Assessment of portable X-ray fluorescence (pXRF) for plant-available nutrient prediction in biochar-amended soils
Author:
Funder
College of Agricultural, Human and Natural Resource Sciences, Washington State University
Oklahoma Agricultural Experiment Station
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-71381-8.pdf
Reference40 articles.
1. Faria, Á. J. et al. Rapid elemental prediction of heterogeneous tropical soils from PXRF DATA: A comparison of models via linear regressions and machine learning algorithms. Soil Res. 61, 598–615 (2023).
2. Silva, S. H. et al. PXRF in tropical soils: Methodology, applications, achievements and challenges. Adv. Agron. https://doi.org/10.1016/bs.agron.2020.12.001 (2021).
3. Pelegrino, M. H. et al. Prediction of soil nutrient content via pXRF spectrometry and its spatial variation in a highly variable tropical area. Precision Agricult. 23, 18–34 (2021).
4. Rawal, A. et al. Determination of base saturation percentage in agricultural soils via portable X-ray fluorescence spectrometer. Geoderma 338, 375–382 (2019).
5. Benedet, L. et al. Rapid soil fertility prediction using X-ray fluorescence data and machine learning algorithms. CATENA 197, 105003 (2021).
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