Assessment of Portable X-Ray Fluorescence for Six Elements in Albic Luvisol Soils: Comparison with Aqua-Regia-Extractable ICP-MS
No Thumbnail Available
Date
2026
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
Portable X-ray fluorescence (pXRF) is increasingly used as a rapid and cost-effective technique for soil analysis; however, its comparability with laboratory-based methods remains uncertain. This study aimed to evaluate the applicability of pXRF for determining the concentrations of six elements (K, Ca, Fe, Pb, Mn, and Zn) in agricultural soils classified as Albic Luvisols with a loamy sand texture. A total of 96 dried, ground soil samples from a long-term fertilization experiment were analyzed using pXRF and compared with inductively coupled plasma mass spectrometry (ICP-MS) following aqua regia digestion. Association and agreement between methods were assessed using correlation analysis, Deming regression, Lin’s concordance correlation coefficient (CCC), and Bland–Altman analysis. Substantial differences were observed between the two methods. The mean pXRF/ICP-MS ratios were approximately 25 for K, 4.0 for Ca, 1.43 for Fe, 1.41 for Mn, 1.21 for Pb, and 1.06 for Zn. The observed discrepancies are attributed to methodological factors. In particular, ICP-MS after aqua regia digestion represents pseudo-total concentrations, whereas pXRF measures total solid-phase content. Bland–Altman analysis revealed substantial systematic differences between methods. The largest biases were observed for K (−13,110 mg kg−1) and Ca (−2904 mg kg−1), indicating differences spanning several orders of magnitude. Smaller biases were found for Fe (−1179 mg kg−1), Mn (−50.0 mg kg−1), Pb (−2.37 mg kg−1), and Zn (−1.30 mg kg−1). The limits of agreement were particularly wide for K and Ca, whereas Zn exhibited the narrowest range. CCC values confirmed poor agreement for most elements (0.00049–0.36), with Zn showing the highest concordance (0.89). Overall, in the study condition, Zn demonstrated the best agreement between methods. Moreover, the results highlight that correlation-based metrics alone are insufficient for comparing methods and should be complemented by agreement-based approaches.
Description
Keywords
soil analysis, agreement analysis, Bland–Altman, concordance correlation coefficient (CCC), Deming regression
Citation
Agriculture 2026, 16(10), 1119