Determination of Spatial Distribution Patterns of Clay and Plant Available Potassium Contents in Surface Soils at the Farm Scale using High Resolution Gamma Ray Spectrometry |
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Authors: | Gabriella Pracilio Matthew L Adams Keith R J Smettem Richard J Harper |
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Institution: | (1) School of Earth Geographical Sciences, The University of Western Australia, 35 Stirling Hwy, 6009 Crawley, WA, Australia;(2) Cooperative Research Centre for Plant Based Management of Dryland Salinity, The University of Western Australia, 6009 Crawley, WA, Australia;(3) Department of Land Information, Satellite Remote Sensing Services, 6014 Floreat, WA, Australia;(4) Centre for Water Research, The University of Western Australia, 6009 Crawley, WA, Australia;(5) Forest Products Commission, 6103 Rivervale, WA, Australia |
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Abstract: | Variation in dryland crop yield is often related to underlying soil properties such as water availability and soil fertility.
There are often significant difficulties in adequately defining the spatial distribution of such properties at the farm scale.
Gamma ray spectrometry (radiometrics) is a relatively new soil sensing technique that can potentially address this by improving
the mapping of soil texture and plant available potassium (bic-K). Three sites North Nolba, South Nolba and Summerset were
investigated using exploratory linear correlation analysis. Mapping analysis was focused on the Summerset site. In contrast
to the two Nolba sites, the soils from Summerset had sufficient soil texture range and parent material conditions that allowed
for calibrations to be developed. Soil properties were mapped at Summerset using multivariate linear regression and tree-based
models with radiometric, topographic and location data as the inputs. A multivariate linear regression analysis using radiometric
data was associated with greater than 70% of the variance in bic-K and soil texture at Summerset. Field checked maps indicated
that up to 66% and 60% of the variation in clay and bic-K contents respectively, could be predicted. The overall lowest map
errors in root mean square error (RMSE) were 2.4 dag/kg clay and 103 mg/kg bic-K contents. This study concludes that for a
site with weathered soils of sufficient soil texture range, radiometrics can reliably predict clay and plant available potassium
contents. Radiometrics has practical farm scale applications at a precision that is useful for understanding potential yield
variation across a farm. |
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Keywords: | radiometrics regression tree soil fertility soil map soil survey soil texture |
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