Quick analysis of organic matter in soil by energy-dispersive X-ray fluorescence and multivariate analysis

Highlights

• OM and TOC concentrations in agricultural soil were determined.

• Samples were differentiated by plateaus and basins using PCA.

• EDXRF combined with PLSR is a straightforward methodology for OM quantification.

• The novelty is the direct quantification of OM and TOC from soil EDXRF spectral data.

Abstract

The rapid, simple and accurate determination of soil quality indicators is fundamental for improvements in precision agriculture and consequently in production efficiency. The objectives of this study were to determine the organic matter (OM) and total organic carbon (TOC) concentrations in agricultural soil and to discriminate soil provenance by energy-dispersive X-ray fluorescence (EDXRF) combined with principal component analysis and partial least square regression. The conventional methods used for the determination of OM and TOC concentrations are the gravimetric and Walkley–Black methods, respectively. Figures of merit such as sensitivity, detection and quantification limits, accuracy and precision were evaluated. Samples were differentiated by their provenance, and the quality of the prediction model shows that EDXRF combined with multivariate analysis is a promising methodology to fulfil the lack of rapid and accurate analytical methods for the assessment of OM and TOC concentrations in agricultural soils.

Introduction

Organic matter (OM) and total organic carbon (TOC), although present in the range of 1–6% in agricultural soil, play an important role in the fertility of the soil because of their contribution to increasing the cation exchange capacity (CEC) and water retention and decreasing compaction and leaching process, among other properties (Magdoff, 1993).

The conventional analytical methods for the determination of OM and TOC concentrations are generally time consuming and cost prohibitive. The most widely used method in several countries is the Walkley–Black (WB) method, which is a wet method that does not follow the green chemistry concept because of the need for concentrated Cr₂O₇^2- and H₂SO₄ use, which could consequently result in the generation of toxic residues (WHO, 1988).

The demand for good quality, inexpensive and high-resolution soil information has been growing in areas such as precision agriculture and land planning. Moreover, the several disadvantages of the conventional techniques lead to the need of developing and validating time- and cost-effective quantitative methods in soil analysis (Zhu et al., 2011, Rossel et al., 2009).

The application of spectroscopic techniques including visible near infrared (VNIR) (Ge et al., 2011, Kookana et al., 2008, Singh et al., 2012, Li et al., 2015), Raman spectroscopy (Luna et al., 2014) and X-ray fluorescence (XRF) (Weindorf et al., 2012) is currently being explored by several research groups, but it remains to be validated before being used in laboratory soil analyses worldwide.

This study proposes the use of energy-dispersive X-ray fluorescence (EDXRF) for soil quality assessment. Recent studies on the non-conventional applications of this technique have come up with good results, for instance, in the texture (Zhu et al., 2011), nutrients (Kaniu et al., 2012), pH (Sharma et al., 2014) and TOC (Sharma et al., 2015, Melquiades et al., 2014).

EDXRF analysis is commonly applied for the simultaneous determination of elements from Na to U. The advantages of EDXRF in soil analysis are that the technique facilitates non-destructive and non-invasive soil analysis of a wide range of elements at various concentrations (from ppm to % level) in a short period of time (30–300 s) with acceptable quantitative results; depending on the chemical composition of the metals, the steps in sample preparation, when necessary, can be minimised. In addition, there is a possibility of in situ analysis using a portable equipment (Kalnicky and Singhvi, 2001; Melquiades et al., 2004). In general, in soil samples, the percentage of light elements (Z < 11, for example H, C and O) is high. As a result, X-ray scattering is increased, which is revealed in the spectrum background and in the intensities of Rayleigh and Compton peaks (Bortoleto et al., 2005). The scattering region of the EDXRF spectra carries implicit information about the samples, which can be exploited using appropriate data treatment. For example, the main compounds of OM are C, N and O whose characteristic X-ray photon energies are low, and their peaks do not appear in the EDXRF spectra, but this information is included in the X-ray scattering peaks and could be evaluated by appropriate multivariate analysis methods.

By combining EDXRF data with multivariate analysis, qualitative and quantitative conclusive results about implicit sample information were obtained by pattern recognition or multivariate regression methods. Results published in the literature for application in different sets of data is vast.

The objectives of this study were to determine the OM and TOC concentrations in agricultural soil and to discriminate the soil depending on its provenance using EDXRF spectroscopy and multivariate analysis. In particular, (a) the principal component analysis (PCA) was used to differentiate the soil depending on its provenance and (b) the partial least square regression (PLSR) was used to quantify OM and TOC based on the results from the WB and gravimetric methods.