A pragmatic workflow towards the generation of pXRF datasets for large-scale soil monitoring programs Article Swipe
YOU?
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· 2025
· Open Access
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· DOI: https://doi.org/10.1071/sr25028
· OA: W4411527678
Compared to conventional laboratory methods, portable X-ray fluorescence (pXRF) can rapidly estimate total elemental concentrations of soil samples. Developing an optimised and efficient data collection protocol is crucial for processing large sample numbers. Factors such as sample preparation methods, manufacturer calibration modes, and associated analysis times can influence pXRF performance. We evaluated the performance of different containers and detection modes (Soil vs Geochem) to determine the most time-efficient scanning protocol under standard instrument operation while maintaining acceptable accuracy for large-scale total elemental concentration analysis. Using 130 representative soil samples from the CSIRO National Soil Archive, results showed strong correlations for most elements (K, Ca, Ti, Fe, Cu, and Zr) across different containers. However, Mg, which has a low atomic number element, showed poor correlations (R2 = 0.05), likely due to the limits of detection (LOD) of the Geochem mode. Al and Si exhibited better R2 values but showed a low Lin’s Concordance Correlation Coefficient (LCCC) value of less than 0.1. Among different modes, elements including K, Ca, Ti, Fe, Cu and Zr maintained strong correlations (R2 > 0.65 and LCCC > 0.7). Scanning soil samples through plastic bags in Geochem mode is recommended due to its shorter measurement and sample preparation time and ability to detect lighter elements (Mg, Al, and Si). This optimised protocol will support national scale soil monitoring programs with large sample sizes (e.g. n > 3000 soil samples). For future work, elemental data acquired can support for example investigations of how soil mineralogy influences carbon storage capacity and provide insights to the biological-chemical stabilisation of soil organic carbon.
