Development of a Chemometric Energy Dispersive X-Ray Fluorescence and Scattering Spectroscopy Method for Rapid Soil Quality Assessment

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 non-

 

invasively 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 ‘bio-

 

available’ 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.

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