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FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS

The detection and mapping of plant-extractable potassium (Ka) using proximal soil sensing and data fusion (DF) techniques are essential to optimise K2O fertiliser application, improve crop yield, and minimise environmental and financial costs. This work evaluates the potential of combined use of p...

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Main Authors: Nawar, Said, Richard, Florence, Mohamed Kassim, Anuar, Tekin, Yucel, Mouazen, Abdul M.
Format: Article
Language:English
Published: Elsevier B.V. 2022
Online Access:http://eprints.utem.edu.my/id/eprint/27014/2/0145830052023.PDF
http://eprints.utem.edu.my/id/eprint/27014/
https://www.sciencedirect.com/science/article/pii/S0167198722001581
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133551864&doi=10.1016%2fj.still.2022.105472&partnerID=40&md5=8654606f9079498fb4a0ab46e79d150e
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spelling my.utem.eprints.270142023-12-14T12:19:33Z http://eprints.utem.edu.my/id/eprint/27014/ FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS Nawar, Said Richard, Florence Mohamed Kassim, Anuar Tekin, Yucel Mouazen, Abdul M. The detection and mapping of plant-extractable potassium (Ka) using proximal soil sensing and data fusion (DF) techniques are essential to optimise K2O fertiliser application, improve crop yield, and minimise environmental and financial costs. This work evaluates the potential of combined use of portable gamma ray and x-ray fluorescence spectroscopy for in field detection and mapping of Ka. After subjected to various pre-processing methods, spectral data were split into calibration (75%) and validation (25%) sets, and single sensor and DF models were developed using partial least squares regression (PLSR). Maps of Ka were used to present spatial variability of potassium across an 8.4 ha Voor de Hoeves target field, in Flanders, Belgium. Results showed that the gamma-ray PLSR model using wet soils had greater predictive ability with coefficient of determination (R2 )= 0.71, ratio of performance deviation (RPD) = 1.89, root mean square error (RMSE) = 31.7 mg kg-1, and ratio of performance to interquartile range (RPIQ) = 2.36 than the corresponding wet-XRF PLSR model (R2 = 0.61, RPD = 1.64, RMSE = 48.8 mg kg-1 and RPIQ = 1.84). The DF PLSR model on wet soils, resulted in a more accurate Ka predictive ability (R2 = 0.75, RPD = 2.03, RMSE = 31.3 mg kg-1 and RPIQ = 2.79), compared to the individual gamma ray or XRF sensors in wet soils. The best accuracy was obtained with XRF spectrometer using dry samples (R2 = 0.77, RPD = 2.14, RMSE = 26.5 mg kg-1 and RPIQ = 3.39). All Ka prediction maps showed spatial similarity to the corresponding measured maps in the target field. In conclusion, since DF increased the Ka prediction accuracy compared to the single sensor models using wet soils, it is recommended to be adopted in future studies as a potential solution for Ka measurement, mapping, and ultimately for site-specific K2O fertilisation management. The XRF analysis of dry spectra is recommended as the best method for accurate measurement of Ka. Elsevier B.V. 2022-09 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/27014/2/0145830052023.PDF Nawar, Said and Richard, Florence and Mohamed Kassim, Anuar and Tekin, Yucel and Mouazen, Abdul M. (2022) FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS. SOIL AND TILLAGE RESEARCH, 223. 01-16. ISSN 0167-1987 https://www.sciencedirect.com/science/article/pii/S0167198722001581 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133551864&doi=10.1016%2fj.still.2022.105472&partnerID=40&md5=8654606f9079498fb4a0ab46e79d150e
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description The detection and mapping of plant-extractable potassium (Ka) using proximal soil sensing and data fusion (DF) techniques are essential to optimise K2O fertiliser application, improve crop yield, and minimise environmental and financial costs. This work evaluates the potential of combined use of portable gamma ray and x-ray fluorescence spectroscopy for in field detection and mapping of Ka. After subjected to various pre-processing methods, spectral data were split into calibration (75%) and validation (25%) sets, and single sensor and DF models were developed using partial least squares regression (PLSR). Maps of Ka were used to present spatial variability of potassium across an 8.4 ha Voor de Hoeves target field, in Flanders, Belgium. Results showed that the gamma-ray PLSR model using wet soils had greater predictive ability with coefficient of determination (R2 )= 0.71, ratio of performance deviation (RPD) = 1.89, root mean square error (RMSE) = 31.7 mg kg-1, and ratio of performance to interquartile range (RPIQ) = 2.36 than the corresponding wet-XRF PLSR model (R2 = 0.61, RPD = 1.64, RMSE = 48.8 mg kg-1 and RPIQ = 1.84). The DF PLSR model on wet soils, resulted in a more accurate Ka predictive ability (R2 = 0.75, RPD = 2.03, RMSE = 31.3 mg kg-1 and RPIQ = 2.79), compared to the individual gamma ray or XRF sensors in wet soils. The best accuracy was obtained with XRF spectrometer using dry samples (R2 = 0.77, RPD = 2.14, RMSE = 26.5 mg kg-1 and RPIQ = 3.39). All Ka prediction maps showed spatial similarity to the corresponding measured maps in the target field. In conclusion, since DF increased the Ka prediction accuracy compared to the single sensor models using wet soils, it is recommended to be adopted in future studies as a potential solution for Ka measurement, mapping, and ultimately for site-specific K2O fertilisation management. The XRF analysis of dry spectra is recommended as the best method for accurate measurement of Ka.
format Article
author Nawar, Said
Richard, Florence
Mohamed Kassim, Anuar
Tekin, Yucel
Mouazen, Abdul M.
spellingShingle Nawar, Said
Richard, Florence
Mohamed Kassim, Anuar
Tekin, Yucel
Mouazen, Abdul M.
FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
author_facet Nawar, Said
Richard, Florence
Mohamed Kassim, Anuar
Tekin, Yucel
Mouazen, Abdul M.
author_sort Nawar, Said
title FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
title_short FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
title_full FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
title_fullStr FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
title_full_unstemmed FUSION OF GAMMA-RAYS AND PORTABLE X-RAY FLUORESCENCE SPECTRAL DATA TO MEASURE EXTRACTABLE POTASSIUM IN SOILS
title_sort fusion of gamma-rays and portable x-ray fluorescence spectral data to measure extractable potassium in soils
publisher Elsevier B.V.
publishDate 2022
url http://eprints.utem.edu.my/id/eprint/27014/2/0145830052023.PDF
http://eprints.utem.edu.my/id/eprint/27014/
https://www.sciencedirect.com/science/article/pii/S0167198722001581
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85133551864&doi=10.1016%2fj.still.2022.105472&partnerID=40&md5=8654606f9079498fb4a0ab46e79d150e
_version_ 1787140267462098944
score 13.211869

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