Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods

Fine-scale spatial information on soil properties is needed to successfully implement precision agriculture. Proximal gamma-ray spectroscopy has recently emerged as a promising tool to collect fine-scale soil information. The objective of this study was to evaluate a proximal gamma-ray spectrometer...

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Main Authors: Hafiz Sultan Mahmood, Willem B. Hoogmoed, Eldert J. van Henten
Format: Article
Language:English
Published: MDPI AG 2013-11-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/13/12/16263
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spelling doaj-c4e3b2e6939947198bc645ef9bd0f7c22020-11-25T00:51:36ZengMDPI AGSensors1424-82202013-11-011312162631628010.3390/s131216263s131216263Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis MethodsHafiz Sultan Mahmood0Willem B. Hoogmoed1Eldert J. van Henten2Farm Technology Group, Wageningen University, PO Box 317, 6700 AH Wageningen, The NetherlandsFarm Technology Group, Wageningen University, PO Box 317, 6700 AH Wageningen, The NetherlandsFarm Technology Group, Wageningen University, PO Box 317, 6700 AH Wageningen, The NetherlandsFine-scale spatial information on soil properties is needed to successfully implement precision agriculture. Proximal gamma-ray spectroscopy has recently emerged as a promising tool to collect fine-scale soil information. The objective of this study was to evaluate a proximal gamma-ray spectrometer to predict several soil properties using energy-windows and full-spectrum analysis methods in two differently managed sandy loam fields: conventional and organic. In the conventional field, both methods predicted clay, pH and total nitrogen with a good accuracy (R2 ≥ 0.56) in the top 0–15 cm soil depth, whereas in the organic field, only clay content was predicted with such accuracy. The highest prediction accuracy was found for total nitrogen (R2 = 0.75) in the conventional field in the energy-windows method. Predictions were better in the top 0–15 cm soil depths than in the 15–30 cm soil depths for individual and combined fields. This implies that gamma-ray spectroscopy can generally benefit soil characterisation for annual crops where the condition of the seedbed is important. Small differences in soil structure (conventional vs. organic) cannot be determined. As for the methodology, we conclude that the energy-windows method can establish relations between radionuclide data and soil properties as accurate as the full-spectrum analysis method.http://www.mdpi.com/1424-8220/13/12/16263proximal soil sensinggamma-ray spectroscopyenergy windowsfull-spectrum analysisprediction of soil properties
collection DOAJ
language English
format Article
sources DOAJ
author Hafiz Sultan Mahmood
Willem B. Hoogmoed
Eldert J. van Henten
spellingShingle Hafiz Sultan Mahmood
Willem B. Hoogmoed
Eldert J. van Henten
Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
Sensors
proximal soil sensing
gamma-ray spectroscopy
energy windows
full-spectrum analysis
prediction of soil properties
author_facet Hafiz Sultan Mahmood
Willem B. Hoogmoed
Eldert J. van Henten
author_sort Hafiz Sultan Mahmood
title Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
title_short Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
title_full Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
title_fullStr Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
title_full_unstemmed Proximal Gamma-Ray Spectroscopy to Predict Soil Properties Using Windows and Full-Spectrum Analysis Methods
title_sort proximal gamma-ray spectroscopy to predict soil properties using windows and full-spectrum analysis methods
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2013-11-01
description Fine-scale spatial information on soil properties is needed to successfully implement precision agriculture. Proximal gamma-ray spectroscopy has recently emerged as a promising tool to collect fine-scale soil information. The objective of this study was to evaluate a proximal gamma-ray spectrometer to predict several soil properties using energy-windows and full-spectrum analysis methods in two differently managed sandy loam fields: conventional and organic. In the conventional field, both methods predicted clay, pH and total nitrogen with a good accuracy (R2 ≥ 0.56) in the top 0–15 cm soil depth, whereas in the organic field, only clay content was predicted with such accuracy. The highest prediction accuracy was found for total nitrogen (R2 = 0.75) in the conventional field in the energy-windows method. Predictions were better in the top 0–15 cm soil depths than in the 15–30 cm soil depths for individual and combined fields. This implies that gamma-ray spectroscopy can generally benefit soil characterisation for annual crops where the condition of the seedbed is important. Small differences in soil structure (conventional vs. organic) cannot be determined. As for the methodology, we conclude that the energy-windows method can establish relations between radionuclide data and soil properties as accurate as the full-spectrum analysis method.
topic proximal soil sensing
gamma-ray spectroscopy
energy windows
full-spectrum analysis
prediction of soil properties
url http://www.mdpi.com/1424-8220/13/12/16263
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