Using genetic programming to transform from Australian to USDA/FAO soil particle-size classification system
José Padarian A B , Budiman Minasny A and Alex McBratney AA Faculty of Agriculture and Environment, The University of Sydney, Biomedical Building, 1 Central Avenue, Australian Technology Park, NSW 2015, Australia.
B Corresponding author. Email: jose.padarian@sydney.edu.au
Soil Research 50(6) 443-446 https://doi.org/10.1071/SR12139
Submitted: 24 May 2012 Accepted: 3 August 2012 Published: 18 September 2012
Abstract
The difference between the International (adopted by Australia) and the USDA/FAO particle-size classification systems is the limit between silt and sand fractions (20 μm for the International and 50 µm for the USDA/FAO). In order to work with pedotransfer functions generated under the USDA/FAO system with Australian soil survey data, a conversion should be attempted. The aim of this work is to improve prior models using larger datasets and a genetic programming technique, in the form of a symbolic regression. The 2–50 µm fraction was predicted using a USDA dataset which included both particle-size classification systems. The presented model reduced the root mean square error (%) by 14.96 and 23.62% (IGBP-DIS dataset and Australian dataset, respectively), compared with the previous model.
Additional keywords: pedotransfer functions, soil texture, symbolic regression.
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