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June 15, 2026Scientific ReportsOpen Access

Evaluating pXRF accuracy for predicting soil fertility: effects of moisture and soil properties

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Authors

JAJoão Arthur AntonângeloWashington State UniversitySCSomsubhra ChakrabortyIndian Institute of Technology KharagpurDMDeepanjan MridhaJadavpur University

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Overview

Randomized trial evaluates pXRF accuracy for predicting soil nutrients in varying moisture levels, highlighting its improved performance with soil properties.

Key Points

  • This study aims to evaluate how different moisture conditions affect the accuracy of pXRF in predicting soil nutrients and the role of key soil properties in enhancing this accuracy.
  • Utilized portable X-ray fluorescence (pXRF) to assess soil nutrients under varying moisture conditions: dry soil, field moisture, saturated paste, and after removing excess water.
  • Employed stepwise multiple linear regression (SMLR) to model macronutrients and micronutrients from pXRF data.
  • Assessed the impact of incorporating soil pH and organic matter (OM) on prediction accuracy.
  • pXRF predictions for macronutrients were strong, with R² values of 0.54-0.74 for K, 0.49-0.59 for Ca, and 0.60-0.69 for Mg (all p<.0001).
  • Incorporating soil pH and organic matter improved model performance, increasing R² values by 1.1 to 6.1-fold compared to pXRF data alone.
  • Predictions for Cu and Zn remained low to moderate, indicating areas for further improvement.

Cite This Study

Antonângelo et al. (2026) studied this question.

synapsesocial.com/papers/6a2f966ca1cfeec490827cc7https://doi.org/10.1038/s41598-026-58282-8
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  5. 5Effects of moisture content on in situ analysis of plant samples using portable XRF2026