Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration

A portable X-ray fluorescence probe (pXRF) is a tool that is used to measure many elements quickly and efficiently in various samples, without any pretreatment. However, each type of sample generally requires different calibrations to be accurate. To overcome this, our work evaluated the efficacy of...

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Autores principales:	João Antonangelo, Hailin Zhang
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	portable XRF net intensity calibration plant nutrients concentration model prediction Agriculture S
Acceso en línea:	https://doaj.org/article/fab00fb2efe947de8f422668678b8e36
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spelling	oai:doaj.org-article:fab00fb2efe947de8f422668678b8e362021-11-25T16:03:19ZSoil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration10.3390/agronomy111121182073-4395https://doaj.org/article/fab00fb2efe947de8f422668678b8e362021-10-01T00:00:00Zhttps://www.mdpi.com/2073-4395/11/11/2118https://doaj.org/toc/2073-4395A portable X-ray fluorescence probe (pXRF) is a tool that is used to measure many elements quickly and efficiently in various samples, without any pretreatment. However, each type of sample generally requires different calibrations to be accurate. To overcome this, our work evaluated the efficacy of determining several elements in forage plant samples using the ‘Soil Nutrient and Metal’ calibration in a commercially available pXRF probe, envisioning that a single calibration can be used to measure samples of different matrixes. For this, the net intensity of the pXRF probe was determined in place of the concentration values that are obtained directly from measurements. Elemental concentrations (P, K, Ca, Mg, S, Cu, Fe, Zn, and Mn) from forage plant samples, collected across Oklahoma, US, were assessed in a representative number of ‘modeling’ and ‘validation’ (independent dataset) samples. Linear regression (LR) associated with the d-index, polynomial regression (PR), and power regression (PwR) were tested for predictions, producing many statistical parameters associated with the models that were used for comparison goals. The pXRF elemental data provided highly reliable predictions of K, S, Zn, and Mn regardless of the regression model. Although all models can be reliable in prediction of Ca and Fe concentrations, the PwR provided better root mean square error (RMSE) values. The predictions of Mg concentrations were less reliable, although highly significant; however, the P and Cu predictions were not acceptable. Our work successfully showed that, once established, a single calibration curve that covers a wide range of concentrations of several elements in soils and plant tissues enables both soil and plant samples to be analyzed. This suggests that manufacturers can develop a new calibration model for a commercially available pXRF probe that covers a wide variety of heterogeneous samples.João AntonangeloHailin ZhangMDPI AGarticleportable XRFnet intensitycalibrationplant nutrients concentrationmodel predictionAgricultureSENAgronomy, Vol 11, Iss 2118, p 2118 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	portable XRF net intensity calibration plant nutrients concentration model prediction Agriculture S
spellingShingle	portable XRF net intensity calibration plant nutrients concentration model prediction Agriculture S João Antonangelo Hailin Zhang Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
description	A portable X-ray fluorescence probe (pXRF) is a tool that is used to measure many elements quickly and efficiently in various samples, without any pretreatment. However, each type of sample generally requires different calibrations to be accurate. To overcome this, our work evaluated the efficacy of determining several elements in forage plant samples using the ‘Soil Nutrient and Metal’ calibration in a commercially available pXRF probe, envisioning that a single calibration can be used to measure samples of different matrixes. For this, the net intensity of the pXRF probe was determined in place of the concentration values that are obtained directly from measurements. Elemental concentrations (P, K, Ca, Mg, S, Cu, Fe, Zn, and Mn) from forage plant samples, collected across Oklahoma, US, were assessed in a representative number of ‘modeling’ and ‘validation’ (independent dataset) samples. Linear regression (LR) associated with the d-index, polynomial regression (PR), and power regression (PwR) were tested for predictions, producing many statistical parameters associated with the models that were used for comparison goals. The pXRF elemental data provided highly reliable predictions of K, S, Zn, and Mn regardless of the regression model. Although all models can be reliable in prediction of Ca and Fe concentrations, the PwR provided better root mean square error (RMSE) values. The predictions of Mg concentrations were less reliable, although highly significant; however, the P and Cu predictions were not acceptable. Our work successfully showed that, once established, a single calibration curve that covers a wide range of concentrations of several elements in soils and plant tissues enables both soil and plant samples to be analyzed. This suggests that manufacturers can develop a new calibration model for a commercially available pXRF probe that covers a wide variety of heterogeneous samples.
format	article
author	João Antonangelo Hailin Zhang
author_facet	João Antonangelo Hailin Zhang
author_sort	João Antonangelo
title	Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
title_short	Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
title_full	Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
title_fullStr	Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
title_full_unstemmed	Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration
title_sort	soil and plant nutrient analysis with a portable xrf probe using a single calibration
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/fab00fb2efe947de8f422668678b8e36
work_keys_str_mv	AT joaoantonangelo soilandplantnutrientanalysiswithaportablexrfprobeusingasinglecalibration AT hailinzhang soilandplantnutrientanalysiswithaportablexrfprobeusingasinglecalibration
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Soil and Plant Nutrient Analysis with a Portable XRF Probe Using a Single Calibration

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