materials (IAEA-Soil 7) and (IAEA-Soil 1) have been used to build spectral library for soil
classification and to perform method validation.
The developed method, hereby referred to as Energy Dispersive X-ray Fluorescence and
Scattering (EDXRFS) spectroscopy, was applied to verify the concentrations of Fe, Cu, Zn,
organic carbon (OC), N, Na, Mg, and P in soil samples from Kitale and Katumani in Kenya. The
two sites are located in high agriculturally potential areas. The macro- and micro-nutrients ‘bioavailable’ concentrations determined viz. laboratory methods of soil analyses at the National
Agricultural Research Laboratory (NARL) were considered as reference nutrient concentrations
with which the chemometric-EDXRFS generated estimates were compared.
The results of the analysis demonstrate the applicability of the method for rapid and
simultaneous SQA with good dynamic range (at trace (μg/g) levels for micronutrient (trace)
elements (Fe, Cu, and Zn) and high (%) levels for macronutrients (OC, N, Na, Mg, and P)). The
method can furnish micro- and macro-nutrient bio-available information simultaneously with no
sample pretreatments even at low signal-to-noise ratios and rapidly (sample irradiation time, 200
seconds), which is a significant reduction in routine analysis time from that for solid samples in
classical EDXRF (sample irradiation time, 2000 S). The coupling of EDXRF spectroscopy with
multivariate calibration (EDXRFS) thus allows for fast, direct and reliable predictions of
chemical SQIs in the soil models used in this study making the approach useful for routine
analysis for determination of the macro- and micro-nutrients.
The PLS and ANNs predicted nutrient concentrations compared to the NARL reference values
using a one-way ANOVA test showed no statistical difference apart from Na for PLS, at 95 %
confidence level. The performance of PLS technique was comparable with that of ANNs for the
determination of micronutrients. ANNs however performed better for the assessment of
macronutrients. Generally the results indicate that EDXRFS is a new method for complex matrix
analysis and quality assurance characterization. The method has proven to be relatively
insensitive to matrix effects, and has shown the potential to be developed for measurement of
other chemical SQIs such as pH, chemical oxygen demand (COD), bio-chemical oxygen demand
(BOD) and humus content. The ability to rapidly characterize large numbers of samples with this
technique has been demonstrated – it opens up new possibilities for SQA and generally
environmental quality assessment at an ecological scale.